Modelling Species-Area Relationships for Plants in Inland Wetlands on a Global Scale
Summary
Wetlands are critical biodiversity hotspots, yet they have faced substantial threats, with 35% of global wetlands having disappeared since 1970 due to human activities and climate change. This rapid decline stresses the urgent need for conservation strategies based on quantified relationships between biodiversity and wetland characteristics. The species-area relationship, a foundational ecological principle, states that the number of unique species increases with increasing area, and offers a framework to explore how wetland area impacts species richness.
This study investigates species-area relationships for inland wetlands on a global scale, using plant species richness and wetland area data from thirteen regions across diverse geographical regions. Univariate linear, power and inverse regression models have been employed to examine regional species-area relationships while linear mixed-effects modelling has been used to integrate datasets from varied sources, accounting for sampling and geographical differences. The study also explores the potential of using saturated area fraction output from the PCR-GLOBWB hydrological model as a proxy for wetland area, aiming to extend the analysis of species-area relations for data-deficient regions.
Power regression analyses reveal significant (p<0.05), positive relationships between species richness and wetland area in ten of the thirteen regions. Linear mixed-effects modelling demonstrates that including the random effects, arising due to different geographical regions and data sources, increase the explanatory power of the model. Area alone explains 11% of the variation in species richness but area combined with the random effects explains 65% of the variation. Saturated area fraction shows limited explanatory power for species richness and its use as a proxy for wetland area is challenging due to inconsistencies in wetland area measurement and varying definitions used in sampling.
Results from the power regression model suggest the importance of wetland area in sustaining biodiversity and those from the linear mixed-effects model indicate that the effect of area, combined with the regional effects of hydroclimatic conditions, vegetation type and sampling differences, are useful to explain the species-area relations on a larger scale. Further research incorporating detailed metadata about wetland area measurements could improve the applicability of saturated area fraction for wetland modelling. Overall, this study provides insights for developing global wetland conservation strategies and improving hydro-ecological modelling to enhance future species-area relationship analyses and assessments.