Quantifying the distribution of animals and identifying underlying characteristics that define suitable habitat are essential for effective conservation of free-ranging species. Prioritizing areas for conservation is important in managing a geographic extent that has a high level of disturbance and limited conservation resources. We examined the potential use of a species distribution model ensemble for multi-species conservation in marine habitats. Using satellite telemetry locations during foraging as input data, and ensemble ecological niche models, we predicted foraging areas for 2 nesting marine turtle species within the Gulf of Mexico (GoM): Kemp’s ridley Lepidochelys kempii (n = 63) and loggerhead Caretta caretta (n = 63). We considered 7 geophysical, biological, and climatic variables and compared contributing factors for each species’ foraging habitat selection. For both species, predicted suitable foraging habitats encompassed large areas along the GoM coast, but only intersected with each other in relatively small areas. Highly parameterized models resulted in overall greater fits, suggesting that multiple factors influence habitat selection by these species. Model validation results were mixed: cross-validation resulted in high prediction accuracy for both species, but an evaluation against independent data resulted in a low omission rate (5%) for Kemp’s ridleys and a high omission rate (72%) for loggerheads. The relatively small intersection of model-predicted foraging areas for these 2 species within the study area may indicate possible niche differentiations. The high omission rate for loggerheads indicates our samples likely underrepresent the population and illustrates the challenges in predicting suitable foraging extents for species that make dynamic movements and have greater individual variability.

中文翻译：

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预测墨西哥湾海龟的多物种觅食热点

量化动物的分布并确定定义合适栖息地的基本特征对于有效保护自由放养物种至关重要。优先保护区域对于管理具有高度干扰和有限保护资源的地理范围很重要。我们研究了物种分布模型集合在海洋栖息地多物种保护中的潜在用途。使用觅食期间的卫星遥测位置作为输入数据和整体生态位模型，我们预测了墨西哥湾 (GoM) 内 2 种筑巢海龟的觅食区域：Kemp'sridley Lepidochelys kempii (n = 63) 和蠵蠵龟 (n = 63) = 63）。我们考虑了 7 个地球物理、生物、和气候变量，并比较了每个物种觅食栖息地选择的影响因素。对于这两个物种，预测合适的觅食栖息地包括沿 GoM 海岸的大片区域，但仅在相对较小的区域内相互交叉。高度参数化的模型导致整体拟合度更高，这表明多种因素会影响这些物种的栖息地选择。模型验证结果喜忧参半：交叉验证导致两个物种的预测准确度很高，但对独立数据的评估导致 Kemp'sridleys 的遗漏率较低 (5%)，而蠵螈的遗漏率较高 (72%)。研究区域内这 2 个物种的模型预测觅食区的相对较小的交叉点可能表明可能存在生态位差异。