ArticleEnvironmental evidence2022
What evidence exists on the impacts of large herbivores on climate change? A systematic map protocol.
Article in Environmental evidence, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
2 citing papers in PubMed.
- Mammalian Browsers Disrupt Eco-Evolutionary Dynamics in a Forest Tree Restoration Planting.Evolutionary applications · 2025Article
- Population size and structure of beisa oryx and gerenuk in Geralle National Park, southeastern Ethiopia.Ecology and evolution · 2024Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundIn recent years there has been an increased focus on the role of large herbivores in ecosystem restoration and climate change mitigation. There are multiple processes by which large herbivores could potentially influence climate feedback and forcing effects, but the evidence has not yet been synthesised in a systematic and accessible format. Grazing, browsing, trampling, defecation, and seed dispersal by large herbivores can influence vegetation and soils in ways that may directly or indirectly contribute to climate change or mitigation. For example, changes in vegetation could impact wildfire regimes, carbon storage, and albedo, with ultimate impacts on climate. These processes may be influenced by herbivore species composition, density, and functional traits. The main aim of this systematic map is to synthesise the range of research on climate feedback and forcing effects from large herbivores (≥ 10 kg) in terrestrial ecosystems. We also aim to identify knowledge clusters and gaps in the research base, as well as assessing the potential for quantitative analyses.
methodsA search of peer-reviewed and grey literature will be conducted using a range of bibliographic databases, search engines and websites. The search strategy will involve using a pre-defined search string with Boolean operators. All search results will be screened for relevance according to specific eligibility criteria. Screening will be conducted in two stages: all articles will initially be screened by title and abstract, then those that meet the eligibility criteria will be screened by full text. At both stages, articles will be excluded if they don't meet all eligibility criteria or if they meet any exclusion criteria. All articles included as eligible after full text screening will be coded. At each stage (of screening and coding) a proportion of articles will be processed independently by two reviewers to assess inter-reviewer reliability and resolve differences. The evidence will be presented in a searchable database with accompanying visual outputs. A narrative synthesis will be provided outlining the range and distribution of evidence, knowledge gaps and clusters, potential bias, and areas for further research.
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What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.