Comparing the network structure and resilience of two benthic estuarine systems following the implementation of nutrient mitigation actions

Abstract

The structure and resilience of benthic communities in coastal and estuarine ecosystems can be strongly affected by human mediated disturbances, such as nutrient enrichment, often leading to changes in a food webs function. In this study, we used the Ecopath model (EwE) to examine two case studies where deliberate management actions aimed at reducing nutrient pollution and restoring ecosystems resulted in ecological recovery. Five mass-balanced models were developed to represent pre and post-management changes in the benthic food web properties of the Tamar (1990, 1992, 2005) and Eden (1999, 2015) estuarine systems (UK). The network functions of interest were measures related to the cycling of carbon, nutrients and the productivity of the systems. Specific attention was given to the trophic structure and cycling pathways within the two ecosystems. The network attribute of ascendency was also examined as a proxy for resilience and used to define safe system-level operating boundaries. The results of the resilience metrics ascendancy (A) and its derivatives capacity (C) and overhead (O) indicate that both systems were more resilient and had higher resistance to potential stressors under low nutrient conditions. The less perturbed networks also cycled material more efficiently, according to Finns cycling index (CI), and longer cycling path lengths were indications of less stressed systems. Relative Ascendency (A/C) also proved useful for comparing estuarine systems of different sizes, suggesting the Tamar and Eden systems network structures have remained within their pre-defined “safe operating zones”. Overall, this analysis presents justification that efforts to reduce nutrient inputs into the Tamar and Eden estuaries have had a positive effect on the trophic networks of each system. Moreover, the consensuses of the network indicators in both systems suggest ecological network analysis (ENA) to be a suitable methodology to compare the recovery patterns of ecosystems of different sizes and complexity.