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Development and validation of scale-dependent habitat models for cavity-nesting birds in Fishlake National Forest, Utah.

机译：犹他州菲什湖国家森林中空洞嵌套鸟类比例尺度生境模型的开发和验证。

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摘要

I examined the relative ability of landscape-scale, stand-scale, nest-tree scale, and multi-scale habitat models to predict nest presence for cavity-nesting birds on Fishlake National Forest, Utah. Using data from 2001, I built stepwise logistic regression models for cavity nesting birds and two cavity-nesting sub-guilds. I validated the habitat models using both internal validation and external validation. Cavity-nesting birds were associated with habitat at multiple spatial scales. Multi-scale and micro-scale models were the best predictors of nest-site presence. Model accuracy decreased as spatial extent increased, and model accuracy was similar for both internal and external validation. The results highlight the importance of the nest tree for cavity-nesting birds. Macro-scale models, which are inexpensive and spatially explicit, cannot currently be used to accurately predict nest presence for cavity nesting birds in aspen forests of southern Utah.
机译：我检查了景观尺度，林分尺度，巢树尺度和多尺度栖息地模型的相对能力，以预测犹他州菲什湖国家森林中空巢鸟类的巢穴存在。利用2001年的数据，我建立了用于巢穴鸟和两个巢穴子行会的逐步logistic回归模型。我使用内部验证和外部验证来验证栖息地模型。巢穴鸟类在多个空间尺度上与栖息地有关。多尺度和微观尺度模型是巢穴存在的最佳预测指标。模型精度随空间范围的增加而降低，内部和外部验证的模型精度均相似。结果突出了巢树对巢状鸟类的重要性。廉价且空间明确的宏观模型目前不能用于精确预测犹他州南部白杨林中空巢鸟的巢存在。

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