Species interactions shape biodiversity patterns, community assemblage, and the dynamics of wildlife populations. Ecological theory posits that the strength of interspecific interactions is fundamentally underpinned by the population sizes of the involved species. Nonetheless, prevalent approaches for modeling species interactions predominantly center around occupancy states. Here, we use simulations to illuminate the inadequacies of modeling species interactions solely as a function of occupancy, as is common practice in ecology. We demonstrate erroneous inference into species interactions due to error in parameter estimates when considering species occupancy alone. To address this critical issue, we propose, develop, and demonstrate an abundance‐mediated interaction framework designed explicitly for modeling species interactions involving two or more species from detection/non‐detection data. We present Markov chain Monte Carlo (MCMC) samplers tailored for diverse ecological scenarios, including intraguild predation, disease‐ or predator‐mediated competition, and trophic cascades. Illustrating the practical implications of our approach, we compare inference from modeling the interactions in a three‐species network involving coyotes (Canis latrans), fishers (Pekania pennanti), and American marten (Martes americana) in North America as a function of occupancy states and as a function of abundance. When modeling interactions as a function of abundance rather than occupancy, we uncover previously unidentified interactions. Our study emphasizes that accounting for abundance‐mediated interactions rather than simple co‐occurrence patterns can fundamentally alter our comprehension of system dynamics. Through an empirical case study and comprehensive simulations, we demonstrate the importance of accounting for abundance when modeling species interactions, and we present a statistical framework equipped with MCMC samplers to achieve this paradigm shift in ecological research.

中文翻译：

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丰度介导的物种相互作用


物种相互作用塑造了生物多样性模式、群落组合和野生动物种群的动态。生态学理论认为，种间相互作用的强度从根本上取决于相关物种的种群规模。尽管如此，模拟物种相互作用的流行方法主要集中在占用状态上。在这里，我们使用模拟来阐明仅将物种相互作用建模为占用率函数的不足，这是生态学中的常见做法。当单独考虑物种占有率时，由于参数估计的误差，我们证明了对物种相互作用的错误推断。为了解决这个关键问题，我们提出、开发和演示了一个丰度介导的相互作用框架，该框架专门用于模拟涉及检测/非检测数据中两个或多个物种的物种相互作用。我们提出了为不同的生态场景量身定制的马尔可夫链蒙特卡洛 （MCMC） 采样器，包括公会内捕食、疾病或捕食者介导的竞争以及营养级联。为了说明我们方法的实际意义，我们比较了在涉及北美郊狼 （Canis latrans）、渔民 （Pekania pennanti） 和美国貂 （Martes americana） 的三个物种网络中相互作用的建模推理，作为占用状态和丰度的函数。当将交互建模为丰度而不是占用率的函数时，我们发现了以前未识别的交互作用。我们的研究强调，解释丰度介导的相互作用而不是简单的共现模式可以从根本上改变我们对系统动力学的理解。 通过实证案例研究和综合模拟，我们证明了在对物种相互作用进行建模时考虑丰度的重要性，并提出了一个配备 MCMC 采样器的统计框架，以实现生态研究的这种范式转变。