COS 19-3 - Can protection of ecosystem services preserve biodiversity? A novel approach combining decision optimization and network models

Tuesday, August 9, 2016: 8:40 AM
220/221, Ft Lauderdale Convention Center
Hui Xiao, Geography, Planning and Environmental Management, The University of Queensland, Brisbane, Australia; School of Geography, Planning and Environmental Management, The University of Queensland, Brisbane, Australia, Régis Sabbadin, Unité de Mathématiques et Informatique Appliquées, INRA-Toulouse, Toulouse, France, Laura Dee, Institute on the Environment, University of Minnesota, Twin Cities, St Paul, MN, Nathalie Peyrard, Unité de Mathématiques et Informatique Appliquées, INRA-Toulouse, France, Iadine Chades, EcoSciences Precinct - Dutton Park, CSIRO, Dutton Park, Australia and Eve McDonald-Madden, School of Geography, Planning and Environmental Management, The University of Queensland, Australia
Background/Question/Methods

Ecosystem plays a critical role in supporting biodiversity (Bio), providing ecosystem services (ES) and mitigating climate change effect. But in recent decades, intensive human activities result in continuous biodiversity loss and ecosystem services degradation. Remarkable effort has been made on ecosystem conservation but the ambiguous objective has been criticized as the culprit of most failures. Decision makers hesitate between strategies focusing on biodiversity and strategies focusing on ecosystem services maximization, hoping to have the reinforcement between both objectives but also worrying about the trade-offs.

Considering the interwoven relationship between biodiversity and ecosystem services, we may wonder: in ecosystem conservation, can we reach biodiversity through services targeted strategy? Will the structure of the ecosystem influence this strategy selection and how?

In this talk we discuss those questions by proposing a novel approach including network theory, decision theory and stochastic dynamic programming techniques. The biodiversity-ecosystem services relationship is considered in the network analysis for the first time to deduce the best management strategy.

Results/Conclusions

Using the proposed novel approach, we derived and analysed the optimal management strategy for 320 simulated ecosystem networks and an empirical ecosystem, the Carpinteria Salt Marsh (California USA). Our results suggest that strategies focusing on ES maximization could reach a similar level of biodiversity as strategies focusing purely on biodiversity outcomes but only for ecosystems with particular characteristics.  

The trophic level of the functional groups providing the services plays a critical role in Bio VS. ES strategy selection. When services are provided by top predators, there are more conflicts in protection priorities between two strategies: ES strategy will result in an acceleration of biodiversity loss by directly protecting high services-performance functional groups (i.e. trop predators), while Bio strategy will provide a more diversified protection priority by protecting each functional group with similar probability. However,  for an ecosystem structure where services are provided by basal groups or ‘randomly distributed’, ES strategy can potentially enhance the services received whilst maintaining a similar level of biodiversity (<1% difference) as Bio strategy. This is achieved as the high services-performance groups are propably also critical in supporting biodiversity.

To conclude, an optimal management strategy should be based on careful consideration of the structure of the ecosystem and the trade-offs between biodiversity and ecosystem services. The proposed novel approach could help decision makers to reach the maximum ecosystem outcome through a quantitative method which has never been investigated before.