Predicting the cumulative effects of multiple stressors on shellfish ecosystem service potential

Abstract

Understanding and anticipating the effects of interacting stressors is critical for the effective management of marine ecosystems and the essential ecosystem services (ES) they provide. A key challenge in integrating cumulative effects and their impacts on ES delivery into spatial tools is to move beyond simple additive stressor interactions in the face of data scarcity, ecosystem complexity and uncertainty. Here we present a novel methodological approach with which to assess the cumulative effects of multiple stressors on the ES potential provided by two estuarine infaunal bivalves (Austrovenus stutchburyi and Paphies australis) which we illustrate in a case study within the Tauranga Harbour, New Zealand. We firstly assess the shift in density distribution and probability of occurrence in response to increasing sediment mud content, harvesting pressure and sea level rise. The single and cumulative effects of these stressors were simulated through species distribution models (SDM). Principle based models were then used to assess the translation of altered environmental conditions and shellfish abundance on the ES potential for food provision, water quality regulation, nitrogen removal and sediment stabilisation. The simulation of single and cumulative stressors at non-lethal levels were found to cause substantial changes to bivalve density and their distribution but could have both positive and negative impacts on ES potential due to shifts in optimal environmental conditions. Increasing the number of stressors delivered a worse outcome in terms of loss of density, particularly for Austrovenus with harvesting pressure being a common driver of decline in high density areas. This effect was similarly reflected in the ES predictions although there were nuances between the species related to habitat association and sensitivity to stressors. For example, the increase of sea level rise and mud had a greater negative impact on Austrovenus. Stressor effects varied spatially with some areas more heavily impacted than others and indicated an overall reduction of high ES areas whilst increasing areas of medium ES potential. This study introduces efficient and accessible means for integrating ES into cumulative effects assessments, the perspective from which renders the results more digestible for management. Using an interactive modelling approach rather than simple additive methods, it provides more robust information, aiding the prevention of ecological surprises. These quantitative spatial predictions will facilitate the identification of vulnerable areas, priority stressors and locations appropriate for restoration and conservation, assisting management in the rehabilitation and protection of bivalve beds and ES.