Data from: A multispecies occupancy model for two or more interacting species

Species occurrence is influenced by environmental conditions and the presence of other species. Current approaches for multispecies occupancy modelling are practically limited to two interacting species and often require the assumption of asymmetric interactions. We propose a multispecies occupancy model that can accommodate two or more interacting species. We generalize the single-species occupancy model to two or more interacting species by assuming the latent occupancy state is a multivariate Bernoulli random variable. We propose modelling the probability of each potential latent occupancy state with both a multinomial logit and a multinomial probit model and present details of a Gibbs sampler for the latter. As an example, we model co-occurrence probabilities of bobcat (Lynx rufus), coyote (Canis latrans), grey fox (Urocyon cinereoargenteus) and red fox (Vulpes vulpes) as a function of human disturbance variables throughout 6 Mid-Atlantic states in the eastern United States. We found evidence for pairwise interactions among most species, and the probability of some pairs of species occupying the same site varied along environmental gradients; for example, occupancy probabilities of coyote and grey fox were independent at sites with little human disturbance, but these two species were more likely to occur together at sites with high human disturbance. Ecological communities are composed of multiple interacting species. Our proposed method improves our ability to draw inference from such communities by permitting modelling of detection/non-detection data from an arbitrary number of species, without assuming asymmetric interactions. Additionally, our proposed method permits modelling the probability two or more species occur together as a function of environmental variables. These advancements represent an important improvement in our ability to draw community-level inference from multiple interacting species that are subject to imperfect detection.物种出现受环境条件与其他物种的共存状况影响。当前的多物种占有建模（multispecies occupancy modelling）方法在实际应用中仅能处理两种互作物种，且通常需要假设交互作用为非对称形式。本研究提出一种可适配两种及以上互作物种的多物种占有建模方法。我们通过假设潜在占有状态为多元伯努利随机变量，将单物种占有模型推广至两种及以上互作物种的场景。我们提出采用多项式logit模型与多项式probit模型对每种潜在占有状态的概率进行建模，并详述了针对后者的吉布斯采样器（Gibbs sampler）实现细节。作为应用示例，我们以美国东部大西洋中部沿岸6个州为研究区域，以人类干扰变量为影响因子，对短尾猫（Lynx rufus）、郊狼（Canis latrans）、灰狐（Urocyon cinereoargenteus）与赤狐（Vulpes vulpes）的共存概率进行建模。研究发现多数物种间存在成对交互作用，且部分物种类对在同一位点的占有概率随环境梯度发生变化；例如，在人类干扰较弱的位点，郊狼与灰狐的占有概率相互独立，而在人类干扰较强的位点，二者共同出现的概率显著更高。生态群落由多个互作物种构成。我们提出的方法允许对任意数量物种的检测/未检测数据进行建模，且无需假设交互作用非对称，从而提升了针对此类群落的统计推断能力。此外，该方法还可针对环境变量对两种及以上物种共同出现的概率进行建模。上述进展显著提升了我们从存在不完全检测的多个互作物种中获取群落水平统计推断的能力。