Using fire to enhance rewilding when agricultural policies fail
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Elsevier
Abstract
Rewilding has been proposed as an opportunity for biodiversity conservation in abandoned landscapes. However, rewilding is challenged by the increasing fire risk associated with more flammable landscapes, and the loss of open-habitat specialist species. Contrastingly, supporting High Nature Value farmlands (HNVf) has been also highlighted as a valuable option, but the effective implementation of agricultural policies often fails leading to uncertain scenarios wherein the effects of wildfire management remain largely unexplored. Herein, we simulated fire-landscape dynamics to evaluate how fire suppression scenarios affect fire regime and biodiversity (102 species of vertebrates) under rewilding and HNVf policies in the future (2050), in a transnational biosphere reserve (Gerês-Xurés Mountains, Portugal-Spain). Rewilding and HNVf scenarios were modulated by three different levels of fire suppression effectiveness. Then, we quantified scenario effects on fire regime (burned and suppressed areas) and biodiversity (habitat suitability change for 2050). Simulations confirm HNVf as a long-term opportunity for fire suppression (up to 30,000 ha of additional suppressed areas between 2031 and 2050 in comparison to rewilding scenario) and for conservation (benefiting around 60% of species). Rewilding benefits some species (20%), including critically endangered, vulnerable and endemic taxa, while several species (33%) also profit from open habitats created by fire. Although HNVf remains the best scenario, rewilding reinforced by low fire suppression management may provide a nature-based solution when societal support through agricultural policies fails
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Science of The Total Environment Volume. 755, Part 1, 10 February 2021, 142897
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https://doi.org/10.1016/j.scitotenv.2020.142897Sponsors
This research was supported by Portuguese national funds through FCT - Foundation for Science and Technology, I.P., under the FirESmart project (PCIF/MOG/0083/2017), and by project INMODES (CGL2017-89999-C2-2-R) funded by the Spanish Ministry of Science and Innovation. AL, FM and FM-F were supported by FCT (DL57/2016/CP1440/CT0001, IF/01053/2015; and DL57/2016/CP1440/CT0010, respectively). AR was supported by the Xunta de Galicia (ED481B2016/084-0) and IACOBUS program (INTERREG V-A España–Portugal, POCTEP 2014–2020)
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© 2020 The Author(s). Published by Elsevier B.V. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/)
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