by Georgina Mace
The efforts made by conservationists to preserve vulnerable species and sustain critical ecosystem services face increasing challenges. Funding is limited, pressures on natural environments are escalating, and competing demands for the use of land and sea are intensifying. So how do conservation practitioners decide what to do with the limited resources available to them, and how might their actions be more efficiently designed?
The two papers that I have selected to highlight for the PLOS Biology XV Collection come from the Possingham group at the University of Queensland, and introduce a formal basis for making conservation decisions (Possingham et al., 2015; Saunders et al. 2017). The case studies in both these papers suggest that the most obvious actions may not be the best, and the authors present analytical approaches to improve decision-making. These approaches require a certain amount of scientific understanding of the system but applying these techniques to guide conservation actions will provide much better outcomes compared to relying on traditional wisdom.
The traditional approach for conservation is, first and foremost, to protect existing habitat. The alternative—habitat restoration—can be very costly, and recent experience reveals that the full suite of species and ecosystem services may be recovered only slowly over time. But even well-managed conservation of intact areas inevitably degrade over time due to growing anthropogenic pressures and environmental change. On the other hand, well-implemented restoration projects can deliver optimal conditions for certain species or ecosystem services. Rather surprisingly these papers show that as restoration techniques improve, there are often circumstances where restoration should be prioritised over protection.
The studies use decision theory, employing resource allocation optimisation models given a fixed budget and a specific desired outcome. The papers are significant for putting conservation practice onto a more formal scientific- and evidence-based footing. They are able to do this by taking a few specific steps that are not common practice in many conservation efforts, but perhaps should be.
The first critical step is to have a clearly defined outcome that is required for the area or habitat under consideration. Possingham et al (2015) investigate two case studies. In the first, the objective is to maximise the storm protection services of intact mangrove ecosystems in the Coral Triangle, and in the second the objective is to minimise bird species extinctions in the Atlantic forest of Paraguay. The second paper (Saunders et al. 2017) investigates the more complex case of coastal ecosystems in Australia where the objective is to restore functional seagrass beds that are strongly affected by land-based sediment flows. Thus there are four choices for conservation actions for this system: restoration or recovery of land or ocean habitats. In each case study there is a fixed budget allocation over the next 30 or 40 years. The final input in each case is a dynamic and temporally explicit landscape or landscape-seascape model that integrates the costs and benefits of restoration or protection to find the optimal decision in each case. These three elements – an explicit objective, a fixed budget, and an effective model of the system are not often available, but when they are the results can be very influential.
In the mangrove case, restoration is favoured over protection because the storm protection service requires intact mangrove forest and restoration achieves a reduction in degradation more quickly, even though it is more costly. In the rapidly degrading Paraguayan forests, the optimal strategy is protection for the first 20 years, effectively reducing the rate area of degraded forest, but thereafter a switch to restoration achieves the greatest reduction in the number of bird extinctions. In the coastal study the surprising result is that the optimal strategy for restoring intact seagrass beds is restoration in the marine environment, and not addressing pollution sources on the land. This turns out to be more effective over the long term despite its higher costs. These conclusions are all sensitive to a number of input assumptions which are explored in the papers.
Crucially, the explicit optimisation models may not be possible in many real world situations – they depend on substantial inputs from ecology and economics as well as practical experience. But both papers also use sensitivity analysis to explore different ecological contexts and provide simple rules of thumb to aid decision-making in practice. In real world cases there are often multiple objectives which complicate the analysis, but need not rule out adopting the approach.
Conservation practice is often far from evidence-based, but certainly should be. These papers provide a clear direction for the kinds of science and decision-making tools that could make a big difference. While the ecological and economic modelling is challenging, the identification of clearly stated quantitative objectives over reasonable time intervals need not be, and can be used along with the rules of thumb to inform better decision-making even under substantial uncertainties.
Possingham HP, Bode M, Klein CJ (2015) Optimal Conservation Outcomes Require Both Restoration and Protection. PLOS Biology 13(1): e1002052.https://doi.org/10.1371/journal.pbio.1002052
Saunders MI, Bode M, Atkinson S, Klein CJ, Metaxas A, Beher J, Beger M, Mills M, Giakoumi S, Tulloch V, Possingham HP. (2017) Simple rules can guide whether land- or ocean-based conservation will best benefit marine ecosystems. PLOS Biology 15(9): e2001886. https://doi.org/10.1371/journal.pbio.2001886
Georgina Mace is a Professor of Biodiversity and Ecosystems, Head of the Centre for Biodiversity and Environment Research at University College London, and is a member of the PLOS Biology Editorial Board.
Featured image Credit: Mark Priest
Georgina Mace image credit: Georgina Mace