Castrillon Juliana, Huston Wilhelmina, Bengtson Nash Susan
Southern Ocean Persistent Organic Pollutants Program Environmental Futures Research Institute (EFRI) Griffith University Nathan QLD Australia.
School of Life Sciences Faculty of Science University of Technology Sydney Ultimo NSW Australia.
Ecol Evol. 2017 Jun 4;7(14):5131-5139. doi: 10.1002/ece3.2913. eCollection 2017 Jul.
The ability to accurately evaluate the energetic health of wildlife is of critical importance, particularly under conditions of environmental change. Despite the relevance of this issue, currently there are no reliable, standardized, nonlethal measures to assess the energetic reserves of large, free-roaming marine mammals such as baleen whales. This study investigated the potential of adipocyte area analysis and further, a standardized adipocyte index (AI), to yield reliable information regarding humpback whale () adiposity. Adipocyte area and AI, as ascertained by image analysis, showed a direct correlation with each other but only a weak correlation with the commonly used, but error prone, blubber lipid-percent measure. The relative power of the three respective measures was further evaluated by comparing humpback whale cohorts at different stages of migration and fasting. Adipocyte area, AI, and blubber lipid-percent were assessed by binary logistic regression revealing that adipocyte area had the greatest probability to predict the migration cohort with a high level of redundancy attributed to the AI given their strong linear relationship (r = -.784). When only AI and lipid-percent were assessed, the performance of both predictor variables was significant but the power of AI far exceeded lipid-percent. The sensitivity of adipocyte metrics and the rapid, nonlethal, and inexpensive nature of the methodology and AI calculation validate the inclusion of the AI in long-term monitoring of humpback whale population health, and further raises its potential for broader wildlife applications.
准确评估野生动物的能量健康状况至关重要，尤其是在环境变化的情况下。尽管这个问题很重要，但目前尚无可靠、标准化的非致命措施来评估大型自由游动海洋哺乳动物（如须鲸）的能量储备。本研究调查了脂肪细胞面积分析以及进一步的标准化脂肪细胞指数（AI）在获取有关座头鲸肥胖可靠信息方面的潜力。通过图像分析确定的脂肪细胞面积和AI彼此呈直接相关，但与常用但容易出错的鲸脂脂质百分比测量仅呈弱相关。通过比较座头鲸在不同洄游和禁食阶段的群体，进一步评估了这三种测量方法各自的相对效力。通过二元逻辑回归评估脂肪细胞面积、AI和鲸脂脂质百分比，结果显示脂肪细胞面积预测洄游群体的概率最大，鉴于AI与脂肪细胞面积有很强的线性关系（r = -0.784），AI具有较高的冗余度。当仅评估AI和脂质百分比时，两个预测变量的表现均显著，但AI的效力远远超过脂质百分比。脂肪细胞指标的敏感性以及该方法和AI计算的快速、非致命和低成本特性，证明将AI纳入座头鲸种群健康的长期监测是合理的，并进一步提高了其在更广泛野生动物应用中的潜力。
