Latest research findings…ecosystem services

New publications from the Wilson lab:

E.A. Law, B.A. Bryan, E. Meijaard, T. Mallawaarachchi, M.J. Struebig, and K.A. Wilson In press. Ecosystem services from a degraded peatland of Central Kalimantan: implications for policy, planning, and management. Ecological Applications.

E.A. Law, B.A. Bryan, N. Torabi, S.A. Bekessy, C.A. McAlpine, and K.A. Wilson. In Press. Measurement matters in managing landscape carbon. Ecosystem Services.

Making decisions to conserve species under climate change

Shoo, L.P., Hoffmann, A.A., Garnett, S., Pressey, R.L., Williams, Y.M., Taylor, M., Falconi, L., Yates, C.J., Scott, J.K., Alagador, D., Williams, S.E. (2013), Making decisions to conserve species under climate change. Climatic Change. February 2013.


Severe impacts on biodiversity are predicted to arise from climate change. These impacts may not be adequately addressed by conventional approaches to conservation. As a result, additional management actions are now being considered. However, there is currently limited guidance to help decision makers choose which set of actions (and in what order) is most appropriate for species that are considered to be vulnerable. Here, we provide a decision framework for the full complement of actions aimed at conserving species under climate change from ongoing conservation in existing refugia through various forms of mobility enhancement to ex situ conservation outside the natural environment. We explicitly recognize that allocation of conservation resources toward particular actions may be governed by factors such as the likelihood of success, cost and likely co-benefits to non-target species in addition to perceived vulnerability of individual species. As such, we use expert judgment of probable tradeoffs in resource allocation to inform the sequential evaluation of proposed management interventions.

Scale Mismatches, Conservation Planning, and the Value of Social-Network Analyses

Guerrero, A.M., McAllister, R.R.J., Corcoran, J. and Wilson, K.A. (2013), Scale Mismatches, Conservation Planning, and the Value of Social-Network Analyses. Conservation Biology, 27: 35–44. doi: 10.1111/j.1523-1739.2012.01964.x 


Many of the challenges conservation professionals face can be framed as scale mismatches. The problem of scale mismatch occurs when the planning for and implementation of conservation actions is at a scale that does not reflect the scale of the conservation problem. The challenges in conservation planning related to scale mismatch include ecosystem or ecological process transcendence of governance boundaries; limited availability of fine-resolution data; lack of operational capacity for implementation; lack of understanding of social-ecological system components; threats to ecological diversity that operate at diverse spatial and temporal scales; mismatch between funding and the long-term nature of ecological processes; rate of action implementation that does not reflect the rate of change of the ecological system; lack of appropriate indicators for monitoring activities; and occurrence of ecological change at scales smaller or larger than the scale of implementation or monitoring. Not recognizing and accounting for these challenges when planning for conservation can result in actions that do not address the multiscale nature of conservation problems and that do not achieve conservation objectives. Social networks link organizations and individuals across space and time and determine the scale of conservation actions; thus, an understanding of the social networks associated with conservation planning will help determine the potential for implementing conservation actions at the required scales. Social-network analyses can be used to explore whether these networks constrain or enable key social processes and how multiple scales of action are linked. Results of network analyses can be used to mitigate scale mismatches in assessing, planning, implementing, and monitoring conservation projects.

Does more mean less? The value of information for conservation planning under sea level rise

Runting, R. K., Wilson, K. A. and Rhodes, J. R. (2013), Does more mean less? The value of information for conservation planning under sea level rise. Global Change Biology, 19: 352–363. doi: 10.1111/gcb.12064


Many studies have explored the benefits of adopting more sophisticated modelling techniques or spatial data in terms of our ability to accurately predict ecosystem responses to global change. However, we currently know little about whether the improved predictions will actually lead to better conservation outcomes once the costs of gaining improved models or data are accounted for. This severely limits our ability to make strategic decisions for adaptation to global pressures, particularly in landscapes subject to dynamic change such as the coastal zone. In such landscapes, the global phenomenon of sea level rise is a critical consideration for preserving biodiversity.

Here, we address this issue in the context of making decisions about where to locate a reserve system to preserve coastal biodiversity with a limited budget. Specifically, we determined the cost-effectiveness of investing in high-resolution elevation data and process-based models for predicting wetland shifts in a coastal region of South East Queensland, Australia. We evaluated the resulting priority areas for reserve selection to quantify the cost-effectiveness of investment in better quantifying biological and physical processes.

We show that, in this case, it is considerably more cost effective to use a process-based model and high-resolution elevation data, even if this requires a substantial proportion of the project budget to be expended (up to 99% in one instance). The less accurate model and data set failed to identify areas of high conservation value, reducing the cost-effectiveness of the resultant conservation plan. This suggests that when developing conservation plans in areas where sea level rise threatens biodiversity, investing in high-resolution elevation data and process-based models to predict shifts in coastal ecosystems may be highly cost effective. A future research priority is to determine how this cost-effectiveness varies among different regions across the globe.