Multiple values from the forest: contribution of non-timber forest products to livelihoods of local communities in Northeastern Thailand

Environment, Development and Sustainability - Local residents near forests often collect non-timber forest products (NTFPs) for a variety of reasons, including food, medicine, firewood, religious...     

Adapting to changing climate risk by local government in New Zealand: institutional practice barriers and enablers

Adaptation to climate change has been reviewed in several developed nations, but in none where consideration of the effects of climate change is required by statute and devolved to local government. We examine the role of institutional arrangements, the players operating under them, the barriers and enablers for adaptation decision-making in the developed nation of New Zealand. We examine how the roles and responsibilities between national, regional and local governments influence the ability of local government to deliver long-term flexible responses to changing climate risk. We found that the disciplinary practices of law, engineering and planning, within legal frameworks, result in the use of static mechanisms which create inflexible responses to changing risk. Several enablers are identified that could create greater integration between the different scales of government, including better use of national policy instruments, shared professional experience, standardised information collection and risk assessment methods that address uncertainties. The framing of climate risk as dynamic and changing that differentiates activities over their lifetime, development of mechanisms to fund transitions towards transformational change, are identified as necessary conditions for delivering flexible responses over time.     

The New Zealand experience of varroa invasion highlights research opportunities for Australia

The Varroa mite (Varroa destructor) is implicated as a major disease factor in honey bee (Apis mellifera) populations worldwide. Honey bees are extensively relied upon for pollination services, and in countries such as New Zealand and Australia where honey bees have been introduced specifically for commercial pollinator services, the economic effects of any decline in honey bee numbers are predicted to be profound. V. destructor established in New Zealand in 2000 but as yet, Australia remains Varroa-free. Here we analyze the history of V. destructor invasion and spread in New Zealand and discuss the likely long-term impacts. When the mite was discovered in New Zealand, it was considered too well established for eradication to be feasible. Despite control efforts, V. destructor has since spread throughout the country. Today, assessing the impacts of the arrival of V. destructor in this country is compromised by a paucity of data on pollinator communities as they existed prior to invasion. Australia’s Varroa-free status provides a rare and likely brief window of opportunity for the global bee research community to gain understanding of honey bee-native pollinator community dynamics prior to Varroa invasion.     

Radon emissions from natural gas power plants at The Pennsylvania State University

Burning natural gas in power plants may emit radon (²²²Rn) into the atmosphere. On the University Park campus of The Pennsylvania State University, atmospheric radon enhancements were measured and modeled in the vicinity of their two power plants. The three-part study first involved measuring ambient outdoor radon concentrations from August 2014 through January 2015 at four sites upwind and downwind of the power plants at distances ranging from 80 m to 310 m. For each plant, one site served as a background site, while three other sites measured radon concentration enhancements downwind. Second, the radon content of natural gas flowing into the power plant was measured, and third, a plume dispersion model was used to predict the radon concentrations downwind of the power plants. These predictions are compared to the measured downwind enhancements in radon to determine whether the observed radon concentration enhancements could be attributed to the power plants’ emissions. Atmospheric radon concentrations were consistently low as compared to the EPA action level of 148 Bq m^?3, averaging 34.5 ± 2.7 Bq m^?3 around the East Campus Steam Plant (ECSP) and 31.6 ± 2.7 Bq m^?3 around the West Campus Steam Plant (WCSP). Significant concentrations of radon, ranging from 516 to 1,240 Bq m^?3, were detected in the natural gas. The measured enhancements downwind of the ECSP averaged 6.2 Bq m^?3 compared to modeled enhancements of 0.08 Bq m^?3. Measured enhancements around the WCSP averaged ?0.2 Bq m^?3 compared to the modeled enhancements of 0.05 Bq m^?3, which were not significant compared to observational error. The comparison of the measured to modeled downwind radon enhancements shows no correlation over time. The measurements of radon levels in the vicinity of the power plants appear to be unaffected by the emissions from the power plants.

Implications: Radon measurements at sites surrounding power plants that utilize natural gas did not indicate that the radon concentrations originated from the plants’ emissions. There were elevated radon concentrations in the natural gas supply flowing into the power plants, but combustion dilution puts the concentration below EPA action levels coming out of the stack, so no hazardous levels were expected downwind. Power plant combustion of natural gas is not likely to pose a radiation health hazard unless very different gas radon concentrations or combustion dilution ratios are encountered.     

Industrial pollution,spatial stigma and economic decline: the case of Asopos river basin through the lens of local small business owners

This paper explores the notion of environmentally induced spatial stigma through an analysis of data from interviews across public attitudes to pollution within the Asopos river basin in central Greece. The area has a 40 year plus history of legal and illicit industrial waste disposal and public debate on the associated environmental degradation. The study focuses on the perceptions and beliefs of a sector of the community likely to be directly and negatively affected by stigma, that is small business owners in the tourism and hospitality sector. The qualitative analysis explores awareness and viewpoints on environmental degradation and water quality within the local context, implications for the local economy and the individual's own enterprise, views on industrial environmental management as well as corporate responsibility and future prospects for the environmental problems of Asopos. Findings reveal a noticeable variation in views on industrial pollution and ecosystem deterioration among the respondents, but overall a strong environmentally induced stigmatization of the area. They also uncover an information asymmetry and lack of credible commitment by government bodies and industry members in disclosing accurate information, a situation likely to increase speculation and uncertainty within the community. The paper concludes by addressing implications of the findings to policy-making and managerial considerations, along with future research perspectives which aim to increase considerations of sustainability aspects for local development.     

Near-term forecasts of stream temperature using deep learning and data assimilation in support of management decisions

Deep learning (DL) models are increasingly used to make accurate hindcasts of management-relevant variables, but they are less commonly used in forecasting applications. Data assimilation (DA) can be used for forecasts to leverage real-time observations, where the difference between model predictions and observations today is used to adjust the model to make better predictions tomorrow. In this use case, we developed a process-guided DL and DA approach to make 7-day probabilistic forecasts of daily maximum water temperature in the Delaware River Basin in support of water management decisions. Our modeling system produced forecasts of daily maximum water temperature with an average root mean squared error (RMSE) from 1.1 to 1.4°C for 1-day-ahead and 1.4 to 1.9°C for 7-day-ahead forecasts across all sites. The DA algorithm marginally improved forecast performance when compared with forecasts produced using the process-guided DL model alone (0%–14% lower RMSE with the DA algorithm). Across all sites and lead times, 65%–82% of observations were within 90% forecast confidence intervals, which allowed managers to anticipate probability of exceedances of ecologically relevant thresholds and aid in decisions about releasing reservoir water downstream. The flexibility of DL models shows promise for forecasting other important environmental variables and aid in decision-making.     

Structural and optical characterization of dissolved organic matter from the lower Athabasca River, Canada

Dissolved organic matter (DOM) is a ubiquitous constituent of natural waters and is comprised of a variety of chemically heterogeneous molecular structures and functional groups. DOM is often considered to be a major ligand for metals in most natural waters and its reactivity is thought to be strongly dependent on its chemical composition and structure. In this study, a combination of UV/visible, emission excitation matrix fluorescence (EEM) and ¹H NMR spectroscopies were used to characterize DOM from the Athabasca River (Alberta, Canada). The chemical characterization of river DOM showed that the most upstream samples located in agricultural areas were blue-shifted and less aromatic and contained more hydrogens connected with oxygen functional groups than those in the wetland dominated area in the Athabasca oil sand deposit region. The presence of paramagnetic ions (Fe and Al) was not found to significantly affect the structural composition of DOM as revealed by ¹H NMR. Such change in the quality of DOM may have a profound impact on metal binding in the Athabasca River watershed.     

Assessment of heterogeneity of metal composition of fine particulate matter collected from eight U.S. counties using principal component analysis

The main objectives of this study are to (1) characterize chemical constituents of particulate matter (PM) and (2) compare overall differences in PM collected from eight US. counties. This project was undertaken as a part of a larger research program conducted by the Johns Hopkins Particulate Matter Research Center (JHPMRC). The goal of the JHPMRC is to explore the relationship between health effects and exposure to ambient PM of differing composition. The JHPMRC collected weekly filter-based ambient fine particle samples from eight US. counties between January 2008 and January 2010. Each sampling effort consisted of a 5-6-week sampling period. Filters were analyzed for 25 metals using inductively coupled plasma mass spectrometry (ICP-MS). Overall compositional differences were ranked by principal component analysis (PCA). The results showed that weekly concentrations of each element varied 3-40 times between the eight counties. PCA showed that the first five principal components explained 85% of the total variance. The authors found significant overall compositional differences in PM as the average of standardized principal component scores differed between the counties. These findings demonstrate PCA is a useful tool to identify the differences in PM compositional mixtures by county. These differences will be helpful for epidemiological and toxicological studies to help explain why health risks associated with PM exposure are different in locations with similar mass concentrations of PM.