Understanding how species ranges shift as climates rapidly change informs us how to effectively conserve vulnerable species. Species distribution models (SDMs) are an important method for examining these range shifts. The tools for performing SDMs are ever improving. Here, we present the megaSDM R package. This package facilitates realistic spatiotemporal SDM analyses by incorporating dispersal probabilities, creating time-step maps of range change dynamics and efficiently handling large datasets and computationally intensive environmental subsampling techniques. Provided a list of species and environmental data, megaSDM synthesizes GIS processing, subsampling methods, MaxEnt modelling, dispersal rate restrictions and additional statistical tools to create a variety of outputs for each species, time period and climate scenario requested. For each of these, megaSDM generates a series of distribution maps and outputs visual representations of statistical data. megaSDM offers several advantages over other commonly used SDM tools. First, many of the functions in megaSDM natively implement parallelization, enabling the package to handle large amounts of data efficiently without the need for additional coding. megaSDM also implements environmental subsampling of occurrences, making the technique broadly available in a way that was not possible before due to computational considerations. Uniquely, megaSDM generates maps showing the expansion and contraction of a species range across all considered time periods (time-maps), and constrains both presence/absence and continuous suitability maps of species ranges according to species-specific dispersal constraints. The user can then directly compare non-dispersal and dispersal-limited distribution predictions. This paper discusses the unique features and highlights of megaSDM, describes the structure of the package and demonstrates the package's features and the model flow through examples.

中文翻译：

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megaSDM：将扩散和时间步长分析整合到物种分布模型中

了解物种范围如何随着气候的迅速变化而变化，可以告诉我们如何有效地保护脆弱的物种。物种分布模型 (SDM) 是检查这些范围变化的重要方法。用于执行 SDM 的工具不断改进。在这里，我们介绍了 megaSDM R 包。该软件包通过结合分散概率、创建范围变化动态的时间步长图以及有效处理大型数据集和计算密集型环境子采样技术，促进了现实的时空 SDM 分析。提供物种和环境数据列表，megaSDM 综合了 GIS 处理、二次采样方法、MaxEnt 建模、扩散率限制和其他统计工具，为每个物种、时间段和所需的气候情景创建各种输出。对于其中的每一个，megaSDM 生成一系列分布图并输出统计数据的可视化表示。与其他常用 SDM 工具相比，megaSDM 具有多项优势。首先，megaSDM 中的许多函数本身就实现了并行化，使包能够有效地处理大量数据，而无需额外编码。megaSDM 还实现了事件的环境子采样，使该技术以一种以前由于计算考虑不可能实现的方式广泛可用。独特的是，megaSDM 生成的地图显示了所有考虑的时间段（时间图）中物种范围的扩展和收缩，并根据物种特定的扩散约束来约束物种范围的存在/不存在和连续适宜性地图。然后，用户可以直接比较非扩散和扩散受限的分布预测。本文讨论了 megaSDM 的独特功能和亮点，描述了包的结构，并通过示例演示了包的功能和模型流程。