Land management practices have significant impacts on biodiversity and climate change processes. Conservation and rewilding practitioners are increasingly seeking to enhance ecosystem functions and carbon sequestration simultaneously, encouraged by climate policies such as the European Green Deal. In recent years, ecosystem restoration involving large herbivores (≥ 10 kg) has attracted growing interest. However, the climate impacts of large herbivores are complex, including direct and indirect impacts from greenhouse gas (GHG) emissions, carbon storage, wildfire and albedo. These impacts can have cooling or warming effects and vary with species, herd density, season and habitat. To date, the diverse research on this topic has not been collated and categorised in a systematic map. Here, we present a systematic map of research on the climate effects of large herbivores in European terrestrial habitats, highlighting research distribution, clusters and gaps, and the potential for further quantitative analyses. We address the primary question of what research exists on the climate effects of large herbivores in Europe. Following our pre-published protocol, we used a pre-defined search string to conduct a search of peer-reviewed and grey literature, using a range of bibliographic databases, search engines and websites. We screened search results for relevance in two stages: by title and abstract, then full text. We excluded articles that failed to meet the eligibility criteria of terrestrial habitats in Europe (Population), large herbivores (Exposure) and climate impacts (Outcome). We coded the included studies by multiple variables, recorded in a spreadsheet alongside the narrative synthesis. We identified 316 articles for inclusion, involving a total of 565 studies (different research comparisons within the same article). Most studies were conducted in Northern Europe (63
The global expansion of salmon aquaculture has transformed marine food systems, offering economic benefits while amplifying environmental and socio-economic challenges. The shift from wild-caught to farmed salmon has led to widespread concerns, including disease transmission, genetic introgression, pollution, and conflicts with Indigenous communities. Additionally, salmon feed supply chains have global implications, such as overfishing in West Africa. Although many studies exist, research is fragmented and dispersed across disciplines, and the influence of industry funding raises questions about bias. This overview of reviews synthesises existing systematic reviews on salmon farming to evaluate the scope, quality, and findings of the secondary literature on its environmental, economic, and social impacts. Specifically, we ask the question: “What systematic review evidence exists on Atlantic and Pacific salmon aquaculture, and what are the characteristics, thematic focus, and methodological quality of this evidence?”. This overview of reviews follows guidelines from the Collaboration for Environmental Evidence (CEE) and the ROSES reporting standards. Systematic reviews (broadly defined as reviews either claiming to or actually using some form of systematic methodology) were identified via searches in Scopus, Web of Science, and Lens.org using a structured, validated search strategy. Inclusion criteria focused on reviews explicitly targeting Atlantic or Pacific salmon aquaculture (including rainbow trout). Metadata were extracted on study methods, topical focus, production stages, and funding sources. Review quality was assessed using the CEESAT critical appraisal tool, and visualisations were produced to identify gaps in coverage and assess methodological rigour. Out of 327 unique records, 37 reviews were included. Most reviews focused on production-related topics (e.g. fish health, sea lice, feed supply), with very few addressing environmental or social impacts. No reviews met the threshold for high methodological rigour, and only four were rated as moderate quality; the remainder were judged as low or exceptionally low quality. Common weaknesses included absence of a priori protocols, lack of critical appraisal, poor reporting of screening and extraction methods, and inappropriate synthesis techniques such as vote counting. Industry co-authorship was present in 7 reviews, and 8 were industry-funded. Research on sustainability was hindered by methodological inconsistency and limited transparency. Despite a growing body of literature on salmon aquaculture, high-quality evidence syntheses remain rare. Most systematic reviews are methodologically flawed and overly focused on productivity, with limited assessment of environmental or socio-economic externalities. Greater attention is urgently needed to unbiased, interdisciplinary, and high-quality evidence synthesis—especially on the broader impacts of salmon farming. Decision-makers should interpret existing evidence syntheses on salmon aquaculture with caution, given the generally low methodological rigour and high risk of bias identified across reviews. Apparent consensus or patterns in the literature may reflect methodological artefacts rather than robust underlying evidence. We therefore call for enhanced rigour in review methods, transparent reporting, and increased scrutiny of industry influence on research agendas.
Tropical areas, particularly Brazil, are home to a significant portion of the world’s biodiversity, with the Brazilian Atlantic Forest (BAF) being a crucial biome recognized as a global biodiversity hotspot. However, the BAF has been subject to severe degradation due to anthropogenic activities, resulting in extensive habitat loss and fragmentation. These changes have prompted numerous studies on their effects on biodiversity, focusing on forest fragments and protected areas. Despite this research, there is a notable lack of meta-data on biodiversity in human-modified landscapes within the BAF- where only 31
We welcome Hodgson et al. (2026) empirical evaluation of ontology-grounded large language models (LLMs) for data extraction in environmental evidence synthesis. The study makes a valuable contribution by quantifying performance across attribute types and by openly documenting where current approaches struggle.
Nature-based solutions (NbS) are defined as actions that protect, conserve, restore, and sustainably use natural or modified ecosystems. These actions aim to deliver environmental services, enhance biodiversity, and support societal well-being. NbS are increasingly promoted across a wide range of sectors, including agriculture, coastal management, and civil engineering. However, despite being introduced almost twenty years ago, NBS appear not to have been widely and explicitly adopted in aquaculture production systems policies and practices, arguably because there is little evidence of their efficacy in improving environmental outcomes and production. This systematic map therefore seeks to address the primary review question: What evidence exists in the literature on reported environmental outcomes associated with nature-based approaches in aquaculture? To answer this question, the study will identify, collate, and characterize the available evidence on nature-based approaches applied within aquaculture systems. This systematic map will follow a structured evidence-synthesis approach to identify and characterize literature on nature-based solutions in aquaculture. Comprehensive searches will be conducted across established scientific databases using carefully developed search strings, and these will be complemented by targeted grey literature searches across specialist aquaculture and NbS platforms, as well as Google Scholar. Retrieved records will be screened at title, abstract, and full-text levels against predefined eligibility criteria. Studies will be included if they focus on aquaculture systems, examine interventions framed as or consistent with NbS, report outcomes related to environmental performance, socio-economic value, or policy relevance, and are based on empirical evidence from peer-reviewed or credible grey literature sources. Data from eligible studies will be extracted and summarized descriptively, followed by a narrative synthesis to identify thematic clusters, geographical patterns, and gaps in the evidence base. The outputs will provide a structured knowledge base to inform researchers, practitioners, and policymakers seeking to expand the application of NbS in aquaculture.
Important ecosystem services (ES), defined by the Millennium Ecosystem Assessment as benefits people obtain from ecosystems, are provided by kelp forests (e.g. nutrient cycling, nursery sites for fisheries and habitat provision). However, kelp forest degradation is extensive and ongoing with 40–60
Abstract Background The tire additive N-(1,3-dimethylbutyl)-Nʹ-phenyl-p-phenylenediamine (6PPD) is widely produced in large volumes as a rubber antidegradant. This chemical can be released into the environment throughout the lifecycle of rubber products. Recently, 6PPD has become the subject of regulatory interest in some jurisdictions due to its widespread environmental occurrence and the acute toxicity of its transformation product N-(1,3-dimethylbutyl)-Nʹ-phenyl-p-phenylenediamine-quinone (6PPDQ) to some salmonids. As research advances for these emerging contaminants, it is critical to understand whether 6PPD and 6PPDQ concentrations in the environment are high enough to pose a risk to living organisms. Here, we present a protocol to conduct two linked systematic evidence maps related to (1) the occurrence of 6PPD and 6PPDQ in the environment and (2) the effects of 6PPD and 6PPDQ on living organisms. Our objective is to collate information on quantification methods, occurrence data, studied species, and toxicity endpoints. This work will contribute to synthesizing a rapidly expanding body of literature and providing insight into knowledge gaps to direct future work. Methods The systematic maps will be developed in accordance with the Collaboration for Environmental Evidence Guidelines and Standards for Evidence Synthesis in Environmental Management. A unified search strategy using chemical names, acronyms, identifiers, and trade names for 6PPD and 6PPDQ will be used for both maps. Searches will be conducted in seven databases, and grey literature will be sourced from key websites and Advisory Board input. Search results will be managed in a reference management software and screened at the title/abstract and full-text levels against predefined eligibility criteria based on the Population-Outcome and Population-Exposure-Comparison-Outcome framework for Map 1 and Map 2, respectively. A decision tree designed a priori will guide concurrent screening to determine article eligibility for either or both maps. For all eligible articles, bibliographic and study-specific data will be coded and entered into a searchable database. Both article screening and data coding will be completed by two independent reviewers. Two systematic evidence maps will summarize the evidence base using narrative synthesis, figures, and tables.
Abstract Background Water contamination by heavy metals poses serious risks to human health, ecosystems, and food security. Established and commonly used remediation methods have limitations in terms of cost, sustainability, and environmental impact, especially in under-resourced, developing, and underdeveloped countries. Recently, the emergence of biodegradable polymer blend foams filled with carbonaceous materials, such as graphene oxide and carbon nanotubes, offers environmentally friendly adsorbents for heavy metals in water. However, a consolidated, synthetic overview of the evidence on material design, properties, adsorption capacities, and efficiencies remains lacking for these foams. The current systematic review aims to synthesise and critically evaluate the existing evidence on the fabrication, properties, adsorption mechanisms, and applicability of biodegradable polymer blend foams filled with carbonaceous materials for adsorbing heavy metals in water. The review also seeks to develop a consolidated evidence document that will inform policy, guide future research, and assist the development and implementation of sustainable treatment technologies for the removal of heavy metals in water in resource-limited areas. Methods This systematic review protocol is based on the question, “What is the adsorption efficiency and capacity of biodegradable polymer blend foams filled with carbonaceous materials in the removal of heavy metals from water?” A comprehensive search will be conducted using electronic bibliographic sources like Web of Science (core collections), Scopus, ScienceDirect, and search engines like PubMed, together with grey literature like Google Scholar, targeting peer-reviewed studies on laboratory and pilot-scale investigations of biodegradable polymer blend foams filled with carbonaceous materials for the removal of heavy metals from water. Eligibility criteria include studies on any type of water contaminated with heavy metals such as lead, copper, chromium, and cadmium. The extraction of data will be focused on material composition, processing techniques, characterisation, and adsorption performance. Quantitative data will be tabulated and, where applicable, subjected to meta-analysis. Researchers, consultants, and municipalities - especially in South Africa- will be consulted to contextualise findings and assist in translating evidence into practical water treatment solutions.
Evidence syntheses are valuable sources of robust and transparent knowledge that can identify gaps in research and inform evidence-based decision making. However, the process of synthesis is time consuming and costly. We investigate a new AI-based method that uses a large-language model (LLM) grounded in ontologies (i.e. structured machine-interpretable glossaries of domain terminology) to extract information from a set of 80 articles on coastal wetland restoration outcomes. We evaluated this method by comparing human-extracted data with data extracted by OntoGPT — a Python package that combines an LLM with ontologies to extract structured information. We found that OntoGPT achieved 65% average agreement with human reviewers but varied based on information type requested for extraction. The highest agreement scores were found when extracting standardized information, and lower agreement scores were found for study-specific and interpretation-heavy information. Precision and recall — two common measurements of artificial intelligence performance — were 58% and 57%. Our results highlight the potential for LLMs to save some labour in the evidence synthesis process but highlight core challenges (e.g., complex information; subjective judgments) where further development is needed. While LLMs cannot replace human reviewers, they have the potential to assist in data extraction.
Automobiles are ubiquitous in the modern world, and chemicals leaching from car tires and from the tire wear particles produced during driving can be toxic to the environment, particularly in aquatic ecosystems. 6PPD-Quinone (6PPD-Q), a recently identified tire and tire wear particle leachate, has been identified as highly toxic to coho salmon and other aquatic species. Research on the distribution and impacts of 6PPD-Q in aquatic ecosystems is rapidly developing, while research on 6PPD-Q in other environmental media is just beginning. With research efforts developing on many fronts, there is a need to better map emerging knowledge about this toxin. To do that, we ask the question: “What research exists on the presence of the 6PPD-Q in different environmental media (water (freshwater), soil, sediment, and air, including dust)?” The ultimate purpose of this systematic map is to generate a literature catalog that serves as a searchable database about 6PPD-Q in different environmental media. The systematic map will follow the Collaboration for Environmental Evidence guidelines and conform to the Reporting Standards for Systematic Evidence Syntheses (ROSES). Relevant English language only literature searches will use a search string using the specified Boolean description of our PECO elements (Population: Environmental media water, soil, sediment, air: including dust; Exposure: N/A; Comparator: N/A; Outcome: The presence of 6PPD-Q/ The concentration of 6PPD-Q). Two bibliographic databases, Web of Science (WOS) Core Collection and ScienceDirect, will be searched. Additional literature will be located through searches of targeted search engines and specialist websites. Screening of titles, abstracts, and full texts will be completed in series using established eligibility criteria. The results of the systematic map will contain a searchable open-access database formatted in Microsoft Excel. Furthermore, the outcome will be presented in a global map of the geographical distribution of included studies and their PICO/PECO elements, including a narrative synthesis, descriptive statistics, tables, and figures.
BACKGROUND:Coastal ecosystems, including seagrass meadows, saltmarshes, and macroalgae, are crucial in the sequestration and storage of organic carbon. These ecosystems provide essential ecosystem services, such as supporting biodiversity, coastal protection, and water quality enhancement. Despite their significance, they face substantial threats from human activities, including pollution, habitat degradation, and overexploitation, further exacerbated by climate change phenomena like heatwaves and ocean acidification. Efforts to protect, restore, or alleviate pressures on blue carbon ecosystems can yield multifaceted benefits beyond climate mitigation, including preserving biodiversity, enhancing climate resilience, and safeguarding vital services for human well-being. Understanding the factors affecting the biodiversity and carbon capacity i.e. the capacity for carbon uptake, storage and sequestration, of these ecosystems is crucial for effective conservation efforts. The goal of the present study is to assess the available quantitative and qualitative evidence on the impacts of human activities on the biodiversity and carbon storage capacity of blue carbon ecosystems in the North-East Atlantic. Developing a systematic map of the available evidence could significantly enhance our understanding of the pressures faced by blue carbon ecosystems in the North-East Atlantic and facilitate the identification of knowledge clusters and gaps thereby determining the scope and depth of the current knowledge base. METHODS:A systematic map on existing evidence of human impacts on the biodiversity and carbon capacity of blue carbon ecosystems in the North-East Atlantic will be conducted using relevant bibliographic databases and a web-based search engine. All searches will be conducted in English and will gather peer reviewed publications from 1980 to 2024. The resulting literature will be screened by two independent screeners at the level of title and abstract followed by full text against a set of eligibility criteria (i.e. population, intervention, outcome, study type). Metadata will be extracted from studies that meet the eligibility criteria and summarize with heatmaps, bar plots, geographic distribution maps, and tabular summaries.
Marine ecosystems worldwide face extreme stress from human activities, with the North Sea being particularly affected and experiencing altered processes. To assess anthropogenic drivers for sustainable management, the Millenium Ecosystem Assessment (MEA) and the Intergovernmental Science-Policy Platform on Biodiversity and Ecosystem Services (IPBES) distinguished five main anthropogenic drivers: direct exploitation of fish and seafood, sea use change, human-driven climate change, pollution, and invasive alien species. However, evidence of the drivers’ relevance and their potential effects on species and the environment over time remains scarce. This systematic map provides knowledge on the five main anthropogenic drivers in the North Sea from 1945 to 2020 and identifies potential knowledge gaps in terms of management implications. To identify relevant articles we used our published systematic map protocol. We conducted systematic searches of academic and grey literature in English, German, and French in online databases (Web of Science, Scopus, PubMed, AquaDocs). The search followed a Population-Exposure-Comparison-Outcome framework and included the period January 1945 to December 2020. A total of 22,511 articles were deduplicated and screened by title and abstract, the remaining 5795 were screened full-text to provide a widely integrated evidence base. A set of 3356 articles were retained following eligibility criteria and were included in the final database. We extracted information on drivers in detail and their effects on study populations within different areas in the North Sea. Knowledge clusters and gaps were identified from the scientific effort and are synthesized narratively. Out of the 3356 articles, the majority focused on pollution throughout the entire period of 75 years. Research interest has increased in climate change and biological invasion only in the most recent decades. We identified knowledge clusters in the southern North Sea, especially in ICES standard species areas 6 and 7, which has the most articles overall, mainly emphasizing pollution. Northern areas were in contrast studied the least. The effects of pollution were mainly linked to changes in chemical water properties and to contamination levels for benthos and fish. The other drivers were rather associated with changes in biomass or abundance, with a strong focus on fish and benthos populations. A key knowledge gap was on the effects of global change, herein defined as simultaneous assessment of all five drivers, at different organizational levels and therein on different populations. This systematic map reveals substantial peer-reviewed evidence on the five main anthropogenic drivers in the North Sea. The map uncovers a strong increase in research interest regarding these drivers over the years, with a strong focus towards pollution and southern North Sea areas. Despite the increasing importance of climate change effects, this map highlights limited research effort on it. As ecosystem management nowadays strives for sustainable use of marine systems, it is more important than ever to understand linkages between drivers, potential cumulative effects and possible repercussions. The map revealed a strong knowledge gap regarding these linkages due to global change. On this basis, further systematic reviews can acknowledge these gaps, identifying the drivers’ impacts and their quick evolvement to support management decision-making at various governance levels.
Estuarine coastal regions play a critical role in global aquatic ecosystems, providing essential benefits such as diverse marine habitats, support for local economies through fisheries and tourism, and serving as important carbon stocks. Nonetheless, these invaluable, dynamic and complex habitats are under increasing threat from human-induced pressures, including pollution from agricultural runoff to sewage discharge, emphasizing the urgent need for innovative monitoring and mitigation strategies. Traditional biomonitoring methods involve the use of indicator species such as fish and benthic macroinvertebrates; however, these can be limited in their ability to detect pollution at an early stage. As a result, alternative monitoring strategies such as the use of algae have become increasingly popular due to their abundance sensitivity to changes in water quality. Previous research recognizes the capacity of various algae species to accumulate pollutants, thereby serving as reliable indicators of ecological stress and water contamination. Despite the growing acknowledgment of their potential, a comprehensive evaluation of the effectiveness of algae as biomonitors in estuaries remains without a systematic review. This map, therefore, seeks to synthesize existing knowledge on the applicability and reliability of algae for coastal environmental monitoring, aiming to highlight existing knowledge gaps for a future systematic review. By focusing on the utility of algae in estuarine contexts, this study aspires to provide a comprehensive overview of current practices and propose recommendations. Such an endeavor is crucial for directing future research, informing stakeholders, and guiding policy formulation towards more sustainable and effective environmental management of estuaries. This map aims to be a valuable resource for those involved in the management and preservation of estuarine environments, contributing to discussions on sustainable water management and ecological conservation. The Collaboration for Environmental Evidence Guidelines and Standards for Evidence Synthesis in Environmental Management will be followed to construct the systematic map. By using a tested search string consisting of English keywords and acronyms, we will look through two published databases (Scopus and Web of Science Core Collection) to find pertinent literature. Terms that describe the exposure (chemicals) and the population (algae in estuaries) will be combined in the search string. To this literature obtained so far, we will add more materials sourced from other search mechanisms. We will add to this body of literature with further material from Google Scholar and other internet searches, including sources in Portuguese. Next, adopting specified eligibility criteria, titles, abstracts, and full-texts will be analyzed one by one. A list of predefined variables will then be extracted from full-texts. A database containing all studies included in the map, along with coded metadata, will be generated. The evidence will be presented in a map report that includes text, figures, and tables. A matrix will be created to display the distribution and frequency of the included studies categorized by types of exposure and outcomes, aimed at identifying potential knowledge gaps and clusters.
As people work towards environmental sustainability for urban environments and everyday lives, tensions have been seen in different efforts on food, housing, environmental management, urban planning, and many cross-cutting issues touching on multiple aspects of social-ecological systems. Urban agriculture (UA) as one multifaceted, cross-cutting arena, has had one particular tension regarding relationships with housing and the built environment: its gentrification potential. However, different accounts have provided evidence and theorization of gentrification as a possible outcome of UA activities, as a risk for UA initiatives, and showing still other relationships between UA and gentrification. These different accounts may be partially explained by different theoretical engagements with gentrification, as well as multiple activities constituting a broad notion of urban agriculture. An overview of the scholarly work regarding these two topics can provide a starting point for understanding how they have been approached and theoretically engaged together, and demonstrate gaps in dominant academic discourses. This research for a systematic mapping of literature seeks to assess the academic work around relationships between urban agriculture and gentrification. The protocol outlines a comprehensive and reliable search and review strategy based on the core components of urban, agriculture, and gentrification in search strings and inclusion criteria. Texts in English, French, and German will be scanned as historically and currently dominant academic languages, while searching nine bibliographic databases or platforms. The protocol details a data coding strategy for metadata, empirical content, and analytic content. The results are expected to uncover sources of evidence for links between urban agriculture and gentrification, producing interoperable datasets of the evidence base, insights of the overall research landscape, and possibilities to find research gaps.
Artificial intelligence (AI) is increasingly being explored as a tool to optimize and accelerate various stages of evidence synthesis. A persistent challenge in environmental evidence syntheses is that these remain predominantly monolingual (English), leading to biased results and misinforming cross-scale policy decisions. AI offers a promising opportunity to incorporate non-English language evidence in evidence syntheses screening process and help to move beyond the current monolingual focus of evidence syntheses. Using a corpus of Spanish-language peer-reviewed papers on biodiversity conservation interventions, we developed and evaluated text classifiers using supervised machine learning models. Our best-performing model achieved 100% recall meaning no relevant papers (n = 9) were missed and filtered out over 70% (n = 867) of negative documents based only on the title and abstract of each paper. The text was encoded using a pre-trained multilingual model and class-weights were used to deal with a highly imbalanced dataset (0.79%). This research therefore offers an approach to reducing the manual, time-intensive effort required for document screening in evidence syntheses-with minimal risk of missing relevant studies. It highlights the potential of multilingual large language models and class-weights to train a light-weight non-English language classifier that can effectively filter irrelevant texts, using only a small non-English language labelled corpus. Future work could build on our approach to develop a multilingual classifier that enables the inclusion of any non-English scientific literature in evidence syntheses.
Evidence synthesists are ultimately responsible for their evidence synthesis, including the decision to use artificial intelligence (AI) and automation, and to ensure adherence to legal and ethical standards.Cochrane, the Campbell Collaboration, JBI, and the Collaboration for Environmental Evidence support the aims of the Responsible use of AI in evidence SynthEsis (RAISE) recommendations, which provide a framework for ensuring responsible use of AI and automation across all roles within the evidence synthesis ecosystem.Evidence synthesists developing and publishing syntheses with Cochrane, the Campbell Collaboration, JBI, and the Collaboration for Environmental Evidence can use AI and automation as long as they can demonstrate that it will not compromise the methodological rigor or integrity of their synthesis.AI and automation in evidence synthesis should be used with human oversight.Any use of AI or automation that makes or suggests judgements should be fully and transparently reported in the evidence synthesis report.AI tool developers should proactively ensure their AI systems or tools adhere to the RAISE recommendations so we have clear, transparent, and publicly available information to inform decisions about whether an AI system or tool could and should be used in evidence synthesis.
The global demand for high-quality, robust and up-to-date evidence to guide decision-making has never been higher. The vast quantity of scientific literature being produced and made accessible presents an unparalleled opportunity for evidence-based decision-making to become a widespread reality. In addition, the world has at its fingertips cutting-edge technologies, such as AI, to make sense of this extensive knowledge base and deliver insights more quickly to decision-makers most in need. AI-powered evidence syntheses promises to be transformative, saving many lives and enhancing livelihoods globally. However, achieving this requires substantial cultural shifts in the evidence community, including amongst both AI developers and users to shape both trustworthy AI and trust in AI. Current efforts to establish best practices are emerging, but progress is hindered by the lack of clear consensus on what constitutes trustworthy AI for evidence synthesis. Philanthropic investments in trustworthy AI systems, alongside robust evaluations of trust in AI for evidence synthesis, must be prioritised to determine the conditions required for an enabling environment. Mainstreaming AI for reliable, faster and cheaper evidence synthesis demands a better understanding of trustworthy AI and trust in these systems. Funders should prioritise aspects of trustworthiness and trust whilst balancing the drive towards ongoing innovation.
Over the last decade, a paradigm shift has been initiated in the field of nature management and conservation with shifting the focus from traditional, more static conservation efforts to dynamic conservation efforts. To promote dynamic restoration efforts, it is essential to provide nature managers with tools to measure the impact and effectiveness of relevant interventions. However, despite increasing practice, quantifying restoration management in a relevant and measurable way remains challenging. Therefore, this systematic map aims to elucidate which metrics are being used to measure the impact of dynamic nature management working with natural processes. To assess which metrics are being used to measure this impact, we will perform a systematic map in Web of Science, Scopus and Agricola. In addition, we will search for grey literature through directed visits to organizational websites, search ProQuest for relevant PhD theses on the topic and perform a search in Google Scholar. For the latter, we will only consider the first 200 articles. We will include articles conducted based on research in natural areas within temperate zones, where natural dynamics (e.g., grazing, hydrology, fire) are present, introduced or restored, and are assessed using before/after or control/impact study designs. The selected studies should mention measurements of the natural process restoration outcome related to relevant biodiversity metrics (e.g., richness, diversity, abundance). Literature from review studies will be included to identify other relevant articles. All studies positively assessed as relevant through the criteria above will be subject to critical appraisal. Hereafter, we will use the critical appraisal tool as issued by Environmental Evidence. The data obtained will be used to create an overview of restoration and conservation current practices in order to identify knowledge gaps. We will disseminate our results to nature managers and provide a time- and cost- assessment of each measurement to create a guide on monitoring of dynamic nature management.
BACKGROUND:Freshwater ecosystems are globally imperiled, with monitored vertebrate populations showing an average 83% decline since 1970. Braiding Traditional Ecological Knowledge (TEK) with Western science is increasingly recognized by global bodies like the IPBES (Intergovernmental Science-Policy Platform on Biodiversity and Ecosystem Services) as essential for achieving the transformative change needed to address this crisis. This systematic map provides a comprehensive, global synthesis of the diverse methodologies used for this purpose by answering the primary question: What is the evidence base for methodologies (approaches, frameworks, or models) that braid the TEK of Indigenous and local communities with Western science in the planning, management, monitoring, or assessment of freshwater social-ecological systems? The resulting synthesis is intended to empower researchers, practitioners, and policymakers to design more effective and equitable management strategies. METHODS:Following Collaboration for Environmental Evidence (CEE) guidelines, our protocol employs a multi-layered search strategy across three core bibliographic databases, targeted grey literature sources (including dissertations and key organizational websites), and a supplementary review-centric snowballing search. Records will be screened for eligibility in a two-stage process (Title/Abstract and Full-text) with robust consistency checking to ensure transparency and minimize bias. Data from included articles will be coded using a detailed protocol designed to answer our secondary questions and build a typology of knowledge braiding methodologies. The systematic map's outputs will include a narrative synthesis identifying knowledge gaps and clusters, a comprehensive public database of included studies, and a suite of interactive data visualizations.
