Winter Habitat Indices (WHIs) for the contiguous US and their relationship with winter bird diversity
Winter Habitat Indices (WHIs) for the contiguous US and their relationship with winter bird diversity
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DOI：
10.1016/j.rse.2021.112309
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发表时间：
2021-03
影响因子：
13.5
通讯作者：
David Gudex‐Cross;Spencer R. Keyser;B. Zuckerberg;D. Fink;Likai Zhu;J. Pauli;V. Radeloff
中科院分区：
文献类型：
--
作者：
David Gudex‐Cross;Spencer R. Keyser;B. Zuckerberg;D. Fink;Likai Zhu;J. Pauli;V. Radeloff
积雪的季节性动态强烈影响生态系统过程和冬季生境，使其成为陆地生物多样性模式的重要驱动力。来自中分辨率成像分光辐射计Aqua和Terra卫星的积雪数据可以在大的时空尺度上捕捉这些动态，从而可以制定具体应用于生态研究和生物多样性预测的指数。在这里，我们的主要目标是从MODIS中获得冬季栖息地指数（WHI），量化雪季长度，积雪变化，以及无雪冻土的患病率作为雪下条件的代理。我们计算了2003/04年至2017/18年美国连续的全雪年（8月至7月）和冬季月份（12月至2月）的WHI，并使用来自797个气象站的地面数据进行了验证。为了展示WHI在生物多样性评估中的潜力，我们模拟了它们与来自eBird观测的冬季鸟类物种丰富度的关系。WHI有明确的空间格局，反映了积雪的海拔和纬度梯度。在高纬度和高海拔地区，雪季长度一般较长，而在中纬度低海拔地区，积雪变化和无雪冻土最高。WHI的变化主要是由西部的海拔和东部的纬度驱动的。雪季长度和冻土无雪最准确地映射，并在所有年份的台站数据的相关性分别为0.91和0.85。冬季的积雪变化被准确地绘制出来（r= 0.79），但整个降雪年的积雪变化没有被准确地绘制出来（r=-0.21）。包含所有三个WHI的模型用于预测整个美国连续的冬季鸟类物种丰富度模式是迄今为止最好的，展示了每个指数的个体值。雪季较长的地区通常支持较少的物种。物种丰富度稳步上升到中等水平的积雪变化和冻土无雪，之后急剧下降。我们的结果表明，MODIS WHI准确地表征了积雪动态的独特梯度，并提供了有关鸟类冬季栖息地条件的重要信息，凸显了它们在生态研究和保护规划方面的潜力。
The seasonal dynamics of snow cover strongly affect ecosystem processes and winter habitat, making them an important driver of terrestrial biodiversity patterns. Snow cover data from the Moderate Resolution Imaging Spectroradiometer (MODIS) Aqua and Terra satellites can capture these dynamics over large spatiotemporal scales, allowing for the development of indices with specific application in ecological research and predicting biodiversity. Here, our primary objective was to derive winter habitat indices (WHIs) from MODIS that quantify snow season length, snow cover variability, and the prevalence of frozen ground without snow as a proxy for subnivium conditions. We calculated the WHIs for the full snow year (Aug-Jul) and winter months (Dec-Feb) across the contiguous US from 2003/04 to 2017/18 and validated them with ground-based data from 797 meteorological stations. To demonstrate the potential of the WHIs for biodiversity assessments, we modeled their relationships with winter bird species richness derived from eBird observations. The WHIs had clear spatial patterns reflecting both altitudinal and latitudinal gradients in snow cover. Snow season length was generally longer at higher latitudes and elevations, while snow cover variability and frozen ground without snow were highest across low elevations of the mid latitudes. Variability in the WHIs was largely driven by elevation in the West and by latitude in the East. Snow season length and frozen ground without snow were most accurately mapped, and had correlations with station data across all years of 0.91 and 0.85, respectively. Snow cover variability was accurately mapped for winter (r= 0.79), but not for the full snow year (r= −0.21). The model containing all three WHIs used to predict winter bird species richness patterns across the contiguous US was by far the best, demonstrating the individual value of each index. Regions with longer snow seasons generally supported fewer species. Species richness increased steadily up to moderate levels of snow cover variability and frozen ground without snow, after which it steeply declined. Our results show that the MODIS WHIs accurately characterized unique gradients of snow cover dynamics and provided important information on winter habitat conditions for birds, highlighting their potential for ecological research and conservation planning.