scholarly journals Modeling Forest Type Transitions in the Southcentral Region: Results from Three Methods

2003 ◽  
Vol 27 (3) ◽  
pp. 190-197 ◽  
Author(s):  
Xiaoping Zhou ◽  
John R. Mills ◽  
Lawrence Teeter
Keyword(s):  
Renewable Resources ◽  
Forest Type ◽  
Hybrid Approach ◽  
Analysis Data ◽  
Forest Types ◽  
Transition Matrices ◽  
Usda Forest Service ◽  
Forest Inventory And Analysis ◽  
The Future ◽  
Resources Planning

Abstract In recent years much interest has developed about the dynamics of forest type transitions, especially the transitions of land to and from southern pine plantations. This article presents 50-yr-forest type projections developed from two approaches to specifying the type transition matrices. One approach used transition matrices derived with remeasured plot data for six forest types using USDA Forest Service Forest Inventory and Analysis data. These data tracked transitions that occurred either naturally or artificially on inventory plots during one remeasurement cycle. The second approach relied on expert opinion surveys that predicted trends in the future of forest management. The transition matrices were developed from the responses regarding managers' intentions to regenerate stands following harvest. The survey was developed for the 2000 Forest and Rangeland Renewable Resources Planning Act Timber Assessment (2000 RPA). The timber inventories in eight states in the southcentral United States are projected with these methods of handling type transitions, and the results are compared to the 2000 RPA, which used a combination or hybrid approach to type transitioning. All three techniques conclude the area of planted pine is expected to increase well into the future. They are contradictory, however, in predicting the area other forest types will occupy, especially natural pine and upland hardwoods. Projections based on recent history give us one result; projections based on managers' intentions show another. South. J. Appl. For. 27(3):190–197.

Contemporary status, distribution, and trends of mixedwoods in the northern United States

2021 ◽  
Author(s):  
Lance A. Vickers ◽  
Benjamin Knapp ◽  
John M Kabrick ◽  
Laura S. Kenefic ◽  
Anthony W. D'Amato ◽  
...  
Keyword(s):  
United States ◽  
New England ◽  
Analysis Data ◽  
Specific Information ◽  
Forest Types ◽  
Forest Inventory And Analysis ◽  
Mixedwood Forests ◽  
Contemporary Status ◽  
Northern United States ◽  
Abundance And Distribution

As interest in managing and maintaining mixedwood forests in the northern United States (US) grows, so does the importance of understanding their abundance and distribution. We analyzed Forest Inventory and Analysis data for insights into mixedwood forests spanning 24 northern US states from Maine south to Maryland and westward to Kansas and North Dakota. Mixedwoods, i.e., forests with both hardwoods and softwoods present but neither exceeding 75-80% of composition, comprise more than 19 million hectares and more than one-quarter of the northern US forest. They are most common in the Adirondack-New England, Laurentian, and Northeast ecological provinces but also occur elsewhere in hardwood-dominated ecological provinces. These mixtures are common even within forest types nominally categorized as either hardwood or softwood. The most common hardwoods within those mixtures were species of Quercus and Acer and the most common softwoods were species of Pinus, Tsuga, and Juniperus. Although mixedwoods exhibited stability in total area during our analysis period, hardwood saplings were prominent, suggesting widespread potential for eventual shifts to hardwood dominance in the absence of disturbances that favor regeneration of the softwood component. Our analyses suggest that while most mixedwood plots remained mixedwoods, harvesting commonly shifts mixedwoods to either hardwood- or softwood-dominated cover types but more specific information is needed to understand the causes of these shifts.

scholarly journals Loblolly and Slash Pine Growth and Yield Prediction for Regional Timber Supply Projection Algorithms

1999 ◽  
Vol 23 (4) ◽  
pp. 230-237
Author(s):  
Bruce E. Borders ◽  
Jeffrey B. Jordan
Keyword(s):  
Loblolly Pine ◽  
Analysis Data ◽  
Growth And Yield ◽  
Yield Prediction ◽  
Projection Algorithms ◽  
Timber Supply ◽  
Usda Forest Service ◽  
Forest Inventory And Analysis ◽  
Pine Stands ◽  
Growth And Yield Models

Abstract Regional and national timber supply models require standing inventory update procedures. To date, most inventory update procedures used in regional timber supply algorithms have not made use of growth and yield methodology. We present growth and yield models to update standing inventories for natural and planted slash and loblolly pine stands in Georgia. These models were fitted to USDA Forest Service Forest Inventory and Analysis data obtained from the sixth survey of Georgia and should prove useful in regional timber supply projection algorithms. South. J. Appl. For. 23(4):230-237.

Using Forest Inventory and Analysis Data to Support National Forest Management: Regional Case Studies

2020 ◽  
Vol 118 (3) ◽  
pp. 313-323 ◽  
Author(s):  
Coeli M Hoover ◽  
Renate Bush ◽  
Marin Palmer ◽  
Emrys Treasure
Keyword(s):  
Case Studies ◽  
Forest Inventory ◽  
Information Needs ◽  
Analysis Data ◽  
National Forest ◽  
Usda Forest Service ◽  
Forest Inventory And Analysis ◽  
Revision Process ◽  
Landscape Scales ◽  
The Many

Abstract Although many forestry practitioners have a general understanding of the Forest Inventory and Analysis (FIA) program and the type of data collected, most non-expert users of FIA reports and basic data are unlikely to be familiar with the breadth of information available and the many potential uses of the data. We present case studies from three USDA Forest Service regions to highlight a variety of applications of FIA data, from informing the forest plan revision process to supplying managers with timely information on important forest attributes at the stand and landscape scales. These examples illustrate the utility of FIA data in meeting managers’ information needs, the importance of the linkages between research and management throughout the agency, and the role that the FIA program can play in fostering those collaborations.

Assessment of Disturbances across Forest Inventory Plots in the Southeastern United States for the Period 1995–2018

2019 ◽  
Vol 66 (2) ◽  
pp. 242-255 ◽  
Author(s):  
Santosh K Ojha ◽  
Kozma Naka ◽  
Luben D Dimov
Keyword(s):  
United States ◽  
Coastal Plain ◽  
Forest Inventory ◽  
Stand Structure ◽  
Forest Type ◽  
Southeastern United States ◽  
Forest Types ◽  
Forest Inventory And Analysis ◽  
Silvicultural Treatments ◽  
Structure And Functions

Abstract Disturbances of varying frequency and intensity shape the species composition, stand structure, and functions of forests. This study assessed the frequency and distribution of disturbances caused by eight agents (insects, diseases, fire, animals, weather, other vegetation, human, and unknown) in the forests of the southeastern United States from 1995 to 2018. We used data from 88,722 inventory measurements of 33,531 plots from the USDA Forest Inventory and Analysis database to assess disturbance among different forest types and to different canopy strata. Disturbances were detected in approximately 14 percent of the plots, located mostly in pine-dominated forest types. Fire was the most frequent disturbance agent (occurring 6 percent of the time), followed by weather and animal agents. The agents that caused the highest mortality rate during the period for saplings were silvicultural treatments (8.6 percent), other vegetation (5.6 percent), and fire (4.4 percent), whereas for trees they were silvicultural treatments (9.8 percent), weather (1.9 percent) and insects (1.7 percent). The forest type that appeared to have been most affected by disturbances was longleaf–slash pine of the Coastal Plain. These results are useful for understanding the spatiotemporal distribution of disturbance events in different southeastern forest types and locations and for guiding forest management activities to mitigate potential impacts.

Assessing the Impact of 41 Years of Forest Management on Native Wildlife Habitat in Minnesota, USA

2021 ◽  
Author(s):  
John M Zobel ◽  
Alan R Ek ◽  
Christopher B Edgar
Keyword(s):  
Forest Management ◽  
Native Species ◽  
Forest Type ◽  
Analysis Data ◽  
Wildlife Habitat ◽  
Harvest Scheduling ◽  
Forest Types ◽  
Wildlife Species ◽  
Agricultural Regions ◽  
The Impact

Abstract Over the last four decades, forest management goals have transitioned to multiuse objectives, begging the question of their impact on wildlife habitat. Using USDA Forest Service Forest Inventory and Analysis data and the WHINGS (Wildlife Habitat Indicator for Native Genera and Species) model, the trends in wildlife habitat were quantified from 1977 to 2018 across Minnesota. Statewide, 35.5% of species experienced significant improvement in habitat, 29% significant reductions, and 35.5% nonsignificant change. The extent of habitat (acreage) increased for 100% of species, but the quality declined for 63% of species. Results were explained by the reduction in acreage of larger size classes of the aspen, balsam, and birch forest type and increases in smaller, younger forest area. Specifically, forest management that converted aspen stands to other forest types benefited certain wildlife species over others. Future forest management should consider the balance between the habitat requirements of the diverse native species in Minnesota. Study Implications Trends in forest wildlife habitat over the last four decades across Minnesota highlight that forest management often favors one species at the expense of another. Statewide, wildlife species with preferences for larger, older aspen experienced diminished habitat, whereas habitat for species preferring younger forest types or older nonaspen types increased. Regionally, the forested ecoregions in Minnesota (northeast) generally saw reduced habitat, whereas the prairie/agricultural regions (south and northwest) saw the largest increases. Through this and further applications, forest and wildlife managers can rapidly assess the habitat implications of proposed management, whether for environmental review, forest planning, or harvest scheduling.

Conterminous U.S. and Alaska Forest Type Mapping Using Forest Inventory and Analysis Data

2008 ◽  
Vol 74 (11) ◽  
pp. 1379-1388 ◽  
Author(s):  
B. Ruefenacht ◽  
M.V. Finco ◽  
M.D. Nelson ◽  
R. Czaplewski ◽  
E.H. Helmer ◽  
...  
Keyword(s):  
Forest Inventory ◽  
Forest Type ◽  
Analysis Data ◽  
Forest Inventory And Analysis ◽  
Type Mapping

Can machine learning be used to forecast the future uncertainty of military teams?

2021 ◽  
pp. 154851292199911
Author(s):  
Ronald H Stevens ◽  
Trysha L Galloway
Keyword(s):  
Machine Learning ◽  
Sensory Information ◽  
Fundamental Property ◽  
Transition Matrices ◽  
Team Members ◽  
Student Teams ◽  
The Future ◽  
Network States ◽  
Uncertainty Models ◽  
Military Teams

Uncertainty is a fundamental property of neural computation that becomes amplified when sensory information does not match a person’s expectations of the world. Uncertainty and hesitation are often early indicators of potential disruption, and the ability to rapidly measure uncertainty would have implications for future educational and training efforts by targeting reflective discussions about past actions, supporting in-progress corrections, and generating forecasts about future disruptions. An approach is described combining neurodynamics and machine learning to provide quantitative measures of uncertainty. Models of neurodynamic information derived from electroencephalogram (EEG) brainwaves have provided detailed neurodynamic histories of US Navy submarine navigation team members. Persistent periods (25–30 s) of neurodynamic information were seen as discrete peaks when establishing the submarine’s position and were identified as periods of uncertainty by an artificial intelligence (AI) system previously trained to recognize the frequency, magnitude, and duration of different patterns of uncertainty in healthcare and student teams. Transition matrices of neural network states closely predicted the future uncertainty of the navigation team during the three minutes prior to a grounding event. These studies suggest that the dynamics of uncertainty may have common characteristics across teams and tasks and that forecasts of their short-term evolution can be estimated.

Stratified forest inventory estimation with mapped plots

2005 ◽  
Vol 35 (10) ◽  
pp. 2382-2386 ◽  
Author(s):  
Paul C Van Deusen
Keyword(s):  
Forest Inventory ◽  
Forest Service ◽  
Forest Types ◽  
Inventory Data ◽  
Expansion Factor ◽  
Usda Forest Service ◽  
Weighted Estimation ◽  
Forest Conditions

Weighted estimation formulas are developed for producing stratified estimates of means and variances where data come from plots that can contain multiple forest conditions. Each plot is mapped to allow the analyst to focus on specific forest types or conditions. The weights required to accommodate mapped plots are somewhat more complicated than the weights for unmapped plots. In particular, these weights depend on the mapped condition of interest. The implication is that a single plot weight or expansion factor will not suffice for all analyses as it does for unmapped plots. The methods are demonstrated using USDA Forest Service inventory data.

scholarly journals Area-Wide Analysis of Hardwood Defoliator Effects on Tree Conditions in the Allegheny Plateau

2004 ◽  
Vol 21 (1) ◽  
pp. 31-39 ◽  
Author(s):  
Randall S. Morin ◽  
Andrew M. Liebhold ◽  
Kurt W. Gottschalk
Keyword(s):  
Tree Mortality ◽  
Forest Health ◽  
National Forest ◽  
Forest Land ◽  
Land Area ◽  
Usda Forest Service ◽  
Forest Inventory And Analysis ◽  
Allegheny Plateau ◽  
Using Data ◽  
Crown Dieback

Abstract The effects of defoliation caused by three foliage feeding insects, the gypsy moth (Lymantria dispar), the cherry scallopshell moth (Hydria prunivorata), and the elm spanworm (Ennomos subsignarius), on tree mortality and crown conditions were evaluated using data collected from 1984 to 1999 in the Allegheny National Forest located in northwestern Pennsylvania. While previous studies have focused on the effects of defoliation on trees in individual stands, this study differed in that it used exhaustive maps of defoliation and an areawide network of plots to assess these effects. A geographic information system was used to map the coincidence of USDA Forest Service Forest Inventory and Analysis and Forest Health Monitoring plot locations with defoliation polygons derived from aerial surveys to calculate cumulative years of defoliation for each pest. Over 85% of the Allegheny National Forest land area was defoliated at least once during the 16-year period from 1984 to 1999. Frequency of defoliation by specific defoliator species was closely associated with the dominance of their primary hosts in stands. Frequency of defoliation was often associated with crown dieback and mortality, but these relationships were not detectable in all species. These results suggest that when impacts are averaged over large areas (such as in this study) effects of defoliation are likely to be considerably less severe than when measured in selected stands (as is the approach taken in most previous impact studies).

Sign in / Sign up

Export Citation Format

Share Document