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| Auteurs principaux: | , , , , , |
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| Format: | Recurso digital |
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Zenodo
2015
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| Accès en ligne: | https://doi.org/10.5281/zenodo.18199277 |
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- (Uploaded by Plazi for the IPBES Invasive Alien Species Assessment) Methods: We used meta-analysis to (1) test whether native and exotic species composition (richness or diversity) and performance (cover, density and biomass) differ in response to wildfire and prescribed fire, and (2) assess how the composition and performance of these species groups vary with time elapsed since fire and habitat types. Results: Most community-level research on how native and exotic species respond to fire has been conducted in the US and Australia, typically over short time scales, and with a focus on temperate forest and grassland ecosystems. Prescribed fire benefited native composition over short time scales (<1 yr) but, on average, had no effect on native performance, nor on exotic composition or performance. In contrast, wildfire consistently enhanced exotic composition and performance over all time scales, while having no effect on native species composition and significantly reducing native performance. Additionally, responses varied by habitat: native species groups responded positively to prescribed fire in heathlands and to a lesser extent in temperate grasslands, while responding negatively to wildfire in arid shrublands and heathlands, and to a more modest degree in tropical savannas. Exotic species groups responded positively to wildfire in arid shrublands, temperate forests and heathlands. Conclusions: This quantitative assessment of the literature revealed strong evidence for a positive response of exotics to wildfire, coupled with a striking near-absence of negative responses. The assessment additionally suggests that while prescribed fire does benefit native composition, on average, it does not appear to greatly facilitate native performance; however site-specific variation in how communities responded to fire was pronounced, underscoring the importance of local assessments in determining mechanistic drivers and management policy.