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10 recordsLinked to original sources
USGS2010

Emerging themes in the ecology and management of North American forests

The 7th North American Forest Ecology Workshop, consisting of 149 presentations in 16 oral sessions and a poster session, reflected a broad range of topical areas currently under investigation in forest ecology and management. There was an overarching emphasis on the role of disturbance, both natural and anthropogenic, in the dynamics of forest ecosystems, and the recognition that legacies from past disturbances strongly influence future trajectories. Climate was invoked as a major driver of ecosystem change. An emphasis was placed on application of research findings for predicting system responses to changing forest management initiatives. Several “needs” emerged from the discussions regarding approaches to the study of forest ecosystems, including (1) consideration of variable spatial and temporal scales, (2) long-term monitoring, (3) development of universal databases more encompassing of time and space to facilitate meta-analyses, (4) combining field studies and modeling approaches, (5) standardizing methods of measurement and assessment, (6) guarding against oversimplification or overgeneralization from limited site-specific results, (7) greater emphasis on plant-animal interactions, and (8) better alignment of needs and communication of results between researchers and managers.

International Journal of Forestry Research↗
USGS2021

Developing species-age cohorts from forest inventory and analysis data to parameterize a forest landscape model

Simulating long-term, landscape level changes in forest composition requires estimates of stand age to initialize succession models. Detailed stand ages are rarely available, and even general information on stand history often is lacking. We used data from USDA Forest Service Forest Inventory and Analysis (FIA) database to estimate broad age classes for a forested landscape to simulate changes in landscape composition and structure relative to climate change at Fort Drum, a 43,000 ha U.S. Army installation in northwestern New York. Using simple linear regression, we developed relationships between tree diameter and age for FIA site trees from the host and adjacent ecoregions and applied those relationships to forest stands at Fort Drum. We observed that approximately half of the variation in age was explained by diameter breast height (DBH) across all species studied ( r 2 = 0.42 for sugar maple Acer saccharum to 0.63 for white ash Fraxinus americana ). We then used age-diameter relationships from published research on northern hardwood species to calibrate results from the FIA-based analysis. With predicted stand age, we used tree species life histories and environmental conditions represented by ecological site types to parameterize a stochastic forest landscape model (LANDIS-II) to spatially and temporally model successional changes in forest communities at Fort Drum. Forest stands modeled over 100 years without significant disturbance appeared to reflect expected patterns of increasing dominance by shade-tolerant mesophytic tree species such as sugar maple, red maple ( Acer rubrum ), and eastern hemlock ( Tsuga canadensis ) where soil moisture was sufficient. On drier sandy soils, eastern white pine ( Pinus strobus ), red pine ( P. resinosa ), northern red oak ( Quercus rubra ), and white oak ( Q. alba ) continued to be important components throughout the modeling period with no net loss at the landscape scale. Our results suggest that despite abundant precipitation and relatively low evapotranspiration rates for the region, low soil water holding capacity and fertility may be limiting factors for the spread of mesophytic species on excessively drained soils in the region. Increasing atmospheric temperatures projected for the region could alter moisture regimes for many coarse-textured soils providing a possible mechanism for expansion of xerophytic tree species.

New York↗
USGS2010

Tree mortality following prescribed fire and a storm surge event in Slash Pine (pinus elliottii var. densa) forests in the Florida Keys, USA

In fire-dependent forests, managers are interested in predicting the consequences of prescribed burning on postfire tree mortality. We examined the effects of prescribed fire on tree mortality in Florida Keys pine forests, using a factorial design with understory type, season, and year of burn as factors. We also used logistic regression to model the effects of burn season, fire severity, and tree dimensions on individual tree mortality. Despite limited statistical power due to problems in carrying out the full suite of planned experimental burns, associations with tree and fire variables were observed. Post-fire pine tree mortality was negatively correlated with tree size and positively correlated with char height and percent crown scorch. Unlike post-fire mortality, tree mortality associated with storm surge from Hurricane Wilma was greater in the large size classes. Due to their influence on population structure and fuel dynamics, the size-selective mortality patterns following fire and storm surge have practical importance for using fire as a management tool in Florida Keys pinelands in the future, particularly when the threats to their continued existence from tropical storms and sea level rise are expected to increase.

Florida↗
USGS2012

Forest Succession and Maternity Day roost selection by Myotis septentrionalis in a mesophytic hardwood forest

Conservation of summer maternity roosts is considered critical for bat management in North America, yet many aspects of the physical and environmental factors that drive roost selection are poorly understood. We tracked 58 female northern bats ( Myotis septentrionalis ) to 105 roost trees of 21 species on the Fort Knox military reservation in north-central Kentucky during the summer of 2011. Sassafras ( Sassafras albidum ) was used as a day roost more than expected based on forest stand-level availability and accounted for 48.6% of all observed day roosts. Using logistic regression and an information theoretic approach, we were unable to reliably differentiate between sassafras and other roost species or between day roosts used during different maternity periods using models representative of individual tree metrics, site metrics, topographic location, or combinations of these factors. For northern bats, we suggest that day-roost selection is not a function of differences between individual tree species per se , but rather of forest successional patterns, stand and tree structure. Present successional trajectories may not provide this particular selected structure again without management intervention, thereby suggesting that resource managers take a relatively long retrospective view to manage current and future forest conditions for bats.

Kentucky↗
USGS2013

Leaf gas exchange and nutrient use efficiency help explain the distribution of two Neotropical mangroves under contrasting flooding and salinity

Rhizophora mangle and Laguncularia racemosa co-occur along many intertidal floodplains in the Neotropics. Their patterns of dominance shift along various gradients, coincident with salinity, soil fertility, and tidal flooding. We used leaf gas exchange metrics to investigate the strategies of these two species in mixed culture to simulate competition under different salinity concentrations and hydroperiods. Semidiurnal tidal and permanent flooding hydroperiods at two constant salinity regimes (10 g L −1 and 40 g L −1 ) were simulated over 10 months. Assimilation (A), stomatal conductance (g w ), intercellular CO 2 concentration (C i ), instantaneous photosynthetic water use efficiency (PWUE), and photosynthetic nitrogen use efficiency (PNUE) were determined at the leaf level for both species over two time periods. Rhizophora mangle had significantly higher PWUE than did L. racemosa seedlings at low salinities; however, L. racemosa had higher PNUE and stomatal conductance and g w , accordingly, had greater intercellular CO 2 (calculated) during measurements. Both species maintained similar capacities for assimilation at 10 and 40 g L−1 salinity and during both permanent and tidal hydroperiod treatments. Hydroperiod alone had no detectable effect on leaf gas exchange. However, PWUE increased and PNUE decreased for both species at 40 g L −1 salinity compared to 10 g L −1 . At 40 g L −1 salinity, PNUE was higher for L. racemosa than R. mangle with tidal flooding. These treatments indicated that salinity influences gas exchange efficiency, might affect how gases are apportioned intercellularly, and accentuates different strategies for distributing leaf nitrogen to photosynthesis for these two species while growing competitively.

Florida;Louisiana↗
USGS2014

Developing a topographic model to predict the northern hardwood forest type within Carolina northern flying squirrel ( Glaucomys sabrinus coloratus ) recovery areas of the southern Appalachians

The northern hardwood forest type is an important habitat component for the endangered Carolina northern flying squirrel (CNFS; Glaucomys sabrinus coloratus ) for den sites and corridor habitats between boreo-montane conifer patches foraging areas. Our study related terrain data to presence of northern hardwood forest type in the recovery areas of CNFS in the southern Appalachian Mountains of western North Carolina, eastern Tennessee, and southwestern Virginia. We recorded overstory species composition and terrain variables at 338 points, to construct a robust, spatially predictive model. Terrain variables analyzed included elevation, aspect, slope gradient, site curvature, and topographic exposure. We used an information-theoretic approach to assess seven models based on associations noted in existing literature as well as an inclusive global model. Our results indicate that, on a regional scale, elevation, aspect, and topographic exposure index (TEI) are significant predictors of the presence of the northern hardwood forest type in the southern Appalachians. Our elevation + TEI model was the best approximating model (the lowest AICc score) for predicting northern hardwood forest type correctly classifying approximately 78% of our sample points. We then used these data to create region-wide predictive maps of the distribution of the northern hardwood forest type within CNFS recovery areas.

North Carolina, Tennessee, Virginia↗
USGS2025

Red spruce forest stand structure and Virginia northern flying squirrel habitat suitability

The Virginia northern flying squirrel ( Glaucomys sabrinus fuscus ; VNFS) is a rare, Pleistocene-relict, disjunct subspecies of the northern flying squirrel. The squirrel occurs only in high-elevation red spruce ( Picea rubens ) forests of the central Appalachian Mountains of Virginia and West Virginia—a forest type that was substantially reduced by exploitative logging and wildfire in the 1890s–1930. Owing to its cryptic nature and difficulty of capture, managers have relied on an evolving series of predicted habitat suitability models that primarily have used topographic measures and red spruce cover class to assess potential occupancy on the landscape. Currently, VNFS is considered the sentinel species in the region whereby its predicted presence indicates red spruce forests with higher relative habitat integrity, and unsuitable habitat highlights where red spruce restoration or enhancement should occur. However, extant VNFS models only use red spruce percent composition and do not provide insights into forest structure, such as forest canopy height or basal area, that are needed by managers to implement restoration or assess effectiveness. We examined recent historical VNFS observations from nest-box surveys and radiotelemetry data (natural dens and foraging points) relative to random pseudoabsence points across red spruce cover classes from the most current VNFS predicted probability habitat model. Using generalized linear models in an information-theoretic approach, we found that within each red spruce composition class, suitable VNFS habitat was related to increased forest canopy height (m), basal area (m 2 ·ha −1 ), quadratic mean diameter (cm), and stem density (number of trees ha −1 ), indicating that, within red spruce and mixed red spruce–northern hardwood forests, VNFS is associated most with mature forest conditions. Accordingly, our results could be recombined with habitat suitability models to prioritize where, for example, red spruce forest structural enhancement would facilitate shifting a given stand to a higher probability condition for VNFS use.

Maryland, Virginia, West Virginia↗
USGS2019

A bibliometric profile of the Remote Sensing Open Access Journal published by MDPI between 2009 and 2018

Remote Sensing Open Access Journal (RS OAJ) is an international leading journal in the field of remote sensing science and technology. It was first published in the year 2009 and is currently celebrating tenth year of publications. In this research, a bibliometric analysis of RS OAJ was conducted based on 5588 articles published during the 10-year (2009–2018) time-period. The bibliometric analysis includes a comprehensive set of indicators such as dynamics and trends of publications, journal impact factor, total cites, eigenfactor score, normalized eigenfactor, CiteScore, h-index, h-classic publications, most productive countries (or territories) and institutions, co-authorship collaboration about countries (territories), research themes, citation impact of co-occurrences keywords, intellectual structure, and knowledge commutation. We found that publications of RS OAJ presented an exponential growth in the past ten years. From 2010 to 2017 (for which complete years data were available), the h-index of RS OAJ is 67. From 2009–2018, RS OAJ includes publications from 129 countries (or territories) and 3826 institutions. The leading nations contributing articles, based on 2009–2018 data, and listed based on ranking were: China, United States, Germany, Italy, France, Spain, Canada, England, Australia, Netherlands, Japan, Switzerland and Austria. The leading institutions, also for the same period and listed based on ranking were: Chinese Academy of Sciences, Wuhan University, University of Chinese Academy of Sciences, Beijing Normal University, The university of Maryland, National Aeronautics and Space Administration, National Oceanic and Atmospheric Administration, China University of Geosciences, United States Geological Survey, German Aerospace Centre, University of Twente, and California Institute of Technology. For the year 2017, RS OAJ had an impressive journal impact factor of 3.4060, a CiteScore of 4.03, eigenfactor score of 0.0342, and normalized eigenfactor score of 3.99. In addition, based on 2009–2018, data co-word analysis determined that “remote sensing”, “MODIS”, “Landsat”, “LiDAR” and “NDVI” are the high-frequency of author keywords co-occurrence in RS OAJ. The main themes of RS OAJ are multi-spectral and hyperspectral remote sensing, LiDAR scanning and forestry remote sensing monitoring, MODIS and LAI data applications, Remote sensing applications and Synthetic Aperture Radar (SAR). Through author keywords citation impact analysis, we find the most influential keyword is Unmanned Aerial Vehicle (UAV), followed, forestry, Normalized Difference Vegetation Index (NDVI), terrestrial laser scanning, airborne laser scanning, forestry inventory, urban heat island, monitoring, agriculture, and laser scanning. By analyzing the intellectual structure of RS OAJ, we identify the main reference publications and find that the themes are about Random Forests, MODIS vegetation indices and image analysis, etc. RS OAJ ranks first in cited journals and third in citing, this indicates that RS OAJ has the internal knowledge flow. Our results will bring more benefits to scholars, researchers and graduate students, who hopes to get a quick overview of the RS OAJ. And this article will also be the starting point for communication between scholars and practitioners. Finally, this paper proposed a nuanced h-index (nh-index) to measure productivity and intellectual contribution of authors by considering h-index based on whether the one is first, second, third, or nth author. This nuanced approach to determining h-index of authors is powerful indicator of an academician’s productivity and intellectual contribution.

Remote Sensing↗
USGS2016

Historical reconstructions of California wildfires vary by data source

Historical data are essential for understanding how fire activity responds to different drivers. It is important that the source of data is commensurate with the spatial and temporal scale of the question addressed, but fire history databases are derived from different sources with different restrictions. In California, a frequently used fire history dataset is the State of California Fire and Resource Assessment Program (FRAP) fire history database, which circumscribes fire perimeters at a relatively fine scale. It includes large fires on both state and federal lands but only covers fires that were mapped or had other spatially explicit data. A different database is the state and federal governments’ annual reports of all fires. They are more complete than the FRAP database but are only spatially explicit to the level of county (California Department of Forestry and Fire Protection – Cal Fire) or forest (United States Forest Service – USFS). We found substantial differences between the FRAP database and the annual summaries, with the largest and most consistent discrepancy being in fire frequency. The FRAP database missed the majority of fires and is thus a poor indicator of fire frequency or indicators of ignition sources. The FRAP database is also deficient in area burned, especially before 1950. Even in contemporary records, the huge number of smaller fires not included in the FRAP database account for substantial cumulative differences in area burned. Wildfires in California account for nearly half of the western United States fire suppression budget. Therefore, the conclusions about data discrepancies and the implications for fire research are of broad importance.

California↗
USGS2025

Component identification of solid biomass fuels using reflected light microscopy: Interlaboratory study 2

As nations transition toward sustainable energy systems , biomass has become a vital component of global energy portfolios. Derived from organic materials such as wood, agricultural residues, forestry byproducts, and organic waste, biomass is a renewable energy source with significant environmental and economic benefits. Responsible biomass energy production can improve waste management, reduce emissions of greenhouse gases, and mitigate environmental pollution. However, as the diversity of biomass-derived fuels increases, robust quality assessment methods are essential to ensure their efficiency, safety, and minimal environmental impact. Reflected light microscopy (RLM) is one such technique with the potential to complement conventional physico-chemical analyses by enabling a rapid identification of material constituents and impurities. To refine this methodology and evaluate the reproducibility of solid biomass component identification using RLM, an interlaboratory study (ILS) was conducted. The study involved the recognition of 58 components across 45 photomicrographs, with the participation of 65 scientists and students from 25 countries. The participants faced high difficulty identifying some of the marked components, and as a result, the percentage of correct answers ranged from 19.0 % to 98.3 %, with an average correct identification rate of 62.7 %. The most challenging aspects of the identification process included distinguishing between woody and non-woody (agro) biomass, accurately identifying petroleum-derived materials, and differentiating agro biomass from inorganic matter. The results suggest that while RLM is an important tool for characterizing solid biomass, further development of methodology guidelines and training are necessary to enhance its effectiveness. Future research should prioritize preparing detailed, image-rich, microscopic morphological descriptions of biomass fuel components, which could improve the accuracy and reliability of using RLM in biomass fuel characterization.

International Journal of Coal Geology↗