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Connectivity networks and delineation of disconnected coastal provinces along the Indian coastline using large-scale Lagrangian transport simulations
Limnology and Oceanography ( IF 3.8 ) Pub Date : 2022-05-09 , DOI: 10.1002/lno.12092
D. K. Bharti 1, 2 , Katell Guizien 3 , M. T. Aswathi‐Das 4, 5 , P. N. Vinayachandran 5 , Kartik Shanker 1
Affiliation  

Ocean circulation is the engine of dispersal and population connectivity in marine ecosystems, knowledge of which is essential for conservation planning. Understanding connectivity patterns at a large scale can help define the spatial extent of metapopulations. In this study, we built connectivity networks from Lagrangian transport simulations of neutrally buoyant particles released along the Indian coastline, a significant region in the Indian Ocean. We assessed the variation in connectivity networks across release periods for the major drivers of oceanography including the two monsoonal seasons, El Niño–Southern Oscillation (ENSO) years and for the entire range of region-specific pelagic larval durations (PLDs) for marine invertebrates. We detected well-connected communities, mapped frequent connectivity breaks, and assessed the functional role of coastal areas within the connectivity network using node metrics. Network characteristics did not differ based on the ENSO year, but varied with season and PLD. Connectance for the Indian coastline was relatively low, ranging from 0.5% to 3.4%, and increased significantly for PLD larger than 20 d. The number of cohesive coastal communities decreased gradually from 60 (PLD < 4 d) to 30 (PLD > 20 d) with increasing PLD. Despite variation in the location of connectivity breaks with the time of particle release within a monsoonal season, four disconnected provinces were consistently identified across the entire PLD range, which partially overlapped with observed genetic and biogeographic breaks reported along the Indian coastline. Our results support the adoption of a coordinated management framework within each of the four provinces delineated in the present study.

中文翻译:

使用大规模拉格朗日交通模拟对沿印度海岸线的不连贯沿海省份进行连通网络和描绘

海洋环流是海洋生态系统中分散和人口连通性的引擎,其知识对于保护规划至关重要。了解大规模的连通性模式可以帮助定义元种群的空间范围。在这项研究中,我们通过对沿印度洋重要区域印度海岸线释放的中性浮力粒子的拉格朗日传输模拟建立了连接网络。我们评估了海洋学主要驱动因素(包括两个季风季节、厄尔尼诺-南方涛动 (ENSO) 年以及海洋无脊椎动物的整个区域特定远洋幼虫持续时间 (PLD) 的整个范围内)的连接网络在释放期间的变化。我们检测到连接良好的社区,映射频繁的连接中断,并使用节点指标评估了沿海地区在连通网络中的功能作用。网络特征不因ENSO年份而异,但随季节和PLD而变化。印度海岸线的连通性相对较低,介于 0.5% 到 3.4% 之间,并且对于大于 20 d 的 PLD 显着增加。随着PLD的增加,具有凝聚力的沿海社区的数量从60个(PLD < 4 d)逐渐减少到30个(PLD > 20 d)。尽管连通性中断的位置随季风季节内粒子释放时间的变化而变化,但在整个 PLD 范围内始终确定了四个不相连的省份,这与印度海岸线沿线报告的观察到的遗传和生物地理中断部分重叠。
更新日期:2022-05-09
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