Research priorities for managing the impacts and dependencies of business upon food,energy, water and the environment

Delivering access to sufficient food, energy and water resources to ensure human wellbeing is a major concern for governments worldwide. However, it is crucial to account for the ‘nexus’ of interactions between these natural resources and the consequent implications for human wellbeing. The private sector has a critical role in driving positive change towards more sustainable nexus management and could reap considerable benefits from collaboration with researchers to devise solutions to some of the foremost sustainability challenges of today. Yet opportunities are missed because the private sector is rarely involved in the formulation of deliverable research priorities. We convened senior research scientists and influential business leaders to collaboratively identify the top forty questions that, if answered, would best help companies understand and manage their food-energy-water-environment nexus dependencies and impacts. Codification of the top order nexus themes highlighted research priorities around development of pragmatic yet credible tools that allow businesses to incorporate nexus interactions into their decision-making; demonstration of the business case for more sustainable nexus management; identification of the most effective levers for behaviour change; and understanding incentives or circumstances that allow individuals and businesses to take a leadership stance. Greater investment in the complex but productive relations between the private sector and research community will create deeper and more meaningful collaboration and cooperation.     

全球鱼类消费

尽管继续有科学不确定性,但表明当前捕捞实践不可持续的证据与日俱增.在国家层次和国际层次上,人们越来越认真地对待关于过度捕捞及其对穷国食品保障的潜在威胁的告诫.近年来已经看到了一波改善渔业管理的协议.然而,无论在当地社区和传统可能处于危急之中的富国,还是在鱼类对于食品供应也具有根本重要性而且捕捞是沿海地区少数几种生活来源之一的穷国,对减少世界捕捞船队的规模都有强大阻力.     

The city as a refuge for insect pollinators

Research on urban insect pollinators is changing views on the biological value and ecological importance of cities. The abundance and diversity of native bee species in urban landscapes that are absent in nearby rural lands evidence the biological value and ecological importance of cities and have implications for biodiversity conservation. Lagging behind this revised image of the city are urban conservation programs that historically have invested in education and outreach rather than programs designed to achieve high‐priority species conservation results. We synthesized research on urban bee species diversity and abundance to determine how urban conservation could be repositioned to better align with new views on the ecological importance of urban landscapes. Due to insect pollinators’ relatively small functional requirements—habitat range, life cycle, and nesting behavior—relative to larger mammals, we argue that pollinators put high‐priority and high‐impact urban conservation within reach. In a rapidly urbanizing world, transforming how environmental managers view the city can improve citizen engagement and contribute to the development of more sustainable urbanization.     

DNA Heat Treatment for Improving qPCR Analysis of Human Adenovirus in Wastewater

PCR inhibitory substances in complex sample matrices can cause false negatives or under-estimation of target concentration. This study assessed DNA heat treatment for reducing inhibition during qPCR analysis of human adenovirus (HAdV) in wastewater samples. Inhibition was reduced by heat treating DNA, where mean HAdV concentration was increased by 0.71 log₁₀ GC/L (and up to 3.04 log₁₀ GC/L in one case), and replicate variability and false negatives were reduced. DNA heat treatment should be further investigated for improving reliability of HAdV concentration estimates in water, which can support more accurate assessment of health risks associated with viral pathogen exposure.     

A hierarchical Bayesian model for forecasting state-level corn yield

Historically, the National Agricultural Statistics Service crop forecasts and estimates have been determined by a group of commodity experts called the Agricultural Statistics Board (ASB). The corn yield forecasts for the “speculative region,” ten states that account for approximately 85 % of corn production, are based on two sets of monthly surveys, a farmer interview survey and a field measurement survey. The members of the ASB subjectively determine a forecast on the basis of a discussion of the survey data and auxiliary information about weather, average planting dates, and crop maturity. The ASB uses an iterative procedure, where initial state estimates are adjusted so that the weighted sum of the final state estimates is equal to a previously-determined estimate for the speculative region. Deficiencies of the highly subjective ASB process are lack of reproducibility and a measure of uncertainty. This paper describes the use of Bayesian methods to model the ASB process in a way that leads to objective forecasts and estimates of the corn yield. First, we use small area estimation techniques to obtain state-level forecasts. Second, we describe a way to adjust the state forecasts so that the weighted sum of the state forecasts is equal to a previously-determined regional forecast. We use several diagnostic techniques to assess the goodness of fit of various models and their competitors. We use Markov chain Monte Carlo methods to fit the models to both historic and current data from the two monthly surveys. Our results show that our methodology can provide reasonable and objective forecasts of corn yields for states in the speculative region.     

The data not collected on community forestry

Conservation and development practitioners increasingly promote community forestry as a way to conserve ecosystem services, consolidate resource rights, and reduce poverty. However, outcomes of community forestry have been mixed; many initiatives failed to achieve intended objectives. There is a rich literature on institutional arrangements of community forestry, but there has been little effort to examine the role of socioeconomic, market, and biophysical factors in shaping both land‐cover change dynamics and individual and collective livelihood outcomes. We systematically reviewed the peer‐reviewed literature on community forestry to examine and quantify existing knowledge gaps in the community‐forestry literature relative to these factors. In examining 697 cases of community forest management (CFM), extracted from 267 peer‐reviewed publications, we found 3 key trends that limit understanding of community forestry. First, we found substantial data gaps linking population dynamics, market forces, and biophysical characteristics to both environmental and livelihood outcomes. Second, most studies focused on environmental outcomes, and the majority of studies that assessed socioeconomic outcomes relied on qualitative data, making comparisons across cases difficult. Finally, there was a heavy bias toward studies on South Asian forests, indicating that the literature on community forestry may not be representative of decentralization policies and CFM globally.     

A hybrid micro-scale model for transport in connected macro-pores in porous media

This paper presents a hybrid model for transport in connected macro-pores in porous media. A pore-scale model is used to parameterize the hybrid model. The hybrid model explicitly models the advection and diffusion of species in the connected macro-pores and treats the porous media around the connected macro-pores as a continuum with effective transport properties. The pore-scale model is used to calculate the effective transport properties of the porous continuum. This approach negates the need to calibrate the hybrid model against experimental data, which is common for continuum-scale models of porous media, and allows an arbitrary microstructure to be considered. The paper presents the multi-scale modeling approach along with the details of the hybrid and pore-scale models. Validation of the model is also presented along with several case studies investigating the applicability of the multi-scale modeling approach to different geometries and transport conditions. The case studies show that the multi-scale modeling approach is accurate for various connected macro-pore geometries given that the porosity of the porous medium around the connected macro-pores is sufficiently small. The accuracy of the hybrid model decreases with increasing porosity of the matrix.     

Explaining support for renewable energy: commitments to self-sufficiency and communion

ABSTRACT

Across the political spectrum, people favour renewable energy. For political liberals, this support has been attributed to concern for the environment; in contrast, the bases of conservatives’ support are less clear. Derived from interviews with a diverse sample of households in Washington State, USA, and a vignette experiment with a representative sample of American households, results show that Democrats (liberals) and Republicans (conservatives) have different moral intuitions, with Democrats emphasizing communion and both Democrats and Republicans valuing self-sufficiency. These findings explain how politically polarized environmental attitudes can exist alongside a shared support for renewable energy. The study therefore contributes to the literature on environmental concern and behaviour, and has implications for policies aimed at increasing adoption of renewable energy as well as pro-environmental behaviour more broadly.