Zelli Edoardo, Ellis Joanne, Pilditch Conrad, Rowden Ashley A, Anderson Owen F, Geange Shane W, Bowden David A, Stephenson Fabrice
School of Science, University of Waikato, Tauranga, New Zealand.
School of Science, University of Waikato, Tauranga, New Zealand.
J Environ Manage. 2025 Jan;373:122635. doi: 10.1016/j.jenvman.2024.122635. Epub 2024 Dec 14.
Vulnerable Marine Ecosystems (VMEs) are recognised as having high ecological significance and susceptibility to disturbances, including climate change. One approach to providing information on the location and biological composition of these ecosystems, especially in difficult-to-reach environments such as the deep sea, is to generate spatial predictions for VME indicator taxa. In this study, the Random Forest algorithm was used to model the spatial distribution of density for 14 deep-water VME indicator taxa under current environmental conditions and future climate change scenarios (SSP2-4.5 and SSP3-7.0) within the New Zealand Territorial Sea and Exclusive Economic Zone (100-1500 m water depth) to evaluate potential changes in the location and distribution of density of these taxa over time. Overall, our species distribution models performed well for all taxa (mean AUC = 0.82; TSS = 0.56; r = 0.40) and predicted a considerable average reduction in density (54%) and habitat extent (61%), by the end of the 21st century under both climate change scenarios. Nevertheless, models identified regions that might serve as internal refugia (approximately 158,000 km), where some taxa are predicted to maintain the high densities predicted for current-day environmental conditions under future climatic conditions, and external refugia (approximately 121,000 km) where taxa were predicted to expand into new locations by the end of the 21st century. Our results represent a significant step forward as they provide predictions of the distribution of taxa densities, rather than just occurrence, under both present and future climatic conditions. Furthermore, these findings carry implications for ecosystem management and spatial planning, suggesting current marine spatial protection measures may not offer adequate protection to VME indicator taxa in the face of climate change. Additionally, activities like bottom trawling, present or future, may jeopardize climate refugia viability. Thus, a comprehensive assessment of cumulative effects on VME indicator taxa is recommended to establish effective protection measures for potential climate refugia, ensuring the continuity of essential ecosystem services.
脆弱海洋生态系统（VMEs）被认为具有很高的生态意义，并且易受包括气候变化在内的干扰影响。提供这些生态系统的位置和生物组成信息的一种方法，特别是在深海等难以到达的环境中，是生成VME指示分类群的空间预测。在本研究中，随机森林算法被用于模拟新西兰领海和专属经济区内（水深100 - 1500米）14种深水VME指示分类群在当前环境条件和未来气候变化情景（SSP2 - 4.5和SSP3 - 7.0）下的密度空间分布，以评估这些分类群的密度位置和分布随时间的潜在变化。总体而言，我们的物种分布模型对所有分类群都表现良好（平均AUC = 0.82；TSS = 0.56；r = 0.40），并预测在两种气候变化情景下，到21世纪末密度将平均大幅降低（54%），栖息地范围将缩小（61%）。尽管如此，模型确定了可能作为内部避难所的区域（约158,000平方千米），预计在未来气候条件下，一些分类群将维持当前环境条件下预测的高密度，以及外部避难所（约121,000平方千米），预计到21世纪末分类群将扩展到新的位置。我们的结果代表了重要的进展，因为它们提供了当前和未来气候条件下分类群密度分布的预测，而不仅仅是出现情况。此外，这些发现对生态系统管理和空间规划具有启示意义，表明面对气候变化，当前的海洋空间保护措施可能无法为VME指示分类群提供充分保护。此外，当前或未来的底拖网等活动可能会危及气候避难所的生存能力。因此，建议对VME指示分类群的累积影响进行全面评估，以建立针对潜在气候避难所的有效保护措施，确保基本生态系统服务的连续性。
