Eyster Harold N, Chan Kai M A, Fletcher Morgan E, Beckage Brian
Gund Institute for Environment, University of Vermont, Burlington, Vermont, USA.
Department of Plant Biology, University of Vermont, Burlington, Vermont, USA.
J Anim Ecol. 2024 Dec;93(12):1854-1867. doi: 10.1111/1365-2656.14194. Epub 2024 Nov 6.
North American bird abundance has declined by 29% over the last 50 years. These continental population dynamics interact with local landscape changes to affect local bird diversity. Mitigating local declines in cities is particularly significant because (a) such declines greatly impact human-bird relationships since most people live in cities and (b) cities provide levers to create bird-friendly habitat, such as managing yards and gardens, street trees, and urban parks. Yet, the potential for cities to modify habitats to mitigate broader bird declines remains unclear. Studies have been stymied by the difficulty of assembling mutidecadal habitat-bird population datasets. Instead, studies have substituted space for time (e.g. used habitat associations across space at one time point to project future species abundance due to changing land use), but this method may fail amidst nonstationary environments of the Anthropocene. Here, we test the validity of space-for-time substitutions for explaining changes in bird abundance in a North American city over the past two decades by examining the degree to which these changes are explainable by changes in local landcover at multiple spatial scales. Specifically, we use longitudinal urban bird surveys of Metro Vancouver, BC, Canada from 1997 and 2020; deep learning models of remote sensing data to classify contemporaneous landcover; out-of-sample prediction and boosted regression trees to identify multiple spatial scales of landcover that best explained bird abundance (i.e. optimal scale of effect for each species by each habitat); and Bayesian multispecies abundance models in Stan to determine relationships between changes in landcover and bird abundance. We found that total bird abundance declined by 26% over the last two decades. Landcover measured at both 50 m and optimal scales explained spatial variation in bird abundance, but only landcover at the optimal scale explained temporal changes, and only partially. These results suggest that space-for-time substitutions overemphasize habitat-bird ecological relationships, urban habitats only partially determine bird abundance, and measuring habitat at the appropriate scale is important for capturing the most relevant changes in landscapes.
在过去50年里，北美鸟类数量减少了29%。这些大陆性的种群动态与当地景观变化相互作用，影响着当地鸟类的多样性。缓解城市地区鸟类数量的减少尤为重要，原因如下：其一，由于大多数人生活在城市，这种减少对人与鸟类的关系产生了重大影响；其二，城市提供了创造有利于鸟类栖息的栖息地的手段，比如管理庭院、街道树木和城市公园。然而，城市改变栖息地以缓解更广泛的鸟类数量减少的潜力仍不明确。由于难以收集数十年的栖息地-鸟类种群数据集，相关研究受到了阻碍。取而代之的是，研究用空间代替了时间（例如，在某一时刻利用跨空间的栖息地关联来预测由于土地利用变化导致的未来物种数量），但在人类世的非平稳环境中，这种方法可能会失效。在这里，我们通过研究北美一个城市过去二十年鸟类数量变化在多大程度上可由多个空间尺度上的当地土地覆盖变化来解释，来检验用空间代替时间的方法在解释鸟类数量变化方面的有效性。具体而言，我们使用了加拿大不列颠哥伦比亚省大温哥华地区1997年至2020年的城市鸟类纵向调查数据；利用遥感数据的深度学习模型对同期土地覆盖进行分类；进行样本外预测和增强回归树分析，以确定能最好解释鸟类数量的土地覆盖的多个空间尺度（即每种栖息地对每个物种的最佳影响尺度）；并在斯坦语言中使用贝叶斯多物种丰度模型来确定土地覆盖变化与鸟类数量之间的关系。我们发现，在过去二十年里，鸟类总数下降了26%。在50米尺度和最佳尺度上测量的土地覆盖解释了鸟类数量的空间变化，但只有最佳尺度上的土地覆盖解释了时间变化，而且只是部分解释。这些结果表明，用空间代替时间的方法过度强调了栖息地与鸟类的生态关系，城市栖息地只是部分决定鸟类数量，并且在适当尺度上测量栖息地对于捕捉景观中最相关的变化很重要。
