The meadows of Posidonia oceanica (L.) Delile are among the most important ecosystems of Mediterranean coastal waters, able to sustain diverse trophic webs with their high productivity, host endangered species and shape the seascape through reef-forming. Their vulnerability and common regression demand timely conservation measures, whose proactive potential, however, is limited by the lack of effective means of predicting their outcomes. To tackle the issue, we coupled two different approaches, i.e. species distribution modelling (SDM) and agent-based modelling (ABM), to develop spatially explicit models predicting meadow dynamics from environmental characteristics at local scale. Specifically, the approach relies on ensemble SDM to derive probability of colonization maps parameterizing ABM kernels for P. oceanica propagation. The ABM model itself comprises modules of meadow growth, based on P. oceanica ecophysiology, and destruction by mooring, fishing or trawling. Through the inclusion of SDM and of environmental dependence of meadow growth/destruction, models can be tuned for each protected area and are susceptible to be updated at any time upon changing of environmental constraints. Although heuristics, model results stem directly from the ecology of P. oceanica and its responses to environmental drivers, including anthropogenic activities, allowing reliable estimates of conservation policies outcomes and their continuous adaptation.

Combined modelling approaches for the conservation of Posidonia oceanica meadows

Alessandro Bellino;Davide Fronda;Floriana Di Stefano;Daniela Baldantoni
2021

Abstract

The meadows of Posidonia oceanica (L.) Delile are among the most important ecosystems of Mediterranean coastal waters, able to sustain diverse trophic webs with their high productivity, host endangered species and shape the seascape through reef-forming. Their vulnerability and common regression demand timely conservation measures, whose proactive potential, however, is limited by the lack of effective means of predicting their outcomes. To tackle the issue, we coupled two different approaches, i.e. species distribution modelling (SDM) and agent-based modelling (ABM), to develop spatially explicit models predicting meadow dynamics from environmental characteristics at local scale. Specifically, the approach relies on ensemble SDM to derive probability of colonization maps parameterizing ABM kernels for P. oceanica propagation. The ABM model itself comprises modules of meadow growth, based on P. oceanica ecophysiology, and destruction by mooring, fishing or trawling. Through the inclusion of SDM and of environmental dependence of meadow growth/destruction, models can be tuned for each protected area and are susceptible to be updated at any time upon changing of environmental constraints. Although heuristics, model results stem directly from the ecology of P. oceanica and its responses to environmental drivers, including anthropogenic activities, allowing reliable estimates of conservation policies outcomes and their continuous adaptation.
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/11386/4773534
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