Drivers of the spatiotemporal patterns of the mangrove crab metacommunity in a tropical bay.

Revealing community patterns and driving forces is essential in community ecology and a prerequisite for effective management and conservation efforts. However, the mangrove ecosystem and its important fauna group such as the crabs, still lack multi-processes research under metacommunity framework, resulting in evidence and theorical application gaps. To fill these gaps, we selected China's most representative mangrove bay reserve in tropical zone as a stable experimental system and conducted a seasonal investigation (July 2020, October 2020, January 2021, and April 2021) of mangrove crabs. We performed a multi-approach analysis using both pattern-based and mechanistic method to distinguish the processes driving the mangrove crab metacommunity. Our results showed that the crab metacommunity exhibits a Clementsian pattern in the bay-wide mangrove ecosystem but is influenced by both local environmental heterogeneity and spatial processes, thus representing a combined paradigm of species sorting and mass effect. Moreover, the long-distance spatial constraints are more pronounced compared to the local environmental factors. This is reflected in the greater importance of the broad-scale Moran's Eigenvector Maps, the distance-decay pattern of similarity, and the difference in beta diversity dominated by the turnover component. This pattern changes throughout the year, mainly due to changes in dominant functional groups caused by the stress of changes in water salinity and temperature induced by air temperature and precipitation. This research provides multi-dimension research data and relevant analysis, offering clear evidence for understanding the patterns and related driving forces of crab metacommunity in tropical bay mangroves, and verifies the applicability of some general laws in the system. Future studies can address more diverse spatiotemporal scales, gaining a clearer understanding to serve the conservation of mangrove ecosystems and economically important fishery species.