Navigating evidence synthesis in applied ecology

Abstract Evidence syntheses use systematic methods to identify, select and synthesise relevant research to address a scientific question. In applied ecology, the most common form of synthesis involves meta‐analysis to quantify the effects of stressors or management interventions, whereas other synthesis methods, such as systematic maps, can help to identify knowledge gaps. Synthesis methods are increasingly used, but many studies fail to implement them robustly. In our experience as journal editors, many authors, reviewers and editors struggle to navigate these methods effectively. To address this, we provide practical guidance for authors, setting out key design expectations and common problems to avoid. Key best‐practice criteria include: (1) a clearly defined, applied research question; (2) full documentation of search strategy; (3) searches using multiple dedicated platforms; (4) clear study selection criteria; (5) full reporting of the screening and selection process; (6) acknowledgment of the limitations of the synthesis study as well as the studies synthesised; and (7) making all underlying data available and, where applicable, the code. For studies adopting a quantitative meta‐analysis, the criteria also include: (9) using weighted meta‐analyses; (9) accounting for non‐independence among effect sizes; (10) analysis of moderators and collinearity; and (11) assessment and, if necessary, correction of sources of bias. In addition to the criteria above, we recommend: (12) the use of benchmark studies to refine searches and maximise comprehensiveness; (13) searches of platforms containing grey literature, such as theses or reports; (14) literature searches in non‐English languages; (15) multi‐reviewer screening of literature and extraction of data to increase replicability; and (16) use of critical appraisal methods to assess the robustness of the synthesised studies. Not all criteria will be appropriate or feasible for every evidence synthesis, so there is scope for flexibility in their application. Where authors deviate from the criteria outlined above, they should clearly explain and justify their decisions. As evidence synthesis methods are part of a fast‐moving research field, this guidance should be viewed as an evolving methodological foundation rather than a static prescription, intended to raise applied ecologists' awareness of the complexity of these methods.

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Publication Details

Journal
Journal of Applied Ecology
Published
2026-10-29
DOI
https://doi.org/10.1111/1365-2664.70618
Primary Topic
Meta-analysis and systematic reviews
Type
article
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article

Navigating evidence synthesis in applied ecology

Jos Barlow, Cate Macinnis‐Ng, Tadeu Siqueira, Martín Andrés Nuñez et al.
Journal of Applied Ecology
Meta-analysis and systematic reviews
article

Navigating evidence synthesis in applied ecology

Jos Barlow, Cate Macinnis‐Ng, Tadeu Siqueira, Martín Andrés Nuñez, Yi Zou, Lorenzo Marini, Kulbhushansingh Ramesh Suryawanshi, Alec P. Christie, Alexandro B. Leverkus, Rowena Gordon, Kasey E. Barton, Romina Rader, Kevin A. Wood, Péter Batáry, Lydia Groves, Philip A. Martin
article en

Abstract

Abstract Evidence syntheses use systematic methods to identify, select and synthesise relevant research to address a scientific question. In applied ecology, the most common form of synthesis involves meta‐analysis to quantify the effects of stressors or management interventions, whereas other synthesis methods, such as systematic maps, can help to identify knowledge gaps. Synthesis methods are increasingly used, but many studies fail to implement them robustly. In our experience as journal editors, many authors, reviewers and editors struggle to navigate these methods effectively. To address this, we provide practical guidance for authors, setting out key design expectations and common problems to avoid. Key best‐practice criteria include: (1) a clearly defined, applied research question; (2) full documentation of search strategy; (3) searches using multiple dedicated platforms; (4) clear study selection criteria; (5) full reporting of the screening and selection process; (6) acknowledgment of the limitations of the synthesis study as well as the studies synthesised; and (7) making all underlying data available and, where applicable, the code. For studies adopting a quantitative meta‐analysis, the criteria also include: (9) using weighted meta‐analyses; (9) accounting for non‐independence among effect sizes; (10) analysis of moderators and collinearity; and (11) assessment and, if necessary, correction of sources of bias. In addition to the criteria above, we recommend: (12) the use of benchmark studies to refine searches and maximise comprehensiveness; (13) searches of platforms containing grey literature, such as theses or reports; (14) literature searches in non‐English languages; (15) multi‐reviewer screening of literature and extraction of data to increase replicability; and (16) use of critical appraisal methods to assess the robustness of the synthesised studies. Not all criteria will be appropriate or feasible for every evidence synthesis, so there is scope for flexibility in their application. Where authors deviate from the criteria outlined above, they should clearly explain and justify their decisions. As evidence synthesis methods are part of a fast‐moving research field, this guidance should be viewed as an evolving methodological foundation rather than a static prescription, intended to raise applied ecologists' awareness of the complexity of these methods.

Journal of Applied EcologyVol. 63(11)
Ikerbasque (ES), University of Hawaiʻi at Mānoa (US), University of Padua (IT), University of Auckland (NZ), Universidad de Granada (ES), Basque Centre for Climate Change (ES), Institute of Ecology and Botany (HU), Wildfowl & Wetlands Trust (GB), HUN-REN Centre for Ecological Research (HU), University of Houston (US), Imperial College London (GB), Lancaster University (GB), Xi’an Jiaotong-Liverpool University (CN), Universidad Nacional del Comahue (AR), Nature Conservation Foundation (IN), British Ecological Society (GB), Universidade Estadual Paulista (Unesp) (BR), University of New England (AU)
Openalex Percentile: Top 11%
Meta-analysis and systematic reviews
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