Inferring dolphin population status: using unoccupied aerial systems to quantify age‐structure

IF 2.8 2区 环境科学与生态学 Q1 BIODIVERSITY CONSERVATION
F. Vivier, C. Andrés, J. Gonzalvo, K. Fertitta, M. van Aswegen, V. Foroughirad, J. Mann, M. McEntee, R. S. Wells, L. Bejder
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引用次数: 0

Abstract

Assessing trends in population abundance and demographics is crucial for managing long‐lived and slow‐reproducing species. Obtaining demographic data, and age‐structure information, is challenging, notably for cetaceans. To address this, we combined Unoccupied Aerial System (UAS; drone) photogrammetry data with long‐term (>20 years) photo identification data to assess the age‐structure of the critically endangered sub‐population of common bottlenose dolphins (Tursiops truncatus) of the Gulf of Ambracia, Greece. We compared our findings with two extensively studied non‐endangered bottlenose dolphin populations (T. aduncus in Shark Bay, Australia, and T. truncatus in Sarasota Bay, USA). Using a log‐linear model, we estimated the total body lengths (TL) of 160 known‐aged dolphins between 2021 and 2023 from blowhole‐to‐dorsal‐fin distance (BHDF) measurements collected during surfacing. Subsequently, we tested four growth models to establish an age‐length growth curve. We assessed the sub‐population's age‐structure using three methods: (1) UAS‐derived TL estimates, (2) age‐length growth curve and (3) long‐term monitoring data (i.e. actual age‐structure). UAS‐measured TL (247.6 ± 32.2 cm) and UAS‐estimated TL (246.0 ± 34.7 cm) of the Greek sub‐population showed no differences. The Richards Growth model suggested an asymptotic length of 258.5 cm. In Greece, resulting age‐structure estimates across the three methods revealed no significant differences (P > 0.1). The Gulf of Ambracia and Shark Bay populations shared similar age‐structures, while Sarasota had higher proportions of 2–10 year‐olds and lower proportions of 10+ year‐olds. All populations had a comparable proportion of 0–2 year‐olds (~14%), indicating a similar reproductive rate. Our findings suggest stability in the Greek sub‐population; however, additional monitoring of reproductive parameters is essential before concluding its status. We demonstrated the effectiveness of UAS‐photogrammetry in rapidly quantifying population age‐structure, including scenarios with limited or no demographic data. This technique shows promise for enhancing precision, timeliness, cost‐effectiveness and efficiency in population monitoring and informing timely conservation management decisions.
推断海豚种群状况:利用无人机系统量化年龄结构
评估种群数量和人口统计趋势对于管理寿命长、繁殖慢的物种至关重要。获取人口统计学数据和年龄结构信息具有挑战性,尤其是对鲸目动物而言。为了解决这个问题,我们将无人机(UAS)摄影测量数据与长期(20 年)照片识别数据相结合,评估了希腊安布拉西亚湾极度濒危的普通瓶鼻海豚(Tursiops truncatus)亚群的年龄结构。我们将研究结果与两个经过广泛研究的非濒危瓶鼻海豚种群(澳大利亚鲨鱼湾的 T. aduncus 和美国萨拉索塔湾的 T. truncatus)进行了比较。我们利用对数线性模型,通过在海豚浮出水面时收集的吹孔至背鳍距离(BHDF)测量值,估算了2021年至2023年期间160头已知年龄海豚的总体长(TL)。随后,我们测试了四种生长模型,以建立年龄-长度生长曲线。我们用三种方法评估了该子种群的年龄结构:(1)UAS 测得的总长度估计值;(2)年龄-长度生长曲线;(3)长期监测数据(即实际年龄结构)。希腊亚群的 UAS 测量 TL(247.6 ± 32.2 厘米)和 UAS 估算 TL(246.0 ± 34.7 厘米)没有显示出差异。理查兹生长模型表明渐近长度为 258.5 厘米。在希腊,三种方法得出的年龄结构估计值无显著差异(P > 0.1)。安布拉西亚湾和鲨鱼湾种群的年龄结构相似,而萨拉索塔种群 2-10 岁的比例较高,10 岁以上的比例较低。所有种群中 0-2 岁的比例相当(约为 14%),表明繁殖率相似。我们的研究结果表明,希腊亚种群具有稳定性;然而,在断定其状况之前,对其繁殖参数的进一步监测是必不可少的。我们证明了无人机摄影测量在快速量化种群年龄结构方面的有效性,包括在人口数据有限或没有人口数据的情况下。这项技术有望提高种群监测的精确性、及时性、成本效益和效率,并为及时的保护管理决策提供信息。
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来源期刊
Animal Conservation
Animal Conservation 环境科学-生态学
CiteScore
7.50
自引率
5.90%
发文量
71
审稿时长
12-24 weeks
期刊介绍: Animal Conservation provides a forum for rapid publication of novel, peer-reviewed research into the conservation of animal species and their habitats. The focus is on rigorous quantitative studies of an empirical or theoretical nature, which may relate to populations, species or communities and their conservation. We encourage the submission of single-species papers that have clear broader implications for conservation of other species or systems. A central theme is to publish important new ideas of broad interest and with findings that advance the scientific basis of conservation. Subjects covered include population biology, epidemiology, evolutionary ecology, population genetics, biodiversity, biogeography, palaeobiology and conservation economics.
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