Species Distribution Modelling of Corals and Sponges in the Maritimes Region for Use in the Identification of Significant Benthic Areas

Effective fisheries and habitat management processes require knowledge of the distribution of areas of high ecological or biological significance. On the Scotian Shelf and Slope, a number of benthic ecologically or biologically significant areas consisting of habitat-forming species such as sponges and deep-water corals have been identified. However, knowledge of their spatial distribution is largely based on targeted surveys that are limited in their spatial extent. We used a species distribution modelling approach called random forest (RF) to predict the probability of occurrence and biomass of sponges, sea pens, and large and small gorgonian corals across the entire spatial extent of Fisheries and Oceans Canada’s (DFO) Maritimes Region. We also modelled the rare sponge Vazella pourtalesi, which forms the largest known aggregation of its kind on the Scotian Shelf. We utilized a number of data sources including DFO multispecies trawl catch data and in situ benthic imagery observations. Most models had excellent predictive capacity with cross-validated Area Under the Receiver Operating Characteristic Curve (AUC) values ranging from 0.760 to 0.977. Areas of suitable habitat were identified for each taxon and were contrasted against their known distribution and when applicable, the location of closure areas designated for their protection. Generalized additive models (GAMs) were developed to predict the biomass distribution of each taxonomic group and serve as a comparison to the RF models. The RF and GAM models provided comparable results, although GAMs provided superior predictions of biomass along the continental slope for some taxonomic groups. In the absence of data observations, the results of this study could be used to identify the potential distribution of sensitive benthic taxa for use in fisheries and habitat management applications. These results could also be used to refine significant concentrations of these taxa as identified through the kernel density analyses.

高效的渔业和栖息地管理流程亟需掌握具有高度生态或生物学意义的区域分布知识。在斯科特浅滩和斜坡地区，已识别出多个生态或生物学意义上的底栖区域，这些区域由形成栖息地的物种构成，例如海绵和深海珊瑚。然而，对这些区域空间分布的了解主要基于范围有限的针对性调查。本研究采用了一种名为随机森林（RF）的物种分布建模方法，以预测加拿大渔业和水产部（DFO）海事区域全空间范围内海绵、海笔、大型和小型海葵的出现概率和生物量。同时，我们还对稀有海绵Vazella pourtalesi进行了建模，该海绵在斯科特浅滩形成了已知种类中最大的聚集。我们利用了包括DFO多物种拖网捕捞数据和现场底栖影像观测在内的多种数据来源。大多数模型具有卓越的预测能力，其交叉验证的受试者工作特征曲线下面积（AUC）值介于0.760至0.977之间。为每个分类单元确定了适宜的栖息地，并与它们的已知分布进行了对比，在适用的情况下，还与为保护它们而指定的封闭区域的位置进行了对比。开发了广义加性模型（GAMs）来预测每个分类组的生物量分布，并作为与RF模型的比较。RF和GAM模型提供了可比的结果，尽管对于某些分类组，GAMs在大陆坡沿线的生物量预测方面表现更优。在缺乏数据观测的情况下，本研究的结果可用于识别敏感底栖分类单元的潜在分布，以便在渔业和栖息地管理应用中使用。这些结果还可以用于通过核密度分析确定的这些分类单元的重要浓度的细化。