Collaborative Research: ORCC: Climate and adaptation deficits: Mechanisms of response to climate change by the endangered North Atlantic right whale

2010年缅因湾的快速气候变化导致濒临灭绝的北大西洋露脊鲸（Eubalaena glacialis）突然重新分布，导致觅食模式发生变化，船只碰撞和渔具纠缠导致的死亡率更高，以及产崽率下降。露脊鲸数量和健康状况的下降促使国际自然保护联盟将露脊鲸的保护状态从濒危重新分类为极度濒危。露脊鲸的案例说明了缺乏对生物如何应对气候变化的理解所造成的生态和社会经济后果。由于露脊鲸的监测和建模工作主要集中在已知的和可接近的历史栖息地，这种快速的重新分布以前是不可预测的。该项目开发了一个新的建模框架，将新的露脊鲸数据与跨界猎物调查相结合，以了解适应性，确定常规监测区域以外的潜在栖息地，并预测未来几十年露脊鲸分布的变化。模型结果将指导联邦机构管理的保护政策的制定和实施，并为扩大动态管理工作提供理论支持。项目综合将应用于包括大西洋大型鲸鱼减少小组和海上风能区域野生动物科学合作组织在内的组织。将制定一个公开的数据科学课程计划，教授空间分析技术，并引发有关保护管理的讨论。本研究旨在利用强大的露脊鲸和浮游动物监测数据来建立下一代物种分布模型，以解释和预测露脊鲸的觅食决策和空间分布模式。这项研究将验证这样一种假设，即存在可测量的猎物密度阈值，从而导致个体动物利用或放弃觅食地点。然而，这些猎物密度阈值可能因环境因素（如猎物种类、地点和季节）或人口统计学因素（如露脊鲸年龄和繁殖状况）而异。通过对已识别个体的连续观测，将建立个体运动模型，以了解觅食决策，并在这种环境和人口变量范围内估计猎物密度阈值。该模型将与露脊鲸粪便样本的遗传分析相结合，以确定不同栖息地和觅食季节的猎物分类和猎物比例。猎物阈值将被纳入跨越北大西洋的猎物斑块模型，以表征合适觅食栖息地的时空发生。然后，将使用下一代物种分布建模框架，该框架利用个体运动模型和猎物斑块发生模型（由粪便样本中的猎物含量参数化）解决的行为阈值。该模型框架将为确定露脊鲸何时可能改变觅食模式以及哪些栖息地适合成为新的觅食热点提供新的预测能力。模型结果将用于量化气候变化对露脊鲸种群影响的生物能量和人为成分。该奖项由GEO/OCE生物海洋学项目和BIO/IOS气候变化有机体响应项目共同资助。该奖项反映了美国国家科学基金会的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

A rapid climate shift in the Gulf of Maine in 2010 caused an abrupt redistribution in the endangered North Atlantic right whale (Eubalaena glacialis), leading to changing foraging patterns, higher mortality rates due to vessel collisions and entanglement in fishing gear, as well as a drop in the calving rate. This decline in population size and health has triggered the International Union for Conservation of Nature to re-classify right whale conservation status from endangered to critically endangered. The case of the right whale illustrates the ecological and socio-economic consequences of a lack of understanding of how an organism responds to climate change. Such rapid redistributions have previously been unpredictable, as right whale monitoring and modeling efforts are focused on known and accessible historic habitats. This project develops a new modeling framework to integrate novel right whale data with trans-boundary prey surveys to understand adaptation, identify potential habitats outside regular monitoring regions, and predict changes to right whale distribution in future decades. Model results will guide the development and implementation of protective policies administered by federal agencies and provide theoretical support for expanding dynamic management efforts. Project synthesis will be applied in organizations including the Atlantic Large Whale Take Reduction Team and the Regional Wildlife Science Collaborative for Offshore Wind. A publicly-available data science lesson plan will be developed to teach spatial analysis techniques and engender discussion on conservation management. This proposal seeks to utilize robust right whale and zooplankton monitoring data to build a next-generation species distribution model to explain and predict right whale foraging decisions and spatial distribution patterns. The research will test the hypothesis that there are measurable thresholds of prey density that cause individual animals to utilize or abandon a foraging site. However, these prey density thresholds may vary depending on environmental factors such as prey species, site, and season, or by demographic factors such as right whale age and reproductive status. Using consecutive sightings of identified individuals, an individual movement model will be developed to understand foraging decision-making and estimate prey density thresholds across this range of environmental and demographic variables. This model will be coupled with genetic analysis of right whale fecal samples to identify prey taxa and prey ratios in distinct habitats and foraging seasons. Prey thresholds will be incorporated into a prey patch model spanning the North Atlantic to characterize the spatial and temporal occurrence of suitable foraging habitat. Then a next-generation species distribution modeling framework will be used that draws on behavioral thresholds resolved from the individual movement model and prey patch occurrence models parameterized by prey content in the fecal samples. This modeling framework will provide new predictive capacity for determining when right whales may shift foraging patterns and which habitats are suitable for becoming a novel foraging hot spot. Model results will be used to quantify the bioenergetic and anthropogenic components of the climate change effect on right whale populations.This award was co-funded through the GEO/OCE Biological Oceanography Program and the BIO/IOS Organismal Responses to Climate Change Program.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.