DIVERSITY DISTRIBUTION PATTERNS AND DRIVING FACTORS OF OCTOCORALS IN SEAMOUNT
Seamounts are hotspots of deep-sea biodiversity,and octocorals as the most diverse and dominant group of seamount megabenthos have been regarded as indicators of seamount vulnerable marine ecosystem.However,the distribution pattern and driving factors of seamount octocorals remain unclear.A total of 24 678 records of octocorals from 392 seamounts worldwide were analyzed statistically,from which the global distribution patterns and the driving factors of seamount octocorals in water layers of 200～1 000 m and below 1 000 m were revealed.Results show that the most octocoral genera recorded were distributed in the waters of the Hawaiian Archipelago in water layer of 200～1 000 m and in the waters of the Hawaiian Islands and the Northwest Atlantic Ocean in waters deeper than 1 000 m.As shown in the results of the hierarchical clustering analysis and the Infomap Bioregions network analysis,the octocorals in the 200～1 000 m water layer were classified into eight biogeographical regions,of which the Alaska-California,the Hawaiian Archipelago,and the tropical Pacific waters were distinct.Likewise,the octocorals genera in waters deeper than 1 000 m were categorized into 11 biogeographical regions,of which the California,the central Pacific Ocean and the southeast sea area of New Zealand are distinct.In addition,the Mantel test analysis showed that the water temperature in the 200～1 000 m was significantly correlated with the difference of biological composition in the biogeographic area,and the hierarchical clustering and network analysis showed that dissolved oxygen and flow velocity were also the driving factors.At last,the T-test and Wilcoxon rank sum test showed that some octocoral genera in the water layers of 200～1 000 m and deeper than 1 000 m showed significant preferences for specific environmental factors such as temperature,dissolved oxygen,salinity,and velocity,which may be the result in the differences in the coral composition among different biogeographical regions.
bioregionhierarchical clusteringnetwork analysisbiodiversity hotspotsbig data
万方数据
维普
