Characteristics that make trophy hunting of giant pandas inconceivable

In November 1928, Theodore Jr. and Kermit Roosevelt led an expedition to China with the expressed purpose of being the first Westerners to kill the giant panda (Ailuropoda melanoleuca). The expedition lasted 8 months and resulted in the brothers shooting a giant panda in the mountains of Sichuan Province. Given the concurrent attention in the popular press describing this celebrated expedition, the giant panda was poised to be trophy hunted much like other large mammals around the world. Today, however, the killing of giant pandas, even for the generation of conservation revenue, is unthinkable for reasons related to the species itself and the context, in time and space, in which the species was popularized in the West. We found that the giant panda's status as a conservation symbol, exceptional charisma and gentle disposition, rarity, value as a nonconsumptive ecotourism attraction, and endemism are integral to the explanation of why the species is not trophy hunted. We compared these intrinsic and extrinsic characteristics with 20 of the most common trophy-hunted mammals to determine whether the principles applying to giant pandas are generalizable to other species. Although certain characteristics of the 20 trophy-hunted mammals aligned with the giant panda, many did not. Charisma, economic value, and endemism, in particular, were comparatively unique to the giant panda. Our analysis suggests that, at present, exceptional characteristics may be necessary for certain mammals to be excepted from trophy hunting. However, because discourse relating to the role of trophy hunting in supporting conservation outcomes is dynamic in both science and society, we suspect these valuations will also change in future.     

The socio-economic vulnerability of the Australian east coast grazing sector to the impacts of climate change

Regional Environmental Change - Research that projects biophysical changes under climate change is more advanced than research that projects socio-economic changes. There is a need in adaptation...     

Fishing‐gear restrictions and biomass gains for coral reef fishes in marine protected areas

Considerable empirical evidence supports recovery of reef fish populations with fishery closures. In countries where full exclusion of people from fishing may be perceived as inequitable, fishing‐gear restrictions on nonselective and destructive gears may offer socially relevant management alternatives to build recovery of fish biomass. Even so, few researchers have statistically compared the responses of tropical reef fisheries to alternative management strategies. We tested for the effects of fishery closures and fishing gear restrictions on tropical reef fish biomass at the community and family level. We conducted 1,396 underwater surveys at 617 unique sites across a spatial hierarchy within 22 global marine ecoregions that represented 5 realms. We compared total biomass across local fish assemblages and among 20 families of reef fishes inside marine protected areas (MPAs) with different fishing restrictions: no‐take, hook‐and‐line fishing only, several fishing gears allowed, and sites open to all fishing gears. We included a further category representing remote sites, where fishing pressure is low. As expected, full fishery closures, (i.e., no‐take zones) most benefited community‐ and family‐level fish biomass in comparison with restrictions on fishing gears and openly fished sites. Although biomass responses to fishery closures were highly variable across families, some fishery targets (e.g., Carcharhinidae and Lutjanidae) responded positively to multiple restrictions on fishing gears (i.e., where gears other than hook and line were not permitted). Remoteness also positively affected the response of community‐level fish biomass and many fish families. Our findings provide strong support for the role of fishing restrictions in building recovery of fish biomass and indicate important interactions among fishing‐gear types that affect biomass of a diverse set of reef fish families.     

Deriving fuel-based emission factor thresholds to interpret heavy-duty vehicle roadside plume measurements

Remote sensing devices have been used for decades to measure gaseous emissions from individual vehicles at the roadside. Systems have also been developed that entrain diluted exhaust and can also measure particulate matter (PM) emissions. In 2015, the California Air Resources Board (CARB) reported that 8% of in-field diesel particulate filters (DPF) on heavy-duty (HD) vehicles were malfunctioning and emitted about 70% of total diesel PM emissions from the DPF-equipped fleet. A new high-emitter problem in the heavy-duty vehicle fleet had emerged. Roadside exhaust plume measurements reflect a snapshot of real-world operation, typically lasting several seconds. In order to relate roadside plume measurements to laboratory emission tests, we analyzed carbon dioxide (CO₂), oxides of nitrogen (NO_X), and PM emissions collected from four HD vehicles during several driving cycles on a chassis dynamometer. We examined the fuel-based emission factors corresponding to possible exceedances of emission standards as a function of vehicle power. Our analysis suggests that a typical HD vehicle will exceed the model year (MY) 2010 emission standards (of 0.2 g NO_X/bhp-hr and 0.01 g PM/bhp-hr) by three times when fuel-based emission factors are 9.3 g NO_X/kg fuel and 0.11 g PM/kg using the roadside plume measurement approach. Reported limits correspond to 99% confidence levels, which were calculated using the detection uncertainty of emissions analyzers, accuracy of vehicle power calculations, and actual emissions variability of fixed operational parameters. The PM threshold was determined for acceleration events between 0.47 and 1.4 mph/sec only, and the NO_X threshold was derived from measurements where after-treatment temperature was above 200°C. Anticipating a growing interest in real-world driving emissions, widespread implementation of roadside exhaust plume measurements as a compliment to in-use vehicle programs may benefit from expanding this analysis to a larger sample of in-use HD vehicles.

Implications: Regulatory agencies, civil society, and the public at large have a growing interest in vehicle emission compliance in the real world. Leveraging roadside plume measurements to identify vehicles with malfunctioning emission control systems is emerging as a viable new and useful method to assess in-use performance. This work proposes fuel-based emission factor thresholds for PM and NOx that signify exceedances of emission standards on a work-specific basis by analyzing real-time emissions in the laboratory. These thresholds could be used to prescreen vehicles before roadside enforcement inspection or other inquiry, enhance and further develop emission inventories, and potentially develop new requirements for heavy-duty inspection and maintenance (I/M) programs, including but not limited to identifying vehicles for further testing.     

An assessment of safety climate,job satisfaction and turnover intention relationships using a national sample of workers from the USA

The association between safety climate, job satisfaction and turnover intention has not been thoroughly researched. This research is needed so that safety researchers and practitioners can begin to delineate the impact of safety on organizational and business outcomes. A path analysis was completed using data from a national sample of workers from the USA (n?=?1525). The overall fit of the model was excellent and analyses determined that both training and resource adequacy positively affected safety climate and job satisfaction. Safety climate also positively influenced job satisfaction. Both safety climate and job satisfaction were negatively associated with respondents’ turnover intention. In the study, the relationship between job satisfaction and turnover intention is reiterated in a sample of workers across many industries. This study is novel because it is one of the first studies to confirm that turnover intention is reduced with increased safety climate in a diverse sample of workers.     

Processing and Morphology Impacts on Mechanical Properties of Fungal Based Biopolymer Composites

Fungal based biopolymer matrix composites with lignocellulosic agricultural waste as the filler are a viable alternative for some applications of synthetic polymers. This research provides insight into the impact of the processing method and composition of agriwaste/fungal biopolymer composites on structure and mechanical properties. The impact of nutrition during inoculation and after a homogenization step on the three-point bend flexural modulus and strength was determined. Increasing supplemental nutrition at inoculation had little effect on the overall composite strength or modulus; however, increasing carbohydrate loading after a homogenization step increased flexural stress at yield and bulk flexural modulus. The contiguity of the network formed was notably higher in the latter scenario, suggesting that the increase in modulus and strength of the final composite after homogenization was the result of contiguous hyphal network formation, which improves the integrity of the matrix and the ability to transfer load to the filler particles.     

Comparison and Evaluation of Gridded Precipitation Datasets in a Kansas Agricultural Watershed Using SWAT

Gridded precipitation datasets are becoming a convenient substitute for gauge measurements in hydrological modeling; however, these data have not been fully evaluated across a range of conditions. We compared four gridded datasets (Daily Surface Weather and Climatological Summaries [DAYMET], North American Land Data Assimilation System [NLDAS], Global Land Data Assimilation System [GLDAS], and Parameter‐elevation Regressions on Independent Slopes Model [PRISM]) as precipitation data sources and evaluated how they affected hydrologic model performance when compared with a gauged dataset, Global Historical Climatology Network‐Daily (GHCN‐D). Analyses were performed for the Delaware Watershed at Perry Lake in eastern Kansas. Precipitation indices for DAYMET and PRISM precipitation closely matched GHCN‐D, whereas NLDAS and GLDAS showed weaker correlations. We also used these precipitation data as input to the Soil and Water Assessment Tool (SWAT) model that confirmed similar trends in streamflow simulation. For stations with complete data, GHCN‐D based SWAT‐simulated streamflow variability better than gridded precipitation data. During low flow periods we found PRISM performed better, whereas both DAYMET and NLDAS performed better in high flow years. Our results demonstrate that combining gridded precipitation sources with gauge‐based measurements can improve hydrologic model performance, especially for extreme events.     

Global and regional potential for bioenergy from agricultural and forestry residue biomass

As co-products, agricultural and forestry residues represent a potential low cost, low carbon, source for bioenergy. A method is developed for estimating the maximum sustainable amount of energy potentially available from agricultural and forestry residues by converting crop production statistics into associated residue, while allocating some of this resource to remain on the field to mitigate erosion and maintain soil nutrients. Currently, we estimate that the world produces residue biomass that could be sustainably harvested and converted into nearly 50 EJ yr⁻¹ of energy. The top three countries where this resource is estimated to be most abundant are currently net energy importers: China, the United States (US), and India. The global potential from residue biomass is estimated to increase to approximately 50–100 EJ yr⁻¹ by mid- to late- century, depending on physical assumptions such as of future crop yields and the amount of residue sustainably harvestable. The future market for biomass residues was simulated using the Object-Oriented Energy, Climate, and Technology Systems Mini Climate Assessment Model (O^bjECTS MiniCAM). Utilization of residue biomass as an energy source is projected for the next century under different climate policy scenarios. Total global use of residue biomass is estimated to be 20–100 EJ yr⁻¹ by mid- to late- century, depending on the presence of a climate policy and the economics of harvesting, aggregating, and transporting residue. Much of this potential is in developing regions of the world, including China, Latin America, Southeast Asia, and India.     

Enhanced science–stakeholder communication to improve ecosystem model performances for climate change impact assessments

In recent years, climate impact assessments of relevance to the agricultural and forestry sectors have received considerable attention. Current ecosystem models commonly capture the effect of a warmer climate on biomass production, but they rarely sufficiently capture potential losses caused by pests, pathogens and extreme weather events. In addition, alternative management regimes may not be integrated in the models. A way to improve the quality of climate impact assessments is to increase the science–stakeholder collaboration, and in a two-way dialog link empirical experience and impact modelling with policy and strategies for sustainable management. In this paper we give a brief overview of different ecosystem modelling methods, discuss how to include ecological and management aspects, and highlight the importance of science–stakeholder communication. By this, we hope to stimulate a discussion among the science–stakeholder communities on how to quantify the potential for climate change adaptation by improving the realism in the models.     

Use of Predictive Weather Uncertainties in an Irrigation Scheduling Tool Part II: An Application of Metrics and Adjoints

We apply predictive weather metrics and land model sensitivities to improve the Colorado State University Water Irrigation Scheduler for Efficient Application (WISE). WISE is an irrigation decision aid that integrates environmental and user information for optimizing water use. Rainfall forecasts and verification performance metrics are used to estimate predictive rainfall probabilities that are used as input data within the irrigation decision aid. These input data errors are also used within a land model sensitivity study to diagnose important prognostic water movement behaviors for irrigation tool development purposes simultaneously performing the analysis in space and time. Thus, important questions such as “how long can a crop water application be delayed while maintaining crop yield production?” are addressed by evaluating crop growth stage interactions as a function of soil depth (i.e., space), rainfall events (i.e., time), and their probabilistic uncertainties. Editor’s note : This paper is part of the featured series on Optimizing Ogallala Aquifer Water Use to Sustain Food Systems. See the February 2019 issue for the introduction and background to the series.