Developing a Rigorous Systematic Review Protocol in Environmental Management: A Step-by-Step Guide

Abstract

This article provides a comprehensive guide for researchers and environmental professionals on developing a robust protocol for systematic reviews in environmental management. It covers the foundational principles of systematic review protocols, detailed methodological steps for their application, solutions to common challenges, and guidance on protocol validation and registration. Adhering to these standards is crucial, as over 95% of environmental reviews claiming to be 'systematic' fail to meet established methodological guidelines. This guide aims to enhance the rigor, transparency, and reliability of evidence synthesis to better inform environmental policy and practice.

Why a Protocol is Your Blueprint for a Unbiased and Transparent Review

A systematic review protocol is a foundational document that serves as the roadmap for the entire review process. It outlines the plan for a systematic review in advance of its conduct, detailing the rationale, objectives, and methodologies to be employed [1]. For researchers in environmental management, where evidence synthesis informs critical policy and conservation decisions, a rigorously developed protocol is indispensable. It ensures the review process is transparent, reproducible, and minimizes bias, thereby contributing reliable evidence to the field [2] [3]. Prospective registration or publication of the protocol is a standard requirement, committing the authors to a predetermined plan and safeguarding the review's integrity from arbitrary changes during its execution [4] [3].

Protocol Registration and Publication

Registering a systematic review protocol is a critical step that improves transparency, reduces duplication of efforts, and enhances the credibility of the subsequent review [1] [5]. For environmental research, specific platforms and journals cater to this need.

Table 1: Protocol Registration and Publication Venues

Venue	Discipline/Focus	Key Features
PROCEED [3]	Environmental Management	Open-access database for registering titles and protocols for CEE (Collaboration for Environmental Evidence) Systematic Reviews.
Collaboration for Environmental Evidence (CEE) [2] [1]	Environmental Management	An organisation supporting and producing systematic reviews on issues of greatest concern to environmental policy and practice.
Open Science Framework (OSF) [1] [5]	Multidisciplinary	An open-source platform to pre-register protocols and share supporting documents. Accepts scoping review protocols.
PROSPERO [1] [5]	Health, Social Care, Welfare, etc.	An international database of prospectively registered systematic reviews. Does not currently accept scoping reviews.
BioMed Central Journals (e.g., Systematic Reviews) [4] [5]	Health Sciences & Multidisciplinary	Publish peer-reviewed protocols for various research types, including systematic reviews.

The following workflow outlines the key stages in developing and finalizing a systematic review protocol:

Core Components of a Systematic Review Protocol

A robust protocol provides a detailed account of the hypothesis, rationale, and methodology of the study before the final data extraction stage begins [4]. Adherence to reporting standards, such as the PRISMA-P checklist, is often mandatory for publication and optimizes the quality and transparency of the reported methodology [4].

Table 2: Essential Sections of a Systematic Review Protocol

Section	Description	Key Elements
Title Page	Identifies the review.	Title matching the review question; author affiliations and contact details [4] [3].
Abstract	A structured summary.	Background, Methods, and Systematic review registration number [4] [3].
Background	Context and rationale for the review.	Explains the background, aims, summary of existing literature, and the necessity of the study [4].
Objective of the Review	The primary and secondary questions.	A clear statement of the primary question, often using a framework like PICO; may include secondary questions [3].
Methods	The detailed plan for conducting the review.	Eligibility criteria, information sources, search strategy, study selection process, data extraction, risk of bias assessment, and data synthesis [4] [1] [3].
Declarations	Administrative and ethical statements.	Ethics, consent, data availability, competing interests, funding, and authors' contributions [4] [3].

Formulating the Research Question and Eligibility Criteria

The foundation of a successful systematic review is a well-defined research question, which structures the entire process and guides the establishment of inclusion and exclusion criteria [6]. In environmental management, frameworks help in creating a focused and answerable question.

• PICO/PICo: The most common framework, adaptable for therapy, diagnosis, and prognosis. It stands for Population/Problem, Intervention/Exposure, Comparator, and Outcome. PICo is a variant used for qualitative reviews (Population, Interest, Context) [6].
• CoCoPop: This framework is recommended for prevalence and incidence reviews, with components for Condition, Context, and Population [6].
• Other Frameworks: SPICE (Setting, Perspective, Intervention, Comparison, Evaluation) and ECLIPSE (Expectation, Client, Location, Impact, Professionals, Service) can be valuable for evaluating services and policies [6].

The eligibility criteria, derived directly from the research question, should be explicitly defined based on:

• Population/Subject: The organisms, ecosystems, or environmental processes under investigation.
• Intervention/Exposure: The management practice, pollutant, or policy being studied.
• Comparator: The alternative intervention, control group, or baseline condition.
• Outcomes: The measured endpoints of interest (e.g., biodiversity indices, water quality parameters).
• Study Designs: The types of studies to be included (e.g., randomized controlled trials, observational studies, case studies) [3].

Search Strategy and Study Selection

A comprehensive, systematic, and reproducible literature search is paramount. The search strategy should be described in sufficient detail to be repeatable [3].

• Information Sources: Search multiple bibliographic databases (e.g., PubMed, Embase, Web of Science) and subject-specific sources relevant to environmental science [6]. Grey literature (e.g., technical reports, theses, government documents) should be included to mitigate publication bias [6].
• Search Strategy: Provide the actual search strings for at least one major database, using a combination of keywords, Boolean operators (AND, OR, NOT), and database-specific subject headings in a supplementary file [1] [3].
• Study Selection Process: Document the methodology for screening titles, abstracts, and full-text articles. This includes using software tools (e.g., Rayyan, Covidence) and a process for resolving disagreements between reviewers, often with consistency checking (e.g., having two reviewers screen a subset of records) [6] [3].

Data Extraction, Risk of Bias, and Synthesis

This phase involves collecting data from included studies and preparing it for synthesis.

• Data Extraction: Use a standardized, pre-piloted form to capture relevant data from each study. The process should be repeatable, and the plan for obtaining missing data from study authors should be described [6] [3].
• Study Validity Assessment (Risk of Bias): Critically appraise the methodological quality and risk of bias of included studies using appropriate tools (e.g., Cochrane Risk of Bias Tool, ROBINS-I). The approach for testing the repeatability of this assessment and how the results will inform the synthesis must be stated [1] [3].
• Data Synthesis: Describe the planned methods for synthesizing the collected data. Narrative synthesis should always be attempted, using descriptive statistics, tables, and figures [3]. If appropriate, a meta-analysis can be planned to statistically combine quantitative data, requiring details on statistical models, measures of effect, and heterogeneity assessment [6]. For scoping reviews, data visualisation (e.g., evidence maps, bar charts, interactive diagrams) is highly recommended to present the mapped evidence [7].

The Researcher's Toolkit for Systematic Reviews

A successful systematic review relies on a suite of tools and software to manage the complex process efficiently and accurately.

Table 3: Essential Research Reagent Solutions for Systematic Reviews

Tool/Resource	Category	Function
Rayyan / Covidence [6]	Study Screening	Web-based tools to streamline the process of title/abstract and full-text screening, allowing for collaboration and conflict resolution.
EndNote / Zotero / Mendeley [6]	Reference Management	Software to collect search results, deduplicate records, and manage citations.
R / RevMan [6]	Data Synthesis & Meta-analysis	Statistical software packages used for conducting meta-analyses, generating forest and funnel plots, and assessing heterogeneity.
Tableau / Flourish [7]	Data Visualisation	Platforms to create static and interactive visualisations (e.g., evidence maps, charts) for presenting results from scoping reviews and evidence maps.
ROSES Form [3]	Reporting Standards	A reporting standard (RepOrting standards for Systematic Evidence Syntheses) specifically for systematic reviews in environmental management.
PRISMA-P Checklist [4]	Reporting Standards	A checklist of recommended items to include in a systematic review protocol. Often required for submission to journals.

The following diagram maps the primary stages of the systematic review workflow to the tools that facilitate them:

The Critical Role of Protocols in Reducing Bias and Ensuring Transparency

Systematic reviews are fundamental for translating environmental health and management science into evidence-based policy and action. The rigor, reliability, and transparency of these syntheses are heavily dependent on the use of a pre-defined, peer-reviewed protocol. This application note delineates the quantitative evidence supporting protocol use, outlines its core principles within established frameworks like the Navigation Guide, and provides detailed methodological procedures for implementing robust protocols in environmental systematic reviews and maps. Adherence to these protocols minimizes bias, enhances reproducibility, and ensures that conclusions are derived from a structured and objective assessment of the evidence.

In environmental health and management, the transition from "expert-based narrative" reviews to systematic methods marks a significant advancement toward more reliable and action-oriented science [8]. Traditional narrative reviews, which do not follow pre-specified, consistently applied rules, are susceptible to various biases, including selection and publication bias, which can skew their conclusions [8] [9]. In contrast, systematic reviews and systematic maps aim to identify, appraise, and synthesize all empirical evidence on a specific question using explicit, systematic methods selected to minimize bias [8] [9]. The foundation of this rigorous approach is the a priori protocol—a detailed plan that is developed before the review commences and is ideally peer-reviewed and publicly registered [9]. This document is critical for pre-defining the review's methods, safeguarding against subjective decisions during the review process, and ensuring the synthesis's findings are both reliable and transparent.

Quantitative Evidence: Protocols Differentiate Systematic and Narrative Reviews

Empirical assessments of the environmental health literature demonstrate a clear performance gap between systematic and non-systematic reviews, with the use of a protocol being a key differentiator.

Table 1: Comparative Performance of Systematic vs. Non-Systematic Reviews

Review Method	Stated Objectives & Protocol	Consistent Risk of Bias Assessment	Transparent Author Contributions	Pre-defined Evidence Bar for Conclusions
Systematic Reviews (n=13)	23% (3/13) [8]	38% (5/13) [8]	38% (5/13) [8]	54% (7/13) [8]
Non-Systematic Reviews (n=16)	Performance was significantly poorer, with the majority receiving "unsatisfactory" or "unclear" ratings in 11 out of 12 methodological domains [8]

A random sample of environmental systematic reviews published between 2018 and 2020 found that 64% did not include any risk of bias assessment, a core component of a rigorous protocol [10]. These deficiencies underscore the need for wider adoption and stricter adherence to protocol-based systematic methods to improve the utility and validity of environmental evidence syntheses [10] [8].

Core Principles and Frameworks

The FEAT Principles for Risk of Bias Assessment

A robust protocol must provide a framework for assessing the internal validity, or risk of bias, of individual studies. The FEAT principles dictate that such assessments must be [10]:

• Focused exclusively on internal validity (systematic error), distinct from other constructs like precision or completeness of reporting.
• Extensive in covering all key sources of bias relevant to the included study designs.
• Applied directly to the synthesis, interpretation, and grading of the evidence.
• Transparent in their methodology and reporting.

The Navigation Guide Framework

The Navigation Guide methodology, developed for environmental health, provides a structured protocol framework that incorporates best practices from evidence-based medicine [11]. Its key elements include:

• A prespecified, peer-reviewed protocol.
• A comprehensive search strategy to capture all available evidence.
• Standardized and transparent documentation.
• A formal assessment of 'risk of bias' in individual studies.
• A clear separation of the scientific assessment from values and preferences [11].

Experimental Protocols and Methodologies

Protocol: Conducting a Systematic Map in Environmental Management

Systematic maps are used to catalogue and describe an evidence base, identifying knowledge gaps and gluts without synthesizing study findings [9].

*Objective:* To produce a searchable database of studies describing the extent and nature of evidence on a broad topic.

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Predefined PECO Elements:

• Population: Define the population of interest (e.g., boreo-temperate farmland systems).
• Exposure/Intervention: Specify the exposure or intervention (e.g., agri-environment schemes).
• Comparator: Note if a comparator is required (often optional in maps).
• Outcome: Describe the scope of outcomes measured (e.g., any biodiversity metric) [9].

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Procedure:

• Protocol Development & Registration: Draft and submit a detailed protocol for peer review (e.g., in Environmental Evidence) to register methods and prevent duplication [9].
• Search Strategy: a. Develop a comprehensive search string for multiple bibliographic databases and grey literature sources. b. Document all search dates, sources, and results.
• Screening: a. Screen records (title/abstract, then full-text) against predefined eligibility criteria. b. Use at least two independent reviewers to minimize selection bias; measure and report inter-rater reliability.
• Data Extraction (Meta-data): a. Extract descriptive information from all included studies into a standardized database. This includes citation details, study setting, population characteristics, intervention/exposure details, and methodology. b. Do not extract quantitative outcome data or study findings.
• Critical Appraisal (Optional): a. If performed, focus on assessing the internal validity (risk of bias) of studies, as external validity is less relevant for broad mapping topics [9].
• Data Synthesis & Outputs: a. Generate a systematic map database (e.g., a searchable .xlsx file or SQL database). b. Produce a report detailing knowledge gaps and clusters. c. Consider creating a geographical information system (GIS) to visually display study locations [9].

Protocol: Risk of Bias Assessment in a Systematic Review

This protocol details the application of the FEAT principles to evaluate the internal validity of studies included in a comparative quantitative systematic review.

*Objective:* To judge the extent to which the design and conduct of each included study may have introduced systematic error, and to apply this judgement to the evidence synthesis.

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Procedure:

• Select/Develop a Tool: Choose a validated risk of bias tool or develop a review-specific instrument based on the FEAT principles and known sources of bias (e.g., confounding, selection bias, misclassification) [10].
• Pilot the Tool: Calibrate the tool and review team using a sample of studies to ensure consistent application.
• Conduct Assessments: a. Have at least two reviewers independently assess each study. b. Judge the risk of bias for specific domains (e.g., sequence generation, blinding, missing data) rather than providing a single global score. c. Support all judgements with explicit quotes or details from the study.
• Apply Assessments to Synthesis: a. Tabulate Results: Present risk of bias judgements for each study and domain in a clear table. b. Use in Narrative Synthesis: Explore the relationship between risk of bias and study findings. c. Incorporate into Meta-Analysis: Consider statistical methods like sensitivity or meta-regression analyses to examine the influence of bias, or use risk of bias as a grouping variable [10].
• Grade the Body of Evidence: Integrate risk of bias assessments with other factors (e.g., precision, consistency) to rate the overall confidence in the evidence for each outcome [11].

Protocol: Creating an Interactive Reference Flow (I-REFF) Diagram

Modernizing the traditional PRISMA flow diagram enhances transparency and efficiency.

*Objective:* To generate an interactive literature flow diagram that is directly linked to the underlying screening data, providing greater traceability and simplifying updates.

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Procedure:

• Screening in a Digital Platform: Conduct literature screening using a systematic review software platform (e.g., DistillerSR).
• Export Screening Data: Export data containing all screening decisions and reference information (e.g., authors, title, journal, URL).
• Data Transformation: Use a tool like Microsoft Power Query for Excel or a KNIME workflow to structure the data for visualization [12].
• Visualization Software Connection: Connect the transformed data to visualization software (e.g., Tableau).
• Design Interactive Diagram: Build a flow diagram where summary counts are automatically calculated. Implement interactive elements (e.g., tooltips, filters, clickable nodes) that allow users to view the list of studies included or excluded at each stage [12].
• Publish and Link: Provide a link to the interactive I-REFF diagram alongside the static version in the final publication [12].

The Scientist's Toolkit: Essential Reagents for Systematic Review

Table 2: Key Research Reagents and Digital Solutions for Systematic Review

Item/Tool	Function/Application in Protocol
PECO/PICO Framework	Defines the review question's core components: Population, Exposure/Intervention, Comparator, and Outcome. Ensures focused eligibility criteria [9].
Systematic Review Software (e.g., DistillerSR)	Digital platform for managing the screening process, facilitating independent dual-reviewer workflows, and maintaining an audit trail [12].
Risk of Bias Tool (e.g., ROBINS-E, review-specific)	Standardized instrument for assessing internal validity of studies, ensuring assessments are Focused, Extensive, Applied, and Transparent (FEAT) [10].
Data Visualization Software (e.g., Tableau)	Creates interactive diagrams (I-REFF) and other data visualizations, linking the review process directly to underlying data for enhanced transparency [12].
Grading of Recommendations, Assessment, Development, and Evaluations (GRADE)	Framework for rating the overall certainty of a body of evidence, integrating risk of bias, precision, consistency, and other factors [11].

Establishing the Rationale, Objectives, and Scope for Your Environmental Question

In environmental management research, formulating a clear, answerable question is the cornerstone of a successful systematic review or map. A well-defined protocol establishes the rationale, objectives, and scope of the review, ensuring the research process is transparent, methodologically rigorous, and reproducible. The use of evidence-based practice (EBP) in conservation and environmental management aims to enhance the quality of interventions, improve outcomes, and reduce unwarranted variations in practice that lead to inefficiencies [13]. This document provides a detailed protocol for establishing the foundational elements of a systematic evidence synthesis, framed within the broader context of advancing methodological standards in environmental research.

Theoretical Foundation and Rationale

The Imperative for Evidence-Based Environmental Management

Evidence-based practice was formally introduced to the environmental literature in the early 2000s, primarily through the field of Evidence-Based Conservation (EBC) [13]. The core motivation was research indicating that conservation decisions were frequently based on personal experience and opinion without consulting scientific evidence, thereby hampering effective conservation outcomes [13]. The EBC paradigm seeks to reduce the influence of subjective opinions, biases, and unfounded beliefs on conservation decisions.

A key challenge in implementing EBP is that it requires practitioners and organizations to redirect time and resources away from direct action. Proponents of EBP often operate on two underlying assumptions: that interventions based on consulting evidence result in better outcomes, and that they are associated with reduced costs, implying a positive return-on-investment (ROI) [13]. However, a knowledge gap exists as to whether these assumptions hold true outside of healthcare, creating a critical need for systematic evaluations of the impacts and ROI of EBP in conservation and environmental management [13].

Defining Evidence in an Environmental Context

For the purposes of this protocol, a broad and inclusive definition of evidence is adopted: "any relevant data, information, knowledge, and wisdom used to assess an assumption, claim, or hypothesis related to a question of interest" [13]. This includes a plurality of sources, such as:

• Evidence syntheses and primary peer-reviewed research
• Grey literature reports
• Practitioner, local, Indigenous, and/or expert knowledge
• Observations and experience [13]

Core Methodology: Defining Rationale, Objectives, and Scope

This section provides a detailed, step-by-step methodology for establishing the core components of a systematic review or map protocol.

Experimental Workflow for Protocol Development

The following diagram visualizes the sequential and iterative process of defining a review's foundational elements.

Step-by-Step Experimental Protocol

Step 1: Establishing the Rationale

The rationale provides the justification for why the review is necessary and should be conducted.

• Procedure:
  • Identify the Knowledge Gap: Conduct a preliminary scoping search to confirm that no existing or ongoing systematic review addresses your specific question. This prevents duplication of effort [13] [14].
  • Articulate the Practical Significance: Clearly state how the review's findings will inform policy, management decisions, or practice. For example, a review might aim to determine the most cost-effective invasive species eradication methods to optimize limited conservation funding [13].
  • Describe the Theoretical Basis: Ground your review in the broader context of EBP. Explain how it will contribute to filling the recognized gap in understanding the impacts and return-on-investment of using evidence in environmental decision-making [13].

Step 2: Defining the Objectives and Research Questions

The objectives are a clear statement of the review's goals, directly operationalized into specific research questions.

• Procedure:
  • Formulate Primary and Secondary Questions: Frame questions that are specific, measurable, and achievable within the review's scope. The PICO (Population, Intervention, Comparator, Outcome) or PCC (Population, Concept, Context) frameworks are commonly used to structure questions [13] [15].
  • Ensure Clarity and Focus: Avoid overly broad or vague questions. A well-structured question guides the entire review process, from search strategy to data extraction.
  • Example from Published Protocol:
    • Primary Question: "When evidence-based practice is implemented for conservation and environmental management, what are the a) human and b) environmental outcomes?" [13]
    • Secondary Question: "Among these documents reporting these outcomes, what are the costs and ROI or VOI of evidence-based practice?" [13]

Step 3: Delineating the Scope

The scope defines the boundaries of the review, ensuring it remains feasible and focused. Using a formal framework like PCC is recommended for scoping reviews [13] [15].

• Procedure:
  • Apply the PCC Framework:
    • Population/Participants: Define the subjects of the research (e.g., specific ecosystems, species, communities, or management interventions).
    • Concept: Clarify the core ideas being investigated (e.g., "effectiveness of EBP," "return-on-investment," "barriers to evidence use").
    • Context: Specify the setting (e.g., geographic region, ecosystem type, policy context, or specific environmental challenges like climate change or pollution).
  • Develop Inclusion/Exclusion Criteria: Create explicit criteria based on the PCC to determine which studies are eligible for inclusion. These criteria should cover document types, publication status, language, and timeframes [15] [16].
  • Document Scope Decisions: Record all decisions regarding scope boundaries with clear justifications to ensure transparency and reproducibility.

The Scientist's Toolkit: Research Reagent Solutions

The following table details key methodological tools and frameworks essential for developing a robust systematic review protocol in environmental research.

Table 1: Essential Methodological Tools for Protocol Development in Environmental Evidence Synthesis

Tool/Framework Name	Function/Purpose	Application Example
PCC Framework (Population, Concept, Context)	Provides a structured approach to define and bound the scope of a scoping review [13] [15].	Used to develop inclusion criteria for a review on the impact of riparian restoration approaches in the tropics [14].
PICO Framework (Population, Intervention, Comparator, Outcome)	A common framework for formulating focused questions in systematic reviews, particularly for evaluating interventions.	Structuring a question on the effectiveness of perches for promoting bird-mediated seed dispersal, where the intervention is "installation of perches" and the outcome is "seed dispersal rate" [14].
PRISMA-P (Preferred Reporting Items for Systematic Review and Meta-Analysis Protocols)	A checklist to ensure the transparent and complete reporting of a systematic review protocol [16].	Used to guide the writing of a protocol for a systematic review on dengue virus detection in wastewater [16].
SYMBALS (SYstematic review Methodology Blending Active Learning and Snowballing)	A comprehensive methodology that incorporates machine learning to assist in the review process, enhancing efficiency [13].	Applied in a scoping review protocol to explore the impacts of EBP using open-source tools like ASReview and SysRev [13].
ROBINS-I (Risk Of Bias In Non-randomized Studies - of Interventions)	A tool for assessing the risk of bias in the results of non-randomized studies included in a systematic review [16].	Used to appraise the quality of observational studies on methodologies for detecting viruses in wastewater [16].

Quantitative Data Presentation

Systematic review protocols should plan for the collection and presentation of specific quantitative data. The table below summarizes common data types and their sources, essential for planning the data extraction phase.

Table 2: Taxonomy of Quantitative Data for Environmental Evidence Synthesis

Data Category	Description	Exemplary Metrics/Units	Source/Context of Use
Bibliometric Data	Quantitative analysis of scientific literature to reveal publication trends and research patterns.	Publication volume per year, co-occurrence of keywords, citation counts, journal sources [15].	A scoping review on Research Data Management in environmental studies used bibliometrics to identify that publications significantly increased from 2012, with peaks in 2020-2021 [15].
Methodological Data	Descriptors of the techniques and approaches used in primary studies.	Sampling techniques (e.g., grab vs. composite), detection methods (e.g., PCR, ELISA), viral load (gene copies, Ct values) [16].	A systematic review protocol on dengue wastewater surveillance plans to extract and synthesize data on sampling methodologies and detection limits [16].
Intervention Outcome Data	Quantitative measures of the effects of a management action or intervention.	Effect sizes (e.g., Hedges' g), percent change, means and standard deviations, odds ratios, survival rates.	A review on the impacts of EBP would seek data comparing environmental or human outcomes between evidence-informed and conventional management actions [13].
Economic Data	Information related to the costs and economic efficiency of interventions or practices.	Return-on-Investment (ROI), cost-benefit ratios, implementation costs, cost savings [13].	A key objective of a scoping review on EBP is to identify and synthesize data on the ROI of implementing evidence-based practices [13].

Advanced Methodological Considerations

Machine Learning and Automation in Evidence Synthesis

The field of evidence synthesis is increasingly leveraging technology to handle the vast volume of scientific literature. Machine learning-assisted review processes using tools like ASReview can optimize the screening of titles and abstracts, significantly increasing efficiency without compromising rigor [13] [14]. Furthermore, the potential use of Generative AI for tasks like qualitative data extraction is being actively piloted, though it requires careful validation and adherence to legal and ethical standards [14].

Incorporating a Plurality of Evidence

When establishing the scope and eligibility criteria, reviewers must decide how to handle different forms of evidence. As defined in the rationale, a broad definition of evidence that includes Traditional Ecological Knowledge (TEK) is increasingly recognized as vital for comprehensive environmental management [13] [14]. Protocols should explicitly state how such knowledge systems will be searched for and incorporated, for instance, by braiding TEK with Western science in the management of freshwater social-ecological systems [14].

Systematic reviews and systematic maps represent the gold standard for synthesizing environmental evidence to inform management and policy decisions. These evidence-based frameworks provide a structured, objective, and transparent methodology for aggregating research findings, thereby reducing bias and increasing reliability [17]. The validity and reproducibility of any systematic review are fundamentally established during the protocol development phase, where key methodological components are pre-specified before the review commences [3]. This application note details the core procedural elements—from establishing screening criteria to planning data extraction—that constitute a robust protocol within environmental management research. Proper protocol development ensures that the subsequent evidence synthesis minimizes errors and selection bias while producing findings that are both scientifically defensible and practically relevant to stakeholders [18] [19].

Developing Eligibility Screening Criteria

Rationale and Structure of Eligibility Criteria

The use of pre-specified, explicit eligibility criteria ensures that the inclusion or exclusion of primary research studies from a systematic review or map is conducted transparently and objectively [18] [19]. This approach reduces the risk of introducing errors or bias that can result from selective, subjective, or inconsistent decisions. Failing to apply eligibility criteria consistently can lead to contradictory conclusions across different evidence syntheses addressing the same question [18].

Eligibility criteria should flow logically from the key elements of the review question. For environmental management questions, a PICO/PECO (Population/Problem, Intervention/Exposure, Comparator, Outcome) framework is commonly used, where the criteria specify which of these elements must be reported in a primary study for it to be eligible for inclusion [18] [19]. The criteria can be expressed as inclusion criteria, exclusion criteria, or both, but should be structured such that a study is excluded if it fails to meet any single inclusion criterion [19]. This efficient approach minimizes the information reviewers must locate in each article.

Table 1: Components of Eligibility Criteria Based on PICO/PECO Framework

PICO/PECO Element	Description	Example from an Environmental Systematic Review
Population/Problem	The subjects or system being studied.	Cropland and participating farmers in China [19].
Intervention/Exposure	The management action or factor of interest.	Participation in the Conversion of Cropland to Forest Programme (CCFP) [19].
Comparator	The control or comparison condition.	Agricultural land not enrolled in the CCFP [19].
Outcome	The measured effects or endpoints.	Environmental (e.g., soil erosion) and socioeconomic outcomes (e.g., household income) [19].

Study Design as an Eligibility Criterion

The types of primary research study designs capable of answering the evidence synthesis question must be considered as potential eligibility criteria [19]. While some protocols explicitly include study design in the question structure (e.g., PICOS, where 'S' stands for Study), it should always be considered in a systematic review protocol. The included study designs must be compatible with the planned data synthesis approach; for instance, some meta-analytic methods specifically require controlled studies [19]. Study design can also indicate the potential validity of the evidence, as certain designs are more prone to bias than others.

Planning the Screening Process

The Stepwise Screening Workflow

Eligibility screening is typically conducted as a stepwise process to efficiently manage the large volume of references retrieved by sensitive systematic searches [18]. The Collaboration for Environmental Evidence (CEE) recommends at least two distinct filters: (1) an initial screening of titles and abstracts to remove clearly irrelevant records, and (2) a rigorous assessment of the full-text documents for the remaining records [19]. This multi-stage process ensures a balance between efficiency and thoroughness.

The following diagram illustrates the sequential workflow for eligibility screening, including key preparatory and quality control steps.

Pilot-Testing and Consistency Checking

Before commencing the full screening process, the eligibility criteria and screening procedure must be pilot-tested [18] [19]. A typical approach involves developing a screening form that lists the inclusion/exclusion criteria with instructions, then having multiple reviewers (at least two) independently apply it to a sample of articles drawn from preliminary searches [19]. This pilot-testing phase is critical for several reasons, which are detailed in the table below.

Table 2: Objectives and Outcomes of Pilot-Testing Screening Criteria

Objective of Pilot-Testing	Expected Outcome
Validate Classification	Check that eligibility criteria correctly distinguish between relevant and irrelevant studies.
Check Agreement	Assess consistency between screeners; poor agreement necessitates revision of criteria or instructions.
Train Review Team	Ensure all team members interpret and apply the eligibility criteria consistently.
Identify Unanticipated Issues	Discover ambiguities or edge cases not previously considered and refine criteria accordingly.
Plan Resources	Provide an estimate of the time required for the full screening process.

Consistency checking (e.g., using measures like Cohen's kappa) should continue during the full screening phase after the pilot-test is complete. A common practice is for a subset of records (e.g., 10-20%) to be screened by at least two reviewers independently, with disagreements resolved through discussion or by a third reviewer [19]. This ongoing process minimizes the risk of introducing selection bias.

Preparing for Screening: Reference Management

Bibliographic searches often yield thousands of references, necessitating efficient organization using reference management software [18]. These tools should facilitate the identification and removal of duplicate articles, import abstracts and full-texts, and allow reviewers to record screening decisions. Key considerations when selecting a tool include: the ability to handle the expected volume of references; support for multiple simultaneous users; functionality for project management and progress monitoring; and options for text mining or machine learning to assist screening where appropriate [18]. As a first step in screening, duplicate articles must be identified and removed to prevent double-counting of data, which could introduce bias [18] [19].

Data Coding and Extraction Strategy

Distinction between Data Coding and Extraction

In evidence synthesis, 'data coding' and 'data extraction' are distinct but often iterative processes. Data coding involves recording relevant characteristics (meta-data) of a study, such as its location, setting, methodology, and population details. This is performed in both Systematic Reviews and Systematic Maps [20]. Data extraction refers specifically to recording the quantitative or qualitative results of the study (e.g., effect sizes, means, variances, key findings) and is undertaken in Systematic Reviews only [20]. The data extraction and coding strategy should be planned in advance and documented in the protocol.

Designing Data Collection Forms

Coded and extracted data should be recorded on carefully designed forms, which are typically piloted on a subset of full-text articles [20]. These forms can be spreadsheets or specialized software interfaces. The structure and components of the form are often guided by the PICO/PECO key elements of the review question [20].

Table 3: Typical Data Coding and Extraction Form Structure

Data Category	Specific Variables	Format/Notes
Study Identification	Author(s), Year, Title, Source	Text
Bibliographic Information	DOI, Journal/Report	Text
Study Context	Location, Habitat, Spatial Scale, Duration	Text; Categorical
Population	Species, Demographics, Sample Size	Text; Numerical
Intervention/Exposure	Type, Intensity, Frequency, Duration	Text; Categorical
Comparator	Type, Description	Text
Study Design	Experimental vs. Observational, Control, Randomization	Categorical
Outcomes	Outcome Type, Measure, Units	Text
Results	Quantitative Data (e.g., means, SD, SE, p-values), Effect Sizes	Numerical; Required for Systematic Reviews
Potential Effect Modifiers	Variables explaining heterogeneity (e.g., altitude, climate)	Context-dependent

For systematic reviews, particular attention should be paid to extracting data in a format amenable to synthesis. This often involves extracting raw or summary data to calculate a common statistic or effect size for each study [20]. The protocol should outline procedures for handling missing or unclear data, including plans to contact original authors and methods for data transformation or imputation, along with any associated sensitivity analyses [20].

Ensuring Consistency and Reproducibility

As with eligibility screening, the processes of data coding and extraction must be pilot-tested and assessed for consistency between reviewers [20]. This ensures the process is reproducible and reliable. Ideally, a second reviewer should check all extracted data; if this is not feasible, a random subset should be verified to ensure a priori rules have been applied consistently and to identify human error (e.g., misinterpreting a standard error as a standard deviation) [20]. For transparency, the completed data extraction forms should be included as an appendix or supplementary material to the final review [20].

Successful execution of a systematic review protocol relies on a suite of methodological "reagents" – the essential tools and resources that facilitate the process from literature retrieval to synthesis. The following table details key solutions for the core phases of the review.

Table 4: Essential Research Reagent Solutions for Systematic Reviews

Research Reagent	Primary Function	Application in Evidence Synthesis
Reference Management Software	Organizes search results, removes duplicates, records screening decisions.	Essential for managing large volumes of references and coordinating team screening. Tools like EndNote, Eppi-Reviewer, and Mendeley are commonly used [18].
Systematic Review Management Platforms	Provides integrated environment for screening, data extraction, and critical appraisal.	Streamlines the entire review process. Platforms like Eppi-Reviewer include machine learning functions to assist with screening prioritization [18].
Pilot Test-List of Articles	A sample of known relevant and irrelevant articles used for development.	Serves as a benchmark for pilot-testing and refining eligibility criteria and screening instructions to ensure they correctly classify studies [19].
Standardized Data Extraction Form	A pre-tested spreadsheet or digital form for recording data.	Ensures all reviewers collect the same information from included studies in a consistent format, which is crucial for reliable synthesis [20].
Critical Appraisal Checklist	A tool to assess the internal validity and risk of bias in included studies.	Allows for standardized quality assessment of study methodologies. The appropriate checklist depends on the study designs being reviewed.

A meticulously crafted protocol is the foundational pillar of a rigorous and credible systematic review or map in environmental management. By pre-specifying and justifying the core components—detailed eligibility criteria, a transparent multi-stage screening process, and a comprehensive strategy for data coding and extraction—researchers can guard against bias and ensure the reproducibility of their work. The methodologies and tools outlined in this application note provide a structured pathway for developing such a protocol. Adherence to these standards, as promoted by organizations like the Collaboration for Environmental Evidence, not only strengthens the scientific integrity of the resulting synthesis but also maximizes its potential to reliably inform environmental policy and practice.

Crafting Your Protocol: A Step-by-Step Methodology with PRISMA-P

Utilizing the PRISMA-P Checklist for Comprehensive Protocol Reporting

The Preferred Reporting Items for Systematic Review and Meta-Analysis Protocols (PRISMA-P) is a reporting guideline specifically designed to facilitate the preparation and reporting of robust protocols for systematic reviews [21]. Developed in 2015, PRISMA-P consists of a 17-item checklist that helps authors document the rationale, hypothesis, and planned methods of their systematic review before the review begins [22] [21]. In environmental management research, where systematic reviews often address complex ecological systems and policy-relevant questions, a well-structured protocol is essential for ensuring methodological rigor, transparency, and reproducibility [23].

Systematic reviews in environmental fields differ from their healthcare counterparts in several important aspects, including the types of evidence considered, synthesis methods employed, and review outputs generated [23]. While PRISMA-P provides a solid foundation for protocol development, environmental researchers must often adapt its application to address field-specific requirements, such as handling diverse study designs, accommodating both quantitative and qualitative synthesis methods, and planning for systematic maps that catalogue evidence rather than synthesize findings [23] [24].

The preparation of a detailed protocol is an essential component of the systematic review process in environmental research; it ensures careful planning and explicit documentation before the review starts, promoting consistent conduct by the review team, accountability, research integrity, and transparency of the eventual completed review [21]. Environmental journals increasingly require or strongly recommend the submission of protocols for systematic reviews, with some offering in-principle acceptance of the final review if conducted according to a pre-approved protocol [24].

PRISMA-P Checklist Components: Application Notes for Environmental Research

The PRISMA-P 2015 statement provides a 17-item checklist addressing different sections of a systematic review protocol [25]. The table below summarizes these items with specific application notes for environmental management research:

Table 1: PRISMA-P Checklist with Application Notes for Environmental Management Research

Section	PRISMA-P Item Number	PRISMA-P Item	Application Notes for Environmental Research
Administrative Information	1	Title	Identify the report as a protocol of a systematic review; include "systematic review" or "meta-analysis" and the research topic [21].
	2	Registration	If registered, provide name of registry and registration number [21]. Environmental reviews can be registered in PROSPERO or other relevant repositories.
	3	Authors	Provide name, institutional affiliation, and email address of all authors [21].
	4	Amendments	If the protocol represents an amendment, give rationale for amendment [21].
	5	Support	Indicate sources of financial or other support; role of funders/sponsors [21].
Introduction	6	Rationale	Describe the rationale for the review in the context of what is known; specifically address environmental policy or management relevance [21].
	7	Objectives	Provide explicit statement of question(s) the review will address with reference to participants, interventions, comparators, and outcomes (PICO/PECO) [21]. For environmental reviews, PECO (Population, Exposure, Comparator, Outcome) is often more appropriate than PICO.
Methods	8	Eligibility Criteria	Specify study characteristics (e.g., PICO/PECO, study design, setting, time frame) and report characteristics (e.g., years considered, language, publication status) used as criteria for eligibility for the review [21]. For environmental reviews, clearly define relevant environmental exposures, interventions, or phenomena.
	9	Information Sources	Describe all intended information sources (e.g., electronic databases, contact with study authors, trial registers) with planned dates of coverage [21]. Environmental reviews should include specialized environmental databases beyond mainstream bibliographic databases.
	10	Search Strategy	Present draft of search strategy to be used for at least one electronic database, including planned keywords, subject headings, and filters [21]. Environmental searches often require broader terminology and ecosystem-specific vocabulary.
	11	Study Records: Data Management	Describe the mechanism(s) that will be used to manage records and data throughout the review [21].
	12	Study Records: Selection Process	Describe the process that will be used for selecting studies (e.g., two independent reviewers) through each phase of the review [21].
	13	Study Records: Data Collection Process	Describe the method of extracting data from reports (e.g., piloted forms, independent extraction), and processes for obtaining and confirming data from investigators [21].
	14	Data Items	List and define all variables for which data will be sought (e.g., PICO items, funding sources), and pre-planned data assumptions and simplifications [21]. For environmental reviews, include contextual variables like ecosystem type, spatial scale, and temporal factors.
	15	Outcomes and Prioritization	List and define all outcomes for which data will be sought, including prioritization of main and additional outcomes, with rationale [21]. Environmental outcomes often include ecological, social, and economic dimensions.
	16	Risk of Bias in Individual Studies	Describe anticipated methods for assessing risk of bias of individual studies, including whether this will be done at the outcome or study level, and how this information will be used in data synthesis [21]. Environmental reviews may need to adapt risk of bias tools from medical fields or use domain-specific tools.
	17	Data Synthesis	Describe criteria under which study data will be quantitatively synthesized, methods for handling quantitative data, and any planned exploration of consistency or sensitivity analyses [21]. For environmental reviews, clearly specify plans for both quantitative and narrative synthesis appropriate to diverse evidence types.

For environmental systematic reviews that may not fit the traditional intervention framework, the ROSES (RepOrting standards for Systematic Evidence Syntheses) forms offer an alternative reporting standard specifically designed for conservation and environmental management [23]. ROSES addresses several limitations of PRISMA for environmental evidence, including better handling of diverse synthesis methods and systematic maps [23]. Some environmental journals explicitly accept both PRISMA and ROSES reporting standards for systematic review submissions [24].

Experimental Protocol: Implementing PRISMA-P for an Environmental Systematic Review

Protocol Development Workflow

The following diagram illustrates the systematic workflow for developing a PRISMA-P compliant protocol for environmental systematic reviews:

Detailed Methodologies for Key Protocol Components

Search Strategy Development Protocol

A comprehensive, reproducible search strategy is fundamental to any systematic review. For environmental topics, this requires special consideration of diverse information sources and terminology.

Experimental Protocol:

• Initial Scope Mapping: Conduct preliminary scoping searches to identify key terminology, concepts, and relevant databases beyond mainstream bibliographic sources (e.g., Web of Science, Scopus). Environmental reviews should include specialized databases such as AGRICOLA, GreenFile, and discipline-specific repositories [23] [24].

• Search String Formulation:

  • Identify primary concepts from the research question
  • Compile comprehensive synonym lists for each concept
  • Account for regional variations in terminology (e.g., "conservation" vs. "preservation")
  • Include scientific and common names for species where relevant
  • Incorporate database-specific subject headings where available
  • Test iterative search versions for sensitivity and precision

• Search Execution and Documentation:

  • Document exact search strings with all Boolean operators and syntax
  • Record database platforms, hosts, and dates of search execution
  • Specify any search filters or limits applied with justification
  • Plan for supplementary searching methods (reference checking, citation chasing, grey literature searches, expert consultation)

• Search Validation:

  • Test search strategy against a set of known relevant articles
  • Calculate and report recall rate of known relevant articles
  • Refine search strategy based on validation results

Table 2: Essential Research Reagent Solutions for Systematic Review Protocols

Research Reagent	Function in Protocol Development	Examples/Specifications
PRISMA-P Checklist	Provides minimum set of items to include in systematic review protocol	17-item checklist; available as PDF or Word document from prisma-statement.org [22] [25]
Protocol Registration Platform	Time-stamped, public documentation of planned methods	PROSPERO, Open Science Framework; PROSPERO specifically for health-related reviews [21]
Search Strategy Documentation Tool	Records search strategies for reproducibility	PRISMA-S extension; specialized templates for recording database-specific syntax [26]
Reference Management Software	Manages records throughout review process	Covidence, Rayyan, EndNote; enables de-duplication and shared screening [21]
Data Extraction Forms	Standardized tools for collecting data from included studies	Pilot-tested electronic forms; should include all variables specified in PRISMA-P Item 14 [21]

Eligibility Criteria Specification Protocol

Clearly defined eligibility criteria are essential for consistent, unbiased study selection throughout the review process.

Experimental Protocol:

• PECO/PICO Framework Application:
  • Population: Define relevant biological taxa, ecosystems, or ecological communities with explicit inclusion/exclusion criteria
  • Exposure/Intervention: Specify environmental exposures, management interventions, or phenomena of interest
  • Comparator: Define appropriate comparison conditions (e.g., pre-intervention baselines, control sites, alternative interventions)
  • Outcomes: Identify primary and secondary outcomes of interest, including ecological, social, and economic endpoints where relevant

• Study Design Considerations:

  • Specify eligible study designs (e.g., experimental, observational, modeling)
  • Justify inclusion of different design types based on review question
  • Define minimum methodological criteria for inclusion (e.g., replication, confounding control)

• Contextual and Methodological Factors:

  • Specify relevant spatial and temporal scales
  • Define geographic and climatic contexts if relevant
  • Establish criteria for study duration and follow-up periods

• Practical Constraints:

  • Specify language restrictions with justification
  • Define publication date ranges if temporally constrained
  • Establish publication status criteria (e.g., inclusion of grey literature)

Adaptation Framework for Environmental Systematic Reviews

While PRISMA-P provides an excellent foundation for protocol development, environmental systematic reviews often require adaptations to address field-specific requirements. The following diagram illustrates the decision pathway for selecting and adapting reporting standards for environmental evidence syntheses:

Field-Specific Modifications to PRISMA-P

Environmental systematic review protocols often require specific modifications to standard PRISMA-P items:

Eligibility Criteria (Item 8): Beyond standard PICO elements, environmental protocols should explicitly define:

• Ecosystem types and contexts
• Spatial and temporal scales of relevance
• Anthropogenic versus natural drivers
• Socio-ecological system boundaries

Information Sources (Item 9): Environmental protocols should plan to search:

• Specialized environmental databases (e.g., AGRICOLA, GreenFile)
• Grey literature sources (government reports, NGO publications)
• Regional and non-English databases where relevant
• Subject-specific repositories for ecological data

Data Synthesis (Item 17): Environmental protocols should specify:

• Plans for both quantitative and narrative synthesis methods
• Approaches for handling heterogeneous study designs
• Methods for addressing statistical non-independence in ecological data
• Strategies for dealing with varying spatial and temporal scales

The PRISMA-P checklist provides an essential framework for developing rigorous, transparent protocols for systematic reviews in environmental management research. By systematically addressing each of the 17 PRISMA-P items while making appropriate field-specific adaptations, environmental researchers can enhance the methodological quality, reproducibility, and utility of their systematic reviews. The structured approach outlined in this protocol, including the experimental methodologies for key protocol components and the decision framework for selecting appropriate reporting standards, offers environmental researchers a comprehensive toolkit for developing robust systematic review protocols that meet evolving standards in evidence-based environmental management.

Systematic reviews distinguish themselves from narrative reviews through the use of pre-specified, explicit eligibility criteria that determine which studies will be included in the evidence synthesis [27]. These criteria form the foundation of a reproducible review process by minimizing selective inclusion of evidence and reducing reviewer bias [19] [18]. In environmental management research, where evidence often encompasses diverse study designs, populations, and exposure scenarios, carefully constructed eligibility criteria are particularly crucial for ensuring the review addresses its intended question while maintaining methodological rigor. The eligibility criteria directly operationalize the review question by defining the specific characteristics that studies must possess to be included, creating a transparent pathway from the research question to the evidence included in the synthesis [27] [28].

The process of defining eligibility criteria typically employs structured frameworks that ensure all relevant aspects of the research question are adequately addressed. While the PICO framework (Population, Intervention, Comparator, Outcome) originated in clinical medicine for intervention studies, environmental systematic reviews frequently utilize the PECO variant (Population, Exposure, Comparator, Outcome) to better accommodate observational evidence and exposure-outcome relationships common in environmental research [29] [30]. These frameworks serve as organizing principles for developing precise inclusion and exclusion criteria that can be consistently applied by multiple reviewers throughout the screening process.

Conceptual Framework and Definitions

Core Components of Eligibility Criteria

Eligibility criteria in systematic reviews are structured around the key elements of the research question, which typically include populations, interventions/exposures, comparators, and outcomes [27] [31]. For each component, review authors must define both the specific characteristics that would qualify a study for inclusion and any explicit exclusion criteria that would render a study ineligible [28]. This binary approach ensures consistent application during the screening process and helps maintain the focus on evidence directly relevant to the review question.

The population, intervention/exposure, and comparator components of the question typically translate directly into eligibility criteria for the review [27]. For example, in a PICO-type question focusing on interventions, the key elements would specify which populations, interventions, comparators, and outcomes must be reported in a primary research study for it to be eligible [19]. It is important to note that outcomes generally should not serve as eligibility criteria in most cases, meaning studies should be included irrespective of whether they report outcome data, unless the review specifically addresses outcomes that may not have been measured [27].

Adapting Frameworks for Environmental Research

Environmental systematic reviews often require adaptations to standard frameworks to address the unique characteristics of environmental evidence. The PECO framework has emerged as the dominant approach for environmental questions involving exposures, where the "E" represents the environmental exposure of interest rather than a deliberate intervention [29]. This framework accommodates the complex exposure scenarios, diverse outcome measures, and varied study designs common in environmental research, including observational studies, controlled experiments, and modeling approaches [18] [30].

Table 1: Comparison of PICO and PECO Frameworks for Systematic Reviews

Framework Component	PICO (Intervention Focus)	PECO (Exposure Focus)
First Element	Population: The participants receiving the intervention	Population: The entities affected by the exposure (may include humans, animals, ecosystems)
Second Element	Intervention: The deliberate action or treatment being evaluated	Exposure: The environmental agent or condition being studied
Third Element	Comparator: The alternative against which the intervention is compared (e.g., placebo, different intervention)	Comparator: The reference scenario against which exposure is compared (e.g., background levels, alternative exposure)
Fourth Element	Outcome: The measured effects or endpoints of interest	Outcome: The measured effects or endpoints of interest
Typical Application	Clinical trials, public health interventions	Environmental health, ecotoxicology, natural resource management

Detailed Eligibility Criteria Specifications

Population Criteria

Defining eligible populations requires specifying the entities of interest and their key characteristics that determine relevance to the review question. For environmental reviews, populations may include human communities, animal species, ecosystems, or other biological entities affected by the intervention or exposure [30]. The criteria should be "sufficiently broad to encompass the likely diversity of studies, but sufficiently narrow to ensure that a meaningful answer can be obtained when studies are considered in aggregate" [27].

When developing population criteria, consider including explicit specifications for:

• Disease/condition definitions using explicit diagnostic criteria that do not unnecessarily exclude older studies applying historical standards [27]
• Demographic factors such as age, sex, ethnicity, or occupational status when relevant to the research question [27] [28]
• Setting or context including geographic location, ecosystem type, urbanization level, or specific environmental conditions [27] [30]
• Health or baseline status including pre-existing conditions, vulnerability factors, or baseline health indicators [28] [30]

Table 2: Population Eligibility Criteria Specification with Environmental Examples

Criterion Category	Specification Elements	Environmental Example 1: Chemical Exposure	Environmental Example 2: Ecosystem Intervention
Entity Type	Humans, animals, plants, ecosystems	Adult human populations (>18 years)	Freshwater river ecosystems
Key Characteristics	Age, sex, health status, species	Occupational groups with documented exposure	Systems with documented pre-intervention baseline data
Setting/Context	Geographic, environmental, socioeconomic	Manufacturing facilities using the chemical of interest	Temperate region watersheds
Diagnostic/Status Criteria	Case definitions, health status, ecosystem condition	No pre-existing respiratory conditions	Watersheds with >50% agricultural land use
Special Considerations	Vulnerable subgroups, rare populations	Susceptible subpopulations (e.g., asthmatics)	Systems with endangered aquatic species

Intervention and Exposure Criteria

The intervention or exposure criteria define the environmental agent, intervention, or factor being studied and the specific circumstances of its application or occurrence. For exposure-focused reviews, this includes specifying the type, level, duration, and timing of exposure [29] [30]. For intervention reviews, this includes the specific activities, implementation methods, and delivery mechanisms.

Key elements to specify for interventions/exposures include:

• Type or nature of the intervention/exposure (e.g., specific chemical, restoration technique, policy mechanism) [28] [30]
• Level, intensity, or dose including concentration ranges, magnitude, or application rates [29] [30]
• Timing and duration including when the exposure/intervention occurred and for how long [29] [30]
• Method of delivery or measurement including application techniques or exposure assessment methods [30]
• Context where the intervention/exposure occurs (e.g., occupational, environmental, agricultural) [28]

Review authors should anticipate and plan for variations in interventions discovered during the review process, as important modifications may only become apparent after data collection begins [27]. For complex environmental interventions, it may be helpful to develop a theory of change or conceptual model that identifies the critical components and potential variants of the intervention [32].

Comparator Criteria

The comparator criteria define the reference scenario against which the intervention or exposure is compared. In environmental contexts, comparators may include untreated controls, alternative interventions, background exposure levels, or different population groups [29] [30]. Defining appropriate comparators is essential for interpreting the measured effects and ensuring meaningful comparisons across studies.

Common comparator types in environmental reviews include:

• No intervention controls (e.g., untreated plots, unexposed populations)
• Alternative interventions (e.g., different restoration techniques, varying policy approaches)
• Different exposure levels (e.g., low vs. high exposure, before vs. after regulation)
• Background or reference conditions (e.g., pristine ecosystems, general population exposure)

For exposure studies, Morgan et al. (2018) describe five paradigmatic scenarios for defining comparators that range from exploring the shape of exposure-response relationships when little is known to evaluating specific exposure cut-offs that can be achieved through interventions [29]. The appropriate approach depends on the review context and what is known about the effects of the exposure on the outcome.

Outcome Criteria

Outcome criteria define the endpoints or effects of interest that the review seeks to evaluate. While outcomes typically should not be used to exclude studies (as this may introduce bias), clearly defining outcome domains and specific measures helps structure the synthesis and analysis plan [27] [31]. Cochrane recommends that reviews "include all outcomes that are likely to be meaningful and not include trivial outcomes," with critical and important outcomes "limited in number and include adverse as well as beneficial outcomes" [27].

When defining outcome criteria, consider specifying:

• Outcome domains or categories of effects (e.g., ecological, health, economic, social)
• Specific measures or indicators including validated scales, biomarkers, or observational parameters
• Timing of measurement including relevant follow-up periods or temporal patterns
• Methods of assessment including measurement techniques, equipment, or protocols

For environmental reviews, outcomes often span multiple domains including ecological integrity, human health, socioeconomic impacts, and ecosystem services [19] [32]. Clearly defining how these diverse outcomes will be categorized and prioritized is essential for a coherent synthesis.

Implementation Protocol

Developing and Refining Eligibility Criteria

The process of developing eligibility criteria should begin during protocol development and involves iterative refinement to ensure the criteria are unambiguous and applicable to the evidence base [19] [18]. The criteria should be drafted based on the review question and then tested against a sample of known relevant and irrelevant studies to identify potential ambiguities or oversights.

A recommended process includes:

• Draft initial criteria based on the structured question (PICO/PECO) and conceptual framework
• Identify known relevant studies from exploratory searches and previous knowledge
• Test criteria application with the review team to identify inconsistencies or ambiguities
• Refine criteria language to improve clarity and consistency of application
• Pilot test with sample of search results to validate discriminative ability
• Finalize and document in the review protocol with examples and rationales

During protocol development, review authors should plan how different variants of PECO elements will be grouped for synthesis, as this will inform the specificity of the eligibility criteria [27]. This involves considering whether certain population characteristics (e.g., age, disease severity) or intervention variants (e.g., dosage, delivery method) should be treated as separate eligibility criteria or as subgroups for analysis.

Eligibility Screening Process

The eligibility screening process typically involves multiple stages of assessment with increasing rigor to efficiently manage large volumes of search results [19] [33]. Environmental evidence syntheses often retrieve thousands of references, making a structured screening process essential for managing workload while minimizing errors [18].

Diagram 1: Eligibility Screening Process Flow. The systematic screening process involves duplicate removal, title/abstract screening, full-text retrieval, and final eligibility assessment.

The screening process should be conducted by at least two independent reviewers with a predefined mechanism for resolving disagreements [19] [33] [30]. This dual screening approach reduces the risk of errors and subjective decisions that could introduce bias into the review. Common disagreement resolution methods include consensus discussions between reviewers or arbitration by a third reviewer with relevant expertise [33].

For the title and abstract screening stage, reviewers typically spend only seconds on each reference making quick judgments about potential relevance [33]. Articles categorized as "maybe" or "unclear" should proceed to full-text review to avoid prematurely excluding potentially relevant evidence. The full-text review stage involves more thorough examination of the complete article to make final eligibility determinations, with detailed documentation of exclusion reasons for all excluded studies [33] [32].

Pilot Testing and Validation

Before implementing the full screening process, the eligibility criteria and screening procedures should be pilot tested using a sample of references to validate their application and identify needed refinements [19] [18]. Pilot testing serves multiple important functions in ensuring a robust screening process.

Pilot testing helps to:

• Validate classification accuracy by checking if criteria correctly identify known relevant and irrelevant studies
• Estimate screening timeline by measuring how long the process takes with representative samples
• Assess inter-reviewer agreement by calculating consistency between independent reviewers
• Identify ambiguous criteria that lead to inconsistent application or frequent "unclear" judgments
• Train review team members in consistent interpretation and application of the criteria

The pilot test should use a representative sample of references drawn from preliminary searches, including both known relevant studies (from benchmark lists) and a random sample of search results [19] [18]. If agreement between reviewers is poor (e.g., kappa < 0.6), the eligibility criteria or screening instructions should be revised and retested until acceptable consistency is achieved [18].

Research Reagent Solutions Toolkit

Table 3: Essential Tools and Resources for Implementing Eligibility Screening

Tool Category	Specific Tools/Solutions	Primary Function in Eligibility Screening
Reference Management Software	EndNote, Mendeley, Zotero	Store, organize, and deduplicate search results; facilitate team collaboration
Systematic Review Software	Covidence, EPPI-Reviewer, Rayyan	Support screening workflow management, dual review processes, and conflict resolution
Screening Form Platforms	Microsoft Forms, Google Forms, Qualtrics	Create standardized screening forms with predefined eligibility criteria
Inter-Rater Reliability Analysis	Cohen's Kappa calculator, Percentage agreement	Measure consistency between reviewers and validate screening protocol
Document Management	Cloud storage ( institutional servers), PDF organizers	Store and provide access to full-text articles for the review team
Communication Platforms	Slack, Microsoft Teams, email	Facilitate discussion of screening conflicts and protocol questions

Documentation and Reporting Standards

Complete documentation of eligibility criteria and the screening process is essential for transparency, reproducibility, and credibility of the systematic review [33] [32]. The PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) statement provides comprehensive guidance on reporting standards, including the eligibility criteria and study selection process [33].

Documentation should include:

• Full eligibility criteria with explicit definitions and examples of included/excluded studies [31] [32]
• Screening procedures including the number of reviewers, process for resolving disagreements, and software tools used [33] [30]
• Flow diagram illustrating the results of the screening process at each stage, typically following PRISMA format [33] [32]
• List of excluded studies with primary reasons for exclusion at the full-text stage [33]
• Inter-rater reliability statistics for both title/abstract and full-text screening stages [33]

Any deviations from the published protocol must be documented and justified in the final review, as post-hoc changes to eligibility criteria can introduce bias if not properly transparent [27] [32]. The Collaboration for Environmental Evidence (CEE) provides specific reporting standards for environmental evidence syntheses that complement general PRISMA guidance [18] [32].

A comprehensive search is a systematic effort to find all available evidence to answer a specific research question. The validity and usefulness of a systematic review hinges on a high-quality comprehensive search that is transparent, replicable, and minimizes bias [34]. For systematic reviews in environmental management, this process is critical given the interdisciplinary nature of the field and the scattered evidence across ecological and social science domains [35]. This protocol provides detailed methodologies for designing and executing a comprehensive search strategy that integrates bibliographic database searching with extensive grey literature and supplementary search methods, specifically contextualized for environmental management research.

Core Components of a Comprehensive Search

A robust search strategy for systematic reviews incorporates multiple complementary approaches to maximize retrieval of relevant studies. The three core components include bibliographic database searching, systematic grey literature searching, and supplementary search techniques. Each component serves a distinct purpose in mitigating different forms of publication bias and ensuring comprehensive coverage [34] [36].

Table 1: Core Components of a Comprehensive Search Strategy

Component	Primary Purpose	Key Sources	Environmental Management Considerations
Bibliographic Databases	Identify peer-reviewed literature using structured search syntax	Discipline-specific databases (e.g., Web of Science, Scopus, CAB Abstracts, GreenFILE)	Must cover interdisciplinary sources spanning ecological, social, and policy dimensions [35]
Grey Literature	Minimize publication bias; access policy documents, reports, unpublished data	Organizational websites, government publications, theses, clinical trials registries	Particularly valuable for policy-relevant documents and local implementation evidence [37] [36]
Supplementary Searching	Identify studies missed by database searches; validate search strategy	Citation tracking, reference list scanning, contact with experts	Crucial for identifying context-specific evidence across different environmental governance levels [36]

Database Search Methodology

Developing the Search Strategy

The development of a systematic search strategy involves a structured process from conceptualization to execution:

• Question Formulation: Begin with a clearly defined research question, typically using PICO (Population, Intervention, Comparison, Outcome) or adapted frameworks for environmental management questions [38].
• Keyword Development: Identify key concepts from the research question and develop comprehensive keyword lists including synonyms, related terms, and variant spellings. For environmental topics, this may include scientific and common names for species, different terminology for interventions across regions, and varied policy terminology [35].
• Subject Headings: Utilize controlled vocabulary (e.g., MeSH in MEDLINE, thesaurus terms in other databases) specific to each database to ensure consistent retrieval of relevant concepts [38].
• Search Syntax: Combine terms using Boolean operators (AND, OR, NOT) with appropriate nesting using parentheses. Implement proximity operators, truncation, and phrase searching as supported by individual databases [38].

Search Strategy Example

The following example illustrates a structured search strategy for a research question on "the effectiveness of riparian buffer zones for improving water quality":

Database Selection for Environmental Management

Table 2: Key Bibliographic Databases for Environmental Management Systematic Reviews

Database	Subject Focus	Platform Options	Coverage Notes
Web of Science Core Collection	Multidisciplinary science	Clarivate	Includes Science Citation Index, Social Sciences Citation Index, Arts & Humanities Citation Index
Scopus	Multidisciplinary	Elsevier	Extensive coverage of peer-reviewed journals with citation tracking
CAB Abstracts	Applied life sciences	Ovid, CAB Direct	Particularly strong in agriculture, environment, and applied ecology
GreenFILE	Environmental topics	EBSCO	Focuses on human impact on environment
Environment Complete	Environmental sciences	EBSCO	Deep coverage in environmental policy, ecosystems, and resources
APA PsycINFO	Behavioral sciences	Ovid, EBSCO	Relevant for human dimensions of environmental management

Grey Literature Search Protocol

Defining and Sourcing Grey Literature

Grey literature is defined as literature "produced on all levels of government, academics, business and industry in print and electronic formats, but which is not controlled by commercial publishers" [37]. In environmental management, grey literature is particularly valuable for accessing policy documents, implementation guides, program evaluations, and local context evidence that may not appear in peer-reviewed literature [37].

A systematic approach to grey literature searching should incorporate four complementary strategies [37]:

• Grey literature databases (e.g., ProQuest Dissertations & Theses Global)
• Customized Google search engines
• Targeted website searching
• Consultation with content experts

Implementation Protocol for Grey Literature Searching

• Step 1: Identify Relevant Organizations: Create a list of governmental agencies, non-governmental organizations, research institutions, and professional associations relevant to the environmental management topic. For example, a review on protected area management might include IUCN, UNEP, WWF, The Nature Conservancy, and relevant national park services [36].

• Step 2: Develop Grey Literature Search Plan: Document specific websites to be searched, search terms to be used, date restrictions, and languages. The plan should be developed a priori to minimize bias [37].

• Step 3: Execute Structured Website Searching: Use site-specific searches (e.g., using "site:example.org" syntax in Google) with targeted search terms. Search multiple sections of websites (publications, reports, resources) where relevant documents may be located [36].

• Step 4: Document Search Process: Record dates searched, URLs, specific search terms used, and number of results identified. Screen items based on abstracts, executive summaries, or tables of contents when full text is not immediately available [37].

• Step 5: Manage Grey Literature Records: Download and store all potentially relevant documents with full citation information. Maintain a tracking spreadsheet documenting search dates, sources, and screening decisions.

Table 3: Grey Literature Sources for Environmental Management Reviews

Source Type	Examples	Access Method	Notes
Theses and Dissertations	ProQuest Dissertations & Theses Global	Database subscription	Valuable for comprehensive research projects [36]
Government Documents	EPA reports, USDA publications, national environmental agency websites	Targeted website searching, specialized portals	Policy documents, technical reports, and program evaluations
Conference Proceedings	Conference Proceedings Citation Index	Database subscription	Emerging research, preliminary findings [36]
Preprint Servers	EarthArXiv, Preprints.org	Open access platforms	Growing importance in rapidly evolving fields [36]
Organizational Reports	IUCN, WRI, WWF, academic research centers	Direct website searching	Implementation guides, case studies, white papers
Trial Registries	ISRCTN Registry, ClinicalTrials.gov	Registry websites	For intervention studies with environmental outcomes [36]

Supplementary Search Methods

Supplementary search methods are essential for identifying studies not captured through database searches and validating the comprehensiveness of the primary search strategy [36].

• Backward Citation Searching: Review reference lists of included studies and relevant systematic reviews to identify earlier publications.
• Forward Citation Searching: Use citation indexes (Web of Science, Scopus, Google Scholar) to identify papers that have cited key studies included in the review.

Handsearching and Expert Consultation

• Handsearching: Selectively browse key journals in environmental management that may not be completely indexed in major databases.
• Contact with Experts: Reach out to researchers, practitioners, and policymakers in the field to identify ongoing, unpublished, or in-press studies [34].

Search Strategy Workflow and Documentation

Comprehensive Search Workflow

The following diagram illustrates the complete workflow for designing and executing a comprehensive search strategy:

Documentation Requirements

Comprehensive documentation is essential for transparency and reproducibility. Documentation should include [34]:

• For database searches: Database names, platforms, date of search, complete search syntax, and limits applied
• For grey literature: Specific sources searched, search terms used, dates of search, and any restrictions applied
• For supplementary methods: Citation searching details (base articles, databases used), journals handsearched, experts contacted

Reporting should follow PRISMA-S guidelines, which provide specific standards for reporting search methods in systematic reviews [34].

Experimental Protocol: Validating Search Strategy Performance

Peer Review of Search Strategies

The Peer Review of Electronic Search Strategies (PRESS) framework provides a structured approach for validating search strategies:

• Step 1: Develop preliminary search strategy for one database
• Step 2: Submit strategy to librarian or information specialist for peer review
• Step 3: Reviewer assesses translation of research concepts, Boolean logic, spelling, syntax, and filters
• Step 4: Implement reviewer feedback and finalize strategy
• Step 5: Translate finalized strategy for other databases [34]

Benchmarking Against Known Relevant Studies

Create a test set of known relevant publications (identified through scoping searches) and verify that the search strategy retrieves these records:

• Step 1: During scoping phase, identify 10-20 key publications that should be included in the review
• Step 2: After developing search strategy, test retrieval of these benchmark articles
• Step 3: If articles are missed, analyze reasons and modify strategy accordingly
• Step 4: Document benchmark testing results in the review methods [38]

Research Reagent Solutions: Essential Tools for Systematic Searching

Table 4: Essential Tools and Resources for Comprehensive Searching

Tool Category	Specific Tools	Function	Application in Environmental Management
Search Translation Tools	Polyglot Search Translator, TERA	Assist in translating search syntax between database interfaces	Maintains search consistency across multidisciplinary databases [38]
Reference Management	EndNote, Zotero, Mendeley	Store, deduplicate, and manage search results	Essential for handling large result sets from multiple sources
Grey Literature Guides	Grey Matters (CADTH), Grey Literature Guide (University of Toronto)	Provide organized sources for grey literature identification	Targeted access to environmental policy documents [36]
Search Filters	ISSG Search Filters Resource, CADTH Search Filters	Pre-tested search strategies for study designs	Can be adapted for environmental intervention studies [38]
Documentation Templates	PRISMA-S checklist, Cochrane search documentation template	Standardize reporting of search methods	Ensures transparent reporting of complex multidisciplinary searches [34]

A comprehensive search strategy for systematic reviews in environmental management requires careful integration of bibliographic database searching, systematic grey literature retrieval, and supplementary search methods. The protocols outlined in this document provide a structured approach to designing, executing, and documenting such searches, with particular attention to the interdisciplinary nature of environmental evidence. By implementing these methods, researchers can maximize retrieval of relevant evidence while maintaining transparency and reproducibility, thereby strengthening the foundation for evidence-based environmental management and policy decisions.

Planning Study Selection, Data Extraction, and Quality Assessment Processes

Systematic reviews in environmental management provide a rigorous and transparent framework for synthesizing evidence to inform policy and practice. The credibility and reliability of a systematic review are fundamentally anchored in the meticulous planning of its core processes: study selection, data extraction, and quality assessment. Predefining these methodologies in a detailed protocol, framed within the context of environmental evidence synthesis, minimizes bias, ensures reproducibility, and enhances the utility of the review's findings [39] [18]. This document outlines detailed application notes and experimental protocols for these critical stages, providing researchers with a structured approach for conducting robust evidence syntheses.

Application Notes: Core Principles and Definitions

A systematic review protocol serves as a detailed work plan, outlining the rationale, objectives, and explicit methods for the review before it begins [39]. Making this protocol publicly available, through registries such as PROSPERO or the Open Science Framework (OSF), promotes transparency, reduces duplication of effort, and guards against selective reporting bias [39] [5].

Within environmental evidence, reviews often address PICO-type questions (Population, Intervention, Comparator, Outcome) to determine the effects of an intervention [18]. The eligibility criteria and all subsequent processes flow logically from this question structure. It is critical to distinguish between different quality assessment concepts. Risk-of-bias tools evaluate how methodological flaws might affect a specific study's findings, while critical appraisal tools assess broader methodological quality, relevance, and applicability [40]. Reporting guidelines (e.g., from the EQUATOR network) concern the quality of writing and completeness of reporting and should not be used for methodological quality assessment [40].

Experimental Protocols

Protocol I: Study Selection and Eligibility Screening

The study selection process, often called eligibility screening, determines the scope of evidence that will answer the review question. A transparent and objective process is vital to reduce the risk of introducing errors or bias [18].

3.1.1 Preliminary Phase: Reference Management and Deduplication Before screening, assemble all search results into a bibliographic reference management tool (e.g., Covidence, Rayyan, Eppi-Reviewer) that allows for efficient project management and recording of screening decisions [18]. An essential first step is the identification and removal of duplicate articles to prevent double-counting of data and unnecessary screening effort. While many tools offer automated "fuzzy matching," this process should be monitored to avoid inadvertently removing non-duplicate records [18].

3.1.2 Defining Eligibility Criteria Eligibility criteria should be pre-specified, explicit, and directly reflective of the review's key question elements [18]. For a PICO-type question in environmental management, this involves specifying the required Population, Intervention, Comparator, and Outcomes. Criteria should be kept short and explicit; an article is included only if it meets all inclusion criteria and is excluded if it fails to meet one or more [18]. The table below provides a structured approach to defining these criteria.

Table 1: Framework for Developing Eligibility Criteria in Environmental Systematic Reviews

Criterion Category	Description	Example from an Environmental Intervention Review
Population/Subject	The specific organisms, ecosystems, or environmental systems under investigation.	Terrestrial ecosystems in East Asia; Soil microbial communities.
Intervention/Exposure	The environmental management action, policy, or stressor being studied.	Implementation of the "Conversion of Cropland to Forest Programme" [18].
Comparator	The alternative against which the intervention is compared.	Conventional agricultural land use; Other conservation programs.
Outcomes	The measured environmental or socioeconomic endpoints.	Soil organic carbon content; Water quality metrics; Household income.
Study Types	The acceptable designs for primary research.	Randomized controlled trials; Cohort studies; Before-and-after studies.

3.1.3 The Screening Process Screening should be conducted in duplicate by independent reviewers to minimize errors and bias [41] [18]. This process involves two stages:

• Title and Abstract Screening: Reviewers independently assess citations against the eligibility criteria. A pilot screening of a small percentage of studies is recommended to calibrate the team and refine criteria if needed [41] [18].
• Full-Text Screening: The full-text articles of citations that pass the first stage are retrieved and assessed independently by reviewers. At this stage, specific reasons for exclusion must be documented for every article [41]. Disagreements at either stage are typically resolved by consensus or by a third reviewer [41].

The entire selection process should be tracked and reported using a PRISMA flow diagram, which records the number of studies identified, screened, excluded, and included, along with the reasons for exclusion at the full-text stage [41].

Figure 1: Study selection workflow demonstrating the multi-stage, dual-reviewer process.

Protocol II: Data Extraction

Data extraction is the process of capturing key characteristics and results from included studies in a structured and standardized form [42] [43]. This structured data forms the basis for evidence tables, synthesis, and conclusions.

3.2.1 Planning and Tool Selection A data extraction form or template should be created a priori. The choice of tool involves a trade-off between functionality, ease of use, and cost. Systematic review software like Covidence is highly recommended as it is designed for dual extraction, automatically highlights discrepancies, and houses the entire review process [42]. Alternatively, spreadsheet software (e.g., Excel, Google Sheets) offers easy customization and familiarity but requires manual discrepancy checking [42].

3.2.2 Data Extraction Fields The specific data to extract should be directly relevant to answering the systematic review question. Consultation of similar published reviews can help identify common fields. The following table outlines typical data points for an environmental intervention review.

Table 2: Core and Specialized Data Extraction Fields for Systematic Reviews

Category	Data Fields	Field Description and Purpose
Core Study Identification	Author, Year, Title, DOI	Basic citation information for referencing.
Study Methodology	Study Design, Location, Duration	Key characteristics that influence the validity and context of the findings.
PICO Elements	Population Details, Intervention/Exposure Details, Comparator, Outcomes Measured	Directly maps to the review question and eligibility criteria.
Quantitative Results	Sample Size, Effect Sizes, Confidence Intervals, Pre/Post-test Data, Statistical Tests	Essential for any quantitative synthesis or meta-analysis.
Qualitative & Contextual Data	Theoretical Framework, Data Collection Methods, Role of Researcher, Key Themes	Critical for qualitative evidence synthesis [42].

3.2.3 The Extraction Process Like screening, data extraction should be performed in duplicate by at least two independent reviewers to minimize transcription errors and subjective interpretations [42] [41]. The team should be trained on the extraction categories, and the form should be piloted on a small sample of studies to ensure it captures the intended data consistently [42]. Discrepancies between extractors are reviewed and resolved through discussion or by a third reviewer.

Protocol III: Quality Assessment (Critical Appraisal and Risk of Bias)

Assessing the methodological quality and risk of bias of included studies is crucial because the conclusions of a systematic review are only as reliable as the studies it contains [44] [45].

3.3.1 Selecting an Appropriate Tool The most critical step is selecting a tool that was created and validated for the specific study designs included in the review [44]. Using a tool designed for randomized controlled trials to appraise a cohort study, for example, would be inappropriate. The table below summarizes widely used tools.

Table 3: Quality and Risk of Bias Assessment Tools by Study Design

Study Design	Recommended Tools	Primary Focus and Key Characteristics
Randomized Controlled Trials (RCTs)	Cochrane Risk of Bias (ROB) 2.0 [44] [45]	Assesses specific sources of bias (e.g., randomization, missing data); preferred for meta-analysis.
Non-Randomized Studies	Newcastle-Ottawa Scale (NOS) [44]	Assesses selection, comparability, and outcome for cohort/case-control studies.
Mixed-Methods Studies	Mixed Methods Appraisal Tool (MMAT) [45]	Appraises qualitative, quantitative, and mixed methods studies.
Systematic Reviews	AMSTAR Checklist [44]	A measurement tool for assessing the methodological quality of systematic reviews.
General Critical Appraisal	CASP Checklists [44] [45]	A series of checklists for various designs (RCT, cohort, qualitative, etc.) focusing on validity and relevance.

3.3.2 The Assessment Process Quality assessment is typically conducted by at least two reviewers independently [44]. The process involves:

• Selecting the Tool: Choose the tool that matches the study design.
• Applying the Checklist: Reviewers use the tool's criteria to judge different aspects of the study's methodology.
• Making Judgments: For risk-of-bias tools, judgments are often categorized as "Low," "High," or "Unclear" risk of bias [40]. Critical appraisal tools may use similar categories or scores.
• Resolving Disagreements: As with screening and extraction, conflicts are resolved through consensus.

It is important to note that a well-reported study (i.e., one that follows reporting guidelines like PRISMA or STROBE) is not necessarily a well-conducted study, and vice versa. Therefore, reporting guidelines should not be used as a substitute for methodological quality assessment [40].

Figure 2: Quality assessment workflow leading to the evaluation of the overall body of evidence.

The Scientist's Toolkit: Research Reagent Solutions

This section details the essential "materials" and tools required to execute the protocols described above.

Table 4: Essential Tools and Resources for Systematic Review Execution

Tool/Resource	Function/Purpose	Example Platforms & Notes
Protocol Registry	Publicly archives the review plan to ensure transparency and prevent duplication.	PROSPERO, Open Science Framework (OSF) [39] [5].
Reference Management & Screening Software	Manages citations, removes duplicates, and facilitates the dual-reviewer screening process.	Covidence, Rayyan, Eppi-Reviewer [42] [18].
Data Extraction Tool	Provides a structured form for collecting and exporting standardized data from studies.	Covidence, Microsoft Excel, Google Sheets [42].
Quality Assessment Tools	Validated checklists to appraise methodological quality and risk of bias of individual studies.	Cochrane ROB 2.0, Newcastle-Ottawa Scale, CASP, MMAT [44] [45].
Reporting Guideline	A checklist to ensure complete and transparent reporting of the final systematic review manuscript.	PRISMA 2020 Statement and Flow Diagram [41].

Selecting Tools for Screening and Management (e.g., Covidence, Rayyan)

Within the rigorous framework of environmental management research, systematic reviews are paramount for synthesizing evidence to inform policy and practice. The reliability and efficiency of these reviews are heavily influenced by the tools used for study screening and management. This article provides detailed application notes and protocols for selecting and utilizing dedicated software tools, focusing on Covidence and Rayyan, to enhance the methodological quality and transparency of systematic reviews in this field.

Tool Comparison and Selection Guide

Selecting the appropriate software is a critical first step in planning a systematic review. The table below provides a structured comparison of two prominent tools based on key operational criteria relevant to environmental research.

Table 1: Comparative overview of systematic review management tools.

Feature	Covidence	Rayyan
Primary Use Case	End-to-end systematic review management [46]	Expedited abstract and title screening [47]
Screening Process	Structured, two-step (title/abstract & full-text) with conflict resolution [46]	Rapid exploration and filtering of search results [47]
Keyword Highlighting	Yes, with phrase matching and word stemming [48]	Not specified in search results
Conflict Resolution	Built-in, blinded process for resolving reviewer disagreements [46]	Not specified in search results
Data Extraction	Customizable forms supporting dual extraction [46] [42]	Not specified in search results
Interrater Reliability Metric	Calculates Cohen's kappa (κ) [46]	Not specified in search results
Automation Features	Limited	"Suggestions" and "hints" based on a prediction model after initial screening [47]
Cost Model	Subscription-based (often provided by institutional libraries) [42]	Freemium model [47]

Key Selection Criteria

• Review Scope and Complexity: For complex environmental reviews involving full-text review, data extraction, and quality assessment, Covidence provides a more integrated, end-to-end platform [46]. For rapid scoping or initial screening of large literature volumes, Rayyan's interface is highly efficient [47].
• Collaboration Needs: Both tools support collaboration, but Covidence offers a structured workflow for independent dual screening and formal conflict resolution, which is essential for reducing bias [46].
• Budget and Institutional Access: Investigate institutional subscriptions, as many universities provide access to Covidence [42]. Rayyan offers a free tier, making it accessible for pilots or smaller projects [47].

Experimental Protocols for Tool Application

Protocol 1: Initial Setup and Pilot Screening

This protocol ensures the review team is calibrated and the tool is configured correctly before full-scale screening begins.

• Upload and Deduplicate: Import search results from bibliographic databases (e.g., RIS, CSV format) into the selected software. Use the tool's automatic deduplication feature, but manually verify a sample for accuracy.
• Configure Eligibility Criteria: Input the pre-defined inclusion and exclusion criteria into the tool. In Covidence, these are displayed during screening [46]. In Rayyan, use labels or tags to reflect criteria.
• Implement Keyword Highlights: To increase screening speed and consistency, input key inclusion/exclusion terms. For example, in Covidence, adding "randomized controlled trial" will highlight this phrase, while adding "random" as a single word might also highlight "randomized," "randomly," and "randomization" due to its stemming algorithm [48].
• Pilot Test Screening: Both reviewers independently screen a random sample of 50-100 titles/abstracts using the configured tool.
• Calculate and Review Agreement: The tool (e.g., Covidence) will calculate the inter-rater reliability (Cohen's kappa). A kappa below 0.6 indicates a need for further discussion and refinement of the eligibility criteria [46].
• Refine Process: Resolve conflicts through discussion. If disagreements persist, clarify and refine the screening protocol and tool configuration before proceeding.

Protocol 2: Full Screening and Conflict Resolution Workflow

This protocol outlines the standard operating procedure for the main screening phase, incorporating tool-specific features to ensure rigor.

• Independent Dual Screening: Two reviewers blindly and independently assess each citation, first at the title/abstract level, then the full text, making include/exclude decisions [46] [41].
• Automatic Sorting: The software automatically sorts citations based on decisions.
  • Agreement to Include/Exclude: The citation moves to the next stage or is excluded [46].
  • Conflict: The citation is moved to a "conflict resolution" queue [46].
• Resolve Conflicts: Reviewers meet to discuss conflicts. The tool's interface displays each reviewer's decision and reason. If consensus cannot be reached, a third reviewer adjudicates [46].
• Document Reasons for Exclusion: At the full-text stage, reviewers must select a pre-specified reason for exclusion for every excluded study. This is critical for the PRISMA flow diagram [46] [41].
• Export for Reporting: Use the tool's auto-population feature to generate a PRISMA flow diagram documenting the screening process [46].

The following workflow diagram visualizes this multi-stage screening and conflict resolution process.

Protocol 3: Data Extraction and Quality Assurance

This protocol transitions from screening to data collection, a phase where Covidence offers specific functionality.

• Develop a Custom Data Extraction Form: Based on the PICO framework and review objectives, create a structured form within the tool. Include fields for study characteristics, population, intervention/exposure, comparators, outcomes, and study validity [42].
• Pilot the Form: Test the form on 2-3 included studies and refine it to ensure it captures all necessary data unambiguously.
• Perform Dual Data Extraction: Two reviewers independently extract data from all included studies using the form. Using software like Covidence, reviewers work in parallel with the PDF and extraction form side-by-side [42].
• Consensus and Error Checking: The tool highlights discrepancies between the two extractors. Reviewers then meet to resolve these differences, referring back to the original source document to ensure accuracy [46] [42].
• Export Data: Once consensus is reached, export the finalized data in a usable format (e.g., CSV) for analysis [46].

The Scientist's Toolkit: Research Reagent Solutions

Beyond software, conducting a high-quality systematic review requires a suite of methodological "reagents."

Table 2: Essential methodological components for a rigorous systematic review.

Item	Function
Pre-registered Protocol (e.g., in PROCEED)	A publicly available, pre-defined plan that outlines the review's objectives and methods, reducing reporting bias and duplication of effort [3].
PRISMA 2020 Checklist	A 27-item checklist for transparently reporting systematic reviews, ensuring all critical methodological details are included [41] [24].
PICO Framework	A structured tool (Population, Intervention, Comparator, Outcome) to formulate a focused research question and define eligibility criteria [41].
Boolean Search Strings	Combinations of search terms using operators (AND, OR, NOT) tailored to bibliographic databases (e.g., MEDLINE, Embase) to ensure a comprehensive and reproducible search [3] [41].
Cohen's Kappa (κ)	A statistical measure of inter-rater reliability (agreement between reviewers) during screening, used to calibrate the team and ensure consistency [46] [41].

The selection and proficient application of specialized tools like Covidence and Rayyan are critical for enhancing the efficiency, transparency, and overall validity of systematic reviews in environmental management. By adhering to the detailed application notes and standardized experimental protocols outlined in this article, researchers can navigate the complexities of evidence synthesis with greater confidence and rigor. This structured approach ensures that the resulting synthesis provides a reliable foundation for environmental decision-making and policy development.

Navigating Common Pitfalls and Enhancing Protocol Rigor

Systematic reviews are foundational to evidence-based practice, designed to minimize bias through a structured, objective, and reproducible methodology [6]. In fields like medicine, they represent the pinnacle of the evidence hierarchy, driving advancements in research and practice [6]. The core distinction of a systematic review lies in its rigorous protocol—which includes a well-defined question, a comprehensive literature search, explicit inclusion and exclusion criteria, a critical quality assessment of primary studies, and a systematic synthesis of findings [6] [49]. This process stands in stark contrast to unstructured narrative reviews, which are more susceptible to author bias and are less comprehensive [49].

Within environmental management and conservation, the adoption of systematic reviews has been promoted as a means to integrate robust science into policy and practice, helping decision-makers navigate vast and sometimes conflicting research findings [49] [50]. However, a significant gap persists between the ideal methodology and common practice. A review of 43 systematic reviews in conservation revealed that many fail to achieve true systematic rigor; only 23 drew concrete conclusions relevant to management, and most covered only a small fraction of their intended geographic and taxonomic scope [49]. This gap undermines the reliability of evidence and its utility for critical environmental decision-making. This article analyzes the causes of this gap and provides detailed application notes and protocols to help researchers achieve true systematic rigor.

Quantitative Evidence of the Gap in Environmental Systematic Reviews

An analysis of the existing body of environmental systematic reviews reveals specific areas where methodological rigor is frequently compromised. The table below summarizes key quantitative findings from a study of 43 conservation-focused systematic reviews.

Table 1: Quantitative Evidence of Gaps in Conservation Systematic Reviews [49]

Metric	Finding	Implication
Reviews with management implications	23 out of 43 (53%)	Nearly half of the reviews did not yield concrete conclusions for managers.
Reviews on practical on-the-ground interventions	35%	A majority focused on policy, indicating a potential misalignment with practitioner needs.
Median geographic coverage	13% of relevant countries	Reviews often fall far short of their stated geographic aims, limiting generalizability.
Median taxonomic coverage	16% of relevant taxa	Similarly, taxonomic breadth is often not achieved, biasing the evidence base.
Primary studies excluded due to quality	88%	A vast majority of identified evidence is excluded, often due to deficiencies in study design.

The data indicates that overly ambitious breadth in a review's scope (geographically or taxonomically) is a key factor associated with a lower likelihood of producing management-relevant implications [49]. Furthermore, the exclusion of the vast majority of primary studies due to methodological weaknesses highlights a critical lack of high-quality, appropriately designed primary research in the environmental field [49].

Root Causes: Why Environmental Reviews Fail to Be Truly Systematic

Several interconnected challenges explain why many environmental reviews fail to achieve full systematic status.

• Resource and Timeliness Constraints: Conducting a full systematic review is a resource-intensive and time-consuming process [50]. Policy-makers often operate under strict deadlines that do not align with the timeline required for a rigorous review [50]. This pressure can lead to the adoption of "rapid review" methodologies, which sacrifice comprehensiveness and rigor for speed.
• Poorly Formulated Research Questions: A systematic review must be built upon a clear, focused, and answerable research question [6]. Many environmental reviews begin with questions that are too broad or are not framed in a way that is usable for a systematic process. A question that is not co-developed with end-users may lack relevance to on-the-ground managers, leading to reviews that, while methodologically sound, are never utilized in practice [49] [50].
• Insufficient and Non-Transparent Search Strategies: A cornerstone of systematic methodology is a comprehensive and reproducible search strategy that minimizes publication bias [6]. Common failures include searching too few databases, neglecting the gray literature (e.g., government and consultancy reports), and failing to document the search strategy fully [49] [50]. This can result in an unrepresentative and biased body of evidence for synthesis.
• Inconsistent Application of Quality Assessment: A critical step that distinguishes systematic reviews from other review types is the formal assessment of the methodological quality and potential for bias in included primary studies [6]. Many environmental reviews either omit this step entirely or apply quality criteria inconsistently, undermining the validity of their conclusions [49].

Application Notes and Experimental Protocols for Robust Systematic Reviews

To bridge the identified gap, researchers must adhere to rigorous, pre-defined protocols. The following section outlines detailed methodologies for key stages of the systematic review process.

Protocol Formulation and Question Definition

A detailed, pre-published protocol is non-negotiable for a true systematic review. It minimizes reviewer bias and ensures transparency and reproducibility.

• Co-Production of the Review Question: Actively engage policy-makers and other stakeholders in defining the review question [50]. This ensures the question addresses evidence needs directly relevant to decision-making, increasing the likelihood of the review's uptake and impact.
• Utilize a Structured Framework: Employ frameworks like PICO (Population, Intervention, Comparator, Outcome) or its extensions to structure the question clearly [6]. For example:
  • Population: A specific threatened species or ecosystem.
  • Intervention: A specific management action (e.g., controlled burning).
  • Comparator: Alternative management actions or no action.
  • Outcome: A measurable outcome (e.g., population size, species richness).
• Develop a Conceptual Model: Co-developing a conceptual model or theory of change with stakeholders can be invaluable for ensuring a shared understanding of the scope and making explicit any technical terms or assumed relationships [50].

The diagram below visualizes the core workflow for establishing a rigorous systematic review protocol.

Comprehensive Literature Search and Screening Protocol

A systematic and documented search strategy is crucial for minimizing selection bias.

• Information Sources and Search Strategy:
  • Database Selection: Search multiple bibliographic databases (at least two are recommended) such as PubMed, EMBASE, Web of Science, and Google Scholar, tailored to the research topic [6]. Environment-specific databases (e.g., the Collaboration for Environmental Evidence library) should be included.
  • Gray Literature: Actively search for gray literature, including governmental reports, theses, and unpublished data, to mitigate publication bias [50]. This may involve directly contacting experts and relevant organizations.
  • Search Terms: Develop a structured search string using Boolean operators (AND, OR, NOT) and, where available, controlled vocabulary like MeSH terms [6]. The search strategy should be trialled and refined.
• Study Selection and Screening:
  • Use Reference Management Software: Tools like EndNote, Zotero, or Mendeley should be used to manage citations and remove duplicates [6].
  • Structured Screening: Employ a two-stage screening process (title/abstract followed by full-text) against pre-defined inclusion/exclusion criteria, as outlined in the protocol.
  • Use Screening Tools: Leverage specialized tools like Rayyan or Covidence to streamline the screening process, allowing for blind collaboration between multiple reviewers [6].

Table 2: Key Research Reagent Solutions for Systematic Reviews

Tool Name	Type	Primary Function in Systematic Review
Covidence [6]	Web-based Software	Streamlines title/abstract screening, full-text review, and data extraction through a collaborative interface.
Rayyan [6]	Web-based Software	Assists in the screening phase by allowing collaborative inclusion/exclusion and suggesting criteria.
EndNote [6]	Reference Manager	Manages citations, removes duplicates, and integrates with word processors for bibliography creation.
PICO Framework [6]	Methodological Framework	Provides a structured approach to formulating a focused and answerable research question.
Cochrane Risk of Bias Tool [6]	Quality Assessment Tool	A widely used tool for assessing the methodological quality and risk of bias in randomized trials.

Data Extraction and Quality Assessment Protocol

This phase transforms the included studies into a synthesized body of evidence.

• Standardized Data Extraction: Use a pre-piloted, standardized data extraction form to ensure consistent capture of information from each study [6]. Extract details on study design, population, intervention, outcomes, and results.
• Critical Quality Assessment: Assess the methodological rigor of each included study using a validated tool. The choice of tool depends on the study design:
  • Randomized Controlled Trials: Cochrane Risk of Bias Tool [6].
  • Non-Randomized Studies: Newcastle-Ottawa Scale [6].
  • The results of the quality assessment should inform the synthesis and interpretation of findings.

The following diagram illustrates the core data processing workflow from initial search to final synthesis.

The gap between the ideal of systematic reviews and their common practice in environmental science stems from identifiable and addressable methodological shortcomings. Overcoming challenges related to scope definition, resource constraints, and stakeholder engagement is paramount. By adopting the detailed application notes and rigorous protocols outlined herein—emphasizing co-produced questions, comprehensive and transparent searches, and stringent quality assessment—researchers can produce truly systematic reviews. Such robust syntheses are essential for building a reliable evidence base that can effectively inform and improve environmental management and policy.

Piloting Your Protocol to Refine Eligibility Criteria and Data Extraction Forms

Piloting your systematic review protocol is a critical, yet often overlooked, stage in environmental management research that directly impacts the review's reliability, reproducibility, and efficiency. This process involves testing and refining the study selection criteria and data extraction forms before full implementation, allowing reviewers to identify ambiguities, inconsistencies, and practical challenges early in the process. In environmental science, where interdisciplinary studies employ diverse methodologies, terminologies, and data reporting formats, piloting is particularly valuable for achieving consistent application of eligibility criteria across reviewers [51]. This structured approach to protocol development reduces screening errors and extraction inaccuracies that could compromise the validity of the synthesis findings, ultimately strengthening the scientific foundation for evidence-based environmental decision-making.

Designing the Pilot Process

Key Components and Objectives

The pilot process systematically addresses the most challenging aspects of systematic review conduct in environmental management. Table 1 outlines the core components, operational objectives, and specific outcomes for each stage of protocol piloting.

Table 1: Key Components and Objectives of Protocol Piloting

Pilot Component	Operational Objectives	Expected Refinement Outcomes
Eligibility Criteria Piloting	Assess clarity, applicability, and consistency of inclusion/exclusion criteria [51]	Revised criteria definitions; Examples of eligible/ineligible studies; Improved decision rules
Data Extraction Form Piloting	Test completeness, usability, and interpretation of data fields [52]	Added/removed data fields; Clarified field definitions; Improved formatting
Reviewer Consistency Assessment	Measure inter-reviewer agreement and identify sources of disagreement [32]	Enhanced training materials; Clarified guidelines; Consensus procedures
Workflow Efficiency Evaluation	Identify practical bottlenecks in screening and extraction processes [43]	Streamlined procedures; Resource allocation adjustments; Timeline revisions

Experimental Protocol for Piloting

Implementing a structured piloting methodology ensures consistent application and meaningful refinement of the systematic review protocol. The following step-by-step protocol outlines the essential procedures:

• Sample Selection: Randomly select a representative sample of 10-15% of the total search results, ensuring inclusion of studies that potentially test the boundaries of eligibility criteria [51]. The sample should be drawn from the actual search results after deduplication.

• Independent Assessment: Multiple reviewers independently apply the eligibility criteria to the pilot sample of titles and abstracts, recording their decisions and any uncertainties encountered [32]. This process should be conducted in duplicate to reliably assess consistency.

• Blinding Procedures: Reviewers should work independently without consultation during the initial assessment phase to prevent early consensus that might mask ambiguities in the protocol.

• Consensus Meeting: Convene a meeting where reviewers discuss discrepancies, document resolutions, and formally propose modifications to refine the eligibility criteria and data extraction forms [51].

• Form Revision: Update the protocol documents based on consensus meeting outcomes, creating detailed documentation of changes made with justifications for each modification [32].

• Validation Round: Conduct a second pilot round with a new sample of studies (5-10% of total) to validate the refined protocol, measuring whether inter-reviewer agreement has improved substantially.

• Finalization: Incorporate any final adjustments based on the validation round and formally document the final protocol version, ensuring all reviewers are trained on the refined criteria and procedures.

Implementing the Pilot for Eligibility Criteria

Workflow and Process Mapping

The piloting process for eligibility criteria follows a sequential, iterative workflow that systematically identifies and resolves ambiguities. The following diagram illustrates this process, from initial independent screening through to protocol finalization:

Quantitative Assessment and Refinement

Measuring inter-reviewer agreement provides quantitative data to assess the clarity and consistency of eligibility criteria application. The following table outlines common metrics, their interpretation, and appropriate refinement actions based on the results:

Table 2: Inter-Reviewer Agreement Metrics and Refinement Actions

Agreement Metric	Calculation Method	Interpretation Guidelines	Recommended Refinement Actions
Percent Agreement	Percentage of screening decisions where reviewers agree	<70%: Substantial issues70-85%: Moderate issues>85%: Good agreement	For low agreement: Major criteria restructuring with added examples
Cohen's Kappa (κ)	Measures agreement beyond chance [51]	<0: No agreement0-0.2: Slight0.21-0.4: Fair0.41-0.6: Moderate0.61-0.8: Substantial0.81-1: Almost perfect	For fair or below: Clarify ambiguous terms; Add decision rules
Inter-Rater Reliability (IRR)	Intraclass correlation coefficient for continuous variables	<0.5: Poor reliability0.5-0.75: Moderate0.75-0.9: Good>0.9: Excellent	For poor reliability: Standardize measurement approaches

Environmental systematic reviews present unique challenges for eligibility criteria application due to interdisciplinary terminology and methods. For example, a systematic review on the relationship between land use and fecal coliform in streams encountered variability in how researchers from hydrology, public health, and urban planning disciplines defined and reported core concepts [51]. During piloting, the team refined their eligibility criteria through four iterative rounds, ultimately creating specific rules for land use/land cover terminology and direct relationship reporting that improved screening consistency.

Piloting Data Extraction Forms

Form Development and Testing Workflow

Data extraction form piloting follows a structured development and testing sequence to ensure all relevant data can be consistently captured. The following diagram visualizes this iterative workflow:

Data Extraction Field Optimization

Piloting data extraction forms reveals field-specific issues that impact data quality and completeness. Table 3 categorizes common extraction challenges, their implications for synthesis, and evidence-based solutions implemented during piloting:

Table 3: Common Data Extraction Challenges and Refinement Strategies

Extraction Challenge	Impact on Synthesis	Piloting Refinement Strategies
Ambiguous Field Definitions	Inconsistent data coding reduces synthesis validity	Add specific examples; Create detailed codebook with decision rules [52]
Missing Essential Data Fields	Inability to address all review questions; Missing effect modifiers	Add fields identified during pilot; Consult content experts for comprehensive list [32]
Incompatible Data Formats	Inability to combine or compare findings across studies	Standardize response options; Add transformation rules; Use standardized effect measures [52]
Variable Reporting Completeness	Missing data creates synthesis bias	Develop strategies for obtaining missing information; Document assumptions [52]

Systematic reviews in environmental management typically extract both descriptive metadata and quantitative/qualitative outcome data. The piloting process should test extraction of: PICO elements (Population/Problem, Intervention/Exposure, Comparator, Outcomes) [43], study methodology details, contextual factors, and outcome data with associated measures of variance. During piloting, environmental systematic reviews often discover the need to extract discipline-specific methodological details, such as water quality sampling techniques, spatial and temporal scales of analysis, and environmental confounding factors that may not be captured by standard extraction templates.

The Researcher's Toolkit

Research Reagent Solutions for Systematic Review Piloting

Implementing a rigorous piloting process requires specific methodological tools and frameworks. The following table details essential "research reagents" – standardized tools, platforms, and frameworks that support protocol refinement:

Table 4: Essential Research Reagents for Protocol Piloting

Tool/Framework	Primary Function	Application in Piloting
ROSES Reporting Forms [32]	Standardized reporting for systematic reviews	Ensures comprehensive reporting of pilot methods and outcomes
PRISMA-P Protocol Guidelines [52]	Structured protocol development	Guides inclusion of piloting procedures in review protocol
Cochrane Data Collection Form [52]	Template for data extraction	Provides starting point for extraction form development and testing
WebAIM Color Contrast Checker	Accessibility validation for visual materials	Ensures diagrams and presentations meet contrast requirements [53]
AI-Assisted Screening Tools [51]	Machine learning classification	Provides consistency benchmarking; Potential screening assistance post-piloting

Systematic review teams should select tools based on their specific environmental research topic, team size, and resource constraints. For example, larger review teams may benefit from specialized systematic review software that supports collaborative piloting and maintains version control of protocol documents, while smaller teams might effectively use customized spreadsheet-based forms coupled with structured consensus meetings.

Implementation Considerations for Environmental Research

Addressing Interdisciplinary Challenges

Environmental management systematic reviews synthesize evidence across multiple disciplines, creating unique challenges for protocol piloting. Different disciplines often employ similar terminology with different meanings, study the same phenomena at different spatial and temporal scales, and use varied methodological approaches that must be harmonized during the review process [51]. During piloting, review teams should specifically test how reviewers from different disciplinary backgrounds interpret and apply eligibility criteria, as their specialized training may lead to different interpretations of the same criteria.

Successful piloting in interdisciplinary contexts often requires creating a shared conceptual framework or theory of change that explicitly links interventions or exposures to outcomes across disciplinary perspectives [32]. This framework helps align reviewer expectations and provides a reference point for resolving disagreements during consensus meetings. Additionally, including reviewers with complementary disciplinary expertise during piloting enhances the identification of discipline-specific assumptions that might otherwise remain implicit and affect screening consistency.

Documentation and Reporting Standards

Comprehensive documentation of the piloting process is essential for review transparency and reproducibility. The systematic review manuscript should report:

• The number and characteristics of studies included in the pilot sample
• Initial inter-reviewer agreement metrics with justification for the statistics used
• Specific modifications made to eligibility criteria and data extraction forms
• The rationale for each protocol modification based on pilot findings
• Final inter-reviewer agreement metrics after protocol refinement

Environmental Evidence journal expects authors to complete the relevant ROSES forms and include a flow diagram reporting the screening process [32]. These reporting standards help ensure the piloting process is adequately documented and accessible to readers. Additionally, the data extraction form should be included as supplementary material to enhance transparency and facilitate replication [52].

Piloting represents a critical investment in systematic review quality that yields substantial returns through improved reliability, efficiency, and credibility of the final synthesis. By systematically testing and refining the review protocol before full implementation, environmental researchers can address methodological challenges proactively rather than reactively, creating a stronger foundation for evidence-based environmental management and policy decisions.

Strategies for Managing Heterogeneity in Complex Environmental Interventions

Application Notes

Background and Rationale

Complex environmental interventions are characterized by multiple interacting components, diverse implementation settings, and varied effects across different populations and contexts. This heterogeneity presents significant challenges for researchers and policymakers attempting to evaluate intervention effectiveness and implement successful strategies. The management of heterogeneity is particularly crucial in systematic reviews of environmental management research, where synthesizing evidence from disparate studies requires careful consideration of variation in effects, contexts, and implementation factors [54].

Recent research emphasizes that environmental regulations and interventions often exhibit competitive rather than cooperative effects when implemented simultaneously. Analysis of heterogeneous subjects participation synergy has demonstrated that an incremental unit of synergy intensity can correspond to a decline of approximately 22%–25% in environmental quality, highlighting the critical importance of strategic heterogeneity management [54]. Furthermore, regions with lower synergy degrees exhibit 36%–42% higher environmental quality compared to those with higher synergy degrees, reinforcing the need for carefully calibrated intervention strategies.

The protocol-driven approach outlined in these application notes addresses these challenges by providing standardized methodologies for identifying, assessing, and accounting for heterogeneity throughout the evidence synthesis process. This structured framework enables researchers to generate more reliable, actionable findings for environmental policy and practice.

Quantitative Evidence on Heterogeneous Effects

Table 1: Heterogeneous Effects of Environmental Interventions Based on Field Experimental Data

Intervention Type	Effect Size on Participation	Duration Effect	Population Variation	Key Moderating Factors
Normative Feedback	Highest participation rates	Decreases over time	Greater effect on individuals with strong personal norms	Strength of pre-existing personal norms, social network density [55]
Biospheric Appeals	Moderate participation rates	Decreases over time	More effective for individuals with biospheric motivations	Biospheric values, environmental identity [55]
Altruistic Appeals	Moderate participation rates	Decreases over time	More effective for individuals with altruistic motivations	Altruistic values, community orientation [55]
Government-Dominant Regulations	Variable effectiveness	Policy-dependent	Varies by regulatory capacity and enforcement	Regulatory stringency, enforcement mechanisms, institutional capacity [54]
Market-Dominant Regulations	Variable effectiveness	Market-dependent	Varies by economic context and market structure	Economic incentives, market maturity, cost structures [54]
Public-Dominant Regulations	Variable effectiveness	Depends on sustained engagement	Varies by public awareness and civic engagement	Public awareness, community organization, civic traditions [54]

Table 2: Synergy Effects in Heterogeneous Environmental Regulations

Regulation Combination	Synergy Type	Environmental Quality Impact	Relative Performance
Environmental Administrative Penalty + Public Environmental Concern	Cooperative	Highest improvement	6%–17% higher environmental benefits compared to administrative penalty + environmental tax [54]
Environmental Administrative Penalty + Environmental Tax	Competitive	Moderate improvement	Baseline for comparison
Environmental Tax + Public Environmental Concern	Competitive	Lower improvement	21%–23% lower benefits compared to administrative penalty + public concern [54]
High Synergy Intensity (All three types)	Competitive	Negative impact	22%–25% decline in environmental quality [54]

Experimental Protocols

Protocol for Systematic Review of Heterogeneous Intervention Effects

Background and Review Question

This protocol outlines the methodology for conducting a systematic review of strategies for managing heterogeneity in complex environmental interventions. The primary review question is: "What is the effectiveness of different strategies for managing heterogeneity in complex environmental interventions, and how do these strategies moderate intervention impacts on environmental outcomes?"

Search Strategy

The search strategy will employ a comprehensive, multi-channel approach to identify relevant literature:

• Bibliographic Databases: Web of Science, Scopus, Google Scholar, Springer Nature Experiments, and specialized environmental databases [56]
• Search Strings: Combinations of terms including "heterogeneity," "environmental interventions," "complex interventions," "moderating factors," "differential effects," and "contextual factors" using Boolean operators
• Grey Literature: Organizational websites, government reports, and conference proceedings [3]
• Supplementary Approaches: Bibliographic searching of included studies, contact with experts, and citation tracking [3]
• Language Restrictions: English-language publications from 2000-present, with non-English literature included where translation resources permit

All search strings will be documented and preserved in searchRxiv to ensure reproducibility and facilitate future updates [3].

Screening and Study Eligibility Criteria

Screening Process:

• Title and Abstract Screening: Initially conducted by one reviewer, with a random 20% subset screened by a second reviewer to ensure consistency [3]
• Full-Text Screening: Conducted independently by two reviewers, with disagreements resolved through discussion or third-party adjudication
• Consistency Testing: Inter-rater reliability will be calculated using Cohen's kappa, with a minimum threshold of 0.7 required before proceeding [3]

Eligibility Criteria:

• Population: Environmental interventions at any scale (local to global)
• Intervention: Complex interventions with multiple components or implementation strategies
• Comparator: Standard interventions, alternative approaches, or no intervention
• Outcomes: Quantitative measures of environmental quality, intervention effectiveness, or heterogeneity effects
• Study Designs: Experimental, quasi-experimental, observational, and modeling studies that explicitly address heterogeneity

A list of articles excluded at full-text review will be maintained with reasons for exclusion [3].

Data Extraction and Management

Data Coding and Extraction Strategy

Data will be extracted using a standardized coding form implemented in a structured spreadsheet. The extraction categories include:

• Study Characteristics: Authors, publication year, location, study design, duration
• Intervention Details: Type, components, implementation context, targeted behaviors
• Heterogeneity Factors: Types of heterogeneity assessed, measurement approaches, moderating variables
• Outcome Data: Primary and secondary outcomes, effect sizes, variability measures, subgroup analyses
• Methodological Factors: Risk of bias, confounding control, analytical approaches

The repeatability of the data extraction process will be tested by having two independent reviewers extract data from a random sample of 10% of included studies, with discrepancies discussed and the coding form refined as needed [3].

Potential Effect Modifiers and Reasons for Heterogeneity

Based on preliminary evidence, the following effect modifiers will be coded and considered in the analysis:

• Intervention Characteristics: Type, complexity, duration, implementation quality
• Contextual Factors: Political setting, regulatory environment, socioeconomic context, physical environment
• Participant Factors: Demographic characteristics, pre-existing attitudes and values, social networks, prior behaviors
• Methodological Factors: Study design, outcome measurement, analytical approach, risk of bias

The list of effect modifiers was compiled through consultation with content experts and review of preliminary evidence [3].

Study Validity Assessment

Study validity will be assessed using customized checklists appropriate to different study designs:

• Experimental Studies: Risk of bias assessment focusing on randomization, allocation concealment, blinding, incomplete outcome data, and selective reporting
• Observational Studies: Assessment of confounding control, selection bias, measurement validity, and analytical appropriateness
• Qualitative Studies: Evaluation of methodological rigor, theoretical basis, data collection comprehensiveness, and analytical transparency

Critical appraisal will be conducted independently by two reviewers, with disagreements resolved through consensus. The results of the validity assessment will inform sensitivity analyses and interpretation of findings [3].

Visualization Diagrams

Systematic Review Workflow

Heterogeneity Assessment Framework

Environmental Regulation Synergy Analysis

Research Reagent Solutions

Table 3: Essential Research Materials and Tools for Heterogeneity Analysis

Research Tool	Function	Application Context	Key Features
Heterogeneity Subject Participation (HSP) Synergy Index	Quantifies synergy intensity among different regulatory approaches	Integrating diverse environmental regulations into unified framework [54]	Measures competitive/cooperative effects, enables cross-regulation comparison
Other-Regarding Intervention (ORI) Framework	Assesses biospheric, altruistic, and normative motivations	Evaluating behavioral interventions in environmental management [55]	Differentiates motivation types, measures intervention effectiveness decay
Panel Data Analysis Methods	Analyzes longitudinal data across multiple regions/contexts	Examining heterogeneous effects across spatial and temporal dimensions [54]	Controls for unobserved heterogeneity, models dynamic effects
Normative Feedback Protocols	Implements social norm-based interventions	Promoting pro-environmental behaviors in diverse populations [55]	Leverages descriptive and injunctive norms, customizable reference groups
Asymmetric Strategy Framework	Optimizes combination of regulatory approaches	Maximizing environmental benefits through strategic policy design [54]	Identifies most effective regulation pairs, quantifies synergy effects
Difference-in-Differences Configuration	Estimates causal effects in quasi-experimental settings	Evaluating policy interventions with staggered implementation [55]	Controls for time-varying confounders, flexible treatment timing
Color Contrast Analysis Tools	Ensures accessibility of research visualizations	Creating inclusive research materials and public-facing content [57] [58]	WCAG compliance checking, multiple color space support

Planning for and Justifying Deviations from the Registered Protocol

In the rigorous domain of systematic reviews within environmental management research, a registered protocol serves as a study's foundational blueprint, detailing the planned methods to minimize bias and ensure transparency [24]. A "planned deviation" occurs when an investigator prospectively and intentionally plans to depart from these approved protocol requirements [59]. Such deviations are not ad-hoc changes but are considered actions, often requested for a single participant or a specific context, such as enrolling a subject who does not meet all eligibility criteria or conducting a procedure outside of a predefined time window [59]. Justifying and managing these deviations is a critical aspect of maintaining the scientific integrity of a systematic review, particularly when conducted within high-stakes fields like environmental health and drug development.

Adhering to a pre-defined protocol is a cornerstone of systematic review methodology, as it guards against the introduction of bias in results and conclusions [24]. However, the practical conduct of a review often encounters unforeseen complexities in the evidence base, necessitating methodological adjustments. Framing these adjustments within a structured framework of planned deviations allows researchers to navigate these challenges without compromising the review's validity. This process aligns with the standards set by leading journals, such as Environment International, which require "reasonable adherence to a pre-published or registered protocol" while acknowledging that deviations may occur [24].

Types and Categories of Protocol Deviations

Protocol deviations can be categorized based on their nature, timing, and impact. Understanding these categories helps in appropriately planning for and justifying the change.

Table 1: Categories of Protocol Deviations

Category	Nature of Deviation	Typical Justification	Impact on Review
Eligibility Criteria	Modification of pre-defined population, intervention, comparator, or outcome (PICO) inclusion/exclusion criteria.	Discovery of an unanticipated body of literature or a more relevant conceptualization of the intervention during the review process.	Can significantly alter the scope and applicability of findings; requires careful justification.
Search Strategy	Alteration of the planned databases, search strings, or grey literature sources.	A pilot search reveals the strategy is missing key benchmark articles or is impractically large.	Affects the comprehensiveness and reproducibility of the evidence base.
Data Extraction & Coding	Changes to the planned data items or the method of extraction (e.g., modifying a coding spreadsheet).	Need to capture additional effect modifiers or outcomes not initially considered but deemed critical.	Influences the depth and direction of the synthesis and analysis.
Synthesis Methodology	Deviation from the pre-specified method of narrative or quantitative synthesis.	The included studies are too heterogeneous for a planned meta-analysis, requiring an alternative synthesis method.	Directly affects the review's conclusions and the strength of the evidence.
Critical Appraisal	Modification of the tool or process for assessing the validity of included studies.	A more appropriate or field-standard appraisal tool is identified after protocol registration.	Impacts the assessment of confidence in the evidence and risk of bias.

The most straightforward categorization differentiates between planned deviations and unplanned deviations. A "planned deviation" is a prospective, intentional change for which investigators seek approval before implementation [59]. In contrast, unplanned deviations (sometimes called protocol violations) are retrospective, unintended departures from the protocol that are identified after they occur. This document focuses on the former, which, when properly managed, are a tool for robust and adaptive research practice.

Justification and Criteria for Approval

A well-justified planned deviation request must provide a compelling rationale that addresses scientific rigor, ethical considerations, and practical necessity. Institutional Review Boards (IRBs) and other oversight bodies typically consider several key factors when reviewing such requests [59].

The primary justification often revolves around the best interest of the subject (or, in the context of a systematic review, the integrity of the evidence synthesis itself). For example, a deviation may be necessary to include a critical study that would otherwise be excluded by an overly rigid eligibility criterion, thereby strengthening the review's conclusions. The reviewer must demonstrate that the deviation "holds out the prospect of direct benefit" to the review's utility or that the risk/benefit ratio introduced by the change is favorable [59]. Another central consideration is the impact on data integrity. The request must clarify whether the change will compromise the validity or interpretability of the collected data. For instance, expanding a search strategy to include additional languages should improve data completeness, whereas narrowing eligibility criteria post-hoc might introduce bias. The justification should explicitly state that the deviation is "not expected to have any effect on data integrity" or, if it does, explain how this impact will be mitigated [59].

Essential Components of a Justification

When submitting a request for a planned deviation, the following information must be included [59]:

• Description of the Deviation: Precisely identify the page and section of the protocol being altered and describe the proposed change.
• Rationale: Provide a clear and detailed scientific justification for why the deviation is necessary.
• Scope: Clarify whether the request is for a single, specific application (e.g., the inclusion of one particular study) or a permanent modification to the protocol methodology.
• Risk-Benefit Analysis: Include a statement on whether the deviation increases risk to the review's validity and describe any anticipated benefits.
• Stakeholder Approval: Documented approval from all relevant oversight entities, such as the review's commissioner or a methodology supervisor, must be obtained before submission [59].

Experimental Protocols for Managing Deviations

Workflow for Submission and Review

The following diagram illustrates the standard operating procedure for submitting and reviewing a planned protocol deviation, ensuring a consistent and transparent process.

Submission Protocol

The submission process for a planned deviation is formalized through a modification request to the overseeing IRB or review committee [59]. For systematic reviews, this oversight body could be the journal that published the protocol, the funder, or an internal review committee.

• Preparation of Submission Package: The investigator must compile a comprehensive submission, which includes:

  • A detailed description of the deviation, citing the specific protocol section [59].
  • A clear and compelling rationale.
  • An analysis of the impact on participant risk (if applicable) and data integrity.
  • Documented approval from the study sponsor, commissioner, or methodological lead [59].
  • For time-sensitive deviations, a rationale for the rush review and the proposed implementation date.

• IRB/Review Body Processing: Rush requests for deviations are typically assigned for immediate processing [59]. The review body will assess the request based on:

  • The time sensitivity of the request.
  • The level of risk involved in both the study itself and the planned alteration.
  • Whether the deviation is in the best interest of the review's validity and conclusions.
  • The favorability of the risk/benefit ratio [59].

• Implementation and Documentation: Upon receipt of approval, the deviation can be implemented. The implementation must be thoroughly documented in the final systematic review manuscript, typically in the methods section, explaining the reason for the change.

Research Reagent Solutions for Systematic Reviews

In the context of a systematic review, "research reagents" refer to the key methodological tools and platforms used to conduct the review. The following table details essential solutions for ensuring a review is rigorous, reproducible, and compliant with standards for managing protocol deviations.

Table 2: Key Research Reagent Solutions for Systematic Review Conduct

Tool Category	Specific Solution/Platform	Primary Function in Protocol Management
Protocol Registration	PROCEED [3]	An open-access database for registering titles and protocols of evidence syntheses in advance, providing a public record of the original plan.
Reporting Standards	ROSES (Reporting standards for Systematic Evidence Syntheses) [3]	A reporting standard and form used to demonstrate that all relevant methodological details, including any deviations, have been reported.
Search Management	searchRxiv [3]	An archive to store, report, and share search strings, obtaining a DOI to ensure reproducibility of the search strategy, even if modified later.
Color Accessibility	Paletton [60] / Coolors [61]	Online tools to design color palettes with sufficient contrast for charts and diagrams, and to check that the contrast fits WCAG requirements.
Diagram Creation	Graphviz (DOT language)	A graph visualization tool used to create clear, accessible diagrams for experimental workflows and logical relationships, as specified in this protocol.

Data Presentation and Synthesis of Deviations

When a deviation is implemented, its impact on the study must be clearly presented. This often involves summarizing quantitative data related to the deviation's effect, for example, on the number of studies included or the characteristics of the extracted data.

Table 3: Exemplar Data Table Showing the Impact of an Eligibility Criteria Deviation

Eligibility Scenario	Number of Studies Identified	Number of Studies Included	Key Population Characteristic (e.g., Mean Age)	Primary Outcome Effect Estimate (e.g., SMD)
Original Protocol Criteria	2,414 [62]	15	45.2 years	-0.55 (-0.88 to -0.22)
Post-Deviation Criteria	2,414 [62]	22	48.7 years	-0.48 (-0.75 to -0.21)
Difference (Δ)	0	+7	+3.5 years	+0.07

Presenting data in this comparative format allows readers and reviewers to quickly grasp the practical consequence of the methodological change. The table should be self-explanatory, with a clear title, column headings that include units of measurement, and data organized for easy comparison, typically vertically [63] [62]. This transparency is crucial for maintaining the trustworthiness of the systematic review's findings.

In environmental management and drug development research, where evidence-based decisions are paramount, the registered protocol is a commitment to scientific rigor. The process of planning for and justifying deviations from this protocol is not a weakness but an integral component of a robust methodological framework. By prospectively identifying necessary changes, providing transparent justifications centered on scientific integrity, obtaining formal approval, and thoroughly documenting the process, researchers can adapt to complex realities without sacrificing validity. Adhering to a structured approach for protocol deviations ultimately strengthens the credibility and utility of systematic reviews, ensuring they remain reliable foundations for policy and practice.

Validating and Registering Your Protocol for Credibility and Impact

Protocol registration is a foundational practice in modern scientific research, serving as a critical safeguard against bias and duplication. Within the framework of Transparency and Openness Promotion (TOP) Guidelines, protocol registration is formalized as a key research practice with multiple implementation levels, from simple disclosure to independent certification [64]. For environmental management researchers, registering a systematic review protocol before commencing the review ensures that the methodology is pre-specified, transparent, and aligned with community standards. This practice commits the research team to a predetermined plan, reducing opportunities for subjective decisions that might bias the findings toward particular outcomes.

The verifiability of research claims is significantly enhanced when a protocol is registered prospectively. According to the TOP 2025 framework, verification practices like Results Transparency depend on having a pre-existing protocol against which final reports can be compared [64]. In environmental management research, where systematic reviews often inform policy and conservation decisions, protocol registration provides stakeholders with confidence that the review process was conducted with methodological rigor and minimal bias. The registration timestamp creates permanent, public documentation of the researcher's intent, allowing any deviations in the final review to be properly identified and justified.

The Registration Imperative: Why Protocol Registration Matters

Core Benefits and Rationale

Protocol registration delivers critical advantages that strengthen research integrity across environmental management studies:

• Prevents Duplication: Publicly registering a protocol announces to the scientific community that a particular systematic review is underway, preventing unnecessary duplication of effort and conserving valuable research resources [65] [66]. This is particularly important in fast-moving environmental fields where multiple research teams might be working on similar questions simultaneously.

• Enhances Transparency and Reduces Bias: Prospective registration locks in research questions, eligibility criteria, and analysis plans, preventing data-driven decisions that could introduce bias [67] [68]. This ensures that environmental management reviews are conducted according to pre-specified methods rather than being influenced by emerging results.

• Facilitates Collaboration and Coordination: Registered protocols with contact information allow other researchers to discover ongoing reviews and potentially collaborate, improving research efficiency and scope [65]. For complex environmental questions requiring diverse expertise, this can lead to more comprehensive and authoritative reviews.

• Supports Funding and Publication Requirements: Many funders and journals now require protocol registration as a condition of support or publication [3] [65]. Environmental Evidence journal, for instance, mandates protocol registration in PROCEED before conducting and submitting a systematic review [3].

Quantitative Evidence of Registration Impact

Table 1: Protocol Registration Requirements and Adoption Across Disciplines

Domain	Primary Registry	Registration Mandate	Time to Publication
Healthcare	PROSPERO	Required by many journals & funders	>6 months reported [68]
Environmental Science	PROCEED	Required by Environmental Evidence journal [3]	Editorial checks before acceptance [69]
Social Sciences	OSF, Campbell Collaboration	Encouraged as best practice [67]	Immediate to 48 hours [68] [70]
Cross-disciplinary	INPLASY	Accepts multiple review types [68]	Within 48 hours [68]

Registration Platforms: A Comparative Analysis

Platform-Specific Capabilities and Requirements

Environmental management researchers can select from several specialized registries, each with distinct advantages:

PROCEED represents a domain-specific solution developed explicitly for the environmental sector. As a global database of prospectively registered evidence reviews, it fills a critical gap for environmental researchers who previously lacked an equivalent to PROSPERO [69]. Operated by the Collaboration for Environmental Evidence, PROCEED requires authors to complete appropriate templates for different review types (Systematic Review, Systematic Map, Rapid Review) and undergoes editorial checks before acceptance into the database [69]. For researchers intending to publish in Environmental Evidence, PROCEED registration is now a standard requirement [3].

PROSPERO remains the most established international registry for systematic reviews with health-related outcomes, though it also covers welfare, public health, education, crime, justice, and international development [71] [68]. Despite its healthcare origins, many environmental management reviews that intersect with human health outcomes (e.g., environmental toxicology, public health ecology) may appropriately use PROSPERO. However, significant registration delays have been reported, with waiting times exceeding six months in some cases [68].

INPLASY (International Platform of Registered Systematic Review and Meta-Analysis Protocols) has emerged as a rapid-alternative registry that accepts a broad range of review types, including interventions, diagnostic accuracy, prognostic factors, and epidemiological characteristics [68]. Notably, INPLASY protocols are typically published within 48 hours of submission, dramatically reducing the registration timeline compared to other platforms [68]. This platform accepts systematic reviews of animal studies and environmental health topics, making it relevant for certain environmental management domains.

Open Science Framework (OSF) provides a flexible, generalist repository for research materials, including systematic review protocols [72] [70]. As a project management tool that supports the entire research lifecycle, OSF enables researchers to capture different aspects and products of their research [70]. While not specifically designed for systematic reviews, OSF offers persistent identifiers (DOIs) for projects and components, making protocols citable in scholarly communication [70]. OSF is particularly valuable for scoping reviews and other evidence synthesis formats that may not fit the criteria of specialized systematic review registries [67].

Comparative Platform Features

Table 2: Systematic Review Protocol Registry Comparison

Feature	PROCEED	PROSPERO	INPLASY	OSF
Primary Scope	Environmental evidence reviews [69]	Health & social care with health-related outcomes [71]	Interventions, prognosis, diagnostics, animal studies [68]	Cross-disciplinary [72]
Registration Speed	After editorial checks [69]	Often >6 months delay [68]	Within 48 hours [68]	Immediate [70]
Cost Structure	Free [69]	Free	Publication fee required [68]	Free [70]
Review Stage Accepted	Prospective only [3]	Primarily prospective [68]	Prospective and retrospective (with justification) [68]	Any stage
Template Guidance	CEE-standardized templates [69]	Detailed item requirements [68]	Comprehensive guideline [68]	Flexible structure

Experimental Protocol: Systematic Review Registration Workflow

Preregistration Laboratory Setup

Table 3: Research Reagent Solutions for Protocol Registration

Reagent/Tool	Function	Application Context
ROSES Forms	Reporting standards for Systematic Evidence Syntheses [3]	Mandatory for Environmental Evidence submissions; demonstrates methodological completeness [3]
PRISMA-P	Evidence-based minimum set of items for systematic review protocols [71]	Protocol development guideline across disciplines; improves reporting quality [67]
PICO Framework	Structured methodology for framing research questions [68]	Defining population, intervention, comparator, outcome elements for review questions [68]
re3data.org	Registry of research data repositories [72]	Identifying discipline-specific repositories for supporting materials
ORCiD	Persistent digital identifier for researchers [72]	Required for many registrations; connects researchers to their work [70]

Methodological Procedures

Phase 1: Preregistration Preparation

The protocol development phase requires careful planning and documentation before registry submission:

• Define Review Question and Scope: Formulate the primary question using appropriate frameworks (e.g., PICO for intervention reviews) [68]. The question should be specific enough to provide clear direction but broad enough to capture relevant evidence. Environmental management reviews might address questions about conservation effectiveness, pollution impacts, or climate adaptation strategies.

• Conduct Preliminary Searches: Check for existing and ongoing systematic reviews to avoid duplication [68]. Search PROCEED, PROSPERO, INPLASY, and published literature using core search terms related to your environmental topic. Document this search to demonstrate the novelty of your proposed review.

• Develop Detailed Methodology: Specify all planned methods including search strategy, eligibility criteria, data extraction approach, critical appraisal tools, and synthesis methods [3] [67]. For environmental reviews, consider specific challenges like multi-language literature or grey literature from governmental sources.

• Complete Reporting Guidelines: Prepare completed ROSES or PRISMA-P forms alongside the protocol text [3] [71]. These forms ensure all methodological aspects have been adequately addressed in the protocol.

Phase 2: Registry Selection and Submission

The registry selection process should align with disciplinary expectations and review requirements:

Diagram 1: Protocol registry selection workflow (Max Width: 760px)

The submission process requires careful attention to registry-specific requirements:

• PROCEED Registration: Access the PROCEED platform through the Collaboration for Environmental Evidence website [69]. Select the appropriate template for your review type (Systematic Review, Systematic Map, or Rapid Review). Complete all required fields, including background, objectives, and methods. Submit for editorial checks, and respond to any revision requests before final acceptance [69].

• PROSPERO Registration: Create an account on the PROSPERO platform and complete all mandatory fields, including review question, search strategy, eligibility criteria, and proposed synthesis methods [68] [66]. Be prepared for potential delays in registration due to high demand and prioritization of UK-based submissions [68].

• INPLASY Registration: Complete the registration form in English, providing all mandatory information including detailed methodology and disclosure of potential conflicts of interest [68]. Pay the required publication fee and await rapid publication typically within 48 hours [68].

• OSF Registration: Create an OSF project and add protocol documentation as files or components [70]. Use the registration feature to create a frozen, time-stamped version of the protocol that receives a persistent identifier [70]. Add collaborators with appropriate permission levels and link supporting materials.

Phase 3: Post-Registration Procedures

After successful registration, researchers should:

• Cite Registration Details: Include the registration number and persistent link in all subsequent publications and grant reports [65].

• Update as Needed: If methodological changes become necessary, update the registered protocol following registry-specific procedures [68]. Document and justify all deviations from the original protocol in the final systematic review.

• Link Related Research Products: Connect the registered protocol to resulting publications, data, and code using the registry's features [64] [70].

Application to Environmental Management Research

The environmental management field presents specific considerations for systematic review protocol registration. Environmental questions often span ecological, social, and economic domains, requiring sophisticated methodological approaches that should be pre-specified to avoid bias. The emergence of PROCEED as an environmental-specific registry addresses longstanding gaps in suitable infrastructure for this discipline [69].

Environmental systematic reviews frequently inform policy and management decisions with significant conservation and resource allocation implications. Protocol registration in this context provides assurance to decision-makers that the review was conducted with minimal bias and maximum methodological transparency [3]. For example, reviews examining the effectiveness of conservation interventions or the impacts of pollution policies benefit from the credibility afforded by prospective registration.

The cross-disciplinary nature of environmental management research necessitates careful registry selection. While PROCEED is ideally suited for purely ecological questions, reviews intersecting with human health outcomes may still benefit from PROSPERO registration [71]. Similarly, systematic maps that scope environmental evidence rather than synthesize findings quantitatively may find appropriate registration options through OSF [67] [70].

Visualizing the Protocol Registration Ecosystem

Diagram 2: Protocol registration ecosystem (Max Width: 760px)

Protocol registration represents an essential practice for environmental management researchers conducting systematic reviews. The evolving registry landscape now offers multiple options tailored to different disciplinary needs and timelines. PROCEED has emerged as the specialized platform for environmental evidence syntheses, while PROSPERO, INPLASY, and OSF provide complementary options for reviews with different scopes and requirements.

The scientific community's increasing emphasis on research transparency, combined with journal and funder mandates, makes protocol registration an indispensable component of rigorous evidence synthesis. Environmental management researchers should prospectively register their systematic review protocols in appropriate registries to enhance the credibility, discoverability, and utility of their work for policy and practice. As the TOP Guidelines emphasize, such transparency practices ultimately increase the verifiability of research claims [64] – a critical consideration for a field addressing complex environmental challenges with significant societal implications.

Using the CEE Checklist for Environmental Systematic Reviews as a Validation Tool

The Collaboration for Environmental Evidence (CEE) Checklist serves as a critical validation tool for researchers, journal editors, and peer-reviewers to assess the methodological rigor and credibility of systematic reviews in environmental management [73]. This application note frames the checklist within the broader context of systematic review protocols for environmental research, addressing the concerning finding that over 95% of published environmental reviews claiming to be "systematic" fail to meet established methodological standards [73] [74]. The checklist functions as a validation instrument by enabling rapid assessment of whether authors' claims to have conducted a systematic review are justified, ensuring such reviews demonstrate high procedural transparency, replicability, and comprehensive, reliable findings with minimal bias [74].

The CEE Checklist is grounded in the CEE guidelines for standards of conduct and the RepOrting standards for Systematic Evidence Syntheses (ROSES) reporting standards [75]. It provides a structured framework to verify that all critical methodological stages of a systematic review have been adequately addressed and reported. For environmental researchers and drug development professionals working on environmental health topics, this validation tool helps safeguard the integrity of evidence syntheses that may inform regulatory decisions, policy development, and clinical research directions [76].

CEE Checklist Components and Quantitative Assessment

The CEE Checklist is organized according to the key stages of systematic review conduct, with specific validation criteria for each stage. The table below summarizes the core components and their validation functions:

Table 1: CEE Checklist Components for Validating Systematic Reviews

Checklist Section	Validation Questions	Compliance Metric	Purpose in Validation
General Methods	Has a protocol been pre-registered? Is the methods section sufficiently detailed for replication?	Yes/No	Validates a priori planning and methodological transparency [74]
Searching	Are all search terms and strings with Boolean operators clearly stated?	Yes/No	Verifies comprehensive search strategy to minimize selection bias [74]
Screening	Are eligibility criteria precisely defined? Are screening results documented via flow diagram?	Yes/No	Assesses objectivity and reproducibility of study selection [74] [33]
Critical Appraisal	Is a recognized tool used to identify sources of bias in included studies?	Yes/No	Validates assessment of internal validity (risk of bias) [74] [77]
Data Extraction	Are all extracted data reported in tables/spreadsheets?	Yes/No	Verifies transparency and accessibility of data for verification [74]
Data Synthesis	Is the synthesis method described in sufficient detail to be replicable?	Yes/No	Assesses appropriateness and transparency of synthesis methodology [74]
Review Limitations	Is there explicit consideration of risk of bias due to review limitations?	Yes/No	Validates self-critical assessment of review weaknesses [74]

The validation protocol requires a "Yes" to all checklist questions for a review to qualify as a systematic review according to CEE standards [74]. This binary assessment approach enables efficient validation while maintaining methodological rigor. For systematic reviews in environmental management, this validation process is particularly crucial given the complex, interdisciplinary nature of environmental evidence and its application to policy and practice [76].

Experimental Protocol for Applying the CEE Validation Checklist

Stage 1: Pre-validation Setup and Protocol Assessment

Objective: Establish the foundation for validation by assessing protocol availability and registration.

• Step 1.1: Check for pre-registered protocol - Identify whether authors registered an a priori protocol in repositories like PROSPERO, Open Science Framework, or the CEE library [1]. The protocol must be freely available online and cited in the review report [74].
• Step 1.2: Verify protocol-content alignment - Assess whether the published review methods align with the pre-registered protocol. Document any deviations with justifications [32].
• Step 1.3: Methods replication assessment - Evaluate whether the methods section provides sufficient methodological detail to enable exact replication of all review stages [74].

Validation Output: Binary assessment (Yes/No) of protocol availability and methodological transparency.

Stage 2: Search Strategy Validation

Objective: Verify the comprehensiveness, systematicity, and transparency of search strategies.

• Step 2.1: Search string replication check - Confirm that search terms and strings with Boolean operators ('AND', 'OR', etc.) and wildcards are clearly stated for each information source [74] [32].
• Step 2.2: Source diversity assessment - Validate that multiple relevant databases, institutional websites, and grey literature sources were searched, with dates and search interfaces documented [32].
• Step 2.3: Search limitation justification - Assess whether date ranges, language restrictions, or other search limitations are adequately justified [32].

Validation Output: Binary assessment (Yes/No) of search replicability and comprehensive coverage.

Stage 3: Screening Process Validation

Objective: Assess the objectivity, consistency, and transparency of study selection.

• Step 3.1: Eligibility criteria assessment - Verify that study eligibility criteria are precisely defined and directly related to each key element of the review question [74] [33].
• Step 3.2: Screening methodology check - Confirm that duplicate independent screening was conducted with a pre-specified process for resolving disagreements [33].
• Step 3.3: Flow documentation verification - Check that a PRISMA-style flow diagram documents the number of records identified, included, and excluded at each stage [74] [32].

Validation Output: Binary assessment (Yes/No) of screening rigor and transparency.

Stage 4: Critical Appraisal Validation

Objective: Evaluate the systematic assessment of internal validity (risk of bias) of included studies.

• Step 4.1: Tool appropriateness assessment - Verify that a recognized critical appraisal tool was used (e.g., CEE Critical Appraisal Tool, Cochrane RoB tool, MMAT) [74] [77].
• Step 4.2: Duplicate assessment confirmation - Check that at least two reviewers independently conducted critical appraisals with a process for resolving disagreements [77].
• Step 4.3: Synthesis integration assessment - Confirm that critical appraisal results were incorporated into the synthesis (e.g., sensitivity analysis) [32].

Validation Output: Binary assessment (Yes/No) of critical appraisal conduct and reporting.

Stage 5: Data Extraction and Synthesis Validation

Objective: Verify the completeness and transparency of data extraction and appropriateness of synthesis methods.

• Step 5.1: Data accessibility check - Confirm that all extracted data are provided in tables, spreadsheets, or supplementary materials [74].
• Step 5.2: Extraction methodology assessment - Verify that data extraction was performed by at least two reviewers independently, with a process for resolving disagreements [32].
• Step 5.3: Synthesis justification evaluation - Assess whether the choice of synthesis method (narrative, quantitative, meta-analysis) is justified based on the characteristics and heterogeneity of included studies [74].

Validation Output: Binary assessment (Yes/No) of data transparency and synthesis appropriateness.

CEE Checklist Validation Workflow

Research Reagent Solutions for Systematic Review Validation

Table 2: Essential Research Reagent Solutions for CEE Checklist Implementation

Tool Category	Specific Solutions	Function in CEE Validation
Protocol Registration	PROSPERO, Open Science Framework, Campbell Systematic Reviews	Enables pre-registration of review protocols for validating a priori methods [1]
Search Reporting	ROSES Forms, PRISMA-S	Standardizes search strategy reporting for transparency and replicability assessment [75]
Screening Tools	Covidence, Rayyan, Systematic Review Accelerator	Facilitates duplicate screening and documents decisions for screening validation [33] [78]
Critical Appraisal Instruments	CEE Critical Appraisal Tool, Cochrane RoB Tool, MMAT, Newcastle-Ottawa Scale	Provides standardized instruments for validating risk of bias assessment [77]
Data Extraction & Management	CADIMA, RevMan, DistillerSR	Supports systematic data extraction and management for transparency verification [78]
Reference Management	EndNote, Zotero, Mendeley	Enables efficient deduplication and reference organization for screening validation [78]

Advanced Validation Methodologies

Inter-Rater Reliability Assessment in Screening Validation

A critical methodological component in validating the screening process is the assessment of inter-rater reliability (IRR). The validation protocol should include:

IRR Calculation Methods:

• Percentage Agreement: IRR = Number of references with reviewer agreement / Total number of references reviewed [33]
• Cohen's Kappa: IRR = (po - pe) / (1 - pe) where po represents relative observed agreement and pe represents hypothetical probability of chance agreement [33]

Validation Thresholds: The CEE checklist validation requires documentation of consistency checking at all screening stages, with results reported in the final systematic review [32]. Low IRR scores during validation indicate problems with the eligibility criteria, review protocol, or reviewers' understanding of the inclusion criteria.

Critical Appraisal Tool Selection Protocol

The validation of critical appraisal methods requires assessment of appropriate tool selection based on study designs included:

Critical Appraisal Tool Selection Validation

The CEE checklist validation requires that authors make an effort to identify all sources of bias relevant to each included study using recognized critical appraisal tools [74] [77]. The validation process must confirm that the selected tools appropriately match the study designs included in the systematic review.

Synthesis Methodology Validation Protocol

Validating the synthesis methodology requires assessment of both the methodological approach and its reporting:

Quantitative Synthesis Validation:

• Check for appropriate effect size calculations and combination methods
• Verify assessment of heterogeneity (I² statistic, confidence intervals)
• Confirm exploration of publication bias (funnel plots, Egger's test)

Qualitative Synthesis Validation:

• Assess whether a structured approach to narrative synthesis was employed
• Verify that synthesis moves beyond description of individual studies to genuine integration of findings
• Confirm appropriate use of tables and graphical presentations to summarize patterns

The validation must confirm that vote-counting (summing studies with positive or negative findings) was not used as a synthesis method, as this approach is methodologically unsound for determining impact or effectiveness [74].

Application in Environmental Management Context

The CEE checklist validation process holds particular significance in environmental management research, where systematic reviews increasingly inform policy and practice decisions [76]. A survey of CEE systematic review authors revealed that 22% of reviews directly prompted a change in policy, while 30% directly prompted a change in practice [76]. The validation protocol ensures that such influential decisions are grounded in methodologically robust evidence syntheses.

Environmental systematic reviews present unique validation challenges, including diverse study designs, interdisciplinary evidence sources, and complex intervention pathways. The CEE checklist accommodates these challenges through its focus on methodological principles rather than rigid prescription, allowing validation across the diverse landscape of environmental research topics from biodiversity conservation to resource management and pollution control [76].

For researchers conducting systematic reviews on environmental interventions, the CEE checklist validation provides a framework for demonstrating methodological rigor to stakeholders, journal editors, and policy-makers. This validation enhances the credibility and potential impact of environmental evidence syntheses in guiding decision-making toward more effective environmental management outcomes.

Within environmental management research, the choice of review methodology is a critical first step that shapes the entire research process, influencing the reliability of findings and their applicability to policy and practice. A thorough understanding of the distinctions between a literature (narrative) review and a systematic review is fundamental for researchers, scientists, and drug development professionals who rely on synthesized evidence. While both aim to summarize existing knowledge, their philosophical underpinnings, methodological rigor, and ultimate outputs differ substantially [79] [80]. A literature review typically offers a broad overview of a topic, whereas a systematic review seeks to answer a specific, focused question using a pre-specified, transparent, and reproducible protocol to minimize bias [81]. This application note delineates these differences through a structured comparison, detailed experimental protocols, and visual workflows, contextualized specifically for the field of environmental management.

Comparative Analysis: Literature Reviews vs. Systematic Reviews

The following table synthesizes the core distinctions between these two review types, providing a clear framework for selection based on research goals.

Table 1: Comparative analysis of literature (narrative) reviews and systematic reviews.

Characteristic	Literature (Narrative) Review	Systematic Review
Research Question	Can be a general topic or a broad question [79].	A clearly defined and specific, answerable question, often structured using PICO (Population, Intervention, Comparator, Outcome) or similar frameworks [79] [81].
Objective & Goal	To provide a comprehensive, critical overview of a topic, establish a theoretical framework, identify patterns, and contextualize new research [79] [80].	To answer a specific clinical or policy question, minimize bias, and produce a robust summary of all existing evidence to inform decision-making [80] [81].
Planning & Protocol	Typically does not involve a pre-registered or published protocol [79].	Requires a detailed, pre-specified protocol developed before the review starts, often registered in platforms like PROSPERO or PROCEED [79] [3].
Search Strategy	Often not systematic or exhaustive; may not be specified in detail, posing a risk of selective citation [79] [81].	A systematic, comprehensive, and reproducible search across multiple databases and grey literature sources to identify all relevant studies [79] [81].
Eligibility Criteria	Not usually pre-specified or applied systematically [80].	Uses pre-defined inclusion and exclusion criteria (e.g., based on PICO elements) applied consistently to all candidate studies [3] [81].
Critical Appraisal	No formal quality assessment of the included studies is required [79].	Rigorous critical appraisal (risk of bias assessment) of included studies is mandatory, often using dual independent reviewers [79] [81].
Data Synthesis	Narrative, qualitative summary, which may be chronological, conceptual, or thematic [79] [82].	Narrative and/or tabular synthesis; may include a meta-analysis for statistical pooling of quantitative data if studies are sufficiently homogeneous [79] [80].
Timeline & Resources	Weeks to months; requires fewer resources [79].	Months to years (average 18 months); resource-intensive, often requiring a team [79] [81].
Output & Conclusions	A perspective on the topic; conclusions are often interpretive and may be influenced by the author's views [80] [81].	An evidence-based summary; conclusions are based directly on the synthesized findings, highlighting certainty and recommendations for practice and research [80] [81].
Risk of Bias	Higher potential for bias due to non-systematic methods and lack of quality assessment [81].	A primary goal is to minimize bias through explicit and reproducible methods at every stage [81].

Experimental Protocols for Systematic Reviews

The rigorous methodology of a systematic review can be conceptualized as a multi-stage workflow. The following diagram, generated using Graphviz, outlines this structured process.

Systematic Review Workflow

Detailed Methodological Steps

The workflow illustrated above can be expanded into a detailed protocol, such as the PSALSAR framework, which is highly applicable to environmental science [83].

• Research Protocol (P): Define the research scope, objectives, and review question using a structured framework like PICO. Develop the detailed systematic review protocol specifying the search strategy, eligibility criteria, data items, and synthesis methods. Register the protocol in a repository like PROCEED, specific to environmental research, or PROSPERO to enhance transparency and reduce duplication of effort [3] [83].
• Systematic Searching (S): Conduct a comprehensive search across multiple bibliographic databases (e.g., Scopus, Web of Science, GreenFile) and other sources. The search strategy must be designed in consultation with a subject librarian and include:
  • Search Strings: Combinations of free-text keywords and controlled vocabulary (e.g., MeSH, Emtree) using Boolean operators (AND, OR, NOT) [3] [81].
  • Sources: Multiple academic databases and supplementary searches for grey literature (e.g., governmental reports, dissertations, clinical trial registries, organizational websites) to mitigate publication bias [3] [81].
  • Documentation: Preserve and archive the final search strategy for each database on platforms like searchRxiv to ensure reproducibility [3].
• Appraisal (A): Screen the retrieved records for eligibility against the pre-defined inclusion/exclusion criteria. This process is typically performed in two phases:
  • Title/Abstract Screening: Initial filtering of records.
  • Full-Text Screening: Detailed assessment of potentially eligible studies. The screening should be performed by at least two reviewers independently, with procedures for resolving conflicts [3] [81]. A list of excluded studies at the full-text stage, with reasons for exclusion, should be maintained and provided [3].
• Data Extraction (S): Extract relevant data from the included studies using a pre-piloted data extraction form. Data points typically include study characteristics (e.g., author, year, location, design), participant/details of the environmental system, interventions/exposures, comparators, outcomes, and key findings. This process should also be performed by two reviewers to ensure accuracy [3] [81].
• Synthesis (A): Synthesize the extracted data. This can be:
  • Narrative Synthesis: A structured textual summary, often using tables and figures to explore relationships and patterns within the data.
  • Quantitative Synthesis (Meta-Analysis): If studies are sufficiently homogeneous, statistical methods are used to calculate a summary estimate of effect. This involves assessing statistical heterogeneity (e.g., using I² statistic) and potential for publication bias (e.g., using funnel plots) [80] [84].
• Reporting Results (R): Prepare the final review manuscript adhering to relevant reporting guidelines such as PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) or ROSES (RepOrting standards for Systematic Evidence Syntheses) for environmental topics [3]. All data extractions and analysis records should be made available as supplementary files [3].

The Scientist's Toolkit: Essential Reagents for Evidence Synthesis

Table 2: Key methodological tools and resources for conducting systematic reviews.

Tool / Reagent	Function & Application
PICO Framework	A structured tool to formulate a focused, answerable research question by defining Population/Problem, Intervention, Comparison, and Outcomes [81].
Systematic Review Protocol	The master plan for the review, detailing the rationale, objectives, and explicit methods. Registration mitigates bias and prevents duplication [3].
Boolean Operators	Logical operators (AND, OR, NOT) used to construct effective and comprehensive search strings for electronic databases [3] [81].
Grey Literature	Evidence not published commercially (e.g., theses, reports, conference proceedings). Its inclusion reduces publication bias and provides a more complete view of the evidence [81].
Critical Appraisal Tool	A checklist or instrument (e.g., Cochrane Risk of Bias tool, ROBINS-I) used to systematically assess the methodological quality and risk of bias in individual studies [3] [81].
PRISMA Statement	An evidence-based minimum set of items for reporting in systematic reviews and meta-analyses, ensuring transparency and completeness [79] [84].
Meta-Analysis Software	Statistical software packages (e.g., R with metafor package, RevMan, Stata) used to combine and analyze quantitative data from multiple studies.

In the rigorous domain of environmental management research, the peer review of systematic review protocols represents a fundamental process for ensuring methodological soundness before full-scale analysis begins. This proactive evaluation serves as a critical quality control mechanism, identifying potential flaws in the research plan at a stage when they can still be economically and effectively addressed [85]. Unlike traditional article peer review that assesses completed research, protocol peer review focuses on the proposed methods, offering external expert opinion on the study design, establishing priority for innovative ideas, and demonstrating to funding bodies that the research plan has undergone expert scrutiny [85]. Within environmental evidence synthesis, where research questions often address complex, multifaceted ecosystems and human health interactions, this early-stage validation is particularly valuable for preventing methodologically poor research and reducing publication bias against null or inconvenient findings [85] [8].

The transition from traditional expert-based narrative reviews to systematic methodologies in environmental science has highlighted the importance of robust, pre-established protocols [8]. Empirical evidence demonstrates that systematic reviews, when properly conducted using predefined protocols, "produced more useful, valid, and transparent conclusions compared to non-systematic reviews" [8]. This application note details the standards, procedures, and practical considerations for implementing effective protocol peer review within the context of environmental management research.

Methodological Standards for Protocol Development

Core Components of a Systematic Review Protocol

A robust systematic review protocol for environmental management research must contain several essential components that provide the roadmap for the entire review process. These components ensure transparency, reproducibility, and methodological rigor throughout the evidence synthesis process [5] [3].

Table 1: Essential Components of a Systematic Review Protocol in Environmental Management

Protocol Section	Content Requirements	Environmental Research Considerations
Background	Context, purpose, and summary of existing literature; clear statement of why the study is necessary [86] [3].	Must frame within environmental decision-making context; identify relevant policy or regulatory frameworks.
Objective/Question	Primary question matching protocol title; secondary questions for subgroup analyses [3].	PECO/PICO elements (Population, Exposure, Comparator, Outcome) specific to environmental evidence [3].
Eligibility Criteria	Explicit definitions of populations, interventions/exposures, comparators, outcomes, and study designs [3].	Consideration of relevant environmental exposures (e.g., chemicals, habitat modifications) and outcomes (ecosystem health).
Search Strategy	Detailed search strings, databases, grey literature sources, and supplementary search methods [3].	Inclusion of environmental databases (e.g., AGRICOLA, GreenFILE), organizational websites, and non-English literature.
Screening Process	Methodology for title/abstract/full-text screening; consistency checking procedures [3].	Plan for handling large result sets common in broad environmental topics; use of machine learning tools where appropriate.
Study Validity Assessment	Approach for critical appraisal and validity assessment of included studies [3].	Adaptation of validity tools for diverse environmental study designs (observational, experimental, modeling).
Data Extraction	Strategy for coding and extracting qualitative/quantitative data [3].	Template for environmental data including exposure metrics, ecological endpoints, and contextual factors.
Data Synthesis	Planned methods for qualitative, quantitative, and narrative synthesis [3].	Consideration of meta-analysis for ecological data; approaches for handling heterogeneous outcome measures.

The protocol should clearly define the roles of all stakeholders, including commissioners, in formulating the research question [3]. Environmental management protocols particularly benefit from stakeholder engagement to ensure the review addresses decision-relevant questions and incorporates appropriate contextual factors.

Reporting Guidelines and Registration Requirements

Adherence to established reporting guidelines and protocol registration represents a critical step in ensuring methodological transparency and reducing reporting bias. Several key standards apply specifically to systematic review protocols in environmental research:

• ROSES Reporting Standards: Environmental Evidence journal requires completion of the RepOrting standards for Systematic Evidence Syntheses (ROSES) form upon submission, which demonstrates comprehensive reporting of methodological details [3]. The ROSES forms should be uploaded as a single-page supplementary PDF with the submitted manuscript.

• PROCEED Registration: The Collaboration for Environmental Evidence (CEE) requires registration of titles and protocols in the PROCEED database before conducting and submitting a systematic review [3]. This registration commits researchers to conducting and submitting their review, reducing publication bias.

• SPIRIT Guidelines: For randomized trials included within environmental health systematic reviews, protocols should follow SPIRIT guidelines, including the flow diagram and populated checklist [86].

Registration in protocols in publicly accessible repositories like PROSPERO or the Open Science Framework (OSF) creates a permanent record of the proposed methods and helps prevent duplication of effort while establishing priority for the research ideas [5].

The Protocol Peer Review Process: Workflow and Evaluation Criteria

Structured Workflow for Protocol Peer Review

The peer review of systematic review protocols follows a structured workflow that maximizes efficiency and ensures comprehensive methodological assessment. The process typically begins after researchers develop a complete protocol but before they begin full-text screening or data extraction [85].

Diagram 1: Protocol peer review and publication workflow

This workflow illustrates the pathway from protocol development through to registration and eventual full review conduct. Authors have the option to submit protocols for "peer-review only" without subsequent publication, which can be valuable when seeking feedback before funding decisions or when reserving disclosure of research plans [85]. The electronic, open-access model employed by many modern journals is particularly well-suited to supporting this workflow due to its flexibility and transparency [85].

Evaluation Criteria for Protocol Peer Review

Peer reviewers of systematic review protocols employ different standards from those used for completed research articles. Rather than making simple "accept" or "reject" decisions, reviewers provide constructive feedback on the research plan with the goal of improving methodological quality [85]. Key evaluation domains include:

Table 2: Key Evaluation Domains for Protocol Peer Review in Environmental Research

Evaluation Domain	Reviewer Considerations	Common Methodological Flaws
Search Strategy	Comprehensiveness, reproducibility, inclusion of grey literature, appropriate databases [3].	Limited search sources; poorly constructed search strings; language restrictions that miss relevant evidence.
Eligibility Criteria	Clarity, appropriateness for research question, explicit inclusion/exclusion rationale [3].	Vague population/exposure definitions; outcome measures not aligned with review question.
Validity Assessment	Use of appropriate critical appraisal tools; plan for assessing study limitations [3].	Lack of predefined validity criteria; no plan for handling high-risk-of-bias studies.
Data Extraction & Management	Completeness of data items; process for obtaining missing data; reproducibility checks [3].	Insufficient detail on planned variables; no method for verifying extraction accuracy.
Synthesis Methods	Alignment between planned analyses and review question; handling of heterogeneity [86].	Inappropriate statistical methods; no plan for exploring heterogeneity in environmental contexts.
Stakeholder Involvement	Appropriate engagement in question formulation; management of competing interests [3].	Unacknowledged stakeholder influence; unclear role of funders in the review process.

Reviewers are specifically asked to comment on potential flaws that might threaten the validity of the research and to suggest improvements to the research plan [85]. This approach differs fundamentally from traditional article review by focusing on strengthening methods rather than judging results.

Implementation in Environmental Research

Environmental Evidence Methodological Framework

The application of systematic review methodologies in environmental management requires specific adaptations to address the unique challenges of ecological and environmental evidence. The Collaboration for Environmental Evidence (CEE) has developed comprehensive guidelines specifically tailored to environmental topics, which include considerations for:

• Complex Causal Pathways: Environmental questions often involve multifaceted causal relationships with multiple confounding factors that must be addressed in the protocol [8].

• Diverse Study Designs: Unlike clinical research dominated by randomized trials, environmental evidence incorporates observational studies, case-control designs, modeling approaches, and before-after comparisons that require specific validity assessment tools [8] [3].

• Heterogeneous Outcomes: Environmental outcomes may include ecological, socioeconomic, and human health endpoints measured using different metrics across studies, requiring careful planning for data synthesis [3].

The Navigation Guide systematic review method, originally developed for environmental health topics, provides a structured framework for integrating human and ecological evidence and has been endorsed by the National Academy of Sciences and World Health Organization [8]. This methodology emphasizes transparent, protocol-based approaches that minimize bias through predefined methods.

Diagram 2: Integrated evidence assessment in environmental reviews

Practical Protocol Registration and Publication Venues

Environmental researchers have multiple options for registering and publishing systematic review protocols, which enhances methodological transparency and establishes priority:

• PROCEED Registry: The CEE's official registry for environmental evidence syntheses, required for reviews submitted to Environmental Evidence journal [3].

• PROSPERO: International prospective register of systematic reviews, which accepts protocols for all health-related reviews including environmental health topics [5].

• Open Science Framework (OSF): Generalized registry suitable for scoping reviews and systematic reviews outside PROSPERO's scope [5].

• Journal Protocol Publication: Journals such as Environmental Evidence, Research Integrity and Peer Review, and Systematic Reviews publish peer-reviewed protocols, providing formal citation and dissemination [86] [3].

Protocols should normally be no longer than 8,000 words and include all elements outlined in Table 1 to facilitate comprehensive peer review [3]. The publication of protocols in open-access venues makes the methods publicly accessible and demonstrates commitment to methodological transparency.

Table 3: Research Reagent Solutions for Protocol Development and Peer Review

Tool/Resource	Function	Application in Environmental Research
ROSES Forms	Standardized reporting forms for systematic evidence syntheses [3].	Ensures comprehensive methodological reporting specific to environmental evidence.
CEE Guidelines	Methodological standards for environmental evidence syntheses [3].	Provides discipline-specific guidance for protocol development.
PRISMA-P	Reporting standards for systematic review protocols [86].	Ensures complete protocol reporting across all domains.
ColorBrewer	Color selection tool for creating accessible figures [87].	Develops color-blind safe visualizations for environmental data presentation.
WebAIM Contrast Checker	Verifies color contrast accessibility [88] [89].	Ensures readability of graphical elements for all readers.
searchRxiv	Archive for storing and citing search strategies [86] [3].	Preserves environmental evidence search strings for reproducibility.
Navigation Guide	Methodology for integrating human and environmental health evidence [8].	Framework for complex environmental health systematic reviews.

Environmental researchers should also utilize discipline-specific resources such as the Society of Environmental Toxicology and Chemistry (SETAC) guidelines, the EPA's Integrated Risk Information System (IRIS) assessment protocols, and the WHO's chemical risk assessment methodologies when developing protocols for relevant topics. These resources provide domain-specific methodological guidance that complements general systematic review standards.

Conclusion

A meticulously developed and publicly registered protocol is the cornerstone of a credible and impactful systematic review in environmental management. It serves as a vital safeguard against bias, enhances methodological transparency, and ensures the review addresses a clearly defined and relevant question. By adhering to established standards like PRISMA-P and leveraging resources from organizations like the Collaboration for Environmental Evidence, researchers can significantly improve the quality of evidence synthesis. The future of informed environmental decision-making depends on this rigor, moving beyond narrative summaries to reliable, reproducible systematic reviews that can effectively guide policy and practice in addressing complex environmental challenges.

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