Abstract Seagrasses form one of the most ecologically important and productive three-dimensional habitats in coastal seas. Knowing the global distribution of seagrass meadows is essential for conservation and blue carbon estimates. Here, we modelled the global distribution of seagrass using 43,037 occurrence records and 13 environmental variables within the modelling software MaxEnt at 30 arc sec resolution (c. 1 km at the equator). We found that sea surface temperature and distance from land contributed most in predicting seagrass distribution globally. Comparison of summing models for individual species, genera, and families found that a model combining all species occurrence records best fitted the known geographic distribution. In addition, this model fills geographic gaps in previous maps. We predicted the seagrass biome may occupy 1,646,788 km2, more than double previous global estimates. Applications for this dataset include blue carbon estimates, spatial planning such as for designing Marine Protected Areas, environmental sensitivity mapping, and monitoring of change in biome cover.

中文翻译：

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海草生物群落的模拟全球分布

摘要 海草是近海中最具生态重要性和生产力的三维生境之一。了解海草草地的全球分布对于保护和蓝碳估算至关重要。在这里，我们使用建模软件 MaxEnt 中的 43,037 条发生记录和 13 个环境变量以 30 弧秒分辨率（赤道约 1 公里）对海草的全球分布进行了建模。我们发现海面温度和与陆地的距离对全球海草分布的预测贡献最大。单个物种、属和科的求和模型的比较发现，结合所有物种发生记录的模型最适合已知的地理分布。此外，该模型填补了以前地图中的地理空白。我们预测海草生物群落可能占据 1,646 个，788 平方公里，是之前全球估计值的两倍多。此数据集的应用包括蓝碳估算、空间规划（例如用于设计海洋保护区）、环境敏感性绘图和生物群落覆盖变化监测。