Density dependence occurs at the individual level and thus is greatly influenced by spatial local heterogeneity in habitat conditions. However, density dependence is often evaluated at the population level, leading to difficulties or even controversies in detecting such a process. Bayesian individual-based models such as spatial capture-recapture (SCR) models provide opportunities to study density dependence at the individual level, but such an approach remains to be developed and evaluated. In this study, we developed a SCR model that links habitat use to apparent survival and recruitment through density dependent processes at the individual level. Using simulations, we found that the model can properly inform habitat use, but tends to underestimate the effect of density dependence on apparent survival and recruitment. The reason for such underestimations is likely due to the difficulties of the current model in identifying the locations of unobserved individuals without using environmental covariates to inform these locations. How to accurately estimate the locations of unobserved individuals, and thus density dependence, remains a challenging topic in spatial statistics and statistical ecology.

翻译：密度依赖性发生在个体层面，因此受到栖息地条件空间局部异质性的显著影响。然而，密度依赖性常在种群层面进行评估，导致检测此类过程存在困难甚至争议。贝叶斯个体模型（如空间捕获-再捕获模型）为在个体层面研究密度依赖性提供了机会，但该方法仍有待开发与评估。本研究开发了一种空间捕获-再捕获模型，通过个体层面的密度依赖过程将栖息地利用与表观存活率和补充率联系起来。通过模拟分析，我们发现该模型能有效反映栖息地利用情况，但倾向于低估密度依赖性对表观存活率和补充率的影响。这种低估的原因可能在于当前模型难以在不使用环境协变量推断位置的情况下，准确识别未观测个体的位置。如何精确估计未观测个体的位置，进而准确评估密度依赖性，仍是空间统计学与统计生态学中的一个挑战性课题。