1. Joint Species Distribution Modelling (JSDM) is becoming an increasingly popular statistical method for analysing data in community ecology. Hierarchical Modelling of Species Communities (HMSC) is a general and flexible framework for fitting JSDMs. HMSC allows the integration of community ecology data with data on environmental covariates, species traits, phylogenetic relationships and the spatio‐temporal context of the study, providing predictive insights into community assembly processes from non‐manipulative observational data of species communities.
2. The full range of functionality of HMSC has remained restricted to Matlab users only. To make HMSC accessible to the wider community of ecologists, we introduce Hmsc 3.0, a user‐friendly r implementation.
3. We illustrate the use of the package by applying Hmsc 3.0 to a range of case studies on real and simulated data. The real data consist of bird counts in a spatio‐temporally structured dataset, environmental covariates, species traits and phylogenetic relationships. Vignettes on simulated data involve single‐species models, models of small communities, models of large species communities and models for large spatial data. We demonstrate the estimation of species responses to environmental covariates and how these depend on species traits, as well as the estimation of residual species associations. We demonstrate how to construct and fit models with different types of random effects, how to examine MCMC convergence, how to examine the explanatory and predictive powers of the models, how to assess parameter estimates and how to make predictions. We further demonstrate how Hmsc 3.0 can be applied to normally distributed data, count data and presence–absence data.
4. The package, along with the extended vignettes, makes JSDM fitting and post‐processing easily accessible to ecologists familiar with r.

中文翻译：

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使用 r-package Hmsc 进行联合物种分布建模

1. 
   联合物种分布模型（JSDM）正在成为一种越来越流行的用于分析群落生态数据的统计方法。物种群落层次建模 (HMSC) 是一个通用且灵活的框架，用于拟合 JSDM。 HMSC 允许将群落生态数据与环境协变量、物种特征、系统发育关系和研究的时空背景数据相整合，从物种群落的非操纵性观测数据中提供对群落组装过程的预测性见解。
2. 
   HMSC 的全部功能仍然仅限于 Matlab 用户。为了使 HMSC 能够被更广泛的生态学家社区使用，我们推出了 H msc 3.0，这是一种用户友好的r实现。
3. 
   我们通过将 H msc 3.0 应用于一系列真实和模拟数据的案例研究来说明该软件包的使用。真实数据包括时空结构化数据集中的鸟类数量、环境协变量、物种特征和系统发育关系。模拟数据的小插图涉及单物种模型、小群落模型、大型物种群落模型和大空间数据模型。我们展示了物种对环境协变量的响应的估计以及这些响应如何依赖于物种特征，以及残余物种关联的估计。我们演示如何构建和拟合具有不同类型随机效应的模型、如何检查 MCMC 收敛性、如何检查模型的解释和预测能力、如何评估参数估计以及如何进行预测。我们进一步演示了 H msc 3.0 如何应用于正态分布数据、计数数据和存在-不存在数据。
4. 
   该软件包以及扩展的插图使熟悉r 的生态学家可以轻松地进行 JSDM 拟合和后处理。