Improving assessments of data-limited populations using life-history theory
Improving assessments of data-limited populations using life-history theory
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DOI：
10.1111/1365-2664.13863
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发表时间：
2021-05-05
影响因子：
5.7
通讯作者：
Matthiopoulos, Jason
中科院分区：
文献类型：
--
作者：
Horswill, Cat;Manica, Andrea;Matthiopoulos, Jason
预测人口如何应对气候变化和人为压力需要详细了解人口特征，如生存和繁殖。然而，这些数据的可用性在空间和分类群之间存在很大差异。因此，通常的做法是通过填写替代物种或同一物种的其他种群的缺失值来进行种群评估。同时使用这些独立的替代值与观察到的数据忽略了生活史的权衡，连接人口的人口统计学的不同方面。因此，这种方法引入的偏见，最终可能导致错误的管理decisions.We使用贝叶斯分层框架结合联合收割机碎片多人口数据与建立生活史理论和重建人口特定的人口数据在一个物种繁殖范围的很大一部分。我们将我们的分析应用于一个长寿的殖民物种，黑腿三趾鸥里萨tridactyla，这是被列为全球脆弱的，并受到越来越多的人为压力，包括海上可再生能源开发的高度威胁。然后，我们使用投影分析，以研究如何重建的人口参数可能会改善人口评估，相比模型，联合收割机结合观察到的数据与独立的代理value.Demographic参数重建使用分层框架可以利用在一系列的人口建模方法。它们也可以用作参考估计值，以评估独立的替代值是否可能高估或低估缺失的人口统计参数。我们发现，来自独立来源的替代值往往被用来填补缺失的参数，有很大的潜在的人口影响，并由此产生的偏见是不可预测的方向，从而排除了一贯的预防性评估。我们的研究大大增加了黑腿三趾鸥特定人群人口统计数据的空间覆盖范围。所提出的重建人口参数也可以立即用于减少英国和爱尔兰海上风电开发的同意过程中的不确定性。更广泛地说，我们表明，这里使用的重建方法提供了一个新的途径，以改善以证据为基础的管理和政策行动的动物和植物种群与分散和容易出错的人口统计数据。
Predicting how populations may respond to climate change and anthropogenic pressures requires detailed knowledge of demographic traits, such as survival and reproduction. However, the availability of these data varies greatly across space and taxa. Therefore, it is common practice to conduct population assessments by filling in missing values from surrogate species or other populations of the same species. Using these independent surrogate values concurrently with observed data neglects the life-history trade-offs that connect the different aspects of a population's demography. Consequently, this approach introduces biases that could ultimately lead to erroneous management decisions.We use a Bayesian hierarchical framework to combine fragmented multi-population data with established life-history theory and reconstruct population-specific demographic data across a substantial part of a species breeding range. We apply our analysis to a long-lived colonial species, the black-legged kittiwake Rissa tridactyla, that is classified as globally Vulnerable and is highly threatened by increasing anthropogenic pressures, including offshore renewable energy development. We then use a projection analysis to examine how the reconstructed demographic parameters may improve population assessments, compared to models that combine observed data with independent surrogate values.Demographic parameters reconstructed using a hierarchical framework can be utilised in a range of population modelling approaches. They can also be used as reference estimates to assess whether independent surrogate values are likely to over or underestimate missing demographic parameters. We show that surrogate values from independent sources are often used to fill in missing parameters that have large potential demographic impact, and that resulting biases are driven in unpredictable directions thus precluding assessments from being consistently precautionary.Synthesis and applications. Our study dramatically increases the spatial coverage of population-specific demographic data for black-legged kittiwakes. The reconstructed demographic parameters presented can also be used immediately to reduce uncertainty in the consenting process for offshore wind development in the United Kingdom and Ireland. More broadly, we show that the reconstruction approach used here provides a new avenue for improving evidence-based management and policy action for animal and plant populations with fragmented and error prone demographic data.