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At least 19 recordsLinked to original sources
USGS2011

Consequences of increasing bioenergy demand on wood and forests: An application of the Global Forest Products Model

The Global Forest Products Model (GFPM) was applied to project the consequences for the global forest sector of doubling the rate of growth of bioenergy demand relative to a base scenario, other drivers being maintained constant. The results showed that this would lead to the convergence of the price of fuelwood and industrial roundwood, raising the price of industrial roundwood by nearly 30% in 2030. The price of sawnwood and panels would be 15% higher. The price of paper would be 3% higher. Concurrently, the demand for all manufactured wood products would be lower in all countries, but the production would rise in countries with competitive advantage. The global value added in wood processing industries would be 1% lower in 2030. The forest stock would be 2% lower for the world and 4% lower for Asia. These effects varied substantially by country. ?? 2011 Department of Forest Economics, SLU Ume??, Sweden.

Journal of Forest Economics↗
USGS2015

The economic viability of smallholder timber production under expanding açaí palm production in the Amazon Estuary

Relatively little attention has been paid to the economic potentials and limitations of tropical timber production and management at smallholder scales, with the most relevant research focusing on community forestry efforts. As a rare tropical example of long-lasting small-scale timber production, in this study we explore the economics of smallholder vertically integrated timber use to better understand the activity in the context of its primary land use alternative in the Amazon Estuary, açaí palm fruit production. We use data from landowner and firm surveys, participatory monitoring of firms, and detailed forest and sawmill operation monitoring to devise financial returns models of smallholder timber micro firms and açaí palm fruit production. We then compare the economics of the two activities to better understand how differences may shape decisions at the small holder scale that impact current land use shifts in the region.

Amazon River, Mazagão watershed↗
USGS2012

The hidden cost of wildfires: Economic valuation of health effects of wildfire smoke exposure in Southern California

There is a growing concern that human health impacts from exposure to wildfire smoke are ignored in estimates of monetized damages from wildfires. Current research highlights the need for better data collection and analysis of these impacts. Using unique primary data, this paper quantifies the economic cost of health effects from the largest wildfire in Los Angeles County's modern history. A cost of illness estimate is \$9.50 per exposed person per day. However, theory and empirical research consistently find that this measure largely underestimates the true economic cost of health effects from exposure to a pollutant in that it ignores the cost of defensive actions taken as well as disutility. For the first time, the defensive behavior method is applied to calculate the willingness to pay for a reduction in one wildfire smoke induced symptom day, which is estimated to be \$84.42 per exposed person per day.

California↗
USGS2020

Paired stated preference methods for valuing management of white pine blister rust: order effects and outcome uncertainty

The literature on nonmarket valuation includes many examples of stated and revealed preference comparisons. However, comparisons within stated preference methods are sparse. Specifically, the literature provides few examples of pairing both a discrete choice experiment (CE) and a contingent valuation (CV) question within a single survey. This paper presents results of a nonmarket valuation study that employs both methods to elicit public preferences over uncertainty of outcomes and over management strategies. The two methods were employed to examine public support for the proactive management of the invasive pathogen, Cronartium ribicola, that causes the lethal disease white pine blister rust in high-elevation forests in North America. By addressing three related questions, this study finds the following main results: First, both methods suggest the importance of presenting outcome uncertainty to respondents. Second, the results provide no evidence that preferences vary over the means taken for pursuing the given ends, which in this case is long term forest health. Third, the paired inclusion of both methods results in order effects for CE results but not for CV results. Results and discussion provide insight into the most appropriate stated preference approach for informing different types of decisions about the efficient management of public lands.

Journal of Forest Economics↗
USGS2025

Wildfire risk information sources and the acceptability of fuels treatments near select WUI communities in the Western United States

Fuels treatments intended to reduce fuel loads and improve forest health on public lands offer one way to reduce wildfire hazards in the wildland-urban interface (WUI), where the natural and built environments meet. However, for fuels treatment implementation to be successful, it must comply with regulatory and scientific standards and be supported by local communities, as lack of acceptance can lead to alterations, delays, or abandonment. To foster support, public land managers can engage directly with residents in communities near treatment areas through various communication channels or engage indirectly through trusted local partners. This research uses paired household survey and observed parcel-level wildfire risk assessment data to investigate wildfire risk information sources' role in the acceptability of fuels treatment approaches on public lands near select WUI communities in the Western United States. We find that information deemed useful from sources is often positively correlated with acceptability, while information deemed not useful is sometimes negatively correlated. Local sources of information tend to be widely received, perceived as useful, and have positive correlations with acceptability, while nonlocal sources vary in their receipt, perceived usefulness, and correlations with acceptability. Public land managers, particularly those from national organizations, may benefit from leveraging and aligning messaging with trusted local partners. Developing fuels treatment plans that consider existing local sentiments may facilitate public trust in managers and acceptability of treatments.

Colorado, New Mexico, Oregon, Washington, Wyoming↗
USGS2003

Carbon dynamics and land-use choices: building a regional-scale multidisciplinary model

Policy enabling tropical forests to approach their potential contribution to global-climate-change mitigation requires forecasts of land use and carbon storage on a large scale over long periods. In this paper, we present an integrated modeling methodology that addresses these needs. We model the dynamics of the human land-use system and of C pools contained in each ecosystem, as well as their interactions. The model is national scale, and is currently applied in a preliminary way to Costa Rica using data spanning a period of over 50 years. It combines an ecological process model, parameterized using field and other data, with an economic model, estimated using historical data to ensure a close link to actual behavior. These two models are linked so that ecological conditions affect land-use choices and vice versa. The integrated model predicts land use and its consequences for C storage for policy scenarios. These predictions can be used to create baselines, reward sequestration, and estimate the value in both environmental and economic terms of including C sequestration in tropical forests as part of the efforts to mitigate global climate change. The model can also be used to assess the benefits from costly activities to increase accuracy and thus reduce errors and their societal costs.

Journal of Environmental Management↗
USGS1995

Non-native animals on public lands

Non-native plants and animals have become part of our surroundings, in cities, agricultural areas, and wildlands. While there are many beneficial purposes for non-native animals, such as for food and sport hunting and as agricultural animals, the introduction of some has had major negative economic consequences (Palmer 1899), and adverse effects on native wildlife, plants, and habitats. The British ecologist Charles Elton, in a major review of introduced species, described the increasing number of invasions as constituting "one of the great historical convulsions in the world's flora and fauna" (Elton 1958, p. 31). Non-native species are significant problems on large areas of state and federal public lands, and areas set aside to protect native plant and animal communities are not immune to such harm. Science and conservation journals have devoted entire issues to the threats posed by non-native plants and animals in nature reserves (e.g., Usher et al. 1988). In a compilation of threats to U.S. national parks, non-native plants and animals were the most often reported threat, and were reported by the most areas; feral cats ( Felis catus ), feral dogs ( Canis familiaris ), and wild pigs ( Sus scrofa ) were the non-native animals cited most often (NPCA 1977). Non-native species present serious threats, but at the same time, coordinated efforts on public lands offer the best possibility for controlling some harmful non-native species, and protecting both native plant and animal communities and human interests and needs. We compiled information on non-native animals on public and private land-management areas by conducting a mail survey to assess their occurrence and management status in land-management areas. Survey results represent contributions from 937 national parks, national forests, national wildlife refuges, Bureau of Land Management field areas, and state and private land-management areas. The results reflect those species that land managers considered of greatest concern, and their general distribution on public lands. Non-native invertebrate animals, particularly forest insects and agricultural pests, cause severe economic and environmental damage as well (OTA 1993), but were not the focus of this survey.

Book chapter↗
USGS2016

Oil and gas development influences big-game hunting in Wyoming

Development from extracting oil and gas resources can have unintended effects on multiple ecosystem functions, with cascading effects on wildlife, ecosystem services, and local economies. Big-game hunting opportunities may be closely related to these effects, but empirical analyses of impacts of energy development on hunting are limited. We examined the influence of oil and gas development density on harvest efficiency, or harvest per unit of hunter effort, within all hunt areas in Wyoming, USA, from 2008 to 2014 for 3 big-game species: elk ( Cervus canadensis ), mule deer ( Odocoileus hemionus ), and pronghorn ( Antilocapra americana ). Using harvest/hunter day as the response variable, we compared linear mixed-effects models for each species that included total well density (i.e., all wells constructed up to the year of record), active well density (i.e., only those wells currently producing oil or gas in that year), or neither as a predictor variable. We used well densities as indicators of development in the absence of data specifying the locations of other oil and gas infrastructure (e.g., roads, well pads). Models also accounted for the fixed effects of road density, hunter density, proportion of the area that is public land with unrestricted hunter access, proportion of the area that is forested, year of observation, and random effects of variation among hunt areas nested within associated game herd units. Presence of oil and gas wells had a positive influence on harvest efficiency for elk and mule deer. Although there was no overall effect to pronghorn, there was a negative influence of wells on juvenile pronghorn harvest efficiency. Changes in harvest efficiency due to expanding oil and gas development could alter the time spent hunting by hunters and their chances of harvesting an animal. This could have subsequent impacts on hunter satisfaction, game populations, and economic revenue generated from recreational hunters.

Wyoming↗
USGS2015

Global land cover mapping using Earth observation satellite data: Recent progresses and challenges

Land cover is an important variable for many studies involving the Earth surface, such as climate, food security, hydrology, soil erosion, atmospheric quality, conservation biology, and plant functioning. Land cover not only changes with human caused land use changes, but also changes with nature. Therefore, the state of land cover is highly dynamic. In winter snow shields underneath various other land cover types in higher latitudes. Floods may persist for a long period in a year over low land areas in the tropical and subtropical regions. Forest maybe burnt or clear cut in a few days and changes to bare land. Within several months, the coverage of crops may vary from bare land to nearly 100% crops and then back to bare land following harvest. The highly dynamic nature of land cover creates a challenge in mapping and monitoring which remains to be adequately addressed. As economic globalization continues to intensify, there is an increasing trend of land cover/land use change, environmental pollution, land degradation, biodiversity loss at the global scale, timely and reliable information on global land cover and its changes is urgently needed to mitigate the negative impact of global environment change.

ISPRS Journal of Photogrammetry and Remote Sensing↗
USGS2024

Exploring the uncertainty of machine learning models and geostatistical mapping of rare earth element potential in Indiana coals, USA

Rare earth elements and yttrium (REEs) have a wide range of applications in high- and low-carbon technologies. The strategic significance of REEs has grown due to their expanding applications in manufacturing industries and the constrained availability of these essential resources. This research explores the applicability of machine learning models and their uncertainty for assessing the REE potential in coal beds using various coal parameters as inputs. The work focuses on developing a predictive model based on geological variables, excluding considerations related to potential shifts in the commodities market. The Indiana Coal Quality Database was used as the data source. The promising and unpromising indicators derived from the outlook coefficient of samples from the database were used as the REE potential indicator for machine learning classification models. The filter-based approach with bootstrap was used to evaluate the importance of the coal parameters and their prediction uncertainties. Four machine learning methods (linear discriminant analysis (LDA), random forest (RF), support vector machine (SVM), and artificial neural networks (ANN), a data balancing and augmentation approach (Synthetic Minority Over-sampling Technique), and bootstrap resampling techniques were used for building the models and evaluating their prediction capabilities under uncertainty. It was determined that the SVM bootstrap model with ten-times balanced and augmented data provided superior results compared with other models. Finally, stochastic spatial maps of the REE potential within the coal basin were generated using sequential indicator simulation. The spatial maps of the REE potential showed that a 29% area of the Indiana section of the Illinois coal basin has economic potential of REEs, with 90% confidence.

Indiana↗
USGS2025

Invasive wild pig movement and space use in a mixed-use forest landscape, South Carolina

Invasive wild pigs ( Sus scrofa ) pose considerable ecological and economic challenges across their introduced range, and understanding their spatial ecology is critical for management. This research and accompanying dataset represents adult wild pig movement in South Carolina, United States based on 16 individuals collared in 2023-2024. Using hourly GPS collar data for 6 males and 5 females, we calculated autocorrelated kernel density estimates (AKDEs) and monthly kernel density estimates (KDEs) to characterize space use. Individual pigs had an average hourly step length of 83 m and average net displacement of 930 m. On average, pigs used 2.32 km 2 monthly, while they used 2.95 km 2 over their entire tracked period (mean = 111 days). This work aims to support management actions and future research on invasive wild pigs.

South Carolina↗
USGS2015

Distribution and dynamics of mangrove forests of South Asia

Mangrove forests in South Asia occur along the tidal sea edge of Bangladesh, India, Pakistan, and Sri Lanka. These forests provide important ecosystem goods and services to the region's dense coastal populations and support important functions of the biosphere. Mangroves are under threat from both natural and anthropogenic stressors; however the current status and dynamics of the region's mangroves are poorly understood. We mapped the current extent of mangrove forests in South Asia and identified mangrove forest cover change (gain and loss) from 2000 to 2012 using Landsat satellite data. We also conducted three case studies in Indus Delta (Pakistan), Goa (India), and Sundarbans (Bangladesh and India) to identify rates, patterns, and causes of change in greater spatial and thematic details compared to regional assessment of mangrove forests. Our findings revealed that the areal extent of mangrove forests in South Asia is approximately 1,187,476 ha representing ∼7% of the global total. Our results showed that from 2000 to 2012, 92,135 ha of mangroves were deforested and 80,461 ha were reforested with a net loss of 11,673 ha. In all three case studies, mangrove areas have remained the same or increased slightly, however, the turnover was greater than the net change. Both, natural and anthropogenic factors are responsible for the change and turnover. The major causes of forest cover change are similar throughout the region; however, specific factors may be dominant in specific areas. Major causes of deforestation in South Asia include (i) conversion to other land use (e.g. conversion to agriculture, shrimp farms, development, and human settlement), (ii) over-harvesting (e.g. grazing, browsing and lopping, and fishing), (iii) pollution, (iv) decline in freshwater availability, (v) floodings, (vi) reduction of silt deposition, (vii) coastal erosion, and (viii) disturbances from tropical cyclones and tsunamis. Our analysis in the region's diverse socio-economic and environmental conditions highlights complex patterns of mangrove distribution and change. Results from this study provide important insight to the conservation and management of the important and threatened South Asian mangrove ecosystem.

Journal of Environmental Management↗
USGS2019

Mapping a keystone shrub species, huckleberry (Vaccinium membranaceum), using seasonal colour change in the Rocky Mountains

Black huckleberries ( Vaccinium membranaceum ) provide a critical food resource to many wildlife species, including apex omnivores such as the grizzly bear ( Ursus arctos ), and play an important socioeconomic role for many communities in western North America, especially indigenous peoples. Remote sensing imagery offers the potential for accurate landscape-level mapping of huckleberries because the shrub changes colour seasonally. We developed two methods, for local and regional scales, to map a shrub species using leaf seasonal colour change from remote sensing imagery. We assessed accuracy with ground-based vegetation surveys. The high-resolution supervised random forest classification from one-meter resolution National Agricultural Imagery Program (NAIP) imagery achieved an overall accuracy of 75.31% (kappa = 0.26). The approach using multi-temporal 30-meter Landsat imagery similarly had an overall accuracy of 79.19% (kappa = .31). We found underprediction error was related to higher forest cover and a lack of visible colour change on the ground in some plots. Where forest cover was low, both models performed better. In areas with <10% forest cover, the high-resolution classification achieved an accuracy of 80.73% (kappa = 0.48), while the Landsat model had an accuracy of 82.55% (kappa = 0.47). Based on the fine-scale predictions, we found that 94% of huckleberry shrubs identified in our study area of Glacier National Park, Montana, USA are over 100 meters from human recreation trails. This information could be combined with productivity and phenology information to estimate the timing and availability of food resources for wildlife and to provide managers with a tool to identify and manage huckleberries. The development of the multi-temporal Landsat models sets the stage for assessment of impacts of disturbance at regional scales on this ecologically, culturally, and economically important shrub species. Our approach to map huckleberries is straightforward, efficient and accessible to wildlife and environmental managers and researchers in diverse fields.

Montana↗
USGS2017

Loss of ecosystem services due to chronic pollution of forests and surface waters in the Adirondack region (USA)

Sustaining recent progress in mitigating acid pollution could require lower emissions caps that will give rise to real or perceived tradeoffs between healthy ecosystems and inexpensive energy. Because most impacts of acid rain affect ecosystem functions that are poorly understood by policy-makers and the public, an ecosystem services (ES) framework can help to measure how pollution affects human well-being. Focused on the Adirondack region (USA), a global ‘hot-spot’ of acid pollution, we measured how the chronic acidification of the region's forests, lakes, and streams has affected the potential economic and cultural benefits they provide to society. We estimated that acid-impaired hardwood forests provide roughly half of the potential benefits of forests on moderate to well-buffered soils – an estimated loss of ∼ $10,000 ha −1 in net present value of wood products, maple syrup, carbon sequestration, and visual quality. Acidic deposition has had only nominal impact – relative to the effects of surficial geology and till depth – on the capacity of Adirondack lakes and streams to provide water suitable for drinking. However, as pH declines in lakes, the estimated value of recreational fishing decreases significantly due to loss of desirable fish such as trout. Hatchery stocking programs have partially offset the pollution-mediated losses of fishery value, most effectively in the pH range 4.8–5.5, but are costly and limited in scope. Although any estimates of the monetary ‘damages’ of acid rain have significant uncertainties, our findings highlight some of the more tangible economic and cultural benefits of pollution mitigation efforts, which continue to face litigation and political opposition.

New York↗
USGS2024

Projected changes in mangrove distribution and vegetation structure under climate change in the southeastern United States

Aim The climate change-induced transition from grass-dominated marshes to woody-plant-dominated mangrove forests has the potential to impact the ecosystem goods and services provided by coastal wetlands. To better anticipate and prepare for these impacts, there is a need to advance understanding of future changes in mangrove distribution and coastal wetland vegetation structural properties due to warming winters. Location Southeastern United States. Time Period Recent (1981–2010) and future (2071–2100). Major Taxa Studied Coastal wetland vegetation. Methods We estimated changes in mangrove distribution and coastal wetland vegetation structure using known climate-ecological relationships, recent climate data for the period 1981–2010, and future projected climate data for the period 2071–2100. We quantified potential changes in mangrove presence, mangrove relative abundance, coastal wetland vegetation height, and coastal wetland vegetation aboveground biomass under two Shared Socio-Economic Pathway scenarios (SSPs; SSP2-4.5 and SSP5-8.5), which correspond to intermediate and high greenhouse gas emissions scenarios, respectively. Results Our analyses indicate that mangrove presence and relative abundance will dramatically increase in the northern Gulf of Mexico and the southeast Atlantic coast of the United States, particularly under the high emissions scenario. Because of the higher stature of mangroves relative to salt marsh vegetation, this expansion will cause a transformative change in coastal wetland vegetation height and aboveground biomass in many areas. However, along the arid southern Texas coast, low precipitation and high salinities are expected to constrain mangrove expansion and growth. Main Conclusions Our results show where and to what extent climate change, in the form of winter temperature warming, is projected to enable the transition from shorter, grass-dominated salt marshes to taller, woody plant-dominated mangrove forests in the southeastern United States, with consequent impacts on ecosystem goods and services.

Journal of Biogeography↗
USGS2020

Trait integration and functional differentiation among co-existing plant species

Premise Determining which traits characterize strategies of coexisting species is important to developing trait‐based models of plant communities. First, global dimensions may not exist locally. Second, the degree to which traits and trait spectra constitute independent dimensions of functional variation at various scales continues to be refined. Finally, traits may be associated with existing categorical groupings. Methods We assessed trait integration and differentiation across 57 forest understory plant species in Douglas‐fir forests of western Oregon, United States. We combined measurements for a range of traits with literature‐based estimates of seed mass and species groupings. We used network analysis and nonmetric multidimensional scaling ordination (NMS) to determine the degree of integration. Results We observed a strong leaf economics spectrum (LES) integrated with stem but not root traits. However, stem traits and intrinsic water‐use efficiency integrated LES and root traits. Network analyses indicated a modest grouping of a priori trait dimensions. NMS indicated that multivariate differences among species were related primarily to (1) rooting depth and plant height vs. specific root length, (2) the LES, and (3) leaf size vs. seed mass. These differences were related to species groupings associated with growth and life form, leaf lifespan and seed dispersal mechanisms. Conclusions The strategies of coexisting understory plant species could not be reduced to a single dimension. Yet, species can be characterized efficiently and effectively for trait‐based studies of plant communities by measuring four common traits: plant height, specific leaf area, leaf size, and seed mass.

Oregon↗
USGS2020

Cost-effective fuel treatment planning: A theoretical justification and case-study

Modelling the spatial prioritisation of fuel treatments and their net effect on values at risk is an important area for applied work as economic damages from wildfire continue to grow. We model and demonstrate a cost-effective fuel treatment planning algorithm using two ecosystem services as benefits for which fuel treatments are prioritised. We create a surface of expected fuel treatment costs to incorporate the heterogeneity in factors affecting the revenue and costs of fuel treatments, and then prioritise treatments based on a cost-effectiveness ratio to maximise the averted loss of ecosystem services from fire. We compare treatment scenarios that employ cost-effectiveness with those that do not, and use common tools and models in a case study of the Sisters Ranger District on the Deschutes National Forest in central Oregon, USA. Using cost-effectiveness not only increases the expected averted losses from fuel treatments, but it also allows a larger area to be treated for the same cost, simply by incorporating costs and cost-effectiveness into the prioritisation routine. These results have considerable implications for policymakers and land managers trying to minimise risk. Incorporating costs into the spatial planning of treatments could allow more effective outcomes without increasing fuel treatment budgets.

Oregon↗
USGS2020

Conterminous United States land cover change patterns 2001–2016 from the 2016 National Land Cover Database

The 2016 National Land Cover Database (NLCD) product suite (available on www.mrlc.gov), includes Landsat-based, 30 m resolution products over the conterminous (CONUS) United States (U.S.) for land cover, urban imperviousness, and tree, shrub, herbaceous and bare ground fractional percentages. The release of NLCD 2016 provides important new information on land change patterns across CONUS from 2001-2016. For land cover, seven epochs were concurrently generated for years 2001, 2004, 2006, 2008, 2011, 2013, and 2016. Products reveal that land cover change is significant across most land cover classes and time periods. The land cover product was validated using existing reference data from the legacy NLCD 2011 accuracy assessment, applied to the 2011 epoch of the NLCD 2016 product line. The legacy and new NLCD 2011 overall accuracies were 82% and 83%, respectively, (standard error was 0.5%), demonstrating a small but significant increase in overall accuracy. Between 2001-2016, the CONUS landscape experienced significant change, with almost 8% of the landscape having experienced a land cover change at least once during this time. Nearly 50% of that change involves forest, driven by change agents of harvest, fire, disease and pests that resulted in an overall forest decline, including increasing fragmentation and loss of interior forest. Agricultural change represented 15.9% of the change, with total agricultural spatial extent showing only a slight increase of 4,778 km2, however there was a substantial decline (7.94%) in pasture/hay during this time, transitioning mostly to cultivated crop. Water and wetland change comprised 15.2% of change and represent highly dynamic land cover classes from epoch to epoch, heavily influenced by precipitation. Grass and shrub change comprise 14.5% of the total change, with most change resulting from fire. Developed change was the most persistent and permanent land change increase adding almost 29,000 km2 over 15 years (5.6% of total CONUS change), with southern states exhibiting expansion much faster than most of the northern states. Temporal rates of developed change increased in 2001-2006 at twice the rate of 2011-2016, reflecting a slowdown in CONUS economic activity. Future NLCD plans include increasing monitoring frequency, reducing latency time between satellite imaging and product delivery, improving accuracy and expanding the variety of products available in an integrated database.

ISPRS Journal of Photogrammetry and Remote Sensing↗