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Results for “Journal of Applied Forestry”

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23 records · Page 2Linked to original sources
USGS2018

Remote sensing analysis of vegetation at the San Carlos Apache Reservation, Arizona and surrounding area

Mapping of vegetation types is of great importance to the San Carlos Apache Tribe and their management of forestry and fire fuels. Various remote sensing techniques were applied to classify multitemporal Landsat 8 satellite data, vegetation index, and digital elevation model data. A multitiered unsupervised classification generated over 900 classes that were then recoded to one of the 16 generalized vegetation/land cover classes using the Southwest Regional Gap Analysis Project (SWReGAP) map as a guide. A supervised classification was also run using field data collected in the SWReGAP project and our field campaign. Field data were gathered and accuracy assessments were generated to compare outputs. Our hypothesis was that a resulting map would update and potentially improve upon the vegetation/land cover class distributions of the older SWReGAP map over the 24,000 km 2 study area. The estimated overall accuracies ranged between 43% and 75%, depending on which method and field dataset were used. The findings demonstrate the complexity of vegetation mapping, the importance of recent, high-quality-field data, and the potential for misleading results when insufficient field data are collected.

Arizona↗
USGS2015

Remote sensing change detection methods to track deforestation and growth in threatened rainforests in Madre de Dios, Peru

Two forestry-change detection methods are described, compared, and contrasted for estimating deforestation and growth in threatened forests in southern Peru from 2000 to 2010. The methods used in this study rely on freely available data, including atmospherically corrected Landsat 5 Thematic Mapper and Moderate Resolution Imaging Spectroradiometer (MODIS) vegetation continuous fields (VCF). The two methods include a conventional supervised signature extraction method and a unique self-calibrating method called MODIS VCF guided forest/nonforest (FNF) masking. The process chain for each of these methods includes a threshold classification of MODIS VCF, training data or signature extraction, signature evaluation, k-nearest neighbor classification, analyst-guided reclassification, and postclassification image differencing to generate forest change maps. Comparisons of all methods were based on an accuracy assessment using 500 validation pixels. Results of this accuracy assessment indicate that FNF masking had a 5% higher overall accuracy and was superior to conventional supervised classification when estimating forest change. Both methods succeeded in classifying persistently forested and nonforested areas, and both had limitations when classifying forest change.

Madre de Dios↗
USGS2010

Effects of precommercial thinning on snowshoe hares in Maine

Snowshoe hares (Lepus americanus) are an important prey species and a dominant herbivore across much of their North American range, and researchers have questioned the influences of forestry practices that alter habitat for hares and the potential community-level effects on carnivores. We examined the effects of precommercial thinning (PCT) from 1 to 11 years posttreatment on snowshoe hares. In the commercial forests of northern Maine, USA, we counted and cleared hare pellets twice a year during 2001 and 2002 on >46 km of pellet transects across 30 regenerating conifer stands (17 treated with PCT) previously treated with an aerial application of herbicide. We compared densities of snowshoe hare pellets among 3 development classes with (1 yr after thinning, 6 yr after thinning, and 11 yr after thinning) and without thinning (stands with a similar history of clearcut and herbicide treatment but no thinning). During both years, densities of hares were lower in stands treated with PCT than in similar unthinned stands across the 3 development classes and during both leaf-off and leaf-on seasons (P < 0.001). Within both thinned and unthinned stands, hare density was greatest in stands in the 1-year development class when compared to the 6-year and 11-year development classes, but a statistical difference (P = 0.048) among classes was evident only during leaf-off seasons. Precommercial thinning was associated with densities of snowshoe hares that were approximately half of those in similar unthinned stands up to at least 11 years posttreatment; however, thinned stands may retain densities of hares greater than stands managed using other forest harvesting regimes. Our results apply to core portions of stands with crop trees spaced at 1.8-2.4-m intervals following complete overstory removal and herbicide treatment. We advocate caution when applying our results to other thinning regimes or across broader spatial scales.

Journal of Wildlife Management↗
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↗
USGS2000

Chapter 4. Predicting post-fire erosion and sedimentation risk on a landscape scale

Historic fire suppression efforts have increased the likelihood of large wildfires in much of the western U.S. Post-fire soil erosion and sedimentation risks are important concerns to resource managers. In this paper we develop and apply procedures to predict post-fire erosion and sedimentation risks on a pixel-, catchment-, and landscape-scale in central and western Colorado. Our model for predicting post-fire surface erosion risk is conceptually similar to the Revised Universal Soil Loss Equation (RUSLE). One key addition is the incorporation of a hydrophobicity risk index (HY-RISK) based on vegetation type, predicted fire severity, and soil texture. Post-fire surface erosion risk was assessed for each 90-m pixel by combining HYRISK, slope, soil erodibility, and a factor representing the likely increase in soil wetness due to removal of the vegetation. Sedimentation risk was a simple function of stream gradient. Composite surface erosion and sedimentation risk indices were calculated and compared across the 72 catchments in the study area. When evaluated on a catchment scale, two-thirds of the catchments had relatively little post-fire erosion risk. Steeper catchments with higher fuel loadings typically had the highest post-fire surface erosion risk. These were generally located along the major north-south mountain chains and, to a lesser extent, in west-central Colorado. Sedimentation risks were usually highest in the eastern part of the study area where a higher proportion of streams had lower gradients. While data to validate the predicted erosion and sedimentation risks are lacking, the results appear reasonable and are consistent with our limited field observations. The models and analytic procedures can be readily adapted to other locations and should provide useful tools for planning and management at both the catchment and landscape scale.

Journal of Sustainable Forestry↗