High-resolution wave data for improving marine habitat suitability models
High-resolution wave data for improving marine habitat suitability models
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DOI：
10.3389/fmars.2022.1004829
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发表时间：
2023-01
期刊：
影响因子：
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通讯作者：
C. M. Bertelli;W. G. Bennett;H. Karunarathna;D. Reeve;R. Unsworth;J. Bull
中科院分区：
文献类型：
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作者：
C. M. Bertelli;W. G. Bennett;H. Karunarathna;D. Reeve;R. Unsworth;J. Bull
生境适宜性模型（HSM）是一种越来越多地被用于帮助指导保护管理决策的工具。它也可以用来集中我们海洋恢复的努力。为了提高模型的性能，需要获得最佳的环境数据和物种分布数据。海洋栖息地往往具有由物理环境条件定义的生态位，对浅水物种特别重要的是波浪能。在这项研究中，我们检查了通过产生高分辨率Delft-3D波高模型数据可以实现的HSM输出的相对改进，以查看是否可以改进精细尺度的模型预测。以海草为例，在精细尺度上的比较表明，与开源的低分辨率波浪能数据相比，预测适合海草生长的区域存在相当大的差异，大大增加了波浪作为预测变量的重要性。
Habitat suitability modelling (HSM) is a tool that is increasingly being used to help guide decision making for conservation management. It can also be used to focus efforts of restoration in our oceans. To improve on model performance, the best available environmental data along with species distribution data are needed. Marine habitats tend to have ecological niches defined by physical environmental conditions and of particular importance for shallow water species is wave energy. In this study we examined the relative improvements to HSM outputs that could be achieved by producing high-resolution Delft-3D modelled wave height data to see if model predictions at a fine-scale can be improved. Seagrasses were used as an exemplar and comparisons at fine-scale showed considerable differences in the area predicted suitable for seagrass growth and greatly increased the importance of waves as a predictor variable when compared with open-source low resolution wave energy data.