Linkages between measures of biodiversity and community resilience in Pacific Island agroforests

Designing agroecosystems that are compatible with the conservation of biodiversity is a top conservation priority. However, the social variables that drive native biodiversity conservation in these systems are poorly understood. We devised a new approach to identify social–ecological linkages that affect conservation outcomes in agroecosystems and in social‐ecological systems more broadly. We focused on coastal agroforests in Fiji, which, like agroforests across other small Pacific Islands, are critical to food security, contain much of the country's remaining lowland forests, and have rapidly declining levels of native biodiversity. We tested the relationships among social variables and native tree species richness in agroforests with structural equation models. The models were built with data from ecological and social surveys in 100 agroforests and associated households. The agroforests hosted 95 native tree species of which almost one‐third were endemic. Fifty‐eight percent of farms had at least one species considered threatened at the national or international level. The best‐fit structural equation model (R² = 47.8%) showed that social variables important for community resilience—local ecological knowledge, social network connectivity, and livelihood diversity—had direct and indirect positive effects on native tree species richness. Cash‐crop intensification, a driver of biodiversity loss elsewhere, did not negatively affect native tree richness within parcels. Joining efforts to build community resilience, specifically by increasing livelihood diversity, local ecological knowledge, and social network connectivity, may help conservation agencies conserve the rapidly declining biodiversity in the region.     

The importance of incorporating functional habitats into conservation planning for highly mobile species in dynamic systems

The distribution of mobile species in dynamic systems can vary greatly over time and space. Estimating their population size and geographic range can be problematic and affect the accuracy of conservation assessments. Scarce data on mobile species and the resources they need can also limit the type of analytical approaches available to derive such estimates. We quantified change in availability and use of key ecological resources required for breeding for a critically endangered nomadic habitat specialist, the Swift Parrot (Lathamus discolor). We compared estimates of occupied habitat derived from dynamic presence‐background (i.e., presence‐only data) climatic models with estimates derived from dynamic occupancy models that included a direct measure of food availability. We then compared estimates that incorporate fine‐resolution spatial data on the availability of key ecological resources (i.e., functional habitats) with more common approaches that focus on broader climatic suitability or vegetation cover (due to the absence of fine‐resolution data). The occupancy models produced significantly (P < 0.001) smaller (up to an order of magnitude) and more spatially discrete estimates of the total occupied area than climate‐based models. The spatial location and extent of the total area occupied with the occupancy models was highly variable between years (131 and 1498 km²). Estimates accounting for the area of functional habitats were significantly smaller (2–58% [SD 16]) than estimates based only on the total area occupied. An increase or decrease in the area of one functional habitat (foraging or nesting) did not necessarily correspond to an increase or decrease in the other. Thus, an increase in the extent of occupied area may not equate to improved habitat quality or function. We argue these patterns are typical for mobile resource specialists but often go unnoticed because of limited data over relevant spatial and temporal scales and lack of spatial data on the availability of key resources. Understanding changes in the relative availability of functional habitats is crucial to informing conservation planning and accurately assessing extinction risk for mobile resource specialists.     

Potential Reflection of Distinct Ecological Units in Plant Endemism Categories

Abstract: The level of endemism at a site may indicate species richness of the site. Nevertheless, assessing endemism levels in taxonomic groups such as plants may be difficult because the species richness of plants is high relative to species richness of other taxonomic groups (e.g., vertebrates). A major problem in determining whether plant species are endemic is the lack of standardization of the geographic extent of endemism: species are considered endemic to, for example, countries, continents, or states. We compiled a history of the concept of endemism as it applies to plants. The application of the concept to geographic distribution dates from the 19th century, when European explorers discovered many taxa exclusive to regions outside Europe. Two types of endemism, paleoendemism and neoendemism, were then acknowledged, according to evolutionary age, and these categories are still in use. In the 20th century, most of the research on endemism focused on explaining range restriction on the basis of cytological data, edaphic and geological factors, and phylogeny. This research led to a vast number of concepts, of which only edaphic endemism remains relatively well accepted. More recently, researchers suggest that competition may determine endemism in some cases. We suggest that plants be labeled as endemic only if their distribution occurs in a distinct ecological unit, such as a biome. On the basis of a literature review of the factors that cause range restriction, we categorized endemic taxa as paleoendemic, neoendemic, edaphically endemic, or suppressed endemic. For example, Schlechtendalia luzulifolia, is a rare forb that is a paleoendemic species of the granite and sandstone‐based grasslands of the Pampa. Levels of endemism in southern Brazilian grasslands are poorly known. We emphasize the importance of recognizing these grasslands as a single transnational biome so that levels of endemism of species therein can be assessed correctly.     

Effects of Economic Downturns on Mortality of Wild African Elephants

Abstract: Declines in economic activity and associated changes in human livelihood strategies can increase threats of species overexploitation. This is exemplified by the effects of economic crises, which often drive intensification of subsistence poaching and greater reliance on natural resources. Whereas development theory links natural resource use to social‐economic conditions, few empirical studies of the effect of economic downturns on wild animal species have been conducted. I assessed the relations between African elephant (Loxodonta africana) mortality and human‐caused wounds in Samburu, Kenya and (1) livestock and maize prices (measures of local economic conditions), (2) change in national and regional gross domestic product (GDP) (measures of macroeconomic conditions), and (3) the normalized difference vegetation index (NDVI) (a correlate of primary productivity). In addition, I analyzed household survey data to determine the attitudes of local people toward protected areas and wild animals in the area. When cattle prices in the pastoralist study region were low, human‐caused wounds to and adult mortality of elephants increased. The NDVI was negatively correlated with juvenile mortality, but not correlated with adult mortality. Changes in Kenyan and East Asian (primary market for ivory) GDP did not explain significant variation in mortality. Increased human wounding of elephants and elephant mortality during periods of low livestock prices (local economic downturns) likely reflect an economically driven increase in ivory poaching. Local but not macroeconomic indices explained significant variation in mortality, likely due to the dominance of the subsistence economy in the study area and its political and economic isolation. My results suggest economic metrics can serve as effective indicators of changes in human use of and resulting effects on natural resources. Such information can help focus management approaches (e.g., antipoaching effort or proffering of alternative occupational opportunities) that address variation in local activities that threaten plant and animal populations.     

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.     

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.