ARC Centre of Excellence for Environmental Decisions, Fenner School of Environment and Society, The Australian National University, Canberra, 2601, Australian Capital Territory, Australia.
School of Earth and Environmental Sciences, University of Queensland, Brisbane, 4072, Queensland, Australia.
Nat Ecol Evol. 2018 Mar;2(3):465-474. doi: 10.1038/s41559-017-0457-3. Epub 2018 Feb 5.
Mitigating the impacts of global anthropogenic change on species is conservation's greatest challenge. Forecasting the effects of actions to mitigate threats is hampered by incomplete information on species' responses. We develop an approach to predict community restructuring under threat management, which combines models of responses to threats with network analyses of species co-occurrence. We discover that contributions by species to network co-occurrence predict their recovery under reduction of multiple threats. Highly connected species are likely to benefit more from threat management than poorly connected species. Importantly, we show that information from a few species on co-occurrence and expected responses to alternative threat management actions can be used to train a response model for an entire community. We use a unique management dataset for a threatened bird community to validate our predictions and, in doing so, demonstrate positive feedbacks in occurrence and co-occurrence resulting from shared threat management responses during ecosystem recovery.
减轻全球人为变化对物种的影响是保护面临的最大挑战。由于对物种应对威胁的反应的信息不完整，预测缓解威胁措施的效果受到阻碍。我们开发了一种预测威胁管理下群落重构的方法，该方法将对威胁的反应模型与物种共存的网络分析相结合。我们发现，物种对网络共存的贡献可以预测它们在减少多种威胁下的恢复情况。与连接较差的物种相比，连接度较高的物种可能会从威胁管理中受益更多。重要的是，我们表明，少数物种关于共存和对替代威胁管理措施的预期反应的信息可以用于训练整个群落的反应模型。我们使用一个受威胁的鸟类群落的独特管理数据集来验证我们的预测，并在此过程中，展示了在生态系统恢复过程中，由于共同的威胁管理反应，出现和共存的正反馈。
