Best-fit relations between hydrological and water quality characteristics of inland wetlands and plant species richness

Abstract

The increasing global population and climate change have intensified water demands, resulting in increased reliance on groundwater resources. The increasing water demand and diminishing recharge rates pose a significant threat to groundwater levels and discharge. This will lead to alterations in the flow regimes and water volumes impacting wetlands and species richness. Slight modifications in flow regimes and water volumes can result in the loss of specific plant and fish species communities, as these communities are adapted to particular conditions. This research focuses on quantifying relationships between hydrological and water quality variables and plant species richness in wetlands in Australia and England. The approach aims to fill knowledge gaps related to plant species-area relationships and their interactions with hydrology and water quality.

A comprehensive literature review is included about wetlands and identifying which drivers impact the species richness in wetlands. For hydrological datasets, the PCR-GLOBWB model output is used. For the water quality data, the DynQual model output and the World Bank’s ‘Quality Unknown’ data are used. General statistics were calculated and a correlation matrix is used to find the highest correlation with plant species richness. The strength of the hydrological and water quality-species richness relationships are quantified using linear, inverse and power regression. The multiple linear regression is done for all variables including cross-validation.

The results indicate that the wetland area holds the strongest correlation with species richness. Power regression models demonstrate significant prediction, particularly for wetland area and organic pollution (BOD concentrations). The multiple linear regression models show that using one predictor variable is insufficient to explain species richness. The area plays a critical role in improving the fit to species richness. This study can be used to understand the contribution of different driving factors in wetland species richness, for example for effective conservation and sustainable management of wetland ecosystems, especially with the growing anthropogenic pressures taken into account