U.S. Geological Survey, National Wetlands Research Center, Lafayette, Louisiana 70506, USA.
Ecol Appl. 2010 Jul;20(5):1467-75. doi: 10.1890/09-0850.1.
Models currently used to estimate patterns of species co-occurrence while accounting for errors in detection of species can be difficult to fit when the effects of covariates on species occurrence probabilities are included. The source of the estimation problems is the particular parameterization used to specify species co-occurrence probability. We develop a new parameterization for estimating patterns of co-occurrence of interacting species that allows the effects of covariates to be specified quite naturally without estimation problems. In our model, the occurrence of one species is assumed to depend on the occurrence of another, but the occurrence of the second species is not assumed to depend on the presence of the first species. This pattern of co-occurrence, wherein one species is dominant and the other is subordinate, can be produced by several types of ecological interactions (predator-prey, parasitism, and so on). A simulation study demonstrated that estimates of species occurrence probabilities were unbiased in samples of 50-100 locations and three surveys per location, provided species are easily detected (probability of detection > or = 0.5). Higher sample sizes (>200 locations) are needed to achieve unbiasedness when species are more difficult to detect. An analysis of data from treefrog surveys in southern Florida indicated that the occurrence of Cuban treefrogs, an invasive predator species, was highest near the point of its introduction and declined with distance from that location. Sites occupied by Cuban treefrogs were 9.0 times less likely to contain green treefrogs and 15.7 times less likely to contain squirrel treefrogs compared to sites without Cuban treefrogs. The detection probabilities of native treefrog species did not depend on the presence of Cuban treefrogs, suggesting that the native treefrog species are naive to the introduced species.
目前用于估计物种共存模式的模型，在考虑到物种检测误差的情况下，当包括协变量对物种出现概率的影响时，可能难以拟合。估计问题的根源在于用于指定物种共存概率的特定参数化。我们开发了一种新的参数化方法来估计相互作用物种的共存模式，该方法允许非常自然地指定协变量的影响，而不会出现估计问题。在我们的模型中，一种物种的出现被假设取决于另一种物种的出现，但第二种物种的出现不被假设取决于第一种物种的存在。这种共存模式，其中一种物种是优势种，另一种是从属种，可以由几种类型的生态相互作用（捕食者-猎物、寄生等）产生。一项模拟研究表明，在 50-100 个地点和每个地点三次调查的样本中，只要物种容易被检测到（检测概率≥0.5），物种出现概率的估计值就是无偏的。当物种更难被检测到时，需要更大的样本量（>200 个地点）才能实现无偏性。对佛罗里达州南部树蛙调查数据的分析表明，入侵捕食者古巴树蛙的出现率在其引入点附近最高，并随着与该地点的距离的增加而下降。与没有古巴树蛙的地点相比，古巴树蛙占据的地点发现绿蛙的可能性低 9 倍，发现松鼠蛙的可能性低 15.7 倍。本地树蛙物种的检测概率不依赖于古巴树蛙的存在，这表明本地树蛙物种对引入物种是无知的。
