Further Development of a Specific Conductivity Approach to Measure Groundwater Discharge Area within Lakes

Groundwater exchanges with most lakes are rarely quantified because there are many technical challenges to quantification. We investigated a lakebed mapping approach to infer the relative areas of groundwater exchange in 12 prairie shallow lakes and five Laurentian mixed forest shallow lakes in Minnesota, USA in 2011. We used a relatively common approach (seepage meters) to provide baseline information on the magnitude and direction of flow at four locations in each lake. To expand from point measurements to the whole‐lake scale, we explored use of specific conductivity as a cheaper and more time efficient proxy for groundwater discharge to lakes. We validated the approach at near shore stations in each lake where seepage meter measurements and specific conductivity surveys overlapped. Specific conductivity surveys provided a similar assessment of groundwater discharge compared to seepage meters for 50% of the lake‐sampling period combinations. The lakebed mapping approach, when validated for a lake with a limited number of seepage meter (or alternative methods) measurements, offers the advantages of being more time and labor efficient over the use of a similar number of seepage meter monitoring locations; seepage meters (or piezometers, for example) are costlier in terms of equipment and labor, even for single‐lake studies. We show the combined approach could provide useful baselines for understanding and mapping groundwater exchange in shallow lakes.     

Framework for improved confidence in modeled nitrous oxide estimates for biofuel regulatory standards

Biofuels vary greatly in their carbon intensity, depending on the specifics of how they are produced. Policy frameworks are needed to ensure that biofuels actually achieve intended reductions in greenhouse gas emissions. Current approaches do not account for important variables during cultivation that influence emissions. Estimating emissions based on biogeochemical models would allow accounting of farm-specific conditions, which in turn provides an incentive for producers to adopt low emissions practices. However, there are substantial uncertainties in the application of biogeochemical models. This paper proposes a policy framework that manages this uncertainty while retaining the ability of the models to account for (and hence incentivize) low emissions practices. The proposed framework is demonstrated on nitrous oxide (N₂O) emissions from the cultivation of winter barley. The framework aggregates uncertainties over time, which (1) avoids penalizing producers for uncertainty in weather, (2) allows for a high degree of confidence in the emissions reductions achieved, and (3) attenuates the uncertainty penalties borne by producers within a timescale of several years. Results indicate that with effective management, N₂O emissions from feedstock cultivation may be <?5% of the carbon intensity of gasoline, whereas the existing policy approach estimates emissions >?20% of the carbon intensity of gasoline. If these emissions reductions are monetized, the framework can provide up to $0.002 per liter credits (0.8 cents per gallon) to fuel producers, which could incentivize emissions mitigation practices by biofuel feedstock suppliers, such as avoiding fall N application on silty clay loam soils. The conservatism in the current approach fails to incentivize the adoption of biofuels, while the lack of specificity fails to incentivize site-level mitigation practices. Improved uncertainty accounting and consideration of farm-level practices will incentivize mitigation efforts at landscape to global scales.     

“I feel your pain”: A critical review of organizational research on empathy

Empathy, a multidimensional construct comprised of cognitive, affective, and behavioral dimensions, has been advanced as a critical predictor of prosocial behavior and effectiveness in the workplace. However, despite organizational interest in empathy, there is a lack of consensus on what empathy is, how empathy should be measured, and how empathy research can meaningfully contribute to our understanding of organizational behavior. This paper aims to provide a roadmap for researchers and practitioners interested in empathy in the workplace. We first provide an updated overview of the state of the broader multidisciplinary literature on empathy. On the basis of this literature, we outline the three dimensions of empathy, discuss the distinctions between state/trait and observer/judged empathy, and compare empathy with related constructs. This integrated multidimensional conceptualization provides the basis for our critical review and recommendations. We review the organizational research on empathy (1983–2018), identifying critical issues with how empathy has been conceptualized, measured, and designed, and offer practical recommendations for the advancement of organizational research on empathy. We conclude by highlighting two fundamental questions: (a) is empathy associated with important outcomes of interest to organizations and employees, and (b) can empathy be changed, and if so, how?     

Conservation implications of density-dependent predation by ghost crabs on hatchling sea turtles running the gauntlet to the sea

Protecting eggs from predators is common practice in sea turtle conservation, but routine protection of hatchlings is not. Of 42 loggerhead hatchlings observed emerging from 10 nests on undeveloped Onslow Beach, North Carolina, 24 % were preyed on by ghost crabs. In experimental trials, ghost crabs similarly threatened and captured neonate freshwater sliders, supporting their substitution as proxy for threatened and endangered sea turtle hatchlings in field experiments testing density dependence. Exploiting natural long-shore variation in ghost crab density, we show that a 2.6-fold higher ghost crab density resulted in 5 times more nocturnal threat encounters with sliders and 3.4 times more slider captures. Sliders released in simulated group emergences experienced lower per capita capture risk by ghost crabs than solitary sliders, implying predator dilution. Non-independence of egg and hatchling depredation motivates consideration of merging sea turtle egg and hatchling stages when modeling and managing food web interactions.     

Cross-combined composite sampling designs for identification of elevated regions

Analyzing soils for contaminants can be costly. Generally, discrete samples are gathered from within a study area, analyzed by a laboratory and the results are used in a site-specific statistical analysis. Because of the heterogeneities that exist in soil samples within study areas, a large amount of variability and skewness may be present in the sample population. This necessitates collecting a large number of samples to obtain reliable inference on the mean contaminant concentration and to understand the spatial patterns for future remediation. Composite, or Incremental, sampling is a commonly applied method for gathering multiple discrete samples and physically combining them, such that each combination of discrete samples requires a single laboratory analysis, which reduces cost and can improve the estimates of the mean concentration. While incremental sampling can reduce cost and improve mean estimates, current implementations do not readily facilitate the characterization of spatial patterns or the detection of elevated constituent regions within study areas. The methods we present in this work provide efficient estimation and inference for the mean contaminant concentration over the entire spatial area and enable the identification of high contaminant regions within the area of interest. We develop sample design methodologies that explicitly define the characteristics of these designs (such as sample grid layout) and quantify the number of incremental samples that must be obtained under a design criteria to control false positive and false negative (Type I and II) decision errors. We present the sample design theory and specifications as well as results on simulated and real data.     

Four priorities for new links between conservation science and accounting research

Article impact statement: New collaborations with accounting research can improve conservation impact of ecosystem-based information systems.     

Practical actions for applied systematic conservation planning

Systematic conservation planning is intended to inform spatially explicit decision making. Doing so requires that it be integrated into complex regulatory and governance processes, and there are limited instances where this has been achieved effectively. South Africa is a global leader in the application of conservation plans, the outputs of which are widely used for spatial planning and decision making in many spheres of government. We aimed to determine how conservation planning in the country progressed from theory to implementation, and to identify practical actions that enabled this transition, by assessing temporal trends in the characteristics of conservation plans (1990–2017, n = 94). Since 2010 conservation planning has entered an operational period characterized by government leadership of plans, administrative rather than ecological planning domains, decreasing size of planning units, increasing emphasis on end-user products, and scheduled revision of plans. Key actions that enabled this progression include transitioning leadership of plans from scientists to practitioners, building capacity within implementing agencies, creating opportunities to integrate plans in legislative processes, establishing a strong community of practice, adopting implementation-focused methods, and balancing standardization with innovation. Learning from this model will allow other countries, particularly those with a similar megadiverse, developing context, to operationalize conservation planning into spatial planning and decision making.