Economics of Grassland Conversion to Cropland in the Prairie Pothole Region

Abstract: Much of the remaining grassland, particularly in North America, is privately owned, and its conversion to cultivated cropland is largely driven by economics. An understanding of why landowners convert grassland to cropland could facilitate more effective design of grassland‐conservation programs. We built an empirical model of land‐use change in the Prairie Pothole Region (north‐central United States) to estimate the probability of grassland conversion to alternative agricultural land uses, including cultivated crops. Conversion was largely driven by landscape characteristics and the economic returns of alternative uses. Our estimate of the probability of grassland conversion to cultivated crops (1.33% on average from 1979 to 1997) was higher than past estimates (0.4%). Our model also predicted that grassland‐conversion probabilities will increase if agricultural commodity prices continue to follow the trends observed from 2001 to 2006 (0.93% probability of grassland conversion to cultivated crops in 2006 to 1.5% in 2011). Thus, nearly 121 million ha (30 million acres) of grassland could be converted by 2011. Conversion probabilities, however, are spatially heterogeneous (range 0.2% to 3%), depending on characteristics of a parcel (e.g., soil quality and economic returns). Grassland parcels with relatively high‐quality land for agricultural production are more likely to be converted to cultivated crops than lower‐quality parcels and are more responsive to changes in the economic returns on alternative agricultural land uses (i.e., conversion probability increases by a larger magnitude for high‐quality parcels when economics returns to alternative uses increase). Our results suggest that grassland conservation programs could be proactively targeted toward high‐risk parcels by anticipating changes in economic returns, such as could occur if a new biofuel processing plant were to be built in an area.     

Calculating Biologically Accurate Mitigation Credits: Insights from the California Tiger Salamander

Abstract:  Current conservation mitigation plans often fail to ensure full in-kind habitat replacement for endangered species, which suggests the need for improved methods for calculating mitigation credits. A simple, yet biologically meaningful method for calculating mitigation credits would be to let the number of mitigation credits assigned to a parcel of land scale with the reproductive value of the individuals occupying that parcel. This can be accomplished by dividing the population into 2 or more subdivisions with different reproductive values, calculating the densities of these subdivisions as a function of one or more habitat parameters, and then forming a weighted sum of these densities such that each density distribution is weighted by the reproductive value of its respective subdivision of the population. This weighted sum is the density distribution of reproductive value, and by integrating it over a particular parcel, one can determine the mitigation value of that parcel. We carried out this procedure for a population of California tiger salamanders ( Ambystoma californiense ), with distance from breeding site as our habitat parameter and the 3 visually identifiable age classes (adults, juveniles, and metamorphs) as our population subdivisions. This led to a density distribution of reproductive value that decreased exponentially with increasing distance from a breeding site. Mitigation strategies derived from this function will be more likely to ensure the persistence of California tiger salamander populations than current approaches, which assign all land within 1.6 km of a breeding site the same mitigation value. Use of the density distribution of reproductive value as a basis for mitigation plans is a procedure that can be applied to all endangered species, and it should improve the quality of mitigation decisions.     

Cattle Grazing Mediates Climate Change Impacts on Ephemeral Wetlands

Abstract:  Climate change impacts depend in large part on land-management decisions; interactions between global changes and local resource management, however, rarely have been quantified. We used a combination of experimental manipulations and simulation modeling to investigate the effects of interactions between cattle grazing and regional climate change on vernal pool communities. Data from a grazing exclosure study indicated that 3 years after the removal of grazing, ungrazed vernal pools dried an average of 50 days per year earlier than grazed control pools. Modeling showed that regional climate change could also alter vernal pool hydrology. Increased temperatures and winter precipitation were predicted to increase periods of inundation. We evaluated the ecological implications of interactions between grazing and climate change for branchiopods and the California tiger salamander (  Ambystoma californiense ) at four sites spanning a latitudinal climate gradient. Grazing played an important role in maintaining the suitability of vernal pool hydrological conditions for fairy shrimp and salamander reproduction. The ecological importance of the interaction varied nonlinearly across the region. Our results show that grazing can confound hydrologic changes driven by climate change and play a critical role in maintaining the hydrologic suitability of vernal pools for endangered aquatic invertebrates and amphibians. These observations suggest an important limitation of impact assessments of climate change based on experiments in unmanaged ecosystems. The biophysical impacts of land management may be critical for understanding the vulnerability of ecological systems to climate change.     

Incorporating Climate Science in Applications of the U.S. Endangered Species Act for Aquatic Species

Aquatic species are threatened by climate change but have received comparatively less attention than terrestrial species. We gleaned key strategies for scientists and managers seeking to address climate change in aquatic conservation planning from the literature and existing knowledge. We address 3 categories of conservation effort that rely on scientific analysis and have particular application under the U.S. Endangered Species Act (ESA): assessment of overall risk to a species; long‐term recovery planning; and evaluation of effects of specific actions or perturbations. Fewer data are available for aquatic species to support these analyses, and climate effects on aquatic systems are poorly characterized. Thus, we recommend scientists conducting analyses supporting ESA decisions develop a conceptual model that links climate, habitat, ecosystem, and species response to changing conditions and use this model to organize analyses and future research. We recommend that current climate conditions are not appropriate for projections used in ESA analyses and that long‐term projections of climate‐change effects provide temporal context as a species‐wide assessment provides spatial context. In these projections, climate change should not be discounted solely because the magnitude of projected change at a particular time is uncertain when directionality of climate change is clear. Identifying likely future habitat at the species scale will indicate key refuges and potential range shifts. However, the risks and benefits associated with errors in modeling future habitat are not equivalent. The ESA offers mechanisms for increasing the overall resilience and resistance of species to climate changes, including establishing recovery goals requiring increased genetic and phenotypic diversity, specifying critical habitat in areas not currently occupied but likely to become important, and using adaptive management. Incorporación de las Ciencias Climáticas en las Aplicaciones del Acta Estadunidense de Especies en Peligro para Especies Acuáticas     

Development of Macroinvertebrate-Based Index for Bioassessment of Idaho Rivers

Theoretical constructs, such as the river continuum concept, predict that the composition of benthic fauna in rivers will be different from that of headwater streams. There exists a need to modify, for use on larger rivers, the bioassessment techniques commonly used on small streams. Using aquatic macroinvertebrates and the “reference condition” approach, we developed and tested a multimetric index for use on the rivers of Idaho. Reference sites were selected to represent the best current conditions (i.e., least impacted) among Idaho rivers. The index performed well in distinguishing reference sites from sites displaying some form of anthropogenic impairment. Individual metrics used in the index included: number of EPT taxa, total number of taxa, percent dominant taxon, percent Elmidae, and percent predators. The index we developed for Idaho rivers was essentially a modification of a framework designed for small streams, suggesting that techniques, including data analysis, currently used for streams can be adapted for use on larger rivers. Adapting these methods for use in rivers is primarily a matter of (1) selecting metrics relevant to the rivers of interest; (2) expanding the field sampling to encompass the greater habitat area and, potentially, heterogeneity of rivers; and (3) selecting an appropriate form of data analysis. The approach we describe here should be applicable to geographic regions other than Idaho.     

Thought self-leadership: the impact of mental strategies training on employee cognition,behavior, and affect

Thought self-leadership involves employee self-influence through cognitive strategies that focus on individual self-dialogue, mental imagery, beliefs and assumptions, and thought patterns. A training intervention-based field study with a control group was undertaken to empirically examine the applicability of thought self-leadership in an organizational setting (of bankruptcy financial status), and the potential for cognitions to be self-controlled. Results suggested that individuals who received the thought self-leadership training experienced increased mental performance, positive affect (enthusiasm), job satisfaction, and decreased negative affect (nervousness) relative to those not receiving the training. Additionally, the trainees reported a strong and positive reaction to the training. Finally, those who received the training experienced enhanced perceptions of self-efficacy and more optimistic perceptions of the organization's bankruptcy condition than those not receiving the training.     

Human Impacts on Regional Avian Diversity and Abundance

Abstract: Patterns of association between humans and biodiversity typically show positive, negative, or negative quadratic relationships and can be described by 3 hypotheses: biologically rich areas that support high human population densities co‐occur with areas of high biodiversity (productivity); biodiversity decreases monotonically with increasing human activities (ecosystem stress); and biodiversity peaks at intermediate levels of human influence (intermediate disturbance). To test these hypotheses, we compared anthropogenic land cover and housing units, as indices of human influence, with bird species richness and abundance across the Midwestern United States. We modeled richness of native birds with 12 candidate models of land cover and housing to evaluate the empirical evidence. To assess which species were responsible for observed variation in richness, we repeated our model‐selection analysis with relative abundance of each native species as the response and then asked whether natural‐history traits were associated with positive, negative, or mixed responses. Native avian richness was highest where anthropogenic land cover was lowest and housing units were intermediate based on model‐averaged predictions among a confidence set of candidate models. Eighty‐three of 132 species showed some pattern of association with our measures of human influence. Of these species approximately 40% were negatively associated, approximately 6% were positively associated, and approximately 7% showed evidence of an intermediate relationship with human influence measures. Natural‐history traits were not closely related to the direction of the relationship between abundance and human influence. Nevertheless, pooling species that exhibited any relationship with human influence and comparing them with unrelated species indicated they were significantly smaller, nested closer to the ground, had shorter incubation and fledging times, and tended to be altricial. Our results support the ecosystem‐stress hypothesis for the majority of individual species and for overall species diversity when focusing on anthropogenic land cover. Nevertheless, the great variability in housing units across the land‐cover gradient indicates that an intermediate‐disturbance relationship is also supported. Our findings suggest preemptive conservation action should be taken, whereby areas with little anthropogenic land cover are given conservation priority. Nevertheless, conservation action should not be limited to pristine landscapes because our results showed that native avian richness and the relative abundance of many species peaked at intermediate housing densities and levels of anthropogenic land cover.     

Linking Indices for Biodiversity Monitoring to Extinction Risk Theory

Biodiversity indices often combine data from different species when used in monitoring programs. Heuristic properties can suggest preferred indices, but we lack objective ways to discriminate between indices with similar heuristics. Biodiversity indices can be evaluated by determining how well they reflect management objectives that a monitoring program aims to support. For example, the Convention on Biological Diversity requires reporting about extinction rates, so simple indices that reflect extinction risk would be valuable. We developed 3 biodiversity indices that are based on simple models of population viability that relate extinction risk to abundance. We based the first index on the geometric mean abundance of species and the second on a more general power mean. In a third index, we integrated the geometric mean abundance and trend. These indices require the same data as previous indices, but they also relate directly to extinction risk. Field data for butterflies and woodland plants and experimental studies of protozoan communities show that the indices correlate with local extinction rates. Applying the index based on the geometric mean to global data on changes in avian abundance suggested that the average extinction probability of birds has increased approximately 1% from 1970 to 2009. Conectando Índices para el Monitoreo de la Biodiversidad con la Teoría de Riesgo de Extinción