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.     

Spatial characteristics of fine particulate matter: identifying representative monitoring locations in Seattle, Washington

This study investigates how PM2.5 varies spatially and how these spatial characteristics can be used to identify potential monitoring sites that are most representative of the overall ambient exposures to PM2.5 among susceptible populations in the Seattle, WA, area. Data collected at outdoor sites at the homes of participants of a large exposure assessment study were used in this study. Harvard impactors (HIs) were used at 40 outdoor sites throughout the Seattle metropolitan area. Up to six sites at a time were monitored for 10 consecutive 24-hr average periods. A fixed-effect analysis of variance (ANOVA) model that included date and location effects was used to analyze the spatial variability of outdoor PM2.5 concentrations. Both date and location effects were shown to be highly significant, explaining 92% of the variability in outdoor PM2.5 measurements. The day-to-day variability was 10 times higher than the spatial variability between sites. The site mean square was more than twice the error mean square, showing that differences between sites, while modest, are potentially an important contribution to measurement error. Variances of the model residuals and site effects were examined against spatial characteristics of the monitoring sites. The spatial characteristics included elevation, distance from arterials, and distance from major PM2.5 point sources. Results showed that the most representative PM2.5 sites were located at elevations of 80-120 m above sea level, and at distances of 100-300 m from the nearest arterial road. Location relative to industrial PM2.5 sources is not a significant predictor of residential outdoor PM2.5 measurements. Additionally, for sites to be representative of the average population exposures to PM2.5 among those highly susceptible to the health effects of PM2.5, areas of high elderly population density were considered. These representative spatial characteristics were used as multiple, overlapping criteria in a Geographic Information System (GIS) analysis to determine where the most representative sites are located.     

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.     

Assessing four methods for establishing native plants on urban vacant land

Urban greening increases vegetation and can restore ecological functions to urban systems. It has ties to restoration ecology, which aims to return degraded land to diverse, functional ecosystems. Both practices can be applied to maximizing ecosystem services and habitat in vacant lots, which are abundant in post-industrial cities, including Chicago, Illinois (USA), where our study took place. We tested four methods for increasing native plant diversity in vacant lots, ranging from low input to resource-intensive: seed bombing, broadcast seeding, planting plugs, and gardening. After three growing seasons, we assessed the growth of eight target native species and all non-target species. We expected that intensive treatments would have more target species stems and flowers and fewer non-target species, but we found that less-intensive options often produce equal or better results. From this, we recommend broadcast seeding as a viable, low-cost method for improving habitat and biodiversity in vacant lots.Electronic supplementary materialThe online version of this article (10.1007/s13280-020-01383-z) contains supplementary material, which is available to authorized users.     

Miscanthus for Renewable Energy Generation: European Union Experience and Projections for Illinois

Mitigation and Adaptation Strategies for Global Change -     

A time‐lagged investigation of the impact of coworker behavior on the effects of demographic dissimilarity

Although it is clear that coworker absenteeism, tardiness, and turnover can influence an employee's actions, scholars have yet to consider the impact of relational demography on the adoption of these behavioral norms. Inspired by social identity, situational strength, and attraction‐selection‐attrition theories, we proposed that individuals who differ from their coworkers in age, sex, or racioethnicity would feel threatened by their outnumbered status and subsequently motivated to be absent, tardy, or more likely to turnover. However, we expected coworker withdrawal behavior to moderate whether or not dissimilar personnel act on these desires. Results from hierarchical multilevel modeling analyses of data from 470 U.S. call center workers nested in 51 work groups revealed that racioethnic dissimilarity was positively related to time‐lagged changes in absenteeism and tardiness as well as heightened turnover likelihood. These effects emerged only among employees whose coworkers engaged in greater withdrawal behavior. Importantly, racioethnically dissimilar employees working in more permissive climates (i.e., those with high levels of coworker absenteeism, tardiness, or turnover) exhibited the greatest increases in absenteeism and tardiness over three months and had the highest supervisor‐rated turnover likelihood. Implications for diversity management are discussed. Copyright © 2015 John Wiley & Sons, Ltd.     

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 comprehensive review of climate adaptation in the United States: more than before, but less than needed

We reviewed existing and planned adaptation activities of federal, tribal, state, and local governments and the private sector in the United States (U.S.) to understand what types of adaptation activities are underway across different sectors and scales throughout the country. Primary sources of review included material officially submitted for consideration in the upcoming 2013 U.S. National Climate Assessment and supplemental peer-reviewed and grey literature. Although substantial adaptation planning is occurring in various sectors, levels of government, and the private sector, few measures have been implemented and even fewer have been evaluated. Most adaptation actions to date appear to be incremental changes, not the transformational changes that may be needed in certain cases to adapt to significant changes in climate. While there appear to be no one-size-fits-all adaptations, there are similarities in approaches across scales and sectors, including mainstreaming climate considerations into existing policies and plans, and pursuing no- and low-regrets strategies. Despite the positive momentum in recent years, barriers to implementation still impede action in all sectors and across scales. The most significant barriers include lack of funding, policy and institutional constraints, and difficulty in anticipating climate change given the current state of information on change. However, the practice of adaptation can advance through learning by doing, stakeholder engagements (including “listening sessions”), and sharing of best practices. Efforts to advance adaptation across the U.S. and globally will necessitate the reduction or elimination of barriers, the enhancement of information and best practice sharing mechanisms, and the creation of comprehensive adaptation evaluation metrics.