Participatory indicator development: what can ecologists and local communities learn from each other?

Given the growing popularity of indicators among policy-makers to measure progress toward conservation and sustainability goals, there is an urgent need to develop indicators that can be used accurately by both specialists and nonspecialists, drawing from the knowledge possessed by each group. This paper uses a case study from the Kalahari, Botswana to show how participatory and ecological methods can be combined to develop robust indicators that are accessible to a range of users to monitor and enhance the sustainability of land management. First, potential environmental sustainability indicators were elicited from pastoralists in three study sites. This knowledge was then evaluated by pastoralists, before being tested empirically using ecological and soil-based techniques. Despite the wealth of local knowledge about indicators, this knowledge was thinly spread. The knowledge was more holistic than published indicator lists for monitoring rangelands, encompassing vegetation, soil, livestock, wild animal, and socioeconomic indicators. Pastoralist preferences for vegetation and livestock indicators match recent shifts in ecological theory suggesting that livestock populations reach equilibrium with key forage resources in semiarid environments. Although most indicators suggested by pastoralists were validated through empirical work (e.g., decreased grass cover and soil organic matter content, and increased abundance of Acacia mellifera and thatching grass), they were not always sufficiently accurate or reliable for objective degradation assessment, showing that local knowledge cannot be accepted unquestioningly. We suggest that, by combining participatory and ecological approaches, it is possible to derive more accurate and relevant indicators than either approach could achieve alone.     

Displaced honey bees perform optimal scale-free search flights

Honey bees (Apis mellifera) are regularly faced with the task of navigating back to their hives from remote food sources. They have evolved several methods to do this, including compass-directed "vector" flights and the use of landmarks. If these hive-centered mechanisms are disrupted, bees revert to searching for the hive, but the nature and efficiency of their searching strategy have hitherto been unknown. We used harmonic radar to record the flight paths of honey bees that were searching for their hives. Our subsequent analysis of these paths revealed that they can be represented by a series of straight line segments that have a scale-free, Lévy distribution with an inverse-square-law tail. We show that these results, combined with the "no preferred direction" characteristic of the segments, demonstrate that the bees were flying an optimal search pattern. Lévy movements have already been identified in a number of other animals. Our results are the best reported example where the movements are mostly attributable to the adoption of an optimal, scale-free searching strategy.     

The effects of landscape structure on space competition and alternative stable states

Many species that compete for space live on heterogeneous landscapes and interact at local scales. The quality, amount, and structure of landscapes may have considerable impact on the ability of species to compete or coexist, yet basic models of space competition do not include that level of detail. We model space competition between two species with positive feedback through recruitment facilitation, which creates the potential for alternative stable states to occur. We compare the predictions of a spatially implicit model with a simulation model that includes explicit space and landscape structure. We create structured landscapes in which we specify the amount of habitat and degree of fragmentation and ask how landscape structure, dispersal strategy, and scale affect the presence of alternative stable states, or bistability. We find that structured landscapes can reduce the range of parameter values that lead to bistability in our model, but they do not eliminate bistability. The type of landscape and the dispersal distance for each species also influence the amount of environmental change needed for abrupt community shifts to occur. Coexistence of the two competitors is possible under certain conditions when connectivity is low. Consequently, landscape structure may lead to considerable disparity between the predictions of simple models and actual dynamics on complex landscapes during environmental change.     

Biodiversity consequences of alternative future land use scenarios in Greater Yellowstone.

Land use is rapidly expanding in the Greater Yellowstone Ecosystem, primarily from growth in the number of rural homes. There is a need to project possible future land use and assess impacts on nature reserves as a guide to future management. We assessed the potential biodiversity impacts of alternative future land use scenarios in the Greater Yellowstone Ecosystem. An existing regression-based simulation model was used to project three alternative scenarios of future rural home development. The spatial patterns of forecasted development were then compared to several biodiversity response variables that included cover types, species habitats, and biodiversity indices. We identified the four biodiversity responses most at risk of exurban development, designed growth management policies to protect these areas, and tested their effectiveness in two alternative future scenarios. We found that the measured biodiversity responses, including riparian habitat, elk winter range, migration corridors, and eight other land cover, habitat, and biodiversity indices, are likely to undergo substantial conversion (between 5% and 40%) to exurban development by 2020. Future habitat conversion to exurban development outside the region's nature reserves is likely to impact wildlife populations within the reserves. Existing growth management policies will provide minimal protection to biodiversity in this region. We identified specific growth management policies, including incentives to cluster future growth near towns, that can protect "at risk" habitat types without limiting overall growth in housing.     

A Multi‐Scale Soil Moisture Monitoring Strategy for California: Design and Validation

A multi‐scale soil moisture monitoring strategy for California was designed to inform water resource management. The proposed workflow classifies soil moisture response units (SMRUs) using publicly available datasets that represent soil, vegetation, climate, and hydrology variables, which control soil water storage. The SMRUs were classified, using principal component analysis and unsupervised K‐means clustering within a geographic information system, and validated, using summary statistics derived from measured soil moisture time series. Validation stations, located in the Sierra Nevada, include transect of sites that cross the rain‐to‐snow transition and a cluster of sites located at similar elevations in a snow‐dominated watershed. The SMRUs capture unique responses to varying climate conditions characterized by statistical measures of central tendency, dispersion, and extremes. A topographic position index and landform classification is the final step in the workflow to guide the optimal placement of soil moisture sensors at the local‐scale. The proposed workflow is highly flexible and can be implemented over a range of spatial scales and input datasets can be customized. Our approach captures a range of soil moisture responses to climate across California and can be used to design and optimize soil moisture monitoring strategies to support runoff forecasts for water supply management or to assess landscape conditions for forest and rangeland management.     

Risk Tradeoffs in Adaptive Ecosystem Management: The Case of the U.S. Forest Service

Natural resource planning processes on public lands in the United States are driven in large part by the requirements of the National Environmental Policy Act (NEPA), which dictates general processes for analyzing and disclosing the likely impacts of proposed actions. The outcomes of these processes are the result of multiple factors, many related to the manifold smaller incremental decisions made by agency personnel directing the processes. Through interviews with decision makers, team leaders, and team members on five NEPA processes within the U.S. Forest Service, this study examines those incremental decisions. Risk, in particular external relationship risk, emerged as a dominant lens through which agency personnel weigh and make process-related decisions. We discuss the tradeoffs associated with agency actors’ emphasis on this form of risk and their potential implications for adaptive ecosystem management and organizational performance.     

Importance of dispersal routes that minimize open‐ocean movement to the genetic structure of island populations

Islands present a unique scenario in conservation biology, offering refuge yet imposing limitations on insular populations. The Kimberley region of northwestern Australia has more than 2500 islands that have recently come into focus as substantial conservation resources. It is therefore of great interest for managers to understand the driving forces of genetic structure of species within these island archipelagos. We used the ubiquitous bar‐shouldered skink (Ctenotus inornatus) as a model species to represent the influence of landscape factors on genetic structure across the Kimberley islands. On 41 islands and 4 mainland locations in a remote area of Australia, we genotyped individuals across 18 nuclear (microsatellite) markers. Measures of genetic differentiation and diversity were used in two complementary analyses. We used circuit theory and Mantel tests to examine the influence of the landscape matrix on population connectivity and linear regression and model selection based on Akaike's information criterion to investigate landscape controls on genetic diversity. Genetic differentiation between islands was best predicted with circuit‐theory models that accounted for the large difference in resistance to dispersal between land and ocean. In contrast, straight‐line distances were unrelated to either resistance distances or genetic differentiation. Instead, connectivity was determined by island‐hopping routes that allow organisms to minimize the distance of difficult ocean passages. Island populations of C. inornatus retained varying degrees of genetic diversity (N_A = 1.83 – 7.39), but it was greatest on islands closer to the mainland, in terms of resistance‐distance units. In contrast, genetic diversity was unrelated to island size. Our results highlight the potential for islands to contribute to both theoretical and applied conservation, provide strong evidence of the driving forces of population structure within undisturbed landscapes, and identify the islands most valuable for conservation based on their contributions to gene flow and genetic diversity.