Environmental, economic, and social changes in rural America visible in survey data and satellite images

This brief focuses on the changing landscapes of different types of rural America where social, economic, and ecological changes are occurring over large areas: the Northern Forest, Central Appalachia, and the Pacific Northwest. These three study sites embody varying historical reliance on land and natural resources and represent very different socioeconomic dynamics. Their common and unique challenges are explored, along with the far-reaching implications of land-cover change in their areas. Data used includes both telephone surveys and satellite imagery to illustrate the unique changes seen in rural America in recent years. (Please note that it is best to print this brief in color.

Generational Aspects of U.S. Public Opinion on Renewable Energy and Climate Change

The topics of climate change and renewable energy often are linked in policy discussions and scientific analysis, but public opinion on these topics exhibits both overlap and divergence. Although renewable energy has potentially broader acceptance than anthropogenic climate change, it can also sometimes face differently-based opposition. Analyses of U.S. and regional surveys, including time series of repeated surveys in New Hampshire (2010–2018) and northeast Oregon (2011–2018), explore the social bases of public views on both issues. Political divisions are prominent, although somewhat greater regarding climate change. Such divisions widen with education, an interaction effect documented in other studies as well. We also see robust age and temporal effects. Younger adults more often prioritize renewable energy development, and agree with scientists on the reality of anthropogenic climate change (ACC). Across all age groups and both regional series, support for renewable energy and recognition of ACC have been gradually rising. These trends, together with age-cohort replacement and possible changes in age-group voting participation, suggest that public pressure for action on these issues could grow

Trust in scientists on climate change and vaccines

On climate change and other topics, conservatives have taken positions at odds with a strong scientific consensus. Claims that this indicates a broad conservative distrust of science have been countered by assertions that while conservatives might oppose the scientific consensus on climate change or evolution, liberals oppose scientists on some other domains such as vaccines. Evidence for disproportionately liberal bias against science on vaccines has been largely anecdotal, however. Here, we test this proposition of opposite biases using 2014 survey data from Oregon and New Hampshire. Across vaccine as well as climate change questions on each of these two surveys, we find that Democrats are most likely to say they trust scientists for information, and Tea Party supporters are least likely, contradicting the proposition of opposite bias. Moreover, partisan divisions tend to widen with education. Theoretical explanations that have been offered for liberal trust or conservative distrust of science in other specific domains such as climate change or environmental protection fit less well with these results on vaccines. Given the much different content of climate change and vaccine issues, the common political pattern appears more consistent with hypotheses of broader ideological divisions on acceptance of science

Optimal land cover mapping and change analysis in northeastern oregon using landsat imagery.

Abstract The necessity for the development of repeatable, efficient, and accurate monitoring of land cover change is paramount to successful management of our planet’s natural resources. This study evaluated a number of remote sensing methods for classifying land cover and land cover change throughout a two-county area in northeastern Oregon (1986 to 2011). In the past three decades, this region has seen significant changes in forest management that have affected land use and land cover. This study employed an accuracy assessment-based empirical approach to test the optimality of a number of advanced digital image processing techniques that have recently emerged in the field of remote sensing. The accuracies are assessed using traditional error matrices, calculated using reference data obtained in the field. We found that, for single-time land cover classification, Bayes pixel-based classification using samples created with scale and shape segmentation parameters of 8 and 0.3, respectively, resulted in the highest overall accuracy. For land cover change detection, using Landsat-5 TM band 7 with a change threshold of 1.75 standard deviations resulted in the highest accuracy for forest harvesting and regeneration mapping

Research on synthetic rope and its future in timber harvesting

Steel wire rope is used for many logging applications. It has served the industry well in terms of strength, durability, and longevity. However, steel wire rope is difficult to use because it is stiff, heavy, and unyielding. These characteristics can lead to fatigue and exhaustion, and may contribute to worker injuries. Ultra-high molecular weight polyethylene synthetic rope has the potential to replace steel wire rope for selected logging applications. Research shows ergonomic gains and other operational effectiveness with its use. This paper presents research results, potentials, and issues in improving economic and ergonomic performance of ground-based and cable logging. Potential social and environmental benefits are also discussed. Further training, research and promotion are necessary to put this new technology into the hands of users and assure adoption in the forestry sector

Validation of Satellite Rainfall Products for Western Uganda.

Central equatorial Africa is deficient in long-term, ground-based measurements of rainfall; therefore, the aim of this study is to assess the accuracy of three high-resolution, satellite-based rainfall products in western Uganda for the 2001–10 period. The three products are African Rainfall Climatology, version 2 (ARC2); African Rainfall Estimation Algorithm, version 2 (RFE2); and 3B42 from the Tropical Rainfall Measuring Mission, version 7 (i.e., 3B42v7). Daily rainfall totals from six gauges were used to assess the accuracy of satellite-based rainfall estimates of rainfall days, daily rainfall totals, 10-day rainfall totals, monthly rainfall totals, and seasonal rainfall totals. The northern stations had a mean annual rainfall total of 1390 mm, while the southern stations had a mean annual rainfall total of 900 mm. 3B42v7 was the only product that did not underestimate boreal-summer rainfall at the northern stations, which had ~3 times as much rainfall during boreal summer than did the southern stations. The three products tended to overestimate rainfall days at all stations and were borderline satisfactory at identifying rainfall days at the northern stations; the products did not perform satisfactorily at the southern stations. At the northern stations, 3B42v7 performed satisfactorily at estimating monthly and seasonal rainfall totals, ARC2 was only satisfactory at estimating seasonal rainfall totals, and RFE2 did not perform satisfactorily at any time step. The satellite products performed worst at the two stations located in rain shadows, and 3B42v7 had substantial overestimates at those stations

Trends and Variability in Localized Precipitation Around Kibale National Park, Uganda, Africa

Our objective was to understand and describe local spatial and temporal variability in precipitation around Kibale National Park, a tropical forest area of high conservation value. Continental or regional-scale trends are often relied upon to make policy and management decisions, but these analyses are often at too coarse a resolution to capture important variability at a finer scale where management actions operate. Monthly rainfall data derived from ten long-term station records (1941-1975) were used to evaluate local spatiotemporal variability in seasonal and annual rainfall for the area surrounding Kibale National Park. The magnitude, direction and significance of trends in seasonal and annual rainfall within the area surrounding the park were identified using the Mann-Kendall trend test and Sen’s slope estimator. The standardized precipitation index was calculated at 3- and 12-month periods to identify areas of relative wetness or dryness. Analysis of annual trends and precipitation indices indicated that patterns in annual time series do not reflect the direction and magnitude of seasonal trends nor the spatial variability in intra-annual rainfall at the local scale. Significant negative trends in the seasonal long rains, following dry season and short rains were identified at stations west of Kibale, while significant positive trends in the seasonal short rains occurred at stations north of the park. Stations along the western park boundary tended to have more years in which the two dry seasons were abnormally dry than those stations located further from the park

Rural environmental concern: Effects of position, partisanship and place

The social bases of environmental concern in rural America resemble those for the nation as a whole, but also reflect the influence of place. Some general place characteristics, such as rates of population growth or resource-industry employment, predict responses across a number of environmental issues. Other unique or distinctive aspects of local society and environment matter as well. We extend earlier work on both kinds of place effects, first by analyzing survey data from northeast Oregon. Results emphasize that “environmental concern” has several dimensions. Second, we contextualize the Oregon results using surveys from other regions. Analysis of an integrated dataset (up to 12,000 interviews in 38 U.S. counties) shows effects from respondent characteristics and political views, and from county rates of population growth and resource-based employment. There also are significant place-to-place variations that are not explained by variables in the models. To understand some of these we return to the local scale. In northeast Oregon, residents describe how perceptions of fire danger from unmanaged forest lands shape their response to the word conservation. Their local interpretation contrasts with more general and urban connotations of this term, underlining the importance of place for understanding rural environmental concern

Integrating landscapes that have experienced rural depopulation and ecological homogenization into tropical conservation planning

If current trends of declining fertility rates and increasing abandonment of rural land as a result of urbanization continue, this will signal a globally significant transformation with important consequences for policy makers interested in conservation planning. This transformation is presently evident in a number of countries and projections suggest it may occur in the future in many developing countries. We use rates of population growth and urbanization to project population trends in rural areas for 25 example countries. Our projections indicate a general decline in population density that has either occurred already (e.g., Mexico) or may occur in the future if current trends continue (e.g., Uganda). Using both temperate and tropical examples we present evidence that this process will lead to ecological homogenization as a dominant habitat (e.g., forest replaces a mosaic of human-maintained landscapes), resulting in declines in biodiversity at the local scale. Building on this information, we consider research programs that need to be conducted so that policy makers are prepared to effectively manage depopulated rural areas

Population pressure and global markets drive a decade of forest cover change in Africa\u27s Albertine Rift

Africa\u27s Albertine Rift region faces a juxtaposition of rapid human population growth and protected areas, making it one of the world\u27s most vulnerable biodiversity hotspots. Using satellite-derived estimates of forest cover change, we examined national socioeconomic, demographic, agricultural production, and local demographic and geographic variables, to assess multilevel forces driving local forest cover loss and gain outside protected areas during the first decade of this century. Because the processes that drive forest cover loss and gain are expected to be different, and both are of interest, we constructed models of significant change in each direction. Although rates of forest cover change varied by country, national population change was the strongest driver of forest loss for all countries – with a population doubling predicted to cause 2.06% annual cover loss, while doubling tea production predicted to cause 1.90%. The rate of forest cover gain was associated positively with increased production of the local staple crop cassava, but negatively with local population density and meat production, suggesting production drivers at multiple levels affect reforestation. We found a small but significant decrease in loss rate as distance from protected areas increased, supporting studies suggesting higher rates of landscape change near protected areas. While local population density mitigated the rate of forest cover gain, loss was also correlated with lower local population density, an apparent paradox, but consistent with findings that larger scale forces outweigh local drivers of deforestation. This implicates demographic and market forces at national and international scales as critical drivers of change, calling into question the necessary scales of forest protection policy in this biodiversity hotspot. Using a satellite derived estimate of forest cover change for both loss and gain added a dynamic component to more traditionally static and unidirectional studies, significantly improving our understanding of landscape processes and drivers at work