Landscape-Scale Effects of Habitat and Weather on Scaled Quail Populations

John T. Edwards, F. Hernández, D. Wester, L. Brennan, C. Parent, Andrea Montalvo, Masahiro Ohnishi
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Abstract

Scaled quail (Callipepla squamata) have declined over the last half century; however, there is spatial variation within their geographic distribution. Interior populations have increased and peripheral populations have generally decreased. Declines have been attributed to habitat loss and degradation. Scaled quail populations also show interannual fluctuations related to precipitation. Our objective was to determine the relative impact of habitat and weather (i.e., precipitation and temperature) on scaled quail population dynamics. Our hypothesis was that habitat metrics would be more important for decreasing populations whereas weather metrics would be more important for increasing populations. We used publicly available datasets for scaled quail abundance measures (Breeding Bird Survey, Christmas Bird Count), weather (PRISM), and land cover (National Land Cover Data) collected over 3 5-year time periods (1990–1994, 1999–2003, 2009–2013). Data were collected at 2 scales: a route scale (5-km route buffer) and region scale (25-km circular buffer). We developed 25 a priori models that fit into 4 “model classes” (habitat amount, habitat fragmentation, matrix quality, weather). Model selection followed a 2-stage approach, where models were initially evaluated within each individual model class, then top models from each class were evaluated in combination to determine a global model. We used mixed-effects models with a negative binomial response distribution, treating route as a random effect. Weather variables were the primary explanatory factor for increasing populations at both scales. Similarly following our hypothesis, habitat variables were generally the most important for decreasing populations, but only at the route scale; weather variables dominated at the region scale. Both abundance datasets provided similar results and explanatory power (R2 ≈ 0.10 for route scale; R2 ≈ 0.27 for region scale), for both increasing and decreasing populations. Comparisons of land cover variables showed increasing populations to have higher amounts of habitat (p = 0.0028), higher mean patch area of habitat (p = 0.0446), and lower urban cover (p = 0.0287). Our hypothesis that weather variables account for more variation of increasing scaled quail populations was generally supported, likely because of increased amounts of habitat in these areas. However, given the low overall explanatory power of our models, it is likely that other factors such as habitat quality may be more important to scaled quail. Increasing temperature and reduced precipitation associated with climate change are likely to exacerbate scaled quail declines both directly and through continued habitat degradation, even within areas with increasing populations. 1 Edwards et al.: Habitat and Weather Effects Scaled Quail
生境和天气对鹌鹑种群的景观尺度影响
在过去的半个世纪里,有鳞的鹌鹑(Callipepla squamata)数量减少了;但其地理分布存在空间差异。内陆人口增加,而外围人口普遍减少。减少的原因是栖息地的丧失和退化。鳞片状鹌鹑种群也显示出与降水有关的年际波动。我们的目标是确定栖息地和天气(即降水和温度)对尺度鹌鹑种群动态的相对影响。我们的假设是栖息地指标对减少的人口更重要而天气指标对增加的人口更重要。我们使用了公开的数据集,收集了3个5年时间段(1990-1994年、1999-2003年、2009-2013年)的鹌鹑丰度测量(繁殖鸟类调查、圣诞节鸟类计数)、天气(PRISM)和土地覆盖(国家土地覆盖数据)。数据采集分为2个尺度:路线尺度(5 km路线缓冲)和区域尺度(25 km环形缓冲)。我们开发了25个先验模型,可分为4个“模型类别”(栖息地数量、栖息地破碎化、基质质量、天气)。模型选择遵循两个阶段的方法,首先在每个单独的模型类别中评估模型,然后组合评估每个类别中的顶级模型,以确定全局模型。我们使用具有负二项响应分布的混合效应模型,将路线视为随机效应。天气变量是两个尺度上种群数量增加的主要解释因素。同样,根据我们的假设,生境变量通常对种群减少最重要,但仅在路线尺度上;天气变量在区域尺度上占主导地位。两个丰度数据集提供了相似的结果和解释力(R2≈0.10);R2≈0.27(区域尺度),对于增加和减少的种群。土地覆盖变量比较结果显示,人口增加,生境面积增大(p = 0.0028),生境平均斑块面积增大(p = 0.0446),城市覆盖面积减小(p = 0.0287)。我们的假设是,天气变量对鹌鹑数量增加的影响更大,这一假设得到了普遍支持,可能是因为这些地区的栖息地数量增加了。然而,考虑到我们模型的整体解释力较低,栖息地质量等其他因素可能对鳞鹌鹑更重要。与气候变化相关的气温升高和降水减少可能会直接或通过栖息地的持续退化加剧鹌鹑数量的下降,即使在人口增加的地区也是如此。1 Edwards等人:栖息地和天气对鳞鹌鹑的影响
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