Predicting Offenses and Crashes from Young Drivers' Offense and Crash Histories

Previous research has indicated that offenses are better predictors of subsequent crashes than crashes themselves. We examined this hypothesis for 13,800 young beginning drivers in Michigan for up to nine years during the initial years of driving. Our analyses indicated that previous-year offenses are better predictors of both subsequent-year offenses and crashes than either previous-year crashes or at-fault crashes. This finding also held for the apparently higher-risk subset of subsequent-year serious offenses and at-fault crashes. Although there were no gender differences in the predictive power of crashes, it was found that the predictive power of previous offenses to subsequent serious offenses was significantly stronger for women than for men. The predictive power of incidents appeared to increase somewhat with increasing driving experience, suggesting that early incidents may be more attributable to inexperience, a characteristic of all beginning drivers, while later incidents may be more attributable to individual differences.     

Relationships between Sensitivity to Agricultural Intensification and Ecological Traits of Insectivorous Mammals and Arthropods

Abstract: We tested the hypothesis that variation in the sensitivity of animals to habitat change is explained by ecological traits (life‐history traits, trophic level, and mobility). We measured the sensitivity of insectivorous mammals (shrews and bats) and their prey (arthropods active at the soil surface and nocturnal aerial arthropods) to three aspects of agricultural intensification in a matched‐pair experimental design: increased use of agrochemicals (comparison of organic and conventional cereal crops, with pairing for the size of the boundary hedge), change in grassland management from hay to silage (with pairing for the size of the boundary hedge), and increased field size due to hedgerow loss (with boundary‐field comparisons as a proxy). We assessed the sensitivity of taxa as the difference in their relative abundance between pairs of high‐ and low‐intensity sites for each aspect of agricultural intensification. We used phylogenetically informed analyses to explore cross‐species relationships between our measures of sensitivity and seven ecological traits of animals (e.g., trophic level, mobility, and reproductive rate). Several traits were related to the sensitivity of animals to agricultural intensification. These traits were mainly associated with fast life histories (high reproductive output and low trophic level) and low mobility. Trophic level of adults was related to sensitivity to habitat change for all three aspects of agricultural intensification, but the direction of the relationship differed between the three aspects of intensification. The significance of the relationship between other ecological traits and sensitivity to intensification varied for the three aspects of agricultural intensification. Our results show that some ecological traits can be used to preselect taxa that are predicted to be sensitive to habitat change, and their sensitivity can be tested empirically for use as biotic indicator taxa. Understanding which traits are related to sensitivity to habitat change is vital because sensitivity is important in determining a taxon's ability to survive in dynamic environments.     

Physiological and Morphological Response Patterns of <Emphasis Type="Italic">Populus deltoides</Emphasis> to Alluvial Groundwater Pumping

We examined the physiological and morphological response patterns of plains cottonwood [Populus deltoides subsp. monilifera (Aiton) Eck.] to acute water stress imposed by groundwater pumping. Between 3 and 27 July 1996, four large pumps were used to withdraw alluvial groundwater from a cottonwood forest along the South Platte River, near Denver, Colorado, USA. The study was designed as a stand-level, split-plot experiment with factorial treatments including two soil types (a gravel soil and a loam topsoil over gravel), two water table drawdown depths (∼0.5 m and >1.0 m), and one water table control (no drawdown) per soil type. Measurements of water table depth, soil water potential (Ψ_s), predawn and midday shoot water potential (Ψ_pd and Ψ_md), and D/H (deuterium/hydrogen) ratios of different water sources were made in each of six 600-m² plots prior to, during, and immediately following pumping. Two additional plots were established and measured to examine the extent to which surface irrigation could be used to mitigate the effects of deep drawdown on P. deltoides for each soil type. Recovery of tree water status following pumping was evaluated by measuring stomatal conductance (g _s ) and xylem water potential (Ψ_xp) on approximately hourly time steps from before dawn to mid-afternoon on 11 August 1996 in watered and unwatered, deep-drawdown plots on gravel soils. P. deltoides responded to abrupt alluvial water table decline with decreased shoot water potential followed by leaf mortality. Ψ_pd and percent leaf loss were significantly related to the magnitude of water table declines. The onset and course of these responses were influenced by short-term variability in surface and ground water levels, acting in concert with physiological and morphological adjustments. Decreases in Ψ_pd corresponded with increases in Ψ_md, suggesting shoot water status improved in response to stomatal closure and crown dieback. Crown dieback caused by xylem cavitation likely occurred when Ψ_pd reached −0.4 to −0.8 MPa. The application of surface irrigation allowed trees to maintain favorable water status with little or no apparent cavitation, even in deep-drawdown plots. Two weeks after the partial canopy dieback and cessation of pumping, g _s and Ψ_xp measurements indicated that water stress persisted in unwatered P. deltoides in deep-drawdown plots.     

Practical Recommendations to Help Students Bridge the Research–Implementation Gap and Promote Conservation

Seasoned conservation researchers often struggle to bridge the research–implementation gap and promote the translation of their work into meaningful conservation actions. Graduate students face the same problems and must contend with obstacles such as limited opportunities for relevant interdisciplinary training and a lack of institutional support for application of research results. However, students also have a crucial set of opportunities (e.g., access to academic resources outside their degree programs and opportunities to design research projects promoting collaboration with stakeholders) at their disposal to address these problems. On the basis of results of breakout discussions at a symposium on the human dimensions of the ocean, a review of the literature, and our own experiences, we devised recommendations on how graduate students can create resources within their academic institutions, institutionalize resources, and engage with stakeholders to promote real‐world conservation outcomes. Within their academic institutions, graduate students should foster links to practitioners and promote knowledge and skill sharing among students. To institutionalize resources, students should cultivate student leaders and faculty sponsors, systematically document their program activities, and engage in strategic planning to promote the sustainability of their efforts. While conducting research, students should create connections to and engage actively with stakeholders in their relevant study areas and disseminate research results both to stakeholders and the broader public. Our recommendations can serve as a template for graduate students wishing to bridge the research–implementation gap, both during their current studies and in their future careers as conservation researchers and practitioners. Recomendaciones Prácticas para Ayudar a Estudiantes a Vencer la Brecha entre Investigación e Implementación y Promover la Conservación     

Site‐Occupancy Distribution Modeling to Correct Population‐Trend Estimates Derived from Opportunistic Observations

Abstract: Species’ assessments must frequently be derived from opportunistic observations made by volunteers (i.e., citizen scientists). Interpretation of the resulting data to estimate population trends is plagued with problems, including teasing apart genuine population trends from variations in observation effort. We devised a way to correct for annual variation in effort when estimating trends in occupancy (species distribution) from faunal or floral databases of opportunistic observations. First, for all surveyed sites, detection histories (i.e., strings of detection–nondetection records) are generated. Within‐season replicate surveys provide information on the detectability of an occupied site. Detectability directly represents observation effort; hence, estimating detectablity means correcting for observation effort. Second, site‐occupancy models are applied directly to the detection‐history data set (i.e., without aggregation by site and year) to estimate detectability and species distribution (occupancy, i.e., the true proportion of sites where a species occurs). Site‐occupancy models also provide unbiased estimators of components of distributional change (i.e., colonization and extinction rates). We illustrate our method with data from a large citizen‐science project in Switzerland in which field ornithologists record opportunistic observations. We analyzed data collected on four species: the widespread Kingfisher (Alcedo atthis) and Sparrowhawk (Accipiter nisus) and the scarce Rock Thrush (Monticola saxatilis) and Wallcreeper (Tichodroma muraria). Our method requires that all observed species are recorded. Detectability was <1 and varied over the years. Simulations suggested some robustness, but we advocate recording complete species lists (checklists), rather than recording individual records of single species. The representation of observation effort with its effect on detectability provides a solution to the problem of differences in effort encountered when extracting trend information from haphazard observations. We expect our method is widely applicable for global biodiversity monitoring and modeling of species distributions.     

Choosing and Using Climate‐Change Scenarios for Ecological‐Impact Assessments and Conservation Decisions

Increased concern over climate change is demonstrated by the many efforts to assess climate effects and develop adaptation strategies. Scientists, resource managers, and decision makers are increasingly expected to use climate information, but they struggle with its uncertainty. With the current proliferation of climate simulations and downscaling methods, scientifically credible strategies for selecting a subset for analysis and decision making are needed. Drawing on a rich literature in climate science and impact assessment and on experience working with natural resource scientists and decision makers, we devised guidelines for choosing climate‐change scenarios for ecological impact assessment that recognize irreducible uncertainty in climate projections and address common misconceptions about this uncertainty. This approach involves identifying primary local climate drivers by climate sensitivity of the biological system of interest; determining appropriate sources of information for future changes in those drivers; considering how well processes controlling local climate are spatially resolved; and selecting scenarios based on considering observed emission trends, relative importance of natural climate variability, and risk tolerance and time horizon of the associated decision. The most appropriate scenarios for a particular analysis will not necessarily be the most appropriate for another due to differences in local climate drivers, biophysical linkages to climate, decision characteristics, and how well a model simulates the climate parameters and processes of interest. Given these complexities, we recommend interaction among climate scientists, natural and physical scientists, and decision makers throughout the process of choosing and using climate‐change scenarios for ecological impact assessment. Selección y Uso de Escenarios de Cambio Climático para Estudios de Impacto Ecológico y Decisiones de Conservación     

Identifying and Managing Threatened Invertebrates through Assessment of Coextinction Risk

Abstract: Invertebrates with specific host species may have a high probability of extinction when their hosts have a high probability of extinction. Some of these invertebrates are more likely to go extinct than their hosts, and under some circumstances, specific actions to conserve the host may be detrimental to the invertebrate. A critical constraint to identifying such invertebrates is uncertainty about their level of host specificity. We used two host‐breadth models that explicitly incorporated uncertainty in the host specificity of an invertebrate species. We devised a decision protocol to identify actions that may increase the probability of persistence of a given dependent species. The protocol included estimates from the host‐breadth models and decision nodes to identify cothreatened species. We applied the models and protocol to data on 1055 insects (186 species) associated with 2 threatened (as designated by the Australian Government) plant species and 19 plant species that are not threatened to determine whether any insect herbivores have the potential to become extinct if the plant becomes extinct. According to the host‐breadth models, 18 species of insect had high host specificity to the threatened plant species. From these 18 insects, the decision protocol highlighted 6 species that had a high probability of extinction if their hosts were to become extinct (3% of all insects examined). The models and decision protocol have added objectivity and rigor to the process of deciding which dependent invertebrates require conservation action, particularly when dealing with largely unknown and speciose faunas.     

On Valuing Information in Adaptive‐Management Models

Abstract: Active adaptive management looks at the benefit of using strategies that may be suboptimal in the near term but may provide additional information that will facilitate better management in the future. In many adaptive‐management problems that have been studied, the optimal active and passive policies (accounting for learning when designing policies and designing policy on the basis of current best information, respectively) are very similar. This seems paradoxical; when faced with uncertainty about the best course of action, managers should spend very little effort on actively designing programs to learn about the system they are managing. We considered two possible reasons why active and passive adaptive solutions are often similar. First, the benefits of learning are often confined to the particular case study in the modeled scenario, whereas in reality information gained from local studies is often applied more broadly. Second, management objectives that incorporate the variance of an estimate may place greater emphasis on learning than more commonly used objectives that aim to maximize an expected value. We explored these issues in a case study of Merri Creek, Melbourne, Australia, in which the aim was to choose between two options for revegetation. We explicitly incorporated monitoring costs in the model. The value of the terminal rewards and the choice of objective both influenced the difference between active and passive adaptive solutions. Explicitly considering the cost of monitoring provided a different perspective on how the terminal reward and management objective affected learning. The states for which it was optimal to monitor did not always coincide with the states in which active and passive adaptive management differed. Our results emphasize that spending resources on monitoring is only optimal when the expected benefits of the options being considered are similar and when the pay‐off for learning about their benefits is large.