Young Mary A, Critchell Kay, Sams Michael A
Deakin Marine Research and Innovation Centre, School of Life and Environmental Sciences, Deakin University, Warrnambool Campus, Warrnambool, Victoria, Australia.
Deakin Marine Research and Innovation Centre, School of Life and Environmental Sciences, Deakin University, Queenscliff Campus, Queenscliff, Victoria, Australia.
Ecol Appl. 2025 Jan;35(1):e3084. doi: 10.1002/eap.3084.
Kelp forests serve as the foundation for shallow marine ecosystems in many temperate areas of the world but are under threat from various stressors, including climate change. To better manage these ecosystems now and into the future, understanding the impacts of climate change and identifying potential refuges will help to prioritize management actions. In this study, we use a long-term dataset of observations of kelp percentage cover for two dominant canopy-forming species off the coast of Victoria, Australia: Ecklonia radiata and Phyllospora comosa. These observations were collected across three scuba sampling programs that extend from 1998 to 2019. We then associated those observations with habitat and environmental variables including depth, seafloor structure, wave climate, currents, temperature, and population connectivity in generalized additive mixed-effects models and used these models to develop predictive maps of kelp cover across the Victorian marine protected areas (MPAs). These models were also used to project kelp coverage into the future by replacing wave climate and temperature with future projections (2090, Representative Concentration Pathways [RCPs] 4.5 and 8.5). Once the spatial predictions were compiled, we calculated percent cover change from 1998 to 2019, stability over the same period, and future predicted change in percent cover (2019-2090) to understand the dynamics for each species across the MPAs. We also used the current percentage cover, stability, and future percentage cover to develop a ranking system for classifying the maps into very unlikely refugia, unlikely refugia, neutral, potential refugia, and likely refugia. A management framework was then developed to use those refugia ranking values to inform management actions, and we applied this framework across three case studies: one at the scale of the MPA network and two at the scale of individual MPAs, one where management decisions were the same for both species, and one where the actions were species-specific. This study shows how species distribution models, both contemporary and with future projections, can help to identify potential refugia areas that can be used to prioritize management decisions and future-proof restoration actions.
海带森林是世界上许多温带地区浅海生态系统的基础，但正受到包括气候变化在内的各种压力源的威胁。为了更好地管理这些生态系统的现在和未来，了解气候变化的影响并确定潜在的避难所将有助于确定管理行动的优先顺序。在本研究中，我们使用了澳大利亚维多利亚州海岸两种主要的形成冠层的海带物种（辐射昆布和毛孢叶海带）的海带覆盖百分比的长期观测数据集。这些观测数据是通过1998年至2019年的三个水肺潜水采样计划收集的。然后，我们在广义相加混合效应模型中将这些观测数据与包括深度、海底结构、波浪气候、洋流、温度和种群连通性在内的栖息地和环境变量相关联，并使用这些模型绘制维多利亚海洋保护区海带覆盖的预测地图。这些模型还通过用未来预测（2090年，代表性浓度路径[RCPs]4.5和8.5）取代波浪气候和温度，来预测未来的海带覆盖率。一旦完成空间预测，我们计算了1998年至2019年的覆盖百分比变化、同期的稳定性以及未来预测的覆盖百分比变化（2019 - 2090年），以了解每个物种在海洋保护区内的动态变化。我们还使用当前的覆盖百分比、稳定性和未来的覆盖百分比来开发一个排名系统，将地图分类为极不可能的避难所、不太可能的避难所、中性、潜在避难所和可能的避难所。然后制定了一个管理框架，利用这些避难所排名值为管理行动提供信息，我们在三个案例研究中应用了这个框架：一个是在海洋保护区网络层面，另外两个是在单个海洋保护区层面，一个案例中两个物种的管理决策相同，另一个案例中行动是针对特定物种的。这项研究展示了当代和未来预测的物种分布模型如何有助于识别潜在的避难所区域，这些区域可用于确定管理决策的优先顺序以及确保恢复行动的未来可行性。
