This influential financial theory has been applied to non-spatial problems in the management of species, populations, and ecosystem services. Some recent studies have also considered spatial planning units as assets to allow for overall risk to be reduced by allocating conservation investment across space. However, these approaches cannot be directly applied to many conservation planning problems that include discrete site selection, multiple conservation objectives, and a consideration of connectivity.
We extended previous applications of MPT by incorporating these additional requirements to design a reserve system for coastal wetlands, taking into account ecosystem services and sea-level rise.
We used our approach to find the optimal reserve configuration for coastal wetlands in Moreton Bay, Queensland, while considering the uncertain effects of sea-level rise. This area contains internationally important coastal wetlands, key ecosystem services, and is highly threatened by further urban development.
Mangroves encroaching on salt marsh near Moreton Bay. Photo: Catherine Lovelock
To design our reserve system, we first simulated many (804) scenarios of wetland change through to the year 2100, incorporating uncertainties in future sea-level rise, elevation data, and other biophysical parameters using the Sea Level Affecting Marshes Model (SLAMM).
We then optimised our risk-sensitive reserve design for three conservation objectives;
- Wetland area (by hectare)
- Blue carbon sequestration (Mg CO2 per year)
- Nursery habitat (by hectare)
For comparison, we also developed conservation plans based on the means of each of the four IPCC projections of sea-level rise.
We applied our MPT approach to reserve design for coastal wetlands and ecosystem services under sea-level rise. Here, coastal wetlands were likely to move landward with sea-level rise, but the exact spatial distribution was uncertain.
We found that there was a substantial change in the distribution of wetlands in 2100 under sea- level rise, with mangroves migrating landward, replacing saltmarsh, Melaleuca, and dryland areas.
However, there was also considerable uncertainty surrounding these future distributions. Spatially, the highest uncertainties occurred at the lowest and highest elevations of the future wetland distribution due to potential losses (continual inundation) and gains (landward movement) in the coastal wetland extent. This variation in the future extent and type of coastal wetlands also affected the ecosystem services that flow from these wetlands, which exhibited even greater variation than the distribution of wetlands.
Risk-return trade-offs for conservation objectives when planning under uncertain sea-level rise. Comparisons with deterministic solutions (i.e., ignoring uncertainty) are also shown.
Reductions in the risk of the final solutions were possible, but this came at the expense of reduced ecosystem service returns. However, approximately 50% of the risk could be reduced for only a 25% reduction in returns.
We also found that incorporating sea-level rise while ignoring uncertainty is always a high-risk strategy, even when planning for worst-case scenario sea-level rise. However, diversifying site selection using MPT can ensure the supply of ecosystem services by reducing risk of failure.
The variation in the total amount of ecosystem services provided by the study site in 2100. The units for each ecosystem service were standardised by the range of returns over the 804 scenarios. White circles indicate the mean, the black rectangle indicates the interquartile range and the black line represents the range less outliers. The grey shading shows the distribution of values.