Bridge building within the province of proactivity

The research questions posed in this study highlight the importance of valuing proactivity in both prompting an individual to engage in proactive behavior and encouraging the expression of that behavior. We integrate a variety of constructs from the proactivity literature to gain a deeper understanding of proactive behavior as it relates to proactive motivation and supervisory performance evaluations. First, we draw upon self‐determination theory, expectancy–value theory, and the recent integration of the proactive motivation literature to hypothesize that proactive behavior is predicted by the interaction of “can do” and “reason to” proactive motivational states. Second, on the basis of performance theory, we hypothesize that the relationship between proactive behavior and performance depends upon the extent to which the supervisor values proactivity. Specifically, we argue that supervisors with proactive personalities are more likely to value and reward subordinate proactive behavior than passive supervisors. Results provide support for both of our hypotheses. Interestingly, results show that proactive behavior did not result in negative consequences but rather that there was a cost (i.e., lower performance rating) for not taking charge for employees with proactive supervisors. Copyright © 2012 John Wiley & Sons, Ltd.     

Cumulative carbon emissions and economic policy: In search of general principles

We exploit recent advances in climate science to develop a physically consistent, yet surprisingly simple, model of climate policy. It seems that key economic models have greatly overestimated the delay between carbon emissions and warming, and ignored the saturation of carbon sinks that takes place when the atmospheric concentration of carbon dioxide rises. This has important implications for climate policy. If carbon emissions are abated, damages are avoided almost immediately. Therefore it is optimal to reduce emissions significantly in the near term and bring about a slow transition to optimal peak warming, even if optimal steady-state/peak warming is high. The optimal carbon price should start relatively high and grow relatively fast.     

Temperature effects on mortality and household adaptation: Evidence from China

This paper examines the effects of extreme temperatures on mortality rates, using random year-to-year variation in temperature based on county-level panel data from China. The analysis finds a robust, U-shaped relationship between temperature and mortality rates, indicating that extremely cold or hot temperatures lead to excess deaths. The heat-related (cold-related) effect is 3.5 times (3.2 times) as large as previous findings that used U.S. data, and it is especially large for the elderly population, mainly due to excess deaths caused by cardiovascular diseases. Applying these results to climate change predictions from Hadley Centre Global Environmental Model shows that by 2061–2080 the annual mortality rate is likely to increase by 14.2% if global greenhouse gas emissions continue to rise throughout the 21st century, the estimated health cost of which is around 0.98 trillion Chinese Yuan per year. The paper also explores households’ adaptation behaviors to extreme temperatures. It finds that although urban households adaptively increase energy consumption when they are exposed to cold temperatures and purchase more air conditioners on hot and cold days, rural households are unresponsive to temperature fluctuations. This finding implies that rural people may be more resource constrained and suffer more when extreme temperatures occur.     

CEO education and corporate environmental footprint

We analyze the effect of CEO education on environmental decision-making. Using a unique sample of Danish firms from 1996 to 2012, we find that CEO education significantly improves firms' energy efficiency. We seek to derive causality using health shocks: the hospitalization of highly educated CEOs induces a drop in energy efficiency, whereas the hospitalization of less educated CEOs does not have any significant effect. Exploring the mechanisms at play, we show that our results are largely driven by advanced education in business degrees. Moreover, we show that CEO education is associated with greater environmental awareness: highly educated CEOs exhibit greater concerns for climate change, as measured by a survey of social preferences, and drive more environmentally efficient cars. Taken together, our findings suggest that education shapes managerial styles giving rise to greater sustainability in corporate actions.     

Temporal trends in agricultural water use and the relationships to hydroclimatic factors in the High Plains aquifer region

The High Plains aquifer (HPA) is the primary water source for agricultural irrigation in the US Great Plains. The water levels in many locations of the aquifer have declined steadily over the past several decades because the rate of water withdrawals exceeds recharge, which has been a serious concern to the water resources management in the region. We evaluated temporal trends and variations in agricultural water use and hydroclimatic variables including precipitation, air temperature, reference evapotranspiration, runoff, groundwater level, and terrestrial water storage across the HPA region for different periods from 1985 to 2020 at the grid, county, or region scale. The results showed that water withdrawals decreased from 21.3 km³/year in 1985 to 18.2 km³/year in 2015, while irrigated croplands increased from 71,928 km² in 1985 to 78,464 km² in 2015 in the entire HPA. The hydroclimatic time-series showed wetting trends in most of the northern HPA, but drying and warming trends in the southern region from 1985 to 2020. The groundwater level time-series indicated flat trends in the north, but significant declining in the central and southern HPA. Trends in irrigation water withdrawals and irrigation area across the HPA were controlled by the advancement of irrigation systems and technologies and the management of sustainable water use, but also were affected by dynamical changes in the hydroclimatic conditions.     

Systematic review of conservation interventions to promote voluntary behavior change

Understanding human behavior is vital to developing interventions that effectively lead to proenvironmental behavior change, whether the focus is at the individual or societal level. However, interventions in many fields have historically lacked robust forms of evaluation, which makes it hard to be confident that these conservation interventions have successfully helped protect the environment. We conducted a systematic review to assess how effective nonpecuniary and nonregulatory interventions have been in changing environmental behavior. We applied the Office of Health Assessment and Translation systematic review methodology. We started with more than 300,000 papers and reports returned by our search terms and after critical appraisal of quality identified 128 individual studies that merited inclusion in the review. We classified interventions by thematic area, type of intervention, the number of times audiences were exposed to interventions, and the length of time interventions ran. Most studies reported a positive effect (n = 96). The next most common outcome was no effect (n = 28). Few studies reported negative (n = 1) or mixed (n = 3) effects. Education, prompts, and feedback interventions resulted in positive behavior change. Combining multiple interventions was the most effective. Neither exposure duration nor frequency affected the likelihood of desired behavioral change. Comparatively few studies tested the effects of voluntary interventions on non-Western populations (n = 17) or measured actual ecological outcome behavior (n = 1). Similarly, few studies examined conservation devices (e.g., energy-efficient stoves) (n = 9) and demonstrations (e.g., modeling the desired behavior) (n = 5). There is a clear need to both improve the quality of the impact evaluation conducted and the reporting standards for intervention results.     

Learning and climate feedbacks: Optimal climate insurance and fat tails

We study the effect of potentially severe climate change on optimal climate change policy, accounting for learning and uncertainty in the climate system. In particular, we test how fat upper tailed uncertainty over the temperature change from a doubling of greenhouse gases (the climate sensitivity), affects economic growth and emissions policy. In addition, we examine whether and how fast uncertainties could be diminished through Bayesian learning. Our results indicate that while overall learning is slow, the mass of the fat tail diminishes quickly, since observations near the mean provide evidence against fat tails. We denote as “tail learning” the case where the planner rejects high values of the climate sensitivity with high confidence, even though significant uncertainty remains. Fat tailed uncertainty without learning reduces current emissions by 38% relative to certainty, indicating significant climate insurance, or paying to limit emissions today to reduce the risk of very high temperature changes, is optimal. However, learning reduces climate insurance by about 50%. The optimal abatement policy is strongly influenced by the current state of knowledge, even though greenhouse gas (GHG) emissions are difficult to reverse. Once the mass of the fat tail diminishes, the remaining uncertainty is largely irrelevant for optimal emissions policy.     

Using the past to contextualize anthropogenic impacts on the present and future distribution of an endemic Caribbean mammal

Island species are difficult to conserve because they face the synergy of climate change, invasive species, deforestation, and increasing human population densities in areas where land mass is shrinking. The Caribbean island of Hispaniola presents particular challenges because of geopolitical complexities that span 2 countries and hinder coordinated management of species across the island. We employed species distribution modeling to evaluate the impacts of climatic change and anthropogenic activities on the distribution of an endemic mammal of conservation concern, the Hispaniolan solenodon (Solenodon paradoxus). We aggregated occurrence points for this poorly known species for the Last Glacial Maximum (LGM) and the present (1975–2016) based on museum collections, online biodiversity databases, and new field surveys. We quantified degree of overlap between periods and scenarios with Schoener's D. Through a conservation paleobiology lens, we found that over time humans played an increasing role in shaping the distribution of S. paradoxus, thus, providing a foundation for developing conservation strategies on appropriate spatiotemporal scales. Human population density was the single most important predictor of S. paradoxus occurrence. Densities >166 people/km² corresponded to a near-zero probability of occurrence. Models that accounted for climate but not anthropogenic variables falsely identified suitable habitat in Haiti, where on-the-ground surveys confirm habitat is unavailable. Climate-only models also significantly overestimated the potential for habitat connectivity between isolated populations. Our work highlights that alternative fates for S. paradoxus in the Anthropocene exist across the political border between the Dominican Republic and Haiti due to the fundamentally different economic and political realities of each country. Relationships in the fossil record confirm that Hispaniola's sociopolitical boundary is not biologically significant but instead represents one imposed on the island's fauna in the past 500 years by colonial activity. Our approach reveals how a paleontological perspective can contribute to concrete management insights.     

Bridging the financial gap in climate adaptation: Dutch planning and land development through a new institutional lens

Based on a case study of the Stadshaven port redevelopment in Rotterdam, this paper explores whether existing spatial planning mechanisms and processes can be used to facilitate local-level investment in climate-resilient public infrastructure and/or whether new processes and mechanisms are required to encourage investment in climate adaptation. The study reveals several key findings. First, a lack of conventional funding sources or formalised regulatory framework allowed room for experimentation with existing mechanisms and flexible strategies. Second, project planners are currently ambivalent towards introducing new mechanisms as a means to overcome implementation challenges. The case provides evidence about the role of the governance process, not simply as a means of system coordination that exists in isolation from institutional norms and values, but rather as a space for innovation, which can contribute towards reducing the financial gap associated with climate adaptation.     

Incorporating putatively neutral and adaptive genomic data into marine conservation planning

The availability of genomic data for an increasing number of species makes it possible to incorporate evolutionary processes into conservation plans. Recent studies show how genetic data can inform spatial conservation prioritization (SCP), but they focus on metrics of diversity and distinctness derived primarily from neutral genetic data sets. Identifying adaptive genetic markers can provide important information regarding the capacity for populations to adapt to environmental change. Yet, the effect of including metrics based on adaptive genomic data into SCP in comparison to more widely used neutral genetic metrics has not been explored. We used existing genomic data on a commercially exploited species, the giant California sea cucumber (Parastichopus californicus), to perform SCP for the coastal region of British Columbia (BC), Canada. Using a RAD-seq data set for 717 P. californicus individuals across 24 sampling locations, we identified putatively adaptive (i.e., candidate) single nucleotide polymorphisms (SNPs) based on genotype–environment associations with seafloor temperature. We calculated various metrics for both neutral and candidate SNPs and compared SCP outcomes with independent metrics and combinations of metrics. Priority areas varied depending on whether neutral or candidate SNPs were used and on the specific metric used. For example, targeting sites with a high frequency of warm-temperature-associated alleles to support persistence under future warming prioritized areas in the southern coastal region. In contrast, targeting sites with high expected heterozygosity at candidate loci to support persistence under future environmental uncertainty prioritized areas in the north. When combining metrics, all scenarios generated intermediate solutions, protecting sites that span latitudinal and thermal gradients. Our results demonstrate that distinguishing between neutral and adaptive markers can affect conservation solutions and emphasize the importance of defining objectives when choosing among various genomic metrics for SCP.