Using joint species distribution modelling to predict distributions of seafloor taxa and identify vulnerable marine ecosystems in New Zealand waters

IF 3 2区 环境科学与生态学 Q1 BIODIVERSITY CONSERVATION Biodiversity and Conservation Pub Date : 2024-07-30 DOI:10.1007/s10531-024-02904-y
Fabrice Stephenson, David A. Bowden, Ashley A. Rowden, Owen F. Anderson, Malcolm R. Clark, Matthew Bennion, Brittany Finucci, Matt H. Pinkerton, Savannah Goode, Caroline Chin, Niki Davey, Alan Hart, Rob Stewart
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Abstract

Effective ecosystem-based management of bottom-contacting fisheries requires understanding of how disturbances from fishing affect seafloor fauna over a wide range of spatial and temporal scales. Spatial predictions of abundance for 67 taxa were developed, using an extensive dataset of faunal abundances collected using a towed camera system and spatially explicit predictor variables including bottom-trawl fishing effort, using a Joint Species Distribution Model (JSDM). The model fit metrics varied by taxon: the mean tenfold cross-validated AUC score was 0.70 ± 0.1 (standard deviation) for presence–absence and an R2 of 0.11 ± 0.1 (standard deviation) for abundance models. Spatial predictions of probability of occurrence and abundance (individuals per km2) varied by taxon, but there were key areas of overlap, with highest predicted taxon richness in areas of the continental shelf break and slope. The resulting joint predictions represent significant advances on previous predictions because they are of abundance, allow the exploration of co-occurrence patterns and provide credible estimates of taxon richness (including for rare species that are often not included in more commonly used single-species distribution modelling). Habitat-forming taxa considered to be Vulnerable Marine Ecosystem (VME) indicators (those taxa that are physically or functionally fragile to anthropogenic impacts) were identified in the dataset. Spatial estimates of likely VME distribution (as well as associated estimates of uncertainty) were predicted for the study area. Identifying areas most likely to represent a VME (rather than simply VME indicator taxa) provides much needed quantitative estimates of vulnerable habitats, and facilitates an evidence-based approach to managing potential impacts of bottom-trawling.

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利用物种联合分布模型预测海底分类群的分布,确定新西兰水域脆弱的海洋生态系统
要对接触底层的渔业进行有效的基于生态系统的管理,就必须了解渔业干扰如何在广泛的空间和时间尺度上影响海底动物。利用拖曳摄像系统收集的大量动物丰度数据集和包括底拖网捕捞强度在内的空间显式预测变量,使用联合物种分布模型(JSDM)对 67 个分类群的丰度进行了空间预测。不同分类群的模型拟合指标各不相同:存在-不存在模型的平均十倍交叉验证 AUC 得分为 0.70 ± 0.1(标准偏差),丰度模型的 R2 为 0.11 ± 0.1(标准偏差)。出现概率和丰度(每平方千米个体数)的空间预测因分类群而异,但存在关键的重叠区域,大陆架断裂和斜坡区域的分类群丰富度预测最高。由此得出的联合预测结果比以往的预测结果有很大进步,因为这些预测结果具有丰富性,可以探索共同出现的模式,并对类群丰富度(包括通常不包括在更常用的单一物种分布建模中的稀有物种)提供可靠的估计。数据集中确定了被认为是脆弱海洋生态系统(VME)指标的生境形成类群(那些在物理或功能上易受人为影响的类群)。预测了研究区域可能的脆弱海洋生态系统分布的空间估计值(以及相关的不确定性估计值)。确定最有可能代表脆弱海洋生态系统的区域(而不仅仅是脆弱海洋生态系统指标类群),可提供亟需的脆弱栖息地定量估算,并有助于采用循证方法管理底拖网捕捞的潜在影响。
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来源期刊
Biodiversity and Conservation
Biodiversity and Conservation 环境科学-环境科学
CiteScore
6.20
自引率
5.90%
发文量
153
审稿时长
9-18 weeks
期刊介绍: Biodiversity and Conservation is an international journal that publishes articles on all aspects of biological diversity-its description, analysis and conservation, and its controlled rational use by humankind. The scope of Biodiversity and Conservation is wide and multidisciplinary, and embraces all life-forms. The journal presents research papers, as well as editorials, comments and research notes on biodiversity and conservation, and contributions dealing with the practicalities of conservation management, economic, social and political issues. The journal provides a forum for examining conflicts between sustainable development and human dependence on biodiversity in agriculture, environmental management and biotechnology, and encourages contributions from developing countries to promote broad global perspectives on matters of biodiversity and conservation.
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