Incorporating species population dynamics into static prioritization: Targeting species undergoing rapid change
Incorporating species population dynamics into static prioritization: Targeting species undergoing rapid change
复制标题
将物种种群动态纳入静态优先级排序：针对正在快速变化的物种
DOI：
10.1111/1365-2664.13291
复制
发表时间：
2018
影响因子：
5.7
通讯作者：
Kadoya Taku
中科院分区：
文献类型：
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作者：
Fukumori Kayoko;Ishida Shinya;Shimoda Michiko;Takenaka Akio;Akasaka Munemitsu;Nishihiro Jun;Takamura Noriko;Kadoya Taku
保护规划通常使用具有物种静态空间分布的模型来预测物种的可能出现。然而，静态数据通常不能捕捉到濒危物种丰度的快速变化或隐藏的生命阶段，如卵和种子的休眠阶段。很少有人知道如何忽视动态人口过程，如恢复过程，可以影响的结果，空间优先级在保护planning.In这项研究中，我们调查了62种水生植物的分布，包括23种受威胁的物种，在415个农业池塘37年来，包括恢复过程中的保护规划的重要性。利用水生植物的长期历史存在-缺失数据和种子库寿命数据，我们估计了每个池塘中每个物种在未来100年的种群消失率和恢复率。85.4%，40.3%和4.8%的水生植物物种的平均恢复率分别超过0，0.2和0.4。模拟结果表明，当考虑恢复过程时，物种的灭绝风险大大降低。我们发现，包括恢复过程中的目标物种种群增加了空间优先级的性能，保护更多的物种在一个较小的保护池塘。池塘物种保护的空间排名差异很大的情况下，包括和排除人口恢复过程，这表明基于互补性分析的保护优先事项是敏感的基本假设。我们的动态方法，考虑物种的恢复过程，有助于更有效的保护规划，减少偏见的预测物种的状态，考虑到神秘的生命阶段是普遍存在于许多植物和一些动物。目标物种的时间序列存在/不存在数据对于该方法非常有用，并且通常通过参与性监测存档。因此，应用我们的方法的机会是广泛的，特别是在地方范围内的保护优先级和决策。
Conservation planning has generally used models with a static spatial distribution of species to predict the likely occurrence of species. However, static data do not usually capture rapid changes in the abundance of endangered species or cryptic life stages such as the dormancy stage of eggs and seeds. Little is known about how neglecting dynamic population processes, such as recovery processes, can affect the outcomes of spatial prioritization in conservation planning.In this study, we investigated the distribution of 62 aquatic plant species, including 23 threatened species, in 415 agricultural ponds for 37 years to examine the importance of including recovery processes in conservation planning. Using long‐term historical presence–absence data and seedbank longevity data for aquatic macrophytes, we estimated rates of population disappearance and recovery for each species in each pond over the next 100 years.Average rates of recovery exceeded 0, 0.2, and 0.4 in 85.4%, 40.3%, and 4.8% of aquatic plant species, respectively. Simulation results suggested that the extinction risk for a species greatly decreased when recovery processes were considered. We found that including recovery processes in target species populations increased the performance of spatial prioritization by protecting more species in a smaller number of protected ponds. Spatial ranking of ponds for species conservation differed substantially among scenarios that included and excluded population recovery processes, suggesting that conservation priorities based on complementarity analysis are sensitive to underlying assumptions.Synthesis and applications. Our dynamic approach, which considers recovery processes of species, contributes to more effective conservation planning by reducing bias in the prediction of species’ state, given that cryptic life stages are ubiquitous among many plants and some animals. Time‐series presence/absence data on target species are quite useful for the approach and are often archived by participatory monitoring. Thus, the opportunities for applying our method are broad, especially for conservation prioritization and decision‐making at the local scale.