Management plans bias the number of threatened species in protected areas: a study case with flora species in the Atlantic Forest

被引:0
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作者
Gabriel Silva Santos
Danielle Oliveira Moreira
Ana Carolina Loss
Mário Luís Garbin
机构
[1] National Institute of the Atlantic Forest (INMA),Departamento de Biologia, Centro de Ciências Exatas, Naturais e da Saúde
[2] Instituto Tamanduá,undefined
[3] Universidade Federal do Espírito Santo,undefined
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关键词
Atlantic forest; Biodiversity biases; Ecosystem management; Public interest in conservation; Biodiversity knowledge shortfall;
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摘要
Ensuring the effectiveness of protected areas (PAs) has become a top-priority conservation action. Without management plans to define clear conservation goals and actions, PAs risk failing to protect biodiversity. Yet, management plans are insufficiently detailed or absent for several PAs worldwide. Although biodiversity knowledge is a cornerstone to guide the creation of PAs, we still lack information on its impact on long-term management. Thus, to better understand how biodiversity inventories might bias the management of protected areas, we investigate how these plans relate to the number of threatened species in PAs. Thus, we mapped 10,407 records corresponding to 1,395 threatened flora species in 863 PAs of the Brazilian Atlantic Forest under different jurisdictions and found that PAs with management plans hold twice the number of threatened flora species than those without such plans. Additionally, we found no support for the idea that larger PAs or those under higher anthropic pressure are more likely to have management plans, suggesting that management plans represent a proxy for the attention that PAs receive that goes far beyond necessity. We suggest two major reasons for this result. First, better-studied PAs are more likely to receive public funds to establish their management plans. Second, PAs with management plans and well-defined conservation goals may attract more studies. Both reasons may act synergistically, and we provide guidance on how managers and scientists should overcome these biases.
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页码:843 / 858
页数:15
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