Characterizing Spatial Uncertainty when Integrating Social Data in Conservation Planning

Recent conservation planning studies have presented approaches for integrating spatially referenced social (SRS) data with a view to improving the feasibility of conservation action. We reviewed the growing conservation literature on SRS data, focusing on elicited or stated preferences derived through social survey methods such as choice experiments and public participation geographic information systems. Elicited SRS data includes the spatial distribution of willingness to sell, willingness to pay, willingness to act, and assessments of social and cultural values. We developed a typology for assessing elicited SRS data uncertainty which describes how social survey uncertainty propagates when projected spatially and the importance of accounting for spatial uncertainty such as scale effects and data quality. These uncertainties will propagate when elicited SRS data is integrated with biophysical data for conservation planning and may have important consequences for assessing the feasibility of conservation actions. To explore this issue further, we conducted a systematic review of the elicited SRS data literature. We found that social survey uncertainty was commonly tested for, but that these uncertainties were ignored when projected spatially. Based on these results we developed a framework which will help researchers and practitioners estimate social survey uncertainty and use these quantitative estimates to systematically address uncertainty within an analysis. This is important when using SRS data in conservation applications because decisions need to be made irrespective of data quality and well characterized uncertainty can be incorporated into decision theoretic approaches.     

Making a Model Meaningful to Coral Reef Managers in a Developing Nation: a Case Study of Overfishing and Rock Anchoring in Indonesia

Abstract: Most of the world's coral reefs line the coasts of developing nations, where impacts from intense and destructive fishing practices form critical conservation issues for managers. Overfishing of herbivorous fishes can cause phase shifts to macroalgal dominance, and fishers’ use of rocks as anchors lowers coral cover, giving further competitive advantage to macroalgae. Overfishing and anchoring have been studied extensively, but the role of their interaction in lowering coral reef resilience has not been quantified formally. We analyzed the combined effects of overfishing and rock anchoring on a range of reef habitat types—varying from high coral and low macroalgae cover to low coral and high macroalgae cover—in a marine park in Indonesia. We parameterized a model of coral and algal dynamics with three intensities of anchoring and fishing pressure. Results of the model indicated that damage caused by rock anchoring was equal to or possibly more devastating to coral reefs in the area than the impact of overfishing. This is an important outcome for local managers, who usually have the funds to distribute less‐damaging anchors, but normally are unable to patrol regularly and effectively enough to reduce the impact of overfishing. We translated model results into an interactive visual tool that allows managers to explore the benefits of reducing anchoring frequency and fishing pressure. The potential consequences of inaction were made clear: the likelihood that any of the reef habitats will be dominated in the future by macroalgae rather than corals depends on reducing anchoring frequency, fishing pressure, or both. The tool provides a platform for strengthened relationships between managers and conservationists and can facilitate the uptake of recommendations regarding resource allocation and management actions. Conservation efforts for coral reefs in developing nations are likely to benefit from transforming model projections of habitat condition into tools local managers can understand and interact with.     

Should We Protect the Strong or the Weak? Risk,Resilience, and the Selection of Marine Protected Areas

Abstract: It is thought that recovery of marine habitats from uncontrollable disturbance may be faster in marine reserves than in unprotected habitats. But which marine habitats should be protected, those areas at greatest risk or those at least risk? We first defined this problem mathematically for 2 alternate conservation objectives. We then analytically solved this problem for both objectives and determined under which conditions each of the different protection strategies was optimal. If the conservation objective was to maximize the chance of having at least 1 healthy site, then the best strategy was protection of the site at lowest risk. On the other hand, if the goal was to maximize the expected number of healthy sites, the optimal strategy was more complex. If protected sites were likely to spend a significant amount of time in a degraded state, then it was best to protect low‐risk sites. Alternatively, if most areas were generally healthy then, counterintuitively, it was best to protect sites at higher risk. We applied these strategies to a situation of cyclone disturbance of coral reefs on Australia's Great Barrier Reef. With regard to the risk of cyclone disturbance, the optimal reef to protect differed dramatically, depending on the expected speed of reef recovery of both protected and unprotected reefs. An adequate consideration of risk is fundamental to all conservation actions and can indicate surprising routes to conservation success.     

Dispersal ecology of deadwood organisms and connectivity conservation

Limited knowledge of dispersal for most organisms hampers effective connectivity conservation in fragmented landscapes. In forest ecosystems, deadwood‐dependent organisms (i.e., saproxylics) are negatively affected by forest management and degradation globally. We reviewed empirically established dispersal ecology of saproxylic insects and fungi. We focused on direct studies (e.g., mark‐recapture, radiotelemetry), field experiments, and population genetic analyses. We found 2 somewhat opposite results. Based on direct methods and experiments, dispersal is limited to within a few kilometers, whereas genetic studies showed little genetic structure over tens of kilometers, which indicates long‐distance dispersal. The extent of direct dispersal studies and field experiments was small and thus these studies could not have detected long‐distance dispersal. Particularly for fungi, more studies at management‐relevant scales (1–10 km) are needed. Genetic researchers used outdated markers, investigated few loci, and faced the inherent difficulties of inferring dispersal from genetic population structure. Although there were systematic and species‐specific differences in dispersal ability (fungi are better dispersers than insects), it seems that for both groups colonization and establishment, not dispersal per se, are limiting their occurrence at management‐relevant scales. Because most studies were on forest landscapes in Europe, particularly the boreal region, more data are needed from nonforested landscapes in which fragmentation effects are likely to be more pronounced. Given the potential for long‐distance dispersal and the logical necessity of habitat area being a more fundamental landscape attribute than the spatial arrangement of habitat patches (i.e., connectivity sensu strict), retaining high‐quality deadwood habitat is more important for saproxylic insects and fungi than explicit connectivity conservation in many cases.