Modeling the ecological impact of phosphorus in catchments with multiple environmental stressors

Publisher
ASA, CSSA and SSSA
Abstract
Despite significant reductions in anthropogenic nutrient concentrations leading to improvement in chemical status, in many catchments corresponding improvements in the ecological status of running waters have not been observed. In this study, we tested a novel combination of complementary statistical modelling approaches, including regression tree analysis, compositional and ordinary linear mixed models to examine the potential reasons for this disparity, using low-frequency regulatory data typically available to catchment managers. A benthic Diatom Index (TDI) was linked to potential stressors, including nutrient concentrations, soluble reactive phosphorus (SRP) loads from different sources, land cover and catchment hydrological characteristics. Modelling suggested that SRP alone, traditionally considered as the bio-available component, may not be the best predictor of P impacts; indicating a stronger and spatially more variable relationship between TP concentrations and TDI than SRP. Nitrate (p<0.001) and TP (p=0.002) also showed negative additive relationship with TDI in models where land cover was not included. Land cover was the strongest predictor of ecological response. The positive effect of semi-natural (p<0.001) and negative effect of urban land cover (p=0.030) may be related to differentiated bioavailability of P fractions in catchments with different characteristics (e.g. P loads from point vs. diffuse sources) as well as resilience factors such as hydro-morphology and habitat condition, supporting the need for further research into factors affecting this pressure-response relationship in different catchment types. We propose that spatially targeted land cover change within river catchments, alongside combined mitigation of both P and nitrogen, may be needed to achieve desired ecological status.
Year
2019
Category
Refereed journal
Output Tags
WP 1.2 Water resources and flood risk management (RESAS 2016-21)