Natural stony and coarse-grained habitats entail important ecological features for the marine environment. Due to the complexity of their bottom characteristics, they host a high biodiversity compared to surrounding soft bottom areas. The German nature conservation area “Helgoländer Steingrund” (HSG; 54°14.00 N and 8°03.00 W) is subject to regular monitoring but lacks information on the spatial distribution of benthic species. Within this study, a new approach using species distribution models (SDM) was tested to fill these gaps of knowledge. Newly recorded environmental data (depth, sediments, current velocities) in the HSG and information on the presence and absences of nine benthic species ( Echinus esculentus , Metridium senile , Cancer pagurus , Phymatolithon spp., Axinella polypoides , Homarus gammarus , Flustra foliacea , Alcyonidium diaphanum , Alcyonium digitatum ), collected using video analysis of drop camera records, was used to perform SDMs. The models revealed good evaluation measures (true skill statistic > 0.7; area under the receiver operation characteristic curve > 0.90), implying that the model showed good predictive performance for the potential distribution of the tested species. The outcome of this study is a clear recommendation on SDM application in further environmental monitoring programs on the HSG and other protected hard ground areas.

中文翻译：

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德国北海受保护的天然硬地区域底栖物种小规模分布模型 (Helgoländer Steingrund)

天然石质和粗粒栖息地对海洋环境具有重要的生态特征。由于其底部特征的复杂性，与周围的软底区域相比，它们拥有高度的生物多样性。德国自然保护区“Helgoländer Steingrund”（HSG；54°14.00 N 和 8°03.00 W）受到定期监测，但缺乏底栖物种空间分布的信息。在这项研究中，测试了一种使用物种分布模型 (SDM) 的新方法来填补这些知识空白。HSG 中新记录的环境数据（深度、沉积物、流速）以及九种底栖物种（Echinus esculentus、Metridium senile、Cancer pagurus、Phymatolithon spp.、Axinella polypoides、Homarus gammarus、Flustra foliacea、Alcyonium diaphanum (Alcyonium digitatum)，使用滴下相机记录的视频分析收集，用于执行 SDM。模型显示出良好的评估指标（真实技能统计 > 0.7；接受者操作特征曲线下面积 > 0.90），这意味着该模型对测试物种的潜在分布显示出良好的预测性能。这项研究的结果是明确建议 SDM 在 HSG 和其他受保护的硬地区域的进一步环境监测计划中的应用。这意味着该模型对被测物种的潜在分布显示出良好的预测性能。这项研究的结果是明确建议 SDM 在 HSG 和其他受保护的硬地区域的进一步环境监测计划中的应用。这意味着该模型对被测物种的潜在分布显示出良好的预测性能。这项研究的结果是明确建议 SDM 在 HSG 和其他受保护的硬地区域的进一步环境监测计划中的应用。