论文标题
使用贝叶斯推理的苗圃栖息地的时空建模:少年蓝蟹的环境驱动力
Spatiotemporal Modeling of Nursery Habitat Using Bayesian Inference: Environmental Drivers of Juvenile Blue Crab Abundance
论文作者
论文摘要
通过丰富的食物资源和避难所,幼儿园有利于少年鱼类和甲壳类动物的生长和生存,并增强人口的次要生产。尽管小规模的研究仍然是评估栖息地的苗圃价值的重要工具,但针对大型时空尺度统一调查数据的目标应用对于推断托儿所功能的推断,确定高生产力的区域并为管理策略提供信息至关重要。我们使用了21年的GIS和空间索引的现场调查数据,对潜在的苗圃栖息地进行了调查数据,我们构建了五个具有不同时空依赖性结构不同的贝叶斯模型,以推断下切萨皮克湾三个支流中蓝蟹C. sapidus的幼年幼年的栖息地价值。来自完全不可分割的时空模型的少年计数的样本外预测优于简单模型的预测。盐沼泽表面积,浊度及其相互作用显示出最大的关联(并且积极)丰富。相对海草区,以前是小型空间尺度研究中最有价值的托儿所,与丰度无关。因此,我们认为,盐沼应被视为蓝蟹的关键苗圃栖息地,甚至在广泛的海草床中。此外,托儿所的识别应基于在包含多个潜在苗圃栖息地的广泛时空尺度上进行的调查,并严格解决时空依赖性。
Nursery grounds are favorable for growth and survival of juvenile fish and crustaceans through abundant food resources and refugia, and enhance secondary production of populations. While small-scale studies remain important tools to assess nursery value of habitats, targeted applications that unify survey data over large spatiotemporal scales are vital to generalize inference of nursery function, identify highly productive regions, and inform management strategies. Using 21 years of GIS and spatiotemporally indexed field survey data on potential nursery habitats, we constructed five Bayesian models with varying spatiotemporal dependence structures to infer nursery habitat value for juveniles of the blue crab C. sapidus within three tributaries in lower Chesapeake Bay. Out-of-sample predictions of juvenile counts from a fully nonseparable spatiotemporal model outperformed predictions from simpler models. Salt marsh surface area, turbidity, and their interaction showed the strongest associations (and positively) with abundance. Relative seagrass area, previously emphasized as the most valuable nursery in small spatial-scale studies, was not associated with abundance. Hence, we argue that salt marshes should be considered a key nursery habitat for blue crabs, even amidst extensive seagrass beds. Moreover, identification of nurseries should be based on investigations at broad spatiotemporal scales incorporating multiple potential nursery habitats, and on rigorously addressing spatiotemporal dependence.