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Dryad

Data for: Patterns of species diversity in a network of artificial wetlands

Data files

May 03, 2023 version files 21.21 KB

Abstract

Aim

Artificial island habitats such as human-made wetlands are emerging novel ecosystems. Understanding the drivers of diversity in such artificial systems is essential for balancing the goals of biodiversity conservation and human socio-economic needs.  

Location

Telangana State, India.

Methods

We surveyed water birds in a network of 57 artificial wetlands and assessed four macroecological biodiversity patterns: spatial beta diversity, temporal beta diversity, species-abundance distributions (SADs), and the species–area relationship (SAR). We employed a mix of phenomenological and mechanistic models to examine the four macro-ecological patterns. We hypothesised that the wetland bird communities are primarily structured by immigration–extinction dynamics and thus that spatial and temporal beta diversity would be high, the within-wetland SADs would exhibit a large number of rare species and a monotonically declining overall shape, and that the SAR across wetlands would be strongly increasing. 

Results

Spatial and temporal beta diversity were both high and mostly attributable to turnover rather than nestedness. While the pooled SAD exhibited an interior mode, the SAD for individual wetlands was generally log-series distributed, consistent with a model in which immigration among wetlands is high. The SAR exhibited an increasing trend, with the “small-island effect”, which reflects constraints on immigration and is often observed for true island archipelagos, being absent. 

Main Conclusions

We tentatively conclude that bird diversity in this network of artificial wetlands is mainly structured by immigration–extinction dynamics, although we acknowledge that some of the patterns are also consistent with niche dynamics and future research should measure relevant biotic and abiotic variables in these wetlands. We encourage future work in which our rich data set is used to fit dynamic models that permit more detailed quantitative inferences about mechanisms structuring diversity in this novel ecosystem, which can ultimately also inform conservation management.