School of Biological and Marine Sciences, University of Plymouth, Drake Circus, Plymouth, PL4 8AA, UK; British Antarctic Survey, NERC, Cambridge, UK; Centre for Environment, Fisheries and Aquaculture Science (Cefas), Pakefield Road, Lowestoft, UK.
British Antarctic Survey, NERC, Cambridge, UK.
J Environ Manage. 2023 Nov 1;345:118325. doi: 10.1016/j.jenvman.2023.118325. Epub 2023 Jun 28.
Spatial management of the deep sea is challenging due to limited available data on the distribution of species and habitats to support decision making. In the well-studied North Atlantic, predictive models of species distribution and habitat suitability have been used to fill data gaps and support sustainable management. In the South Atlantic and other poorly studied regions, this is not possible due to a massive lack of data. In this study, we investigated whether models constructed in data-rich areas can be used to inform data-poor regions (with otherwise similar environmental conditions). We used a novel model transfer approach to identify to what extent a habitat suitability model for Desmophyllum pertusum reef, built in a data-rich basin (North Atlantic), could be transferred usefully to a data-poor basin (South Atlantic). The transferred model was built using the Maximum Entropy algorithm and constructed with 227 presence and 3064 pseudo-absence points, and 200 m resolution environmental grids. Performance in the transferred region was validated using an independent dataset of D. pertusum presences and absences, with assessments made using both threshold-dependent and -independent metrics. We found that a model for D. pertusum reef fitted to North Atlantic data transferred reasonably well to the South Atlantic basin, with an area under the curve of 0.70. Suitable habitat for D. pertusum reef was predicted on 20 of the assessed 27 features including seamounts. Nationally managed Marine Protected Areas provide significant protection for D. pertusum reef habitat in the region, affording full protection from bottom trawling to 14 of the 20 suitable features. In areas beyond national jurisdiction (ABNJ), we found four seamounts that provided suitable habitat for D. pertusum reef to be at least partially protected from bottom trawling, whilst two did not fall within fisheries closures. There are factors to consider when developing models for transfer including data resolution and predictor type. Nevertheless, the promising results of this application demonstrate that model transfer approaches stand to provide significant contributions to spatial planning processes through provision of new, best available data. This is particularly true for ABNJ and areas that have previously undergone little scientific exploration such as the global south.
深海的空间管理具有挑战性，因为缺乏有关物种和生境分布的可用数据，难以支持决策制定。在北大西洋等研究充分的地区，可以使用物种分布和生境适宜性预测模型来填补数据空白并支持可持续管理。在南大西洋和其他研究较少的地区，由于缺乏大量数据，这种方法就行不通。在这项研究中，我们调查了在数据丰富的地区构建的模型是否可以用于为数据匮乏的地区（具有相似的环境条件）提供信息。我们使用一种新颖的模型转移方法来确定在多大程度上，在数据丰富的海域（北大西洋）构建的用于 Desmophyllum pertusum 珊瑚礁的生境适宜性模型可以有用地转移到数据匮乏的海域（南大西洋）。转移模型使用最大熵算法构建，使用 227 个存在点和 3064 个伪缺失点以及 200 m 分辨率的环境网格进行构建。使用 D. pertusum 存在和缺失的独立数据集验证了转移区域中的模型性能，使用基于阈值和独立的指标进行了评估。我们发现，拟合北大西洋数据的 D. pertusum 珊瑚礁模型可以很好地转移到南大西洋盆地，曲线下面积为 0.70。在评估的 27 个特征中的 20 个特征上预测到了 D. pertusum 珊瑚礁的适宜生境，包括海山。该地区的国家管理海洋保护区为 D. pertusum 珊瑚礁生境提供了重要保护，使 20 个适宜特征中的 14 个免受底拖网捕捞的影响。在国家管辖范围以外区域（ABNJ），我们发现了四个海山，它们为 D. pertusum 珊瑚礁提供了适宜的生境，至少有一部分免受底拖网捕捞的影响，而另外两个海山不在渔业关闭区范围内。在开发用于转移的模型时，需要考虑数据分辨率和预测器类型等因素。尽管如此，这种应用的有希望的结果表明，模型转移方法有望通过提供新的最佳可用数据，为空间规划过程做出重大贡献。对于 ABNJ 和以前很少进行科学探索的地区（如南半球）来说，情况尤其如此。
