Influence of tree spatial pattern and sample plot type and size on inventory

Treesearch

John-Pascall Berrill; Kevin L. O' Hara

2012-01-01

Sampling with different plot types and sizes was simulated using tree location maps and data collected in three even-aged coast redwood (Sequoia sempervirens) stands selected to represent uniform, random, and clumped spatial patterns of tree locations. Fixed-radius circular plots, belt transects, and variable-radius plots were installed by...

Land Use, Recreation, and Wildlife Habitats: GIS Applications Using FIA Plot Data

Treesearch

Victor A. Rudis

2001-01-01

Spatial contexts govern whether and how land is used. Forest surveys inventory land uses from sampled plots and provide common forest resource summaries with limited information about associated nearby uses, or the landscape context. I used the USDA Forest Service's Forest Inventory and Analysis program of the South-Central States survey region (Alabama, Arkansas...

Florida, 2011-forest inventory and analysis factsheet

Treesearch

Mark J. Brown; Jarek Nowak

2013-01-01

Forest Inventory and Analysis (FIA) factsheets are produced periodically to keep the public up to date on the extent and condition of the forest lands in each State. The forestrelated estimates in the factsheets are based upon data collected from thousands of sample plots distributed across the landscape in a systematic manner. The total number of these plots is...

Where are the Black Walnut Trees in Michigan? 1995

Treesearch

J. Michael Vasievich; Neal P. Kingsley

1995-01-01

The latest Michigan forest inventory was completed in 1993 by the North Central Forest Experiment Station and the Michigan DNR, Forest Management Division. In total, 18,484 sample points were examined on aerial photographs to identify ground sample plots. Of these, 10,849 forest plots were visited and measured on the ground by field crews. These plot measurements...

Sampling methods for titica vine (Heteropsis spp.) inventory in a tropical forest

Treesearch

Carine Klauberg; Edson Vidal; Carlos Alberto Silva; Michelliny de M. Bentes; Andrew Thomas Hudak

2016-01-01

Titica vine provides useful raw fiber material. Using sampling schemes that reduce sampling error can provide direction for sustainable forest management of this vine. Sampling systematically with rectangular plots (10× 25 m) promoted lower error and greater accuracy in the inventory of titica vines in tropical rainforest.

Application of an imputation method for geospatial inventory of forest structural attributes across multiple spatial scales in the Lake States, U.S.A

NASA Astrophysics Data System (ADS)

Deo, Ram K.

Credible spatial information characterizing the structure and site quality of forests is critical to sustainable forest management and planning, especially given the increasing demands and threats to forest products and services. Forest managers and planners are required to evaluate forest conditions over a broad range of scales, contingent on operational or reporting requirements. Traditionally, forest inventory estimates are generated via a design-based approach that involves generalizing sample plot measurements to characterize an unknown population across a larger area of interest. However, field plot measurements are costly and as a consequence spatial coverage is limited. Remote sensing technologies have shown remarkable success in augmenting limited sample plot data to generate stand- and landscape-level spatial predictions of forest inventory attributes. Further enhancement of forest inventory approaches that couple field measurements with cutting edge remotely sensed and geospatial datasets are essential to sustainable forest management. We evaluated a novel Random Forest based k Nearest Neighbors (RF-kNN) imputation approach to couple remote sensing and geospatial data with field inventory collected by different sampling methods to generate forest inventory information across large spatial extents. The forest inventory data collected by the FIA program of US Forest Service was integrated with optical remote sensing and other geospatial datasets to produce biomass distribution maps for a part of the Lake States and species-specific site index maps for the entire Lake State. Targeting small-area application of the state-of-art remote sensing, LiDAR (light detection and ranging) data was integrated with the field data collected by an inexpensive method, called variable plot sampling, in the Ford Forest of Michigan Tech to derive standing volume map in a cost-effective way. The outputs of the RF-kNN imputation were compared with independent validation datasets and extant map products based on different sampling and modeling strategies. The RF-kNN modeling approach was found to be very effective, especially for large-area estimation, and produced results statistically equivalent to the field observations or the estimates derived from secondary data sources. The models are useful to resource managers for operational and strategic purposes.

Annual design-based estimation for the annualized inventories of forest inventory and analysis: sample size determination

Treesearch

Hans T. Schreuder; Jin-Mann S. Lin; John Teply

2000-01-01

The Forest Inventory and Analysis units in the USDA Forest Service have been mandated by Congress to go to an annualized inventory where a certain percentage of plots, say 20 percent, will be measured in each State each year. Although this will result in an annual sample size that will be too small for reliable inference for many areas, it is a sufficiently large...

Forests of Michigan, 2013

Treesearch

Scott A. Pugh

2014-01-01

This publication provides an overview of forest resources in Michigan based on inventories conducted by the U.S. Forest Service, Forest Inventory and Analysis (FIA) program of the Northern Research Station. Since 1999, FIA has employed an annual inventory measuring data on a nominal 20 percent of sample plots each year. For the 2013 inventory, estimates for current...

Forests of Vermont, 2013

Treesearch

Randall S. Morin; Scott A. Pugh

2014-01-01

This publication provides an overview of forest resources in Vermont based on inventories conducted by the U.S. Forest Service, Forest Inventory and Analysis (FIA) program of the Northern Research Station. Since 1999, FIA has employed an annual inventory measuring data on a nominal 20 percent of sample plots each year. For the 2013 inventory, estimates for current...

Forests of New Hampshire, 2013

Treesearch

Randall S. Morin; Scott A. Pugh

2014-01-01

This publication provides an overview of forest resources in New Hampshire based on inventories conducted by the U.S. Forest Service, Forest Inventory and Analysis (FIA) program of the Northern Research Station. Since 1999, FIA has employed an annual inventory measuring data on a nominal 20 percent of sample plots each year. For the 2013 inventory, estimates for...

Comparison of a fully mapped plot design to three alternative designs for volume and area estimates using Maine inventory data

Treesearch

Stanford L. Arner

1998-01-01

A fully mapped plot design is compared to three alternative designs using data collected for the recent inventory of Maine's forest resources. Like the fully mapped design, one alternative eliminates the bias of previous procedures, and should be less costly and more consistent. There was little difference in volume and area estimates or in sampling errors among...

A novel statistical methodology to overcome sampling irregularities in the forest inventory data and to model forest changes under dynamic disturbance regimes

Treesearch

Nikolay Strigul; Jean Lienard

2015-01-01

Forest inventory datasets offer unprecedented opportunities to model forest dynamics under evolving environmental conditions but they are analytically challenging due to irregular sampling time intervals of the same plot, across the years. We propose here a novel method to model dynamic changes in forest biomass and basal area using forest inventory data. Our...

Sampling protocol, estimation, and analysis procedures for the down woody materials indicator of the FIA program

Treesearch

Christopher Woodall

2005-01-01

The Forest Inventory and Analysis (FIA) program of the USDA Forest Service conducts a national inventory of forests of the United States. A subset of FIA permanent inventory plots are sampled every year for numerous indicators of forest health ranging from soils to understory vegetation. Down woody material (DWM) is an FIA indicator that provides estimates of forest...

Effects of cycle length and plot density on estimators for a national-scale forest monitoring sample design

Treesearch

Francis A. Roesch; Todd A. Schroeder; James T. Vogt

2017-01-01

The resilience of a National Forest Inventory and Monitoring sample design can sometimes depend upon the degree to which it can adapt to fluctuations in funding. If a budget reduction necessitates the observation of fewer plots per year, some practitioners weigh the problem as a tradeoff between reducing the total number of plots and measuring the original number of...

Scaling wood volume estimates from inventory plots to landscapes with airborne LiDAR in temperate deciduous forest.

PubMed

Levick, Shaun R; Hessenmöller, Dominik; Schulze, E-Detlef

2016-12-01

Monitoring and managing carbon stocks in forested ecosystems requires accurate and repeatable quantification of the spatial distribution of wood volume at landscape to regional scales. Grid-based forest inventory networks have provided valuable records of forest structure and dynamics at individual plot scales, but in isolation they may not represent the carbon dynamics of heterogeneous landscapes encompassing diverse land-management strategies and site conditions. Airborne LiDAR has greatly enhanced forest structural characterisation and, in conjunction with field-based inventories, it provides avenues for monitoring carbon over broader spatial scales. Here we aim to enhance the integration of airborne LiDAR surveying with field-based inventories by exploring the effect of inventory plot size and number on the relationship between field-estimated and LiDAR-predicted wood volume in deciduous broad-leafed forest in central Germany. Estimation of wood volume from airborne LiDAR was most robust (R 2  = 0.92, RMSE = 50.57 m 3 ha -1  ~14.13 Mg C ha -1 ) when trained and tested with 1 ha experimental plot data (n = 50). Predictions based on a more extensive (n = 1100) plot network with considerably smaller (0.05 ha) plots were inferior (R 2  = 0.68, RMSE = 101.01 ~28.09 Mg C ha -1 ). Differences between the 1 and 0.05 ha volume models from LiDAR were negligible however at the scale of individual land-management units. Sample size permutation tests showed that increasing the number of inventory plots above 350 for the 0.05 ha plots returned no improvement in R 2 and RMSE variability of the LiDAR-predicted wood volume model. Our results from this study confirm the utility of LiDAR for estimating wood volume in deciduous broad-leafed forest, but highlight the challenges associated with field plot size and number in establishing robust relationships between airborne LiDAR and field derived wood volume. We are moving into a forest management era where field-inventory and airborne LiDAR are inextricably linked, and we encourage field inventory campaigns to strive for increased plot size and give greater attention to precise stem geolocation for better integration with remote sensing strategies.

The National Inventory of Down Woody Materials: Methods, Outputs, and Future Directions

Treesearch

Christopher W. Woodall

2003-01-01

The Forest Inventory and Analysis Program (FIA) of the USDA Forest Service conducts a national inventory of forests of the United States. A subset of FIA permanent inventory plots are sampled every year for numerous forest health indicators ranging fiom soils to understory vegetation. Down woody material (DWM) is an FIA indicator that refines estimation of forest...

Estimating Uncertainty in Annual Forest Inventory Estimates

Treesearch

Ronald E. McRoberts; Veronica C. Lessard

1999-01-01

The precision of annual forest inventory estimates may be negatively affected by uncertainty from a variety of sources including: (1) sampling error; (2) procedures for updating plots not measured in the current year; and (3) measurement errors. The impact of these sources of uncertainty on final inventory estimates is investigated using Monte Carlo simulation...

Alternative sampling designs and estimators for annual surveys

Treesearch

Paul C. Van Deusen

2000-01-01

Annual forest inventory systems in the United States have generally converged on sampling designs that: (1) measure equal proportions of the total number of plots each year; and (2) call for the plots to be systematically dispersed. However, there will inevitably be a need to deviate from the basic design to respond to special requests, natural disasters, and budgetary...

Effects of plot size on forest-type algorithm accuracy

Treesearch

James A. Westfall

2009-01-01

The Forest Inventory and Analysis (FIA) program utilizes an algorithm to consistently determine the forest type for forested conditions on sample plots. Forest type is determined from tree size and species information. Thus, the accuracy of results is often dependent on the number of trees present, which is highly correlated with plot area. This research examines the...

Composition, biomass and structure of mangroves within the Zambezi River Delta

Treesearch

Carl C. Trettin; Christina E. Stringer; Stan Zarnoch

2015-01-01

We used a stratified random sampling design to inventory the mangrove vegetation within the Zambezi River Delta, Mozambique, to provide a basis for estimating biomass pools. We used canopy height, derived from remote sensing data, to stratify the inventory area, and then applied a spatial decision support system to objectively allocate sample plots among five...

True versus perturbed forest inventory plot locations for modeling: a simulation study

Treesearch

John W. Coulston; Kurt H. Riitters; Ronald E. McRoberts; William D. Smith

2006-01-01

USDA Forest Service Forest Inventory and Analysis plot information is widely used for timber inventories, forest health assessments, and environmental risk analyses. With few exceptions, true plot locations are not revealed; the plot coordinates are manipulated to obscure the location of field plots and thereby preserve plot integrity. The influence of perturbed plot...

Forests of Maryland, 2016

Treesearch

Tonya W. Lister

2017-01-01

This publication provides an overview of forest resources in Maryland based on inventories conducted by the U.S. Forest Service, Forest Inventory and Analysis (FIA) program of the Northern Research Station. From 2004-2013, FIA employed an annual inventory measuring data on 20 percent of all sample plots each year in Maryland. Beginning in 2014, FIA is on a 7-year cycle...

Forests of Delaware, 2015

Treesearch

Tonya Lister; Richard Widmann

2016-01-01

This publication provides an overview of forest resources in Delaware based on inventories conducted by the U.S. Forest Service, Forest Inventory and Analysis (FIA) program of the Northern Research Station. From 2004-2013, FIA employed an annual inventory with a cycle length of 5 years, measuring data on 20 percent of all sample plots each year in Delaware. Beginning...

Forests of Maryland, 2015

Treesearch

Tonya Lister; Richard Widmann

2016-01-01

This publication provides an overview of forest resources in Maryland based on inventories conducted by the U.S. Forest Service, Forest Inventory and Analysis (FIA) program of the Northern Research Station. From 2004-2013, FIA employed an annual inventory, measuring 20 percent of all sample plots each year in Maryland. Beginning in 2014, FIA is on a 7-year cycle,...

Forests of Delaware, 2016

Treesearch

Stephen Potter

2017-01-01

This publication provides an overview of forest resources in Delaware based on inventories conducted by the U.S. Forest Service, Forest Inventory and Analysis (FIA) program of the Northern Research Station. From 2004-2013, FIA employed an annual inventory with a cycle length of 5 years, measuring data on 20 percent of all sample plots each year in Delaware. Beginning...

Crown-condition classification: a guide to data collection and analysis

Treesearch

Michael E. Schomaker; Stanley J. Zarnoch; William A. Bechtold; David J. Latelle; William G. Burkman; Susan M. Cox

2007-01-01

The Forest Inventory and Analysis (FIA) Program of the Forest Service, U.S. Department of Agriculture, conducts a national inventory of forests across the United States. A systematic subset of permanent inventory plots in 38 States is currently sampled every year for numerous forest health indicators. One of these indicators, crown-condition classification, is designed...

Forests of Delaware, 2014

Treesearch

T.W. Lister; R.H. Widmann

2015-01-01

This publication provides an overview of forest resources in Delaware based on inventories conducted by the U.S. Forest Service, Forest Inventory and Analysis (FIA) program of the Northern Research Station. From 2004-2013, FIA employed an annual inventory with a cycle length of 5 years, measuring data on 20 percent of all sample plots each year in Delaware. Beginning...

Forests of Maryland, 2014

Treesearch

T.W. Lister; R.H. Widmann

2015-01-01

This publication provides an overview of forest resources in Maryland based on inventories conducted by the U.S. Forest Service, Forest Inventory and Analysis (FIA) program of the Northern Research Station. From 2004-2013, FIA employed an annual inventory measuring data on 20 percent of all sample plots each year in Maryland. Beginning in 2014, FIA is on a 7-year cycle...

A test of point-sampling in northern hardwoods

Treesearch

Dale S. Solomon

1975-01-01

Plot- and point-sampling were compared with a complete inventory of two different stands of northern hardwoods. Prisms with basal-area factors of 5, 10, 20, 30, and 40 and a ¼-acre plot were used. Only the 5-factor prism gave a significantly different estimate. Therefore, a prism factor of 10 or greater is suggested for use in northern hardwoods.

An evaluation of the properties of the variance estimator used by FIA

Treesearch

John P. Brown; James A. Westfall

2012-01-01

The Forest Inventory and Analysis (FIA) program of the U.S. Forest Service currently conducts inventories utilizing the protocols of the national enhanced FIA Program. Due to the permanent locations of the sample plots, the stratification of the population occurs after the selection of sample units, i.e., post-stratification. In situations where the population is of...

Virginia, 2012 - forest inventory and analysis factsheet

Treesearch

Anita K. Rose

2014-01-01

This science update is a brief look at some of the basic metrics that describe the status of and changes in forest resources in Virginia. Estimates presented here are for the measurement year 2012. Information for the factsheets is updated by means of the Forest Inventory and Analysis (FIA) annualized sample design. Each year 20 percent of the sample plots (one panel)...

Virginia, 2011 forest inventory and analysis factsheet

Treesearch

Anita K. Rose

2013-01-01

This science update is a brief look at some of the basic metrics that describe the status and trends of forest resources in Virginia. Estimates presented here are for the measurement year 2011. Information for the factsheets is updated by means of the Forest Inventory and Analysis (FIA) annualized sample design. Each year 20 percent of the sample plots (one panel) in...

Virginia, 2010 forest inventory and analysis factsheet

Treesearch

Anita K. Rose

2012-01-01

This science update is a brief look at some of the basic metrics that describe the status of forest resources in Virginia. Estimates presented here are for the measurement year 2010. Information for this factsheet is updated by means of the Forest Inventory and Analysis (FIA) annualized sample design. Virginia has about 4,600 sample plots across the State and each year...

Virginia, 2009 forest inventory and analysis factsheet

Treesearch

Anita K. Rose

2011-01-01

This science update is a brief look at some of the basic metrics that describe forest resources in Virginia. Estimates presented here are for the measurement year 2009. Information for the factsheet is updated by means of the Forest Inventory and Analysis (FIA) annualized sample design. Virginia has about 4,600 sample plots across the State, and each year 20 percent of...

The use of multiple imputation in the Southern Annual Forest Inventory System

Treesearch

Gregory A. Reams; Joseph M. McCollum

2000-01-01

The Southern Research Station is currently implementing an annual forest survey in 7 of the 13 States that it is responsible for surveying. The Southern Annual Forest Inventory System (SAFIS) sampling design is a systematic sample of five interpenetrating grids, whereby an equal number of plots are measured each year. The area-representative and time-series...

The use of multiple imputation in the Southern Annual Forest Inventory System

Treesearch

Gregory A. Reams; Joseph M. McCollum

2000-01-01

The Southern Research Station is currently implementing an annual forest survey in 7 of the 13 states that it is responsible for surveying. The Southern Annual Forest Inventory System (SAFIS) sampling design is a systematic sample of five interpenetrating grids, whereby an equal number of plots are measured each year. The area representative and time series nature of...

Comparing alternatives for increasing sampling intensity in forest inventories

Treesearch

J. Blackard; P. Patterson

2014-01-01

Each of the U.S. Forest Service’s Forest Inventory and Analysis (FIA) regions has an occasional need to intensify the national sampling grid. A variety of methodologies exist within the various FIA regions and National Forest Systems regions for constructing plot intensifications, and there is no consensus on a national procedure The primary objectives of this paper...

Statistics and quality assurance for the Northern Research Station Forest Inventory and Analysis Program, 2016

Treesearch

Dale D. Gormanson; Scott A. Pugh; Charles J. Barnett; Patrick D. Miles; Randall S. Morin; Paul A. Sowers; Jim Westfall

2017-01-01

The U.S. Forest Service Forest Inventory and Analysis (FIA) program collects sample plot data on all forest ownerships across the United States. FIA's primary objective is to determine the extent, condition, volume, growth, and use of trees on the Nation's forest land through a comprehensive inventory and analysis of the Nation's forest resources. The...

Plots, pixels, and partnerships: prospects for mapping, monitoring and modeling biodiversity.

Treesearch

H. Gyde Lund; Victor A. Rudis; Kenneth W. Stolte

1998-01-01

Many biodiversity inventories are conducted in relatively small areas, yet information is needed at the national, regional, and global levels.Most nations have forest inventory plot networks.While forest inventories may not contain the detailed species information that biodiversity inventories do, the forest inventory plot networks do represent large areas.Linkages...

Effects of field plot size on prediction accuracy of aboveground biomass in airborne laser scanning-assisted inventories in tropical rain forests of Tanzania.

PubMed

Mauya, Ernest William; Hansen, Endre Hofstad; Gobakken, Terje; Bollandsås, Ole Martin; Malimbwi, Rogers Ernest; Næsset, Erik

2015-12-01

Airborne laser scanning (ALS) has recently emerged as a promising tool to acquire auxiliary information for improving aboveground biomass (AGB) estimation in sample-based forest inventories. Under design-based and model-assisted inferential frameworks, the estimation relies on a model that relates the auxiliary ALS metrics to AGB estimated on ground plots. The size of the field plots has been identified as one source of model uncertainty because of the so-called boundary effects which increases with decreasing plot size. Recent research in tropical forests has aimed to quantify the boundary effects on model prediction accuracy, but evidence of the consequences for the final AGB estimates is lacking. In this study we analyzed the effect of field plot size on model prediction accuracy and its implication when used in a model-assisted inferential framework. The results showed that the prediction accuracy of the model improved as the plot size increased. The adjusted R 2 increased from 0.35 to 0.74 while the relative root mean square error decreased from 63.6 to 29.2%. Indicators of boundary effects were identified and confirmed to have significant effects on the model residuals. Variance estimates of model-assisted mean AGB relative to corresponding variance estimates of pure field-based AGB, decreased with increasing plot size in the range from 200 to 3000 m 2 . The variance ratio of field-based estimates relative to model-assisted variance ranged from 1.7 to 7.7. This study showed that the relative improvement in precision of AGB estimation when increasing field-plot size, was greater for an ALS-assisted inventory compared to that of a pure field-based inventory.

Comparison of estimation techniques for a forest inventory in which double sampling for stratification is used

Treesearch

Michael S. Williams

2001-01-01

A number of different estimators can be used when forest inventory plots cover two or more distinctly different condition classes. In this article the properties of two approximate Horvitz- Thompson (HT) estimators, a ratio of means (RM), and a mean of ratios (MR) estimator are explored in the framework of double sampling for stratification. Relevant theoretical...

Volume equations for the Northern Research Station's Forest Inventory and Analysis Program as of 2010

Treesearch

Patrick D. Miles; Andrew D. Hill

2010-01-01

The U.S. Forest Service's Forest Inventory and Analysis (FIA) program collects sample plot data on all forest ownerships across the United States. This report documents the methodology used to estimate live-tree gross, net, and sound volume for the 24 States inventoried by the Northern Research Station's (NRS) FIA unit. Sound volume is of particular interest...

The enhanced forest inventory and analysis program of the USDA forest service: historical perspective and announcements of statistical documentation

Treesearch

Ronald E. McRoberts; William A. Bechtold; Paul L. Patterson; Charles T. Scott; Gregory A. Reams

2005-01-01

The Forest Inventory and Analysis (FIA) program of the USDA Forest Service has initiated a transition from regional, periodic inventories to an enhanced national FIA program featuring annual measurement of a proportion of plots in each state, greater national consistency, and integration with the ground sampling component of the Forest Health Monitoring (FHM) program...

A timer inventory based upon manual and automated analysis of ERTS-1 and supporting aircraft data using multistage probability sampling. [Plumas National Forest, California

NASA Technical Reports Server (NTRS)

Nichols, J. D.; Gialdini, M.; Jaakkola, S.

1974-01-01

A quasi-operational study demonstrating that a timber inventory based on manual and automated analysis of ERTS-1, supporting aircraft data and ground data was made using multistage sampling techniques. The inventory proved to be a timely, cost effective alternative to conventional timber inventory techniques. The timber volume on the Quincy Ranger District of the Plumas National Forest was estimated to be 2.44 billion board feet with a sampling error of 8.2 percent. Costs per acre for the inventory procedure at 1.1 cent/acre compared favorably with the costs of a conventional inventory at 25 cents/acre. A point-by-point comparison of CALSCAN-classified ERTS data with human-interpreted low altitude photo plots indicated no significant differences in the overall classification accuracies.

Strategies for minimizing sample size for use in airborne LiDAR-based forest inventory

USGS Publications Warehouse

Junttila, Virpi; Finley, Andrew O.; Bradford, John B.; Kauranne, Tuomo

2013-01-01

Recently airborne Light Detection And Ranging (LiDAR) has emerged as a highly accurate remote sensing modality to be used in operational scale forest inventories. Inventories conducted with the help of LiDAR are most often model-based, i.e. they use variables derived from LiDAR point clouds as the predictive variables that are to be calibrated using field plots. The measurement of the necessary field plots is a time-consuming and statistically sensitive process. Because of this, current practice often presumes hundreds of plots to be collected. But since these plots are only used to calibrate regression models, it should be possible to minimize the number of plots needed by carefully selecting the plots to be measured. In the current study, we compare several systematic and random methods for calibration plot selection, with the specific aim that they be used in LiDAR based regression models for forest parameters, especially above-ground biomass. The primary criteria compared are based on both spatial representativity as well as on their coverage of the variability of the forest features measured. In the former case, it is important also to take into account spatial auto-correlation between the plots. The results indicate that choosing the plots in a way that ensures ample coverage of both spatial and feature space variability improves the performance of the corresponding models, and that adequate coverage of the variability in the feature space is the most important condition that should be met by the set of plots collected.

Estimating tree species richness from forest inventory plot data

Treesearch

Ronald E. McRoberts; Dacia M. Meneguzzo

2007-01-01

Montreal Process Criterion 1, Conservation of Biological Diversity, expresses species diversity in terms of number of forest dependent species. Species richness, defined as the total number of species present, is a common metric for analyzing species diversity. A crucial difficulty in estimating species richness from sample data obtained from sources such as inventory...

Forests of Illinois, 2017

Treesearch

Susan J. Crocker

2018-01-01

This update provides an overview of forest resources in Illinois following an inventory by the USDA Forest Service, Forest Inventory and Analysis program, Northern Research Station. Estimates are derived from field data collected using an annualized sample design. Current variable estimates such as area and volume are based on 5,994 (1,046 forested) plots measured in...

Evaluating imputation and modeling in the North Central region

Treesearch

Ronald E. McRoberts

2000-01-01

The objectives of the North Central Research Station, USDA Forest Service, in developing procedures for annual forest inventories include establishing the capability of producing annual estimates of timber volume and related variables. The inventory system developed to accomplish these objectives features an annual sample of measured field plots and techniques for...

Modeling post-fire woody carbon dynamics with data from remeasured inventory plots

Treesearch

Bianca N.I. Eskelson; Jeremy Fried; Vicente Monleon

2015-01-01

In California, the Forest Inventory and Analysis (FIA) plots within large fires were visited one year after the fire occurred resulting in a time series of measurements before and after fire. During this additional plot visit, the standard inventory measurements were augmented for these burned plots to assess fire effects. One example of the additional measurements is...

Practical Considerations When Using Perturbed Forest Inventory Plot Locations To Develop Spatial Models: A Case Study

Treesearch

John W. Coulston; Gregory A. Reams; Ronald E. McRoberts; William D. Smith

2006-01-01

U.S. Department of Agriculture Forest Service Forest Inventory and Analysis plot information is used in many capacities including timber inventories, forest health assessments, and environmental risk analyses. With few exceptions, actual plot locations cannot be revealed to the general public. The public does, however, have access to perturbed plot coordinates. The...

Regional variation in Caribbean dry forest tree species composition

Treesearch

Janet Franklin; Julie Ripplinger; Ethan H. Freid; Humfredo Marcano-Vega; David W. Steadman

2015-01-01

How does tree species composition vary in relation to geographical and environmental gradients in a globally rare tropical/subtropical broadleaf dry forest community in the Caribbean? We analyzed data from 153 Forest Inventory and Analysis (FIA) plots from Puerto Rico and the U.S. Virgin Islands (USVI), along with 42 plots that we sampled in the Bahamian Archipelago (...

Statistics and quality assurance for the Northern Research Station Forest Inventory and Analysis Program

Treesearch

Dale D. Gormanson; Scott A. Pugh; Charles J. Barnett; Patrick D. Miles; Randall S. Morin; Paul A. Sowers; James A. Westfall

2018-01-01

The U.S. Forest Service Forest Inventory and Analysis (FIA) program collects sample plot data on all forest ownerships across the United States. FIA’s primary objective is to determine the extent, condition, volume, growth, and use of trees on the Nation’s forest land through a comprehensive inventory and analysis of the Nation’s forest resources. The FIA program...

Calibration and Application of FOREST-BGC in NorthWestern of Portugal

NASA Astrophysics Data System (ADS)

Rodrigues, M. A.; Lopes, D. M.; Leite, M. S.; Tabuada, V. M.

2010-05-01

Net primary production (NPP) is one of the most important variables in terms of ecosystems inventory and management, because it quantifies its growth and reflects the impact of biotic and abiotic factors, which could affect it. Interest in NP has increased recently because of the increasing interesting in climate change and the need in understanding its impact on the environment. There are ecophysiologic models, as Forest-BGC that allow for estimating NPP. The types of models offer a possible methodology to test these phenomena, beyond temporal and spatial scales, not available with tradicional inventory methodologies. To analyze the Forest-BGC performance, NPP data obtained with model were compared with collected data in the field, in the same sampling plots. For a parameterization and validation of the FOREST-BGC, this study was carried on based on 500m2 sampling plots from the National Forest Inventory 2006 and are located in several County Halls of the district of Vila Real, Portugal (Montalegre, Chaves, Valpaços, Boticas, Vila Pouca de Aguiar, Murça, Mondim de Basto, Alijó, Sabrosa and Vila Real). In order to quantify Biomass dinamics, we have selected 45 sampling plots: 19 from Pinus pinaster stands, 17 from Quercus pyreneica and 10 from mixed of Quercus with Pinus. Adaptation strategies for climate change impacts can be proposed based on these research results.

Modeled forest inventory data suggest climate benefits from fuels management

Treesearch

Jeremy S. Fried; Theresa B. Jain; Jonathan. Sandquist

2013-01-01

As part of a recent synthesis addressing fuel management in dry, mixed-conifer forests we analyzed more than 5,000 Forest Inventory and Analysis (FIA) plots, a probability sample that represents 33 million acres of these forests throughout Washington, Oregon, Idaho, Montana, Utah, and extreme northern California. We relied on the BioSum analysis framework that...

North Carolina, 2011 forest inventory and analysis factsheet

Treesearch

Mark J. Brown; Barry D. New

2013-01-01

Forest Inventory and Analysis (FIA) factsheets are produced periodically to keep the public updated on the extent and condition of forest lands in each State. Estimates in the factsheets are based upon data collected from thousands of sample plots distributed across the landscape in a systematic manner. In North Carolina, this process is a collaborative effort between...

Evaluating Classified MODIS Satellite Imagery as a Stratification Tool

Treesearch

Greg C. Liknes; Mark D. Nelson; Ronald E. McRoberts

2004-01-01

The Forest Inventory and Analysis (FIA) program of the USDA Forest Service collects forest attribute data on permanent plots arranged on a hexagonal network across all 50 states and Puerto Rico. Due to budget constraints, sample sizes sufficient to satisfy national FIA precision standards are seldom achieved for most inventory variables unless the estimation process is...

Mapping U.S. forest biomass using nationwide forest inventory data and moderate resolution information

Treesearch

J. A. Blackard; M. V. Finco; E. H. Helmer; G. R. Holden; M. L. Hoppus; D.M. Jacobs; A. J. Lister; G. G. Moisen; M. D. Nelson; R. Riemann; B. Ruefenacht; D. Salajanu; D. L. Weyermann; K. C. Winterberger; T. J. Brandeis; R. L. Czaplewski; R. E. McRoberts; P. L. Patterson; R. P. Tymcio

2008-01-01

A spatially explicit dataset of aboveground live forest biomass was made from ground measured inventory plots for the conterminous U.S., Alaska and Puerto Rico. The plot data are from the USDA Forest Service Forest Inventory and Analysis (FIA) program. To scale these plot data to maps, we developed models relating field-measured response variables to plot attributes...

Approach of regionalisation c-stocks in forest soils on a national level

NASA Astrophysics Data System (ADS)

Wellbrock, Nicole; Höhle, Juliane; Dühnelt, Petra; Holzhausen, Marieanna

2010-05-01

Introduction In December 2006, the German government decided to manage forests as carbon sinks to reduce greenhouse gas emissions in accordance with Article 3.4 of the Kyoto Protocol. The National Forest Monitoring data contribute to the fulfilment of these reporting commitments. In Germany, National Forest Monitoring includes the systematical extensive National Soil Condition Survey (BZE) and the detailed case studies (Level-II) which determine the processes within forests. This complex monitoring system is appropriate to Germany's greenhouse gas reporting (THG 2008 to 2012). The representative BZE plots can be used to obtain regional data for the National Carbon Stock Inventory. Here, an approach adopting a combination of geostatistics and regression analysis is preferred. The difficulty of showing the statistical significance of expected small changes while carbon stocks are generally high is one of the major challenges in carbon stock monitoring. However, through intensive preparation and cooperation with the forestry authorities of each federal state, the errors uncured in determining changes in carbon stocks in forest soils, which must be stipulated in greenhouse gas monitoring, could be minimised. In contrast to the detailed soil case studies, in which essentially the sources of error occur repeatedly in carbon stock change calculations, the BZE data can be stratified to form plots with homogenous properties, thereby reducing the standard error of estimate. Subsequently, the results of the stratification are projected across Germany, the reporting unit for greenhouse gas monitoring. National Forest Monitoring The BZE represents a national, systematic sampling inventory of the condition of forest soils. The first BZE inventory (BZE I: 1987 to 1993) was carried out on a systematic 8 x 8 km grid on the same sampling plots adopted in the Forest Condition Survey (WZE). In some areas the network of sampling plots involves 1900 grid points. The first BZE I survey was repeated after 15 years, between 2006 and 2008, by the national and the state authorities in cooperation. Afterwards, extensive laboratory and statistical analyses were conducted. Necessary parameters are listed in table 1. Upscaling approach There are different approaches for presenting extensive carbon stock data (Baritz et al., 2006). The availability of georeference plots means one can merge the point data with map data. In Germany, an approach was tested that used homogenous soil areas und plot-information from the national soil inventory. For every soil area c-stocks were regionalised. Only information form BZE-plots were involved which were characteristic for the soil area. The indicators were soil type and substrate class. For every soil area the forest areas were taken in account to calculate c-stock per forest area. The sum of every c-stock per soil area is the c-stock in forest soils of Germany. Tab.1: List of parameters for the carbon inventory (BZE II) Components Parameters Point level Field sampling Width of depth classes, Fine roots, humus (< 2 cm), dry bulk density, stone content, area of humus layer sampled, height a.s.l., litterfall, deadwood (from 10 cm) Analysis C content, fine soil fraction, weight of humus layer, Carbon stock calculations Carbon stock Regional Level Plot Soil type, parent material, vegetation type or forest Regionalisation Soil and land use maps, statistical models, ecological regions, digital elevation models, climate regions

Advancements in LiDAR-based registration of FIA field plots

Treesearch

Demetrios Gatziolis

2012-01-01

Meaningful integration of National Forest Inventory field plot information with spectral imagery acquired from satellite or airborne platforms requires precise plot registration. Global positioning system-based plot registration procedures, such as the one employed by the Forest Inventory and Analysis (FIA) Program, yield plot coordinates that, although adequate for...

Maintaining the confidentiality of plot locations by exploiting the low sensitivity of forest structure models to different spectral extraction kernels

Treesearch

Sean P. Healey; Elizabeth Lapoint; Gretchen G. Moisen; Scott L. Powell

2011-01-01

The United States Forest Service Forest Inventory and Analysis (FIA) unit maintains a large national network of inventory plots.While the consistency and extent of this network make FIA data attractive for ecological modelling, the FIA is charged by statute not to publicly reveal inventory plot locations. However, use of FIA plot data by the remote sensing community...

Potential applications of prefield land use and canopy cover data: Examples from nonforest and nonsampled forest inventory plots

Treesearch

Sara A. Goeking

2012-01-01

The Forest Inventory and Analysis (FIA) prefield workflow involves interpreting aerial imagery to determine whether each plot in a given inventory year may meet FIA’s definition of forest land. The primary purpose of this determination is to minimize inventory costs by avoiding unnecessary ground surveys of plots that are obviously in nonforest areas. Since the...

Comparison of Imputation Procedures for Replacing Denied-access Plots

Treesearch

Susan L. King

2005-01-01

In forest inventories, missing plots are caused by hazardous terrain, inaccessible locations, or denied access. Maryland had a large number of denied-access plots in the latest periodic inventory conducted by the Northeastern Forest Inventory and Analysis unit. The denial pattern, which can introduce error into the estimates, was investigated by dropping the 1999...

Conducting tests for statistically significant differences using forest inventory data

Treesearch

James A. Westfall; Scott A. Pugh; John W. Coulston

2013-01-01

Many forest inventory and monitoring programs are based on a sample of ground plots from which estimates of forest resources are derived. In addition to evaluating metrics such as number of trees or amount of cubic wood volume, it is often desirable to make comparisons between resource attributes. To properly conduct statistical tests for differences, it is imperative...

Analyzing lichen indicator data in the Forest Inventory and Analysis Program

Treesearch

Susan Will-Wolf

2010-01-01

Lichens are one of several forest health indicators sampled every year for a subset of plots on the permanent grid established by the Forest Inventory and Analysis (FIA) Program of the U.S. Department of Agriculture Forest Service. This report reviews analysis procedures for standard FIA lichen indicator data. Analyses of lichen data contribute to state, regional, and...

State-of-the-art technologies of forest inventory and monitoring in Taiwan

Treesearch

Fong-Long Feng

2000-01-01

Ground surveys, remote sensing (RS), global positioning systems (GPS), geographic information systems (GIS), and permanent sampling plots (PSP) were used to inventory and monitor forests in the development of an ecosystem management plan for the island of Taiwan. While the entire island has been surveyed, this study concentrates on the Hui-Sun and Hsin-Hua Experimental...

A simplified Forest Inventory and Analysis database: FIADB-Lite

Treesearch

Patrick D. Miles

2008-01-01

This publication is a simplified version of the Forest Inventory and Analysis Data Base (FIADB) for users who do not need to compute sampling errors and may find the FIADB unnecessarily complex. Possible users include GIS specialists who may be interested only in identifying and retrieving geographic information and per acre values for the set of plots used in...

Big trees in the southern forest inventory

Treesearch

Christopher M. Oswalt; Sonja N. Oswalt; Thomas J. Brandeis

2010-01-01

Big trees fascinate people worldwide, inspiring respect, awe, and oftentimes, even controversy. This paper uses a modified version of American Forests’ Big Trees Measuring Guide point system (May 1990) to rank trees sampled between January of 1998 and September of 2007 on over 89,000 plots by the Forest Service, U.S. Department of Agriculture, Forest Inventory and...

Forest inventory and analysis data for FVS modelers

Treesearch

Patrick D. Miles

2008-01-01

The USDA Forest Service, Forest Inventory and Analysis (FIA) program has been in continuous operation for over 70 years. FIA’s primary objective is to determine the extent, condition, volume, growth, and depletion of timber on the Nation’s forest land. To accomplish this objective, FIA collects sample plot information on all ownerships across the United States.

Application of mapped plots for single-owner forest surveys

Treesearch

Paul C. Van Deusen; Francis Roesch

2009-01-01

Mapped plots are used for the nation forest inventory conducted by the U.S. Forest Service. Mapped plots are also useful foro single ownership inventoires. Mapped plots can handle boundary overlap and can aprovide less variable estimates for specified forest conditions. Mapping is a good fit for fixed plot inventories where the fixed area plot is used for both mapping...

Pilot Inventory of mammals, reptiles, and amphibians, Golden Gate National Recreation Area, California, 1990-1997

USGS Publications Warehouse

Semenoff-Irving, M.; Howell, J.A.

2005-01-01

The United States Geological Survey Golden Gate Field Station conducted a baseline inventory of terrestrial vertebrates within the Golden Gate National Recreation Area (GGNRA), Marin, San Francisco, and San Mateo Counties, California between 1990 and 1997. We established 456 permanent study plots in 6 major park habitats, including grassland, coastal scrub, riparian woodland, coastal wetland, broad-leaved evergreen forest, and needle-leaved evergreen forest. We tested multiple inventory methods, including live traps, track plate stations, and artificial cover boards, across all years and habitats. In most years, sampling occurred in 3?4 primary sampling sessions between July and September. In 1994, additional sampling occurred in February and May in conjunction with an assessment of Hantavirus exposure in deer mice (Peromyscus maniculatus). Overall, we detected 32 mammal, 14 reptile, and 6 amphibian species during 25,222 trap-nights of effort. The deer mouse?the most abundant species detected--accounted for 67% of total captures. We detected the Federal Endangered salt marsh harvest mouse (Reithrodontomys raviventris) at one coastal wetland plot in 1992. This project represents the first phase in the development of a comprehensive terrestrial vertebrate inventory and monitoring program for GGNRA. This report summarizes data on relative abundance, frequency of occurrence, distribution across habitat types, and trap success for terrestrial vertebrates detected during this 7-year effort. It includes comprehensive descriptions of the inventory methods and sampling strategies employed during this survey and is intended to help guide the park in the implementation of future longterm ecological monitoring programs.

Pilot Inventory of Mammals, Reptiles, and Amphibians, Golden Gate National Recreation Area, California, 1990-1997

USGS Publications Warehouse

Semenoff-Irving, Marcia; Howell, Judd A.

2005-01-01

The United States Geological Survey Golden Gate Field Station conducted a baseline inventory of terrestrial vertebrates within the Golden Gate National Recreation Area (GGNRA), Marin, San Francisco, and San Mateo Counties, California between 1990 and 1997. We established 456 permanent study plots in 6 major park habitats, including grassland, coastal scrub, riparian woodland, coastal wetland, broad-leaved evergreen forest, and needle-leaved evergreen forest. We tested multiple inventory methods, including live traps, track plate stations, and artificial cover boards, across all years and habitats. In most years, sampling occurred in 3-4 primary sampling sessions between July and September. In 1994, additional sampling occurred in February and May in conjunction with an assessment of Hantavirus exposure in deer mice (Peromyscus maniculatus). Overall, we detected 32 mammal, 14 reptile, and 6 amphibian species during 25,222 trap-nights of effort. The deer mouse-the most abundant species detected--accounted for 67% of total captures. We detected the Federal Endangered salt marsh harvest mouse (Reithrodontomys raviventris) at one coastal wetland plot in 1992. This project represents the first phase in the development of a comprehensive terrestrial vertebrate inventory and monitoring program for GGNRA. This report summarizes data on relative abundance, frequency of occurrence, distribution across habitat types, and trap success for terrestrial vertebrates detected during this 7-year effort. It includes comprehensive descriptions of the inventory methods and sampling strategies employed during this survey and is intended to help guide the park in the implementation of future longterm ecological monitoring programs.

Evaluating different methods used in ethnobotanical and ecological studies to record plant biodiversity

PubMed Central

2014-01-01

Background This study compares the efficiency of identifying the plants in an area of semi-arid Northeast Brazil by methods that a) access the local knowledge used in ethnobotanical studies using semi-structured interviews conducted within the entire community, an inventory interview conducted with two participants using the previously collected vegetation inventory, and a participatory workshop presenting exsiccates and photographs to 32 people and b) inventory the vegetation (phytosociology) in locations with different histories of disturbance using rectangular plots and quadrant points. Methods The proportion of species identified using each method was then compared with Cochran’s Q test. We calculated the use value (UV) of each species using semi-structured interviews; this quantitative index was correlated against values of the vegetation’s structural importance obtained from the sample plot method and point-centered quarter method applied in two areas with different historical usage. The analysis sought to correlate the relative importance of plants to the local community (use value - UV) with the ecological importance of the plants in the vegetation structure (importance value - IV; relative density - RD) by using different sampling methods to analyze the two areas. Results With regard to the methods used for accessing the local knowledge, a difference was observed among the ethnobotanical methods of surveying species (Q = 13.37, df = 2, p = 0.0013): 44 species were identified in the inventory interview, 38 in the participatory workshop and 33 in the semi-structured interviews with the community. There was either no correlation between the UV, relative density (RD) and importance value (IV) of some species, or this correlation was negative. Conclusion It was concluded that the inventory interview was the most efficient method for recording species and their uses, as it allowed more plants to be identified in their original environment. To optimize researchers’ time in future studies, the use of the point-centered quarter method rather than the sample plot method is recommended. PMID:24916833

North Carolina, 2010 forest inventory and analysis factsheet

Treesearch

Mark J. Brown; Barry D. New

2012-01-01

North Carolina’s first annualized forest survey was completed in 2007 and results were published in e-Science Update SRS–029. There were 5,800 ground based samples distributed across the State. At that time, field measurements were collected on 20 percent (a panel) of these plots annually until all plots were completed. This factsheet is an annualized update of panel...

Integrating field plots, lidar, and landsat time series to provide temporally consistent annual estimates of biomass from 1990 to present

Treesearch

Warren B. Cohen; Hans-Erik Andersen; Sean P. Healey; Gretchen G. Moisen; Todd A. Schroeder; Christopher W. Woodall; Grant M. Domke; Zhiqiang Yang; Robert E. Kennedy; Stephen V. Stehman; Curtis Woodcock; Jim Vogelmann; Zhe Zhu; Chengquan Huang

2015-01-01

We are developing a system that provides temporally consistent biomass estimates for national greenhouse gas inventory reporting to the United Nations Framework Convention on Climate Change. Our model-assisted estimation framework relies on remote sensing to scale from plot measurements to lidar strip samples, to Landsat time series-based maps. As a demonstration, new...

South Carolina, 2010 forest inventory and analysis factsheet

Treesearch

Roger C. Conner

2011-01-01

The Forest Inventory and Analysis (FIA) Program implemented a nationally consistent annual inventory system in 1998. Under the new design, one-fifth of all inventory plots in South Carolina are visited each year. The southern FIA unit, working cooperatively with South Carolina Forestry Commission crews, established the State’s initial annual inventory plots during the...

Field methods and data processing techniques associated with mapped inventory plots

Treesearch

William A. Bechtold; Stanley J. Zarnoch

1999-01-01

The U.S. Forest Inventory and Analysis (FIA) and Forest Health Monitoring (FHM) programs utilize a fixed-area mapped-plot design as the national standard for extensive forest inventories. The mapped-plot design is explained, as well as the rationale for its selection as the national standard. Ratio-of-means estimators am presented as a method to process data from...

Development of carbon response trajectories using FIA plot data and FVS growth simulator: challenges of a large scale simulation project

Treesearch

James B. McCarter; Sean Healey

2015-01-01

The Forest Carbon Management Framework (ForCaMF) integrates Forest Inventory and Analysis (FIA) plot inventory data, disturbance histories, and carbon response trajectories to develop estimates of disturbance and management effects on carbon pools for the National Forest System. All appropriate FIA inventory plots are simulated using the Forest Vegetation Simulator (...

Evaluating Plot Designs for the Tropics

Treesearch

Paul C. van Deusen; Bruce Bayle

1991-01-01

Theory and procedures are reviewed for determining the best type of plot for a given forest inventory. A general methodology is given that clarifies the relationship between different plot designs and the associated methods to produce the inventory estimates.

Portable gamma spectrometry: measuring soil erosion in-situ at four Critical Zone Observatories in P. R. China

NASA Astrophysics Data System (ADS)

Sanderson, N. K.; Green, S. M.; Chen, Z.; Wang, J.; Wang, Y.; Wang, R.; Yu, K.; Tu, C.; Jia, X.; Li, G.; Peng, X.; Quine, T. A.

2017-12-01

Detecting patterns of soil erosion, redistribution, and/soil nutrient loss is important for long-term soil conservation and agricultural sustainability. Caesium-137 (137Cs) and other fallout radionuclide inventories have been used over the the last 50 years to track soil erosion, transport and deposition on a catchment scale, and have been shown to be useful for informing models of temporal/spatial soil redistribution. Traditional sampling methods usually involves coring, grinding, sieving, sub-sampling and laboratory analysis using HPGe detectors, all of which can be costly and time consuming. In-situ measurements can provide a mechanism for assessment of 137Cs over larger areas that integrate the spatial variability, and expand turnover of analyses. Here, we assess the applicability of an in-situ approach based on radionuclide principles, and provide a comparison of the two approaches: laboratory vs. in-situ. The UK-China Critical Zone Observatory (CZO) programme provides an ideal research platform to assess the in-situ approach to measuring soil erosion: using a portable gamma spectrometer to determine 137Cs inventories. Four extensive field slope surveys were conducted in the CZO's, which covers four ecosystem types in China: karst, red soil, peri-urban, and loess plateau. In each CZO, 3-6 plots were measured along 2 slope transects, with 3 replicated 1 hour counts of 137Cs in each plot. In addition, 137Cs soil depth and bulk density profiles were also sampled for each plot, and lab-derived inventories calculated using traditional methods for comparison. Accurately and rapidly measuring 137Cs inventories using a portable field detector allows for a greater coverage of sampling locations and the potential for small-scale spatial integration, as well as the ability to re-visit sites over time and continually adapt and improve soil erosion/redistribution models, thus more effectively targeting areas of interest with reduced cost and time constraints.

Forests of Virginia,2013

Treesearch

Anita K. Rose

2015-01-01

This resource update provides an overview of forest resources in Virginia. Information for this factsheet was updated by means of the Forest Inventory and Analysis (FIA) annualized sample design. Each year, 20 percent of the sample plots (one panel) in Virginia are measured by field crews, the data compiled, and new estimates produced.

Pilot Inventory of FIA plots traditionally called `nonforest'

Treesearch

Rachel Riemann

2003-01-01

Forest-inventory data were collected on plots defined as ?nonforest? by the USDA Forest Service?s Forest Inventory and Analysis (FIA) unit. Nonforest plots may have trees on them, but they do not fit FIA?s definition of forest because the area covered by trees is too small, too sparsely populated by trees, too narrow (e.g., trees between fields or in the middle of a...

Location uncertainty and the tri-areal design

Treesearch

Francis A. Roesch

2007-01-01

The U.S. Department of Agriculture Forest Service Forest Inventory and Analysis Program (FIA) uses a field plot design that incorporates multiple sample selection mechanisms. Not all of the five FIA units currently use the entire suite of available sample selection mechanisms. These sampling selection mechanisms could be described in a number of ways with respect to...

Photo stratification improves northwest timber volume estimates.

Treesearch

Colin D. MacLean

1972-01-01

Data from extensive timber inventories of 12 counties in western and central Washington were analyzed to test the relative efficiency of double sampling for stratification as a means of estimating total volume. Photo and field plots, when combined in a stratified sampling design, proved about twice as efficient as simple field sampling. Although some gains were made by...

Sampling coarse woody debris along spoked transects

Treesearch

Paul C. Van Deusen; Jeffery H. Gove

2011-01-01

Line transects are commonly used for sampling coarse woody debris (CWD). The USDA Forest Service Forest Inventory and Analysis programme uses a variant of this method that involves sampling for CWD along transects that radiate from the centre of a circular plot-like spokes on a wheel. A new approach for analysis of data collected with spoked transects is developed....

Location uncertainty and the tri-areal design

Treesearch

Francis A. Roesch

2005-01-01

The U.S. Department of Agriculture Forest Service Forest Inventory and Analysis Program (FTA) uses a field plot design that incorporates multiple sample selection mechanisms. Not all of the five FIA units currently use the entire suite of available sample selection mechanisms. These sampling selection mechanisms could be described in a number of ways with respect to...

An analytical method to assess spruce beetle impacts on white spruce resources, Kenai Peninsula, Alaska.

Treesearch

Willem W.S. van Hees

1992-01-01

Forest inventory data collected in 1987 fTom sample plots established on the Kenai Peninsula were analyzed to provide point-in-time estimates of the trend and current status of a spruce beetle infestation. Ground plots were categorized by stage of infestation. Estimates of numbers of live and dead white spruce trees, cubic-foot volume in those trees, and areal extent...

Ancient human disturbances may be skewing our understanding of Amazonian forests.

PubMed

McMichael, Crystal N H; Matthews-Bird, Frazer; Farfan-Rios, William; Feeley, Kenneth J

2017-01-17

Although the Amazon rainforest houses much of Earth's biodiversity and plays a major role in the global carbon budget, estimates of tree biodiversity originate from fewer than 1,000 forest inventory plots, and estimates of carbon dynamics are derived from fewer than 200 recensus plots. It is well documented that the pre-European inhabitants of Amazonia actively transformed and modified the forest in many regions before their population collapse around 1491 AD; however, the impacts of these ancient disturbances remain entirely unaccounted for in the many highly influential studies using Amazonian forest plots. Here we examine whether Amazonian forest inventory plot locations are spatially biased toward areas with high probability of ancient human impacts. Our analyses reveal that forest inventory plots, and especially forest recensus plots, in all regions of Amazonia are located disproportionately near archaeological evidence and in areas likely to have ancient human impacts. Furthermore, regions of the Amazon that are relatively oversampled with inventory plots also contain the highest values of predicted ancient human impacts. Given the long lifespan of Amazonian trees, many forest inventory and recensus sites may still be recovering from past disturbances, potentially skewing our interpretations of forest dynamics and our understanding of how these forests are responding to global change. Empirical data on the human history of forest inventory sites are crucial for determining how past disturbances affect modern patterns of forest composition and carbon flux in Amazonian forests.

Stratifying to reduce bias caused by high nonresponse rates: A case study from New Mexico’s forest inventory

Treesearch

Sara A. Goeking; Paul L. Patterson

2013-01-01

The USDA Forest Service’s Forest Inventory and Analysis (FIA) Program applies specific sampling and analysis procedures to estimate a variety of forest attributes. FIA’s Interior West region uses post-stratification, where strata consist of forest/nonforest polygons based on MODIS imagery, and assumes that nonresponse plots are distributed at random across each stratum...

A tool to determine crown and plot canopy transparency for forest inventory and analysis phase 3 plots using digital photographs

Treesearch

Matthew F. Winn; Philip A. Araman

2012-01-01

The USDA Forest Service Forest Inventory and Analysis (FIA) program collects crown foliage transparency estimates for individual trees on Phase 3 (P3) inventory plots. The FIA crown foliage estimate is obtained from a pair of perpendicular side views of the tree. Researchers with the USDA Forest Service Southern Research Station have developed a computer program that...

Austrian National Forest Inventory: caught in the past and heading toward the future

Treesearch

Klemens Schadauer; Thomas Gschwantner; Karl Gabler

2007-01-01

The Austrian National Forest Inventory (AFI) started in 1961 on a temporary plot design with a systematic grid and a period of 10 years. For the first 30 years it was conducted as a continuous forest inventory. Since 1981 a permanent plot system has been used and the assessment period was reduced. Only slight changes in the plot design have occurred since the beginning...

Herbaceous vegetation in thinned and defoliated forest stands in north central West Virginia

Treesearch

S. L. C. Fosbroke; D. Feicht; R. M. Muzika

1995-01-01

Herbaceous vegetation was inventoried in 1992 and 1993 in eight Appalachian mixed hardwood stands ( 50% basal area/acre in oak species) in north central West Virginia. Vegetation was sampled on 20 6-foot radius plots per stand twice each growing season (once during late spring to sample spring ephemeral...

Forests of Virginia, 2014

Treesearch

Anita Rose

2016-01-01

This resource update provides an overview of forest resources in Virginia. Information for this factsheet was updated by means of the Forest Inventory and Analysis (FIA) annualized sample design. Each year, 20 percent of the sample plots (one panel) in Virginia are measured by field crews, the data compiled, and new estimates produced. After 5 years of measurements,...

The effect of using complete and partial forested FIA plot data on biomass and forested area classifications from MODIS satellite data

Treesearch

Dumitru Salajanu; Dennis M. Jacobs

2006-01-01

Authors’ objective was to determine at what level biomass and forest area obtained from partial and complete forested plot inventory data compares with forested area and biomass estimates from the national inventory data. A subset of 3819 inventory plots (100% forested, 100% non-forested, mixed-forest/non-forest) was used to classify the land cover and model the...

Inventory implications of using sampling variances in estimation of growth model coefficients

Treesearch

Albert R. Stage; William R. Wykoff

2000-01-01

Variables based on stand densities or stocking have sampling errors that depend on the relation of tree size to plot size and on the spatial structure of the population, ignoring the sampling errors of such variables, which include most measures of competition used in both distance-dependent and distance-independent growth models, can bias the predictions obtained from...

Variable Selection Strategies for Small-area Estimation Using FIA Plots and Remotely Sensed Data

Treesearch

Andrew Lister; Rachel Riemann; James Westfall; Mike Hoppus

2005-01-01

The USDA Forest Service's Forest Inventory and Analysis (FIA) unit maintains a network of tens of thousands of georeferenced forest inventory plots distributed across the United States. Data collected on these plots include direct measurements of tree diameter and height and other variables. We present a technique by which FIA plot data and coregistered...

Ancient human disturbances may be skewing our understanding of Amazonian forests

PubMed Central

McMichael, Crystal N. H.; Matthews-Bird, Frazer; Farfan-Rios, William; Feeley, Kenneth J.

2017-01-01

Although the Amazon rainforest houses much of Earth’s biodiversity and plays a major role in the global carbon budget, estimates of tree biodiversity originate from fewer than 1,000 forest inventory plots, and estimates of carbon dynamics are derived from fewer than 200 recensus plots. It is well documented that the pre-European inhabitants of Amazonia actively transformed and modified the forest in many regions before their population collapse around 1491 AD; however, the impacts of these ancient disturbances remain entirely unaccounted for in the many highly influential studies using Amazonian forest plots. Here we examine whether Amazonian forest inventory plot locations are spatially biased toward areas with high probability of ancient human impacts. Our analyses reveal that forest inventory plots, and especially forest recensus plots, in all regions of Amazonia are located disproportionately near archaeological evidence and in areas likely to have ancient human impacts. Furthermore, regions of the Amazon that are relatively oversampled with inventory plots also contain the highest values of predicted ancient human impacts. Given the long lifespan of Amazonian trees, many forest inventory and recensus sites may still be recovering from past disturbances, potentially skewing our interpretations of forest dynamics and our understanding of how these forests are responding to global change. Empirical data on the human history of forest inventory sites are crucial for determining how past disturbances affect modern patterns of forest composition and carbon flux in Amazonian forests. PMID:28049821

Improving estimates of forest disturbance by combining observations from Landsat time series with U.S. Forest Service Forest Inventory and Analysis data

Treesearch

Todd A. Schroeder; Sean P. Healey; Gretchen G. Moisen; Tracey S. Frescino; Warren B. Cohen; Chengquan Huang; Robert E. Kennedy; Zhiqiang Yang

2014-01-01

With earth's surface temperature and human population both on the rise a new emphasis has been placed on monitoring changes to forested ecosystems the world over. In the United States the U.S. Forest Service Forest Inventory and Analysis (FIA) program monitors the forested land base with field data collected over a permanent network of sample plots. Although these...

Updating older forest inventory data with a growth model and satellite records to improve the responsiveness and currency of national carbon monitoring

NASA Astrophysics Data System (ADS)

Healey, S. P.; Zhao, F. R.; McCarter, J. B.; Frescino, T.; Goeking, S.

2017-12-01

International reporting of American forest carbon trends depends upon the Forest Service's nationally consistent network of inventory plots. Plots are measured on a rolling basis over a 5- to 10-year cycle, so estimates related to any variable, including carbon storage, reflect conditions over a 5- to 10-year window. This makes it difficult to identify the carbon impact of discrete events (e.g., a bad fire year; extraction rates related to home-building trends), particularly if the events are recent.We report an approach to make inventory estimates more sensitive to discrete and recent events. We use a growth model (the Forest Vegetation Simulator - FVS) that is maintained by the Forest Service to annually update the tree list for every plot, allowing all plots to contribute to a series of single-year estimates. Satellite imagery from the Landsat platform guides the FVS simulations by providing information about which plots have been disturbed, which are recovering from disturbance, and which are undergoing undisturbed growth. The FVS model is only used to "update" plot tree lists until the next field measurement is made (maximum of 9 years). As a result, predicted changes are usually small and error rates are low. We present a pilot study of this system in Idaho, which has experienced several major fire events in the last decade. Empirical estimates of uncertainty, accounting for both plot sampling error and FVS model error, suggest that this approach greatly increases temporal specificity and sensitivity to discrete events without sacrificing much estimate precision at the level of a US state. This approach has the potential to take better advantage of the Forest Service's rolling plot measurement schedule to report carbon storage in the US, and it offers the basis of a system that might allow near-term, forward-looking analysis of the effects of hypothetical forest disturbance patterns.

Towards the harmonization between National Forest Inventory and Forest Condition Monitoring. Consistency of plot allocation and effect of tree selection methods on sample statistics in Italy.

PubMed

Gasparini, Patrizia; Di Cosmo, Lucio; Cenni, Enrico; Pompei, Enrico; Ferretti, Marco

2013-07-01

In the frame of a process aiming at harmonizing National Forest Inventory (NFI) and ICP Forests Level I Forest Condition Monitoring (FCM) in Italy, we investigated (a) the long-term consistency between FCM sample points (a subsample of the first NFI, 1985, NFI_1) and recent forest area estimates (after the second NFI, 2005, NFI_2) and (b) the effect of tree selection method (tree-based or plot-based) on sample composition and defoliation statistics. The two investigations were carried out on 261 and 252 FCM sites, respectively. Results show that some individual forest categories (larch and stone pine, Norway spruce, other coniferous, beech, temperate oaks and cork oak forests) are over-represented and others (hornbeam and hophornbeam, other deciduous broadleaved and holm oak forests) are under-represented in the FCM sample. This is probably due to a change in forest cover, which has increased by 1,559,200 ha from 1985 to 2005. In case of shift from a tree-based to a plot-based selection method, 3,130 (46.7%) of the original 6,703 sample trees will be abandoned, and 1,473 new trees will be selected. The balance between exclusion of former sample trees and inclusion of new ones will be particularly unfavourable for conifers (with only 16.4% of excluded trees replaced by new ones) and less for deciduous broadleaves (with 63.5% of excluded trees replaced). The total number of tree species surveyed will not be impacted, while the number of trees per species will, and the resulting (plot-based) sample composition will have a much larger frequency of deciduous broadleaved trees. The newly selected trees have-in general-smaller diameter at breast height (DBH) and defoliation scores. Given the larger rate of turnover, the deciduous broadleaved part of the sample will be more impacted. Our results suggest that both a revision of FCM network to account for forest area change and a plot-based approach to permit statistical inference and avoid bias in the tree sample composition in terms of DBH (and likely age and structure) are desirable in Italy. As the adoption of a plot-based approach will keep a large share of the trees formerly selected, direct tree-by-tree comparison will remain possible, thus limiting the impact on the time series comparability. In addition, the plot-based design will favour the integration with NFI_2.

Michigan's forests, 2004: statistics and quality assurance

Treesearch

Scott A. Pugh; Mark H. Hansen; Gary Brand; Ronald E. McRoberts

2010-01-01

The first annual inventory of Michigan's forests was completed in 2004 after 18,916 plots were selected and 10,355 forested plots were visited. This report includes detailed information on forest inventory methods, quality of estimates, and additional tables. An earlier publication presented analyses of the inventoried data (Pugh et al. 2009).

Diameter Growth Models for Inventory Applications

Treesearch

Ronald E. McRoberts; Christopher W. Woodall; Veronica C. Lessard; Margaret R. Holdaway

2002-01-01

Distant-independent, individual-tree, diametar growth models were constructed to update information for forest inventory plots measured in previous years. The models are nonlinear in the parameters and were calibrated weighted nonlinear least squares techniques and forest inventory plot data. Analyses of residuals indicated that model predictions compare favorably to...

Estimating forest floor fuels in eastern U.S. forests

Treesearch

David C. Chojnacky; Steven G. McNulty; Jennifer Moore Myers; Michael K. Gavazzi

2005-01-01

The Forest Inventory Analysis (FIA) program (U.S. Department of Agriculture, Forest Service) systematically samples the nation's forests and currently measures variable related to down woody material (DWM) on a subsample of its plots in the third phase of a 3-phase sampling design. This paper focuses on: (1) compiling estimates of DWM within limitations of...

Forests of South Carolina, 2014

Treesearch

Anita K. Rose

2015-01-01

This resource update provides an overview of forest resources in South Carolina. Information for this factsheet was updated by means of the Forest Inventory and Analysis (FIA) annualized sample design. Each year 20 percent of the sample plots (one panel) in South Carolina are measured by field crews, the data compiled, and new estimates produced. After 5 years of...

Forests of South Carolina, 2013

Treesearch

Anita K. Rose

2015-01-01

This resource update provides an overview of forest resources in South Carolina. Information for this factsheet was updated by means of the Forest Inventory and Analysis (FIA) annualized sample design. Each year 20 percent of the sample plots (one panel) in South Carolina are measured by field crews, the data compiled, and new estimates produced. After 5 years of...

An investigation of condition mapping and plot proportion calculation issues

Treesearch

Demetrios Gatziolis

2007-01-01

A systematic examination of Forest Inventory and Analysis condition data collected under the annual inventory protocol in the Pacific Northwest region between 2000 and 2004 revealed the presence of errors both in condition topology and plot proportion computations. When plots were compiled to generate population estimates, proportion errors were found to cause...

Prefield methods: streamlining forest or nonforest determinations to increase inventory efficiency

Treesearch

Sara Goeking; Gretchen Moisen; Kevin Megown; Jason Toombs

2009-01-01

Interior West Forest Inventory and Analysis has developed prefield protocols to distinguish forested plots that require field visits from nonforested plots that do not require field visits. Recent innovations have increased the efficiency of the prefield process. First, the incorporation of periodic inventory data into a prefield database increased the amount of...

Nebraska's forests, 2005: statistics, methods, and quality assurance

Treesearch

Patrick D. Miles; Dacia M. Meneguzzo; Charles J. Barnett

2011-01-01

The first full annual inventory of Nebraska's forests was completed in 2005 after 8,335 plots were selected and 274 forested plots were visited and measured. This report includes detailed information on forest inventory methods, and data quality estimates. Tables of various important resource statistics are presented. Detailed analysis of the inventory data are...

Kansas's forests, 2005: statistics, methods, and quality assurance

Treesearch

Patrick D. Miles; W. Keith Moser; Charles J. Barnett

2011-01-01

The first full annual inventory of Kansas's forests was completed in 2005 after 8,868 plots were selected and 468 forested plots were visited and measured. This report includes detailed information on forest inventory methods and data quality estimates. Important resource statistics are included in the tables. A detailed analysis of Kansas inventory is presented...

Multi-Scale Mapping of Vegetation Biomass

NASA Astrophysics Data System (ADS)

Hudak, A. T.; Fekety, P.; Falkowski, M. J.; Kennedy, R. E.; Crookston, N.; Smith, A. M.; Mahoney, P.; Glenn, N. F.; Dong, J.; Kane, V. R.; Woodall, C. W.

2016-12-01

Vegetation biomass mapping at multiple scales is important for carbon inventory and monitoring, reporting, and verification (MRV). Project-level lidar collections allow biomass estimation with high confidence where associated with field plot measurements. Predictive models developed from such datasets are customarily used to generate landscape-scale biomass maps. We tested the feasibility of predicting biomass in landscapes surveyed with lidar but without field plots, by withholding plot datasets from a reduced model applied to the landscapes, and found support for a generalized model in the northern Idaho ecoregion. We are also upscaling a generalized model to all forested lands in Idaho. Our regional modeling approach is to sample the 30-m biomass predictions from the landscape-scale maps and use them to train a regional biomass model, using Landsat time series, topographic derivatives, and climate variables as predictors. Our regional map validation approach is to aggregate the regional, annual biomass predictions to the county level and compare them to annual county-level biomass summarized independently from systematic, field-based, annual inventories conducted by the US Forest Inventory and Analysis (FIA) Program nationally. A national-scale forest cover map generated independently from 2010 PALSAR data at 25-m resolution is being used to mask non-forest pixels from the aggregations. Effects of climate change on future regional biomass stores are also being explored, using biomass estimates projected from stand-level inventory data collected in the National Forests and comparing them to FIA plot data collected independently on public and private lands, projected under the same climate change scenarios, with disturbance trends extracted from the Landsat time series. Our ultimate goal is to demonstrate, focusing on the ecologically diverse Northwest region of the USA, a carbon monitoring system (CMS) that is accurate, objective, repeatable, and transparent.

Shortening the Xerostomia Inventory

PubMed Central

Thomson, William Murray; van der Putten, Gert-Jan; de Baat, Cees; Ikebe, Kazunori; Matsuda, Ken-ichi; Enoki, Kaori; Hopcraft, Matthew; Ling, Guo Y

2011-01-01

Objectives To determine the validity and properties of the Summated Xerostomia Inventory-Dutch Version in samples from Australia, The Netherlands, Japan and New Zealand. Study design Six cross-sectional samples of older people from The Netherlands (N = 50), Australia (N = 637 and N = 245), Japan (N = 401) and New Zealand (N = 167 and N = 86). Data were analysed using the Summated Xerostomia Inventory-Dutch Version. Results Almost all data-sets revealed a single extracted factor which explained about half of the variance, with Cronbach’s alpha values of at least 0.70. When mean scale scores were plotted against a “gold standard” xerostomia question, statistically significant gradients were observed, with the highest score seen in those who always had dry mouth, and the lowest in those who never had it. Conclusion The Summated Xerostomia Inventory-Dutch Version is valid for measuring xerostomia symptoms in clinical and epidemiological research. PMID:21684773

Compensating for missing plot observations inforest inventory estimation

Treesearch

Ronald E. McRoberts

2003-01-01

The Enhanced Forest Inventory and Analysis program of the U.S. Forest Service has established a nationwide array of permanent field plots, each representing approximately 2400 ha. Each plot has been assigned to one of five interpenetrating, nonoverlapping panels, with one panel selected for measurement on a rotating basis each year. As with most large surveys,...

FIADB vegetation diversity and structure indicator (VEG)

Treesearch

Bethany K. Schulz; Kevin Dobelbower

2012-01-01

The Vegetation Diversity and Structure (VEG) Indicator is a suite of measurements including an inventory of vascular plants on an extensive systematic network of forest plots across the United States. This network is a subset of the standard forest inventory plots established by the U.S. Forest Service Forest Inventory and Analysis program. The VEG indicator provides...

A Simulation Algorithm to Approximate the Area of Mapped Forest Inventory Plots

Treesearch

William A. Bechtold; Naser E. Heravi; Matthew E. Kinkenon

2003-01-01

Calculating the area of polygons associated with mapped forest inventory plots can be mathematically cumbersome, especially when computing change between inventories. We developed a simulation technique that utilizes a computer-generated dot grid and geometry to estimate the area of mapped polygons within any size circle. The technique also yields a matrix of change in...

Forest resources of southeast Alaska, 2000: results of a single-phase systematic sample.

Treesearch

Willem W.S. van Hees

2003-01-01

A baseline assessment of forest resources in southeast Alaska was made by using a single-phase, unstratified, systematic-grid sample, with ground plots established at each grid intersection. Ratio-of-means estimators were used to develop population estimates. Forests cover an estimated 48 percent of the 22.9-million-acre southeast Alaska inventory unit. Dominant forest...

Inventory of montane-nesting birds in Katmai and Lake Clark national parks and preserves

USGS Publications Warehouse

Ruthrauff, Daniel R.; Tibbitts, Lee; Gill, Robert E.; Handel, Colleen M.

2007-01-01

As part of the National Park Service’s Inventory and Monitoring Program, biologists from the U. S. Geological Survey’s Alaska Science Center conducted an inventory of birds in montane regions of Katmai and Lake Clark National Parks and Preserves during 2004–2006. We used a stratified random survey design to allocate samples by ecological subsection. To survey for birds, we conducted counts at 468 points across 29, 10-km x 10-km (6.2-mi x 6.2-mi) sample plots in Katmai and 417 points across 25, 10-km x 10-km sample plots in Lake Clark. We detected 92 and 104 species in Katmai and Lake Clark, respectively, including 40 species of conservation concern. We detected three species not previously recorded in Katmai (Ring-necked Duck [Aythya collaris], Lesser Scaup [Aythya affinis], and White-tailed Ptarmigan [Lagopus leucurus]) and two species not previously recorded in Lake Clark (Northern Flicker [Colaptes auratus ] and Olive-sided Flycatcher [Contopus cooperi]). The most commonly detected species in both parks was Golden-crowned Sparrow (Zonotrichia atricapilla); Fox Sparrow (Passerella iliaca) and American Pipit (Anthus rubescens) were abundant and widely-distributed as well. We defined sites as low (100–350 m), middle (351–600 m), or high (601–1,620 m) elevation based on the distribution of vegetation cover, and similarly categorized the 34 most-commonly detected species based on the mean elevation of sample points at which they were detected. High elevation (i.e., alpine) sites were characterized by high percent cover of dwarf shrub and bare ground habitat and supported species like Rock Ptarmigan (L. mutus), American Golden-Plover (Pluvialis dominica), Wandering Tattler (Tringa incana), Surfbird (Aphriza virgata), and Snow Bunting (Plectrophenax nivalis), all species of conservation concern. This inventory represents the first systematic survey of birds nesting in montane regions of both parks. Results from this inventory can form the foundation of subsequent monitoring efforts

A technique for identifying treatment opportunities from western Oregon and Washington forest survey plots.

Treesearch

Colin D. MacLean

1980-01-01

Identification of opportunities for silvicultural treatment from inventory data is an important objective of Renewable Resources Evaluation in the Pacific Northwest. This paper describes the field plot design and data analysis procedure used by what used to be known as Forest Survey to determine the treatment opportunity associated with each inventory plot in western...

Selection of Plot Remeasurement in an Annual Inventory

Treesearch

Mark H. Hansen; Hans T. Schreuder; Dave Heinzen

2000-01-01

A plot selection approach is proposed based on experience from the Annual Forest Inventory System (AFIS) in the Aspen-Birch Unit of northestern Minnesota. The emphasisis on a mixture of strategies. Although the Agricultural Act of 1998 requires that a fixed 20 percent of plots be measured each year in each state, sooner or later we will need to vary the scheme to...

The status of accurately locating forest inventory and analysis plots using the Global Positioning System

Treesearch

Michael Hoppus; Andrew Lister

2007-01-01

Historically, field crews used Global Positioning System (GPS) coordinates to establish and relocate plots, as well as document their general location. During the past 5 years, the increase in Geographic Information System (GIS) capabilities and in customer requests to use the spatial relationships between Forest Inventory and Analysis (FIA) plot data and other GIS...

Plot intensity and cycle-length effects on growth and removals estimates from forest inventories

Treesearch

Paul C. Van Deusen; Francis A. Roesch

2015-01-01

Continuous forest inventory planners can allocate the budget to more plots per acre or a shorter remeasurement cycle. A higher plot intensity benefits small area estimation and allows for more precision in current status estimates. Shorter cycles may provide better estimates of growth, removals and mortality. On a fixed budget, the planner can't have both greater...

New Method for Determining the Relative Stand Density of Forest Inventory Plots

Treesearch

Christopher W. Woodall; Patrick D. Miles

2006-01-01

Determining the relative density of Forest Inventory and Analysis plots is complicated by the various species and tree size combinations in the Nation?s forested ecosystems. Stand density index (SDI), although developed for use in even-aged monocultures, has been used for stand density assessment in largescale forest inventories. To improve application of SDI in uneven...

Modeling the uncertainty of estimating forest carbon stocks in China

NASA Astrophysics Data System (ADS)

Yue, T. X.; Wang, Y. F.; Du, Z. P.; Zhao, M. W.; Zhang, L. L.; Zhao, N.; Lu, M.; Larocque, G. R.; Wilson, J. P.

2015-12-01

Earth surface systems are controlled by a combination of global and local factors, which cannot be understood without accounting for both the local and global components. The system dynamics cannot be recovered from the global or local controls alone. Ground forest inventory is able to accurately estimate forest carbon stocks at sample plots, but these sample plots are too sparse to support the spatial simulation of carbon stocks with required accuracy. Satellite observation is an important source of global information for the simulation of carbon stocks. Satellite remote-sensing can supply spatially continuous information about the surface of forest carbon stocks, which is impossible from ground-based investigations, but their description has considerable uncertainty. In this paper, we validated the Lund-Potsdam-Jena dynamic global vegetation model (LPJ), the Kriging method for spatial interpolation of ground sample plots and a satellite-observation-based approach as well as an approach for fusing the ground sample plots with satellite observations and an assimilation method for incorporating the ground sample plots into LPJ. The validation results indicated that both the data fusion and data assimilation approaches reduced the uncertainty of estimating carbon stocks. The data fusion had the lowest uncertainty by using an existing method for high accuracy surface modeling to fuse the ground sample plots with the satellite observations (HASM-SOA). The estimates produced with HASM-SOA were 26.1 and 28.4 % more accurate than the satellite-based approach and spatial interpolation of the sample plots, respectively. Forest carbon stocks of 7.08 Pg were estimated for China during the period from 2004 to 2008, an increase of 2.24 Pg from 1984 to 2008, using the preferred HASM-SOA method.

Estimating the number of tree species in forest populations using current vegetation survey and forest inventory and analysis approximation plots and grid intensities

Treesearch

Hans T. Schreuder; Jin-Mann S. Lin; John Teply

2000-01-01

We estimate number of tree species in National Forest populations using the nonparametric estimator. Data from the Current Vegetation Survey (CVS) of Region 6 of the USDA Forest Service were used to estimate the number of tree species with a plot close in size to the Forest Inventory and Analysis (FIA) plot and the actual CVS plot for the 5.5 km FIA grid and the 2.7 km...

American Samoa's forest resources, 2001.

Treesearch

Joseph A. Donnegan; Sheri S. Mann; Sarah L. Butler; Bruce A. Hiserote

2004-01-01

The Forest Inventory and Analysis Program of the Pacific Northwest Research Station collected, analyzed, and summarized data from field plots, and mapped land cover on four islands in American Samoa. This statistical sample provides estimates of forest area, stem volume, biomass, numbers of trees, damages to trees, and tree size distribution. The summary provides...

Using publically available forest inventory data in climate-based modes of tree species distribution: Examining effects of true versus altered location coordinates

Treesearch

Jacob Gibson; Gretchen Moisen; Tracey Frescino; Thomas C. Edwards

2013-01-01

Species distribution models (SDMs) were built with US Forest Inventory and Analysis (FIA) publicly available plot coordinates, which are altered for plot security purposes, and compared with SDMs built with true plot coordinates. Six species endemic to the western US, including four junipers (Juniperus deppeana var. deppeana, J. monosperma, J. occidentalis, J....

Redrawing the baseline: a method for adjusting biased historical forest estimates using a spatial and temporally representative plot network

Treesearch

Sara A. Goeking; Paul L. Patterson

2015-01-01

Users of Forest Inventory and Analysis (FIA) data sometimes compare historic and current forest inventory estimates, despite warnings that such comparisons may be tenuous. The purpose of this study was to demonstrate a method for obtaining a more accurate and representative reference dataset using data collected at co-located plots (i.e., plots that were measured...

Selection of plot remeasurement in an annual inventory

Treesearch

Mark H. Hansen; Hans T. Schreuder; Dave Heinzen

2000-01-01

A plot selection approach is proposed based on experience from the Annual Forest Inventory System (AFIS) in the Aspen-Birch Unit of northeastern Minnesota. The emphasis is on a mixture of strategies. Although the Agricultural Act of 1998 requires that a fixed 20 percent of plots be measured each year in each state, sooner or later we will need to vary the scheme to...

Use of ancillary data to improve the analysis of forest health indicators

Treesearch

Dave Gartner

2013-01-01

In addition to its standard suite of mensuration variables, the Forest Inventory and Analysis (FIA) program of the U.S. Forest Service also collects data on forest health variables formerly measured by the Forest Health Monitoring program. FIA obtains forest health information on a subset of the base sample plots. Due to the sample size differences, the two sets of...

Analysis of area level and unit level models for small area estimation in forest inventories assisted with LiDAR auxiliary information.

PubMed

Mauro, Francisco; Monleon, Vicente J; Temesgen, Hailemariam; Ford, Kevin R

2017-01-01

Forest inventories require estimates and measures of uncertainty for subpopulations such as management units. These units often times hold a small sample size, so they should be regarded as small areas. When auxiliary information is available, different small area estimation methods have been proposed to obtain reliable estimates for small areas. Unit level empirical best linear unbiased predictors (EBLUP) based on plot or grid unit level models have been studied more thoroughly than area level EBLUPs, where the modelling occurs at the management unit scale. Area level EBLUPs do not require a precise plot positioning and allow the use of variable radius plots, thus reducing fieldwork costs. However, their performance has not been examined thoroughly. We compared unit level and area level EBLUPs, using LiDAR auxiliary information collected for inventorying 98,104 ha coastal coniferous forest. Unit level models were consistently more accurate than area level EBLUPs, and area level EBLUPs were consistently more accurate than field estimates except for large management units that held a large sample. For stand density, volume, basal area, quadratic mean diameter, mean height and Lorey's height, root mean squared errors (rmses) of estimates obtained using area level EBLUPs were, on average, 1.43, 2.83, 2.09, 1.40, 1.32 and 1.64 times larger than those based on unit level estimates, respectively. Similarly, direct field estimates had rmses that were, on average, 1.37, 1.45, 1.17, 1.17, 1.26, and 1.38 times larger than rmses of area level EBLUPs. Therefore, area level models can lead to substantial gains in accuracy compared to direct estimates, and unit level models lead to very important gains in accuracy compared to area level models, potentially justifying the additional costs of obtaining accurate field plot coordinates.

Analysis of area level and unit level models for small area estimation in forest inventories assisted with LiDAR auxiliary information

PubMed Central

Monleon, Vicente J.; Temesgen, Hailemariam; Ford, Kevin R.

2017-01-01

Forest inventories require estimates and measures of uncertainty for subpopulations such as management units. These units often times hold a small sample size, so they should be regarded as small areas. When auxiliary information is available, different small area estimation methods have been proposed to obtain reliable estimates for small areas. Unit level empirical best linear unbiased predictors (EBLUP) based on plot or grid unit level models have been studied more thoroughly than area level EBLUPs, where the modelling occurs at the management unit scale. Area level EBLUPs do not require a precise plot positioning and allow the use of variable radius plots, thus reducing fieldwork costs. However, their performance has not been examined thoroughly. We compared unit level and area level EBLUPs, using LiDAR auxiliary information collected for inventorying 98,104 ha coastal coniferous forest. Unit level models were consistently more accurate than area level EBLUPs, and area level EBLUPs were consistently more accurate than field estimates except for large management units that held a large sample. For stand density, volume, basal area, quadratic mean diameter, mean height and Lorey’s height, root mean squared errors (rmses) of estimates obtained using area level EBLUPs were, on average, 1.43, 2.83, 2.09, 1.40, 1.32 and 1.64 times larger than those based on unit level estimates, respectively. Similarly, direct field estimates had rmses that were, on average, 1.37, 1.45, 1.17, 1.17, 1.26, and 1.38 times larger than rmses of area level EBLUPs. Therefore, area level models can lead to substantial gains in accuracy compared to direct estimates, and unit level models lead to very important gains in accuracy compared to area level models, potentially justifying the additional costs of obtaining accurate field plot coordinates. PMID:29216290

Field instructions for the annual inventory of California, Oregon, and Washington 2010: Supplement for: Fire effects and recovery study

Treesearch

Theresa B. Jain; Jeremy S. Fried

2010-01-01

This field guide supplemental describes the data items to record for Fire Effects and Recovery Study (FERS) plots; it is a supplement to the 2010 Field Instructions for the Annual Inventory of California, Oregon, and Washington (i.e., "2010 PFSL manual"). These plots are pre-selected; data items are required as specified when FIRE PLOT = Y. Additional...

SPRUCE Deep Peat Heat (DPH) Metagenomes for Peat Samples Collected June 2015

DOE Data Explorer

Klumber, Laurel A. [Oak Ridge National Laboratory, U.S. Department of Energy, Oak Ridge, Tennessee, U.S.A.; Yang, Zamin K. [Oak Ridge National Laboratory, U.S. Department of Energy, Oak Ridge, Tennessee, U.S.A.; Schadt, Christopher W. [Oak Ridge National Laboratory, U.S. Department of Energy, Oak Ridge, Tennessee, U.S.A.

2015-01-01

This data set provides links to the results of metagenomic analyses of 38 peat core samples collected on 16 June 2015 from SPRUCE experiment treatment plots after approximately one year of belowground heating. These metagenomes are archived in the U.S. Department of Energy Joint Genome Institute (DOE JGI) Integrated Microbial Genomes (IMG) system and are available at the accession numbers provided in the accompanying inventory file.

Evaluating Site-Specific and Generic Spatial Models of Aboveground Forest Biomass Based on Landsat Time-Series and LiDAR Strip Samples in the Eastern USA

Treesearch

Ram Deo; Matthew Russell; Grant Domke; Hans-Erik Andersen; Warren Cohen; Christopher Woodall

2017-01-01

Large-area assessment of aboveground tree biomass (AGB) to inform regional or national forest monitoring programs can be efficiently carried out by combining remotely sensed data and field sample measurements through a generic statistical model, in contrast to site-specific models. We integrated forest inventory plot data with spatial predictors from Landsat time-...

Guam's forest resources, 2002.

Treesearch

Joseph A. Donnegan; Sarah L. Butler; Walter Grabowiecki; Bruce A. Hiserote; David. Limtiaco

2004-01-01

The Forest Inventory and Analysis Program collected, analyzed, and summarized field data on 46 forested plots on the island of Guam. Estimates of forest area, tree stem volume and biomass, the numbers of trees, tree damages, and the distribution of tree sizes were summarized for this statistical sample. Detailed tables and graphical highlights provide a summary of Guam...

Model-assisted estimation of forest resources with generalized additive models

Treesearch

Jean D. Opsomer; F. Jay Breidt; Gretchen G. Moisen; Goran Kauermann

2007-01-01

Multiphase surveys are often conducted in forest inventories, with the goal of estimating forested area and tree characteristics over large regions. This article describes how design-based estimation of such quantities, based on information gathered during ground visits of sampled plots, can be made more precise by incorporating auxiliary information available from...

Aspen, climate, and sudden decline in western USA

Treesearch

Gerald E. Rehfeldt; Dennis E. Ferguson; Nicholas L. Crookston

2009-01-01

A bioclimate model predicting the presence or absence of aspen, Populus tremuloides, in western USA from climate variables was developed by using the Random Forests classification tree on Forest Inventory data from about 118,000 permanent sample plots. A reasonably parsimonious model used eight predictors to describe aspen's climate profile. Classification errors...

Palau's forest resources, 2003.

Treesearch

Joseph A. Donnegan; Sarah L. Butler; Olaf Kuegler; Brent J. Stroud; Bruce A. Hiserote; Kashgar. Rengulbai

2007-01-01

The Forest Inventory and Analysis Program collected, analyzed, and summarized field data on 54 forested plots on the islands in the Republic of Palau. Estimates of forest area, tree stem volume and biomass, the numbers of trees, tree damages, and the distribution of tree sizes were summarized for this statistical sample. Detailed tables and graphical highlights provide...

Sensitivity of FIA Volume Estimates to Changes in Stratum Weights and Number of Strata

Treesearch

James A. Westfall; Michael Hoppus

2005-01-01

In the Northeast region, the USDA Forest Service Forest Inventory and Analysis (FIA) program utilizes stratified sampling techniques to improve the precision of population estimates. Recently, interpretation of aerial photographs was replaced with classified remotely sensed imagery to determine stratum weights and plot stratum assignments. However, stratum weights...

Replication Study of the Milwaukee Inventory for Subtypes of Trichotillomania–Adult Version in a Clinically Characterized Sample

PubMed Central

Keuthen, Nancy J.; Tung, Esther S.; Woods, Douglas W.; Franklin, Martin E.; Altenburger, Erin M.; Pauls, David L.; Flessner, Christopher A.

2015-01-01

In the present study, we evaluated the Milwaukee Inventory for Subtypes of Trichotillomania–Adult Version (MIST-A) in a replication sample of clinically characterized hair pullers using exploratory factor analysis (EFA; N = 193). EFA eigenvalues and visual inspection of our scree plot revealed a two-factor solution. Factor structure coefficients and internal consistencies suggested a 13-item scale with an 8-item “Intention” scale and a 5-item “Emotion” scale. Both scales displayed good construct and discriminant validity. These findings indicate the need for a revised scale that provides a more refined assessment of pulling phenomenology that can facilitate future treatment advances. PMID:25868534

Tree-level imputation techniques to estimate current plot-level attributes in the Pacific Northwest using paneled inventory data

Treesearch

Bianca Eskelson; Temesgen Hailemariam; Tara Barrett

2009-01-01

The Forest Inventory and Analysis program (FIA) of the US Forest Service conducts a nationwide annual inventory. One panel (20% or 10% of all plots in the eastern and western United States, respectively) is measured each year. The precision of the estimates for any given year from one panel is low, and the moving average (MA), which is considered to be the default...

STP K Basin Sludge Sample Archive at the Pacific Northwest National Laboratory FY2014

DOE Office of Scientific and Technical Information (OSTI.GOV)

Fiskum, Sandra K.; Smoot, Margaret R.; Schmidt, Andrew J.

2014-06-01

The Pacific Northwest National Laboratory (PNNL) currently houses 88 samples (~10.5 kg) of K Basin sludge (81 wet and seven dry samples) on behalf of the Sludge Treatment Project (STP), which is managed for the U.S. Department of Energy (DOE) by the CH2M Hill Plateau Remediation Company (CHPRC). Selected samples are intended to serve, in part, as sentinels to enhance understanding of sludge properties after long-term storage, and thus enhance understanding of sludge behavior following transfer to sludge transfer and storage containers (STSCs) and storage at the Hanford 200 Area central plateau. In addition, remaining samples serve in contingency formore » future testing requirements. At PNNL, the samples are tracked and maintained under a prescriptive and disciplined monthly sample-monitoring program implemented by PNNL staff. This report updates the status of the K Basin archive sludge sample inventory to April 2014. The previous inventory status report, PNNL 22245 (Fiskum et al. 2013, limited distribution report), was issued in February of 2013. This update incorporates changes in the inventory related to repackaging of 17 samples under test instructions 52578 TI052, K Basin Sludge Sample Repackaging for Continued Long Term Storage, and 52578 TI053, K Basin Sludge Sample Repackaging Post-2014 Shear Strength Measurements. Note that shear strength measurement results acquired in 2014 are provided separately. Specifically, this report provides the following: • a description of the K Basin sludge sample archive program and the sample inventory • a summary and images of the samples that were repackaged in April 2014 • up-to-date images and plots of the settled density and water loss from all applicable samples in the inventory • updated sample pedigree charts, which provide a roadmap of the genesis and processing history of each sample in the inventory • occurrence and deficiency reports associated with sample storage and repackaging« less

An analysis of mortality inventory tally using large plots compared to tally using small plot clusters

Treesearch

Vernon J. LaBau; John W. Hazard

2000-01-01

During an inventory to assess spruce bark beetle impact on the Kenai Peninsula in south-central Alaska, 5-year mortality estimates were made for all growing-stock trees on 0.6 ha areas, on 0.4 ha areas, and on a cluster of four 1/60-ha subplots. The analysis of the results of the comparison between cluster data and the larger plot data highlighted some of the problems...

FIA forest inventory data for wildlife habitat assessment

Treesearch

David C. Chojnacky

2000-01-01

The Forest Inventory and Analysis (FIA) program of the USDA Forest Service maintains a network of permanent plots to monitor changing forest conditions. These plots were originally established to monitor the nation's timber supply; however, these data have great potential for evaluating other forest resources. To demonstrate a wildlife application, an assessment...

Critique of Sikkink and Keane's comparison of surface fuel sampling techniques

Treesearch

Clinton S. Wright; Roger D. Ottmar; Robert E. Vihnanek

2010-01-01

The 2008 paper of Sikkink and Keane compared several methods to estimate surface fuel loading in western Montana: two widely used inventory techniques (planar intersect and fixed-area plot) and three methods that employ photographs as visual guides (photo load, photoload macroplot and photo series). We feel, however, that their study design was inadequate to evaluate...

Estimating mangrove in Florida: trials monitoring rare ecosystems

Treesearch

Mark J. Brown

2015-01-01

Mangrove species are keystone components in coastal ecosystems and are the interface between forest land and sea. Yet, estimates of their area have varied widely. Forest Inventory and Analysis (FIA) data from ground-based sample plots provide one estimate of the resource. Initial FIA estimates of the mangrove resource in Florida varied dramatically from those compiled...

Optimized endogenous post-stratification in forest inventories

Treesearch

Paul L. Patterson

2012-01-01

An example of endogenous post-stratification is the use of remote sensing data with a sample of ground data to build a logistic regression model to predict the probability that a plot is forested and using the predicted probabilities to form categories for post-stratification. An optimized endogenous post-stratified estimator of the proportion of forest has been...

Forest statistics for Arkansas' delta counties

Treesearch

Richard T. Quick; Mary S. Hedlund

1979-01-01

These tables were derived from data obtained during a 1978 inventory of 21 counties comprising the North and South Delta Units of Arkansas (fig. 1). Forest area was estimated from aerial photos with an adjustment for ground truth at selected locations. Sample plots were systematically established at three-mile intervals using a grid oriented roughly N-S and E-W. At...

Forest statistics for Arkansas' Ouachita counties

Treesearch

T. Richard Quick; Marry S. Hedlund

1979-01-01

These tables were derived from data obtained during a 1978 inventory of 10 counties comprising the Quachita Unit of Arkansas (fig. 1). Forest area was estimated from aerial photos with an adjustment of ground truth at selected locations. Sample plots were systematically established at three-mile intervals using a grid orientated roughly N-S and E-W. At each locations,...

Forest statistics for Arkansas' Ozark counties

Treesearch

T. Richard Quick; Mary S. Hedlund

1979-01-01

These tables were derived from data obtained during a 1978 inventory of 24 counties comprising the Ozark Unit of Arkansas (fib. 1). Forest area was estimated from aerial photos with an adjustment of ground truth at selected locations. Sample plots were systematically established at three-mile intervals using a grid orientated roughly N-S and E-W. At each location,...

A Forested Tract-Size Profile of Florida's NIPF Landowners

Treesearch

Michael T. Thompson

1999-01-01

Abstract: Information gathered from 2,713 permanent Forest Inventory and Analysis (FIA) sample plots showed that over 1.0 million acres, or 15 percent of the nonindustrial private forest (NIPF) timberland in Florida is in forested tracts £ 10 acres. Forested tracts ranging from 11 to 100 acres accounted for the largest proportion of NIPF...

Selection of stand variables in southern Maine for making volume estimates from aerial photos

Treesearch

Earl J. Rogers; Gene Avery; Roy A. Chapman

1959-01-01

Aerial photographs are used widely in forest inventories. But there is a continuing need for improving the techniques of photo interpretation and making more efficient use of photographs. When the number or intensity of sample ground plots is controlled by airphoto classifications, a reliable stratification of the timber area is a must.

Biomass of first and second rotation loblolly pine plantations in the South Carolina Coastal Plain

Treesearch

Charles A. Gresham

2006-01-01

In the South Carolina Coastal Plain, intensive loblolly pine (Pinus taeda L.) plantation management, without fertilization, was sustainable through two rotations as measured by biomass accumulation. Fixed plot tree inventories and destructive tree sampling of first and second rotation sections of the same plantations were used to produce area based...

US army land condition-trend analysis (LCTA) program

NASA Astrophysics Data System (ADS)

Diersing, Victor E.; Shaw, Robert B.; Tazik, David J.

1992-05-01

The US Army Land Condition-Trend Analysis (LCTA) program is a standardized method of data collection, analysis, and reporting designed to meet multiple goals and objectives. The method utilizes vascular plant inventories, permanent field plot data, and wildlife inventories. Vascular plant inventories are used for environmental documentation, training of personnel, species identification during LCTA implementation, and as a survey for state and federal endangered or threatened species. The permanent field plot data documents the vegetational, edaphic, topographic, and disturbance characteristics of the installation. Inventory plots are allocated in a stratified random fashion across the installation utilizing a geographic information system that integrates satellite imagery and soil survey information. Ground cover, canopy cover, woody plant density, slope length, slope gradient, soil information, and disturbance data are collected at each plot. Plot data are used to: (1) describe plant communities, (2) characterize wildlife and threatened and endangered species habitat, (3) document amount and kind of military and nonmilitary disturbance, (4) determine the impact of military training on vegetation and soil resources, (5) estimate soil erosion potential, (6) classify land as to the kind and amount of use it can support, (7) determine allowable use estimates for tracked vehicle training, (8) document concealment resources, (9) identify lands that require restoration and evaluate the effectiveness of restorative techniques, and (10) evaluate potential acquisition property. Wildlife inventories survey small and midsize mammals, birds, bats, amphibians, and reptiles. Data from these surveys can be used for environmental documentation, to identify state and federal endangered and threatened species, and to evaluate the impact of military activities on wildlife populations. Short- and long-term monitoring of permanent field plots is used to evaluate and adjust land management decisions.

Using Forest Service multiple species inventory and monitoring protocols to count birds at forest inventory and analysis plots on the Caribbean landscape: results, observations, and challenges from year 1 of a 2-year study

Treesearch

Sonja N. Oswalt; Thomas J. Brandeis; David W. Steadman; Scott K. Robinson

2009-01-01

We conducted double-observer point counts of birds from December 3 to December 31, 2005, on preestablished permanent Forest Inventory and Analysis (FIA) plots and National Park Service System trails within the Virgin Islands National Park, St. John, U.S. Virgin Islands. We had three objectives: (1) to collect abundance and distribution data for wintering land birds,...

Weighted analysis methods for mapped plot forest inventory data: Tables, regressions, maps and graphs

Treesearch

Paul C. Van Deusen; Linda S. Heath

2010-01-01

Weighted estimation methods for analysis of mapped plot forest inventory data are discussed. The appropriate weighting scheme can vary depending on the type of analysis and graphical display. Both statistical issues and user expectations need to be considered in these methods. A weighting scheme is proposed that balances statistical considerations and the logical...

Forest Inventory and Analysis and Forest Health Monitoring: Piecing the Quilt

Treesearch

Joseph M. McCollum; Jamie K. Cochran

2005-01-01

Against the backdrop of a discussion about patchwork quilt assembly, the authors present background information on global grids. They show how to compose hexagons, an important task in systematically developing a subset of Forest Health Monitoring (FHM) Program plots from Forest Inventory and Analysis (FIA) plots. Finally, they outline the FHM and FIA grids, along with...

Vision for the Future of FIA: Paean to Progress, Possibilities, and Partners

Treesearch

Susan L. King; Charles T. Scott

2006-01-01

The Forest Inventory and Analysis (FIA) program of the U.S. Department of Agriculture Forest Service has made significant progress implementing the annualized inventory in 46 States in 2004. Major increases in program performance included the availability of plot data and the plots? corresponding approximate coordinates. A mill site study and biomass models were used...

North Dakota's forests, 2005: statistics, methods, and quality assurance

Treesearch

Patrick D. Miles; David E. Haugen; Charles J. Barnett

2011-01-01

The first full annual inventory of North Dakota's forests was completed in 2005 after 7,622 plots were selected and 164 forested plots were visited and measured. This report includes detailed information on forest inventory methods and data quality estimates. Important resource statistics are included in the tables. A detailed analysis of the North Dakota...

South Dakota's forests, 2005: statistics, methods, and quality assurance

Treesearch

Patrick D. Miles; Ronald J. Piva; Charles J. Barnett

2011-01-01

The first full annual inventory of South Dakota's forests was completed in 2005 after 8,302 plots were selected and 325 forested plots were visited and measured. This report includes detailed information on forest inventory methods and data quality estimates. Important resource statistics are included in the tables. A detailed analysis of the South Dakota...

Map of distribution of six forest ownership types in the conterminous United States

Treesearch

Jaketon H. Hewes; Brett J. Butler; Greg C. Liknes; Mark D. Nelson; Stephanie A. Snyder

2014-01-01

This map depicts the spatial distribution of ownership types across forest land in the conterminous United States circa 2009. The distribution is derived, in part, from Forest Inventory and Analysis (FIA) data that are collected at a sample intensity of approximately one plot per 2400 ha across the United States (U.S. Forest Service 2012). Ownership categories were...

Incidence of insects, diseases, and other damaging agents in Oregon forests.

Treesearch

Paul A. Dunham

2008-01-01

This report uses data from a network of forest inventory plots sampled at two points in time, annual aerial insect and disease surveys, and specialized pest damage surveys to quantify the incidence and impact of insects, diseases, and other damaging agents on Oregon's forests. The number and volume of trees damaged or killed by various agents is summarized....

Northeastern FIA Tree Taper Study: Current Status and Future Work

Treesearch

James A. Westfall; Charles T. Scott

2005-01-01

The northeastern unit of the Forest Inventory and Analysis program (NE-FIA) is engaged in an ongoing project to develop regionwide tree taper equations. Sampling intensity is based on NE-FIA plot data and is stratified by species, diameter class, and height class. To date, modeling research has been aimed largely at evaluating existing model forms (and hybrids thereof...

Missouri Ozark Forest Ecosystem Project: site history, soils, landforms, woody and herbaceous vegetation, down wood, and inventory methods for the landscape experiment.

Treesearch

Stephen R. Shifley; Brian L., eds. Brookshire

2000-01-01

Describes vegetation and physical site conditions at the initiation (1991-1995) of the Missouri Ozark Forest Ecosystem Project (MOFEP) in the southeastern Missouri Ozarks. Provides detailed information on sampling protocols and summarizes initial conditions of the landscape experiment prior to harvest treatments. Summaries are by plot, by ~800-acre...

The power of FIA Phase 3 Crown-Indicator variables to detect change

Treesearch

William Bechtold; KaDonna Randolph; Stanley Zarnoch

2009-01-01

The goal of Phase 3 Detection Monitoring as implemented by the Forest Inventory and Analysis Program is to identify forest ecosystems where conditions might be deteriorating in subtle ways over large areas. At the relatively sparse sampling intensity of the Phase 3 plot network, a rough measure of success for the forest health indicators developed for this purpose is...

Estimating and circumventing the effects of perturbing and swapping inventory plot locations

Treesearch

Ronald E. McRoberts; Geoffrey R. Holden; Mark D. Nelson; Greg C. Liknes; Warren K. Moser; Andrew J. Lister; Susan L. King; Elizabeth B. LaPoint; John W. Coulston; W. Brad Smith; Gregory A. Reams

2005-01-01

The Forest Inventory and Analysis (FIA) program of the USDA Forest Service reports data and information about the Nation's forest resources. Increasingly, users request that FIA data and information be reported and distributed in a geospatial context, and they request access to exact plot locations for their own analyses. However, the FIA program is constrained by...

Use of FVS for a forest-wide inventory on the Spokane Indian Reservation

Treesearch

Ted Hensold

2008-01-01

The Forest Vegetation Simulator (FVS) was used with Continuous Forest Inventory (CFI) data on the Spokane Indian Reservation to provide predicted yields over a 100-year period for 994 1/5 acre plots. The plots were grouped into five strata based on habitat type groupings, projected separately, and the stratum results were combined after processing. Results from the...

Evaluating the potential of structure from motion technology for forest inventory data collection

Treesearch

Demetrios Gatziolis

2015-01-01

Since the inception of its annual plot design, the Forest Inventory and Analysis (FIA) Program of the USDA Forest Service has integrated into its data collection operations elements of digital technology, including data loggers, laser distance recorders and clinometers, and GPS devices. Data collected with the assistance of this technology during a typical plot visit...

Inventory of oaks on California's national forest lands

Treesearch

Thomas Gaman; Kevin Casey

2002-01-01

California has 18+ million acres of land owned by the USDA Forest Service. This is almost 20 percent of the area of the state. From 1994-2000 the Region 5 Remote Sensing Lab collected forest, vegetation and fuels inventory data from thousands of permanent monitoring plots established on diverse sites on Forest Service lands throughout the region. The plots are...

The AFIS tree growth model for updating annual forest inventories in Minnesota

Treesearch

Margaret R. Holdaway

2000-01-01

As the Forest Service moves towards annual inventories, states may use model predictions of growth to update unmeasured plots. A tree growth model (AFIS) based on the scaled Weibull function and using the average-adjusted model form is presented. Annual diameter growth for four species was modeled using undisturbed plots from Minnesota's Aspen-Birch and Northern...

Patterns of exotic plant invasions in Pennsylvania's Allegheny National Forest using intensive Forest Inventory and Analysis plots

Treesearch

Cynthia D. Huebner; Randall S. Morin; Ann Zurbriggen; Robert L. White

2009-01-01

Intensive Forest Inventory and Analysis (FIA) plot data collected in the Allegheny National Forest (ANF), Pennsylvania, between 1999 and 2006 were evaluated for their ability to predict ANF's vulnerability to invasion by exotic plants. A total of 26 variables classified by biotic, abiotic, or disturbance characteristics were examined. Likelihood of colonization by...

Quantifying allometric model uncertainty for plot-level live tree biomass stocks with a data-driven, hierarchical framework

Treesearch

Brian J. Clough; Matthew B. Russell; Grant M. Domke; Christopher W. Woodall

2016-01-01

Accurate uncertainty assessments of plot-level live tree biomass stocks are an important precursor to estimating uncertainty in annual national greenhouse gas inventories (NGHGIs) developed from forest inventory data. However, current approaches employed within the United States’ NGHGI do not specifically incorporate methods to address error in tree-scale biomass...

NASA/BLM APT, phase 2. Volume 2: Technology demonstration. [Arizona

NASA Technical Reports Server (NTRS)

1981-01-01

Techniques described include: (1) steps in the preprocessing of LANDSAT data; (2) the training of a classifier; (3) maximum likelihood classification and precision; (4) geometric correction; (5) class description; (6) digitizing; (7) digital terrain data; (8) an overview of sample design; (9) allocation and selection of primary sample units; (10) interpretation of secondary sample units; (11) data collection ground plots; (12) data reductions; (13) analysis for productivity estimation and map verification; (14) cost analysis; and (150) LANDSAT digital products. The evaluation of the pre-inventory planning for P.J. is included.

Spatially Locating FIA Plots from Pixel Values

Treesearch

Greg C. Liknes; Geoffrey R. Holden; Mark D. Nelson; Ronald E. McRoberts

2005-01-01

The USDA Forest Service Forest Inventory and Analysis (FIA) program is required to ensure the confidentiality of the geographic locations of plots. To accommodate user requests for data without releasing actual plot coordinates, FIA creates overlays of plot locations on various geospatial data, including satellite imagery. Methods for reporting pixel values associated...

Strategies for Preserving Owner Privacy in the National Information Management System of the USDA Forest Service's Forest Inventory and Analysis Unit

Treesearch

Andrew Lister; Charles Scott; Susan King; Michael Hoppus; Brett Butler; Douglas Griffith

2005-01-01

The Food Security Act of 1985 prohibits the disclosure of any information collected by the USDA Forest Service's FIA program that would link individual landowners to inventory plot information. To address this, we developed a technique based on a "swapping" procedure in which plots with similar characteristics are exchanged, and on a ...

Assessing estimation techniques for missing plot observations in the U.S. forest inventory

Treesearch

Grant M. Domke; Christopher W. Woodall; Ronald E. McRoberts; James E. Smith; Mark A. Hatfield

2012-01-01

The U.S. Forest Service, Forest Inventory and Analysis Program made a transition from state-by-state periodic forest inventories--with reporting standards largely tailored to regional requirements--to a nationally consistent, annual inventory tailored to large-scale strategic requirements. Lack of measurements on all forest land during the periodic inventory, along...

Improving estimates of forest disturbance by combining observations from Landsat time series with U.S

Treesearch

Todd A. Schroeder; Sean P. Healey; Gretchen G. Moisen; Tracey S. Frescino; Warren B. Cohen; Chengquan Huang; Robert E. Kennedy; Zhiqiang Yang

2014-01-01

With earth's surface temperature and human population both on the rise a new emphasis has been placed on monitoring changes to forested ecosystems the world over. In the United States the U.S. Forest Service Forest Inventory and Analysis (FIA) program monitors the forested land base with field data collected over a permanent network of sample plots. Although these...

Forest resources of the Clearwater National Forest

Treesearch

Ryan P. Hughes

2011-01-01

The Interior West Forest Inventory and Analysis (IWFIA) Program of the USDA Forest Service, Rocky Mountain Research Station, as part of our National Forest System cooperative inventories, conducted a forest resource inventory on the Clearwater National Forest using a nationally standardized mapped-plot design (for more details see section "Inventory methods...

Forest resources of the Medicine Bow National Forest

Treesearch

Jim Steed

2008-01-01

The Interior West Forest Inventory and Analysis (IWFIA) Program of the USDA Forest Service, Rocky Mountain Research Station, as part of our National Forest System cooperative inventories, conducted a forest resource inventory on the Medicine Bow National Forest using a nationally standardized mapped-plot design (for more details see "Inventory methods"...

The poor man's Geographic Information System: plot expansion factors

Treesearch

Paul C. Van Deusen

2007-01-01

Plot expansion factors can serve as a crude Geographic Information System for users of Forest Inventory and Analysis (FIA) data. Each FIA plot has an associated expansion factor that is often interpreted as the number of forested acres that the plot represents. The derivation of expansion factors is discussed and it is shown that the mapped plot design requires a...

A first look at measurement error on FIA plots using blind plots in the Pacific Northwest

Treesearch

Susanna Melson; David Azuma; Jeremy S. Fried

2002-01-01

Measurement error in the Forest Inventory and Analysis work of the Pacific Northwest Station was estimated with a recently implemented blind plot measurement protocol. A small subset of plots was revisited by a crew having limited knowledge of the first crew's measurements. This preliminary analysis of the first 18 months' blind plot data indicates that...

High-fidelity national carbon mapping for resource management and REDD+

PubMed Central

2013-01-01

Background High fidelity carbon mapping has the potential to greatly advance national resource management and to encourage international action toward climate change mitigation. However, carbon inventories based on field plots alone cannot capture the heterogeneity of carbon stocks, and thus remote sensing-assisted approaches are critically important to carbon mapping at regional to global scales. We advanced a high-resolution, national-scale carbon mapping approach applied to the Republic of Panama – one of the first UN REDD + partner countries. Results Integrating measurements of vegetation structure collected by airborne Light Detection and Ranging (LiDAR) with field inventory plots, we report LiDAR-estimated aboveground carbon stock errors of ~10% on any 1-ha land parcel across a wide range of ecological conditions. Critically, this shows that LiDAR provides a highly reliable replacement for inventory plots in areas lacking field data, both in humid tropical forests and among drier tropical vegetation types. We then scale up a systematically aligned LiDAR sampling of Panama using satellite data on topography, rainfall, and vegetation cover to model carbon stocks at 1-ha resolution with estimated average pixel-level uncertainty of 20.5 Mg C ha-1 nationwide. Conclusions The national carbon map revealed strong abiotic and human controls over Panamanian carbon stocks, and the new level of detail with estimated uncertainties for every individual hectare in the country sets Panama at the forefront in high-resolution ecosystem management. With this repeatable approach, carbon resource decision-making can be made on a geospatially explicit basis, enhancing human welfare and environmental protection. PMID:23866822

Accuracy assessment of biomass and forested area classification from modis, landstat-tm satellite imagery and forest inventory plot data

Treesearch

Dumitru Salajanu; Dennis M. Jacobs

2007-01-01

The objective of this study was to determine how well forestfnon-forest and biomass classifications obtained from Landsat-TM and MODIS satellite data modeled with FIA plots, compare to each other and with forested area and biomass estimates from the national inventory data, as well as whether there is an increase in overall accuracy when pixel size (spatial resolution...

Measurement repeatability of a large-scale inventory of forest fuels

Treesearch

J.A. Westfall; C.W. Woodall

2007-01-01

An efficient and accurate inventory of forest fuels at large scales is critical for assessment of forest fire hazards across landscapes. The Forest Inventory and Analysis (FIA) program of the USDA Forest Service conducts a national inventory of fuels along with blind remeasurement of a portion of inventory plots to monitor and improve data quality. The goal of this...

TRIM timber projections: an evaluation based on forest inventory measurements.

Treesearch

John R. Mills

1989-01-01

Two consecutive timberland inventories collected from permanent plots in the natural pine type in North Carolina were used to evaluate the timber resource inventory model (TRIM). This study compares model predictions with field measurements and examines the effect of inventory data aggregation on the accuracy of projections. Projections were repeated for two geographic...

Forest resources of the Idaho Panhandle National Forest

Treesearch

Joshua C. Holte

2012-01-01

The Interior West Forest Inventory and Analysis (IWFIA) Program of the USDA Forest Service, Rocky Mountain Research Station, as part of our National Forest System cooperative inventories, conducted a forest resource inventory on the Idaho Panhandle National Forest (IPNF) using a nationally standardized mapped-plot design (for more details see "The inventory...

Forest resources of the Black Hills National Forest

Treesearch

Larry T. DeBlander

2002-01-01

The Interior West Forest Inventory and Analysis (IWFIA) Program of the USDA Forest Service, Rocky Mountain Research Station, as part of our National Forest System cooperative inventories, conducted a forest resource inventory on the Black Hills National Forest using a nationally standardized mapped-plot design (for more details see section "How was the inventory...

Forest resources of the Nez Perce National Forest

Treesearch

Michele Disney

2010-01-01

As part of a National Forest System cooperative inventory, the Interior West Forest Inventory and Analysis (IWFIA) Program of the USDA Forest Service conducted a forest resource inventory on the Nez Perce National Forest using a nationally standardized mapped-plot design (for more details see the section "Inventory methods"). This report presents highlights...

Forest resources of the Shoshone National Forest

Treesearch

James Menlove

2008-01-01

The Interior West Forest Inventory and Analysis (IWFIA) Program of the USDA Forest Service, Rocky Mountain Research Station, as part of our National Forest System cooperative inventories, conducted a forest resource inventory on the Shoshone National Forest using a nationally standardized mapped-plot design. This report presents the highlights of this 1999 inventory...

Baseline results from the Lichen Community Indicator Program in the Pacific Northwest: Air quality patterns and evidence of a nitrogen pollution problem

Treesearch

Sarah Jovan

2009-01-01

Why Are Epiphytic Lichen Communities Important? Lichens are one of the bioindicators used by the Forest Inventory and Analysis (FIA) Program to monitor forest health. To obtain data for use in its Lichen Community Indicator Program, FIA samples a regular network of permanent field plots to determine the composition of epiphytic, i.e., tree dwelling, lichen communities...

A comparison of two estimates of standard error for a ratio-of-means estimator for a mapped-plot sample design in southeast Alaska.

Treesearch

Willem W.S. van Hees

2002-01-01

Comparisons of estimated standard error for a ratio-of-means (ROM) estimator are presented for forest resource inventories conducted in southeast Alaska between 1995 and 2000. Estimated standard errors for the ROM were generated by using a traditional variance estimator and also approximated by bootstrap methods. Estimates of standard error generated by both...

Spatial Structure of Above-Ground Biomass Limits Accuracy of Carbon Mapping in Rainforest but Large Scale Forest Inventories Can Help to Overcome.

PubMed

Guitet, Stéphane; Hérault, Bruno; Molto, Quentin; Brunaux, Olivier; Couteron, Pierre

2015-01-01

Precise mapping of above-ground biomass (AGB) is a major challenge for the success of REDD+ processes in tropical rainforest. The usual mapping methods are based on two hypotheses: a large and long-ranged spatial autocorrelation and a strong environment influence at the regional scale. However, there are no studies of the spatial structure of AGB at the landscapes scale to support these assumptions. We studied spatial variation in AGB at various scales using two large forest inventories conducted in French Guiana. The dataset comprised 2507 plots (0.4 to 0.5 ha) of undisturbed rainforest distributed over the whole region. After checking the uncertainties of estimates obtained from these data, we used half of the dataset to develop explicit predictive models including spatial and environmental effects and tested the accuracy of the resulting maps according to their resolution using the rest of the data. Forest inventories provided accurate AGB estimates at the plot scale, for a mean of 325 Mg.ha-1. They revealed high local variability combined with a weak autocorrelation up to distances of no more than10 km. Environmental variables accounted for a minor part of spatial variation. Accuracy of the best model including spatial effects was 90 Mg.ha-1 at plot scale but coarse graining up to 2-km resolution allowed mapping AGB with accuracy lower than 50 Mg.ha-1. Whatever the resolution, no agreement was found with available pan-tropical reference maps at all resolutions. We concluded that the combined weak autocorrelation and weak environmental effect limit AGB maps accuracy in rainforest, and that a trade-off has to be found between spatial resolution and effective accuracy until adequate "wall-to-wall" remote sensing signals provide reliable AGB predictions. Waiting for this, using large forest inventories with low sampling rate (<0.5%) may be an efficient way to increase the global coverage of AGB maps with acceptable accuracy at kilometric resolution.

Estimating down deadwood from FIA forest inventory variables in Maine

Treesearch

David C. Chojnacky; Linda S. Heath

2002-01-01

Down deadwood (DDW) is a carbon component important in the function and structure of forest ecosystems, but estimating DDW is problematic because these data are not widely available in forest inventory databases. However, DDW data were collected on USDA Forest Service Forest Inventory and Analysis (FIA) plots during Maine's 1995 inventory. This study examines ways...

Estimating down dead wood from FIA forest inventory variables in Maine

Treesearch

David C. Chojnacky; Linda S. Heath

2002-01-01

Down deadwood (DDW) is a carbon component important in the function and structure of forest ecosystems, but estimating DDW is problematic because these data are not widely available in forest inventory databases. However, DDW data were collected on USDA Forest Service Forest Inventory and Analysis (FIA) plots during Maine's 1995 inventory. This study examines ways...

Bridging the gap between strategic and management forest inventories

Treesearch

Ronald E. McRoberts

2009-01-01

Strategic forest inventory programs collect information for a large number of variables on a relatively sparse array of field plots. Data from these inventories are used to produce estimates for large areas such as states and provinces, regions, or countries. The purpose of management forest inventories is to guide management decisions for small areas such as stands....

A Multinomial Logit Approach to Estimating Regional Inventories by Product Class

Treesearch

Lawrence Teeter; Xiaoping Zhou

1998-01-01

Current timber inventory projections generally lack information on inventory by product classes. Most models available for inventory projection and linked to supply analyses are limited to projecting aggregate softwood and hardwood. The objective of this research is to develop a methodology to distribute the volume on each FIA survey plot to product classes and...

A density management diagram for even-aged ponderosa pine stands

Treesearch

James N. Long; John D. Shaw

2005-01-01

We developed a density management diagram (DMD) for ponderosa pine using Forest Inventory and Analysis (FIA) data. Analysis plots were drawn from all FIA plots in the western United States on which ponderosa pine occurred. A total of 766 plots met the criteria for analysis. Selection criteria were for purity, defined as ponderosa pine basal area 80% of plot basal area...

Integrating P3 Data Into P2 Analyses: What is the Added Value

Treesearch

James R. Steinman

2001-01-01

The Forest Inventory and Analysis and Forest Health Monitoring Programs of the USDA Forest Service are integrating field procedures for measuring their networks of plots throughout the United States. These plots are now referred to as Phase 2 (P2) and Phase 3 (P3) plots, respectively, and 1 out of every 16 P2 plots will also be a P3 plot. Mensurational methods will be...

The role of pre-field operations at four forest inventory units: We can see the trees, not just the forest

Treesearch

Sara A. Goeking; Greg C. Liknes

2009-01-01

The Forest Inventory and Analysis (FIA) program attempts to inventory all forested lands throughout the United States. Each of the four FIA units has developed a process to minimize inventory costs by refraining from visiting those plots in the national inventory grid that are undoubtedly nonforest. We refer to this process as pre-field operations. Until recently, the...

Modeling biophysical properties of broad-leaved stands in the hyrcanian forests of Iran using fused airborne laser scanner data and ultraCam-D images

NASA Astrophysics Data System (ADS)

Mohammadi, Jahangir; Shataee, Shaban; Namiranian, Manochehr; Næsset, Erik

2017-09-01

Inventories of mixed broad-leaved forests of Iran mainly rely on terrestrial measurements. Due to rapid changes and disturbances and great complexity of the silvicultural systems of these multilayer forests, frequent repetition of conventional ground-based plot surveys is often cost prohibitive. Airborne laser scanning (ALS) and multispectral data offer an alternative or supplement to conventional inventories in the Hyrcanian forests of Iran. In this study, the capability of a combination of ALS and UltraCam-D data to model stand volume, tree density, and basal area using random forest (RF) algorithm was evaluated. Systematic sampling was applied to collect field plot data on a 150 m × 200 m sampling grid within a 1100 ha study area located at 36°38‧- 36°42‧N and 54°24‧-54°25‧E. A total of 308 circular plots (0.1 ha) were measured for calculation of stand volume, tree density, and basal area per hectare. For each plot, a set of variables was extracted from both ALS and multispectral data. The RF algorithm was used for modeling of the biophysical properties using ALS and UltraCam-D data separately and combined. The results showed that combining the ALS data and UltraCam-D images provided a slight increase in prediction accuracy compared to separate modeling. The RMSE as percentage of the mean, the mean difference between observed and predicted values, and standard deviation of the differences using a combination of ALS data and UltraCam-D images in an independent validation at 0.1-ha plot level were 31.7%, 1.1%, and 84 m3 ha-1 for stand volume; 27.2%, 0.86%, and 6.5 m2 ha-1 for basal area, and 35.8%, -4.6%, and 77.9 n ha-1 for tree density, respectively. Based on the results, we conclude that fusion of ALS and UltraCam-D data may be useful for modeling of stand volume, basal area, and tree density and thus gain insights into structural characteristics in the complex Hyrcanian forests.

Average Stand Age from Forest Inventory Plots Does Not Describe Historical Fire Regimes in Ponderosa Pine and Mixed-Conifer Forests of Western North America.

PubMed

Stevens, Jens T; Safford, Hugh D; North, Malcolm P; Fried, Jeremy S; Gray, Andrew N; Brown, Peter M; Dolanc, Christopher R; Dobrowski, Solomon Z; Falk, Donald A; Farris, Calvin A; Franklin, Jerry F; Fulé, Peter Z; Hagmann, R Keala; Knapp, Eric E; Miller, Jay D; Smith, Douglas F; Swetnam, Thomas W; Taylor, Alan H

Quantifying historical fire regimes provides important information for managing contemporary forests. Historical fire frequency and severity can be estimated using several methods; each method has strengths and weaknesses and presents challenges for interpretation and verification. Recent efforts to quantify the timing of historical high-severity fire events in forests of western North America have assumed that the "stand age" variable from the US Forest Service Forest Inventory and Analysis (FIA) program reflects the timing of historical high-severity (i.e. stand-replacing) fire in ponderosa pine and mixed-conifer forests. To test this assumption, we re-analyze the dataset used in a previous analysis, and compare information from fire history records with information from co-located FIA plots. We demonstrate that 1) the FIA stand age variable does not reflect the large range of individual tree ages in the FIA plots: older trees comprised more than 10% of pre-stand age basal area in 58% of plots analyzed and more than 30% of pre-stand age basal area in 32% of plots, and 2) recruitment events are not necessarily related to high-severity fire occurrence. Because the FIA stand age variable is estimated from a sample of tree ages within the tree size class containing a plurality of canopy trees in the plot, it does not necessarily include the oldest trees, especially in uneven-aged stands. Thus, the FIA stand age variable does not indicate whether the trees in the predominant size class established in response to severe fire, or established during the absence of fire. FIA stand age was not designed to measure the time since a stand-replacing disturbance. Quantification of historical "mixed-severity" fire regimes must be explicit about the spatial scale of high-severity fire effects, which is not possible using FIA stand age data.

Average Stand Age from Forest Inventory Plots Does Not Describe Historical Fire Regimes in Ponderosa Pine and Mixed-Conifer Forests of Western North America

PubMed Central

Stevens, Jens T.; Safford, Hugh D.; North, Malcolm P.; Fried, Jeremy S.; Gray, Andrew N.; Brown, Peter M.; Dolanc, Christopher R.; Dobrowski, Solomon Z.; Falk, Donald A.; Farris, Calvin A.; Franklin, Jerry F.; Fulé, Peter Z.; Hagmann, R. Keala; Knapp, Eric E.; Miller, Jay D.; Smith, Douglas F.; Swetnam, Thomas W.; Taylor, Alan H.

2016-01-01

Quantifying historical fire regimes provides important information for managing contemporary forests. Historical fire frequency and severity can be estimated using several methods; each method has strengths and weaknesses and presents challenges for interpretation and verification. Recent efforts to quantify the timing of historical high-severity fire events in forests of western North America have assumed that the “stand age” variable from the US Forest Service Forest Inventory and Analysis (FIA) program reflects the timing of historical high-severity (i.e. stand-replacing) fire in ponderosa pine and mixed-conifer forests. To test this assumption, we re-analyze the dataset used in a previous analysis, and compare information from fire history records with information from co-located FIA plots. We demonstrate that 1) the FIA stand age variable does not reflect the large range of individual tree ages in the FIA plots: older trees comprised more than 10% of pre-stand age basal area in 58% of plots analyzed and more than 30% of pre-stand age basal area in 32% of plots, and 2) recruitment events are not necessarily related to high-severity fire occurrence. Because the FIA stand age variable is estimated from a sample of tree ages within the tree size class containing a plurality of canopy trees in the plot, it does not necessarily include the oldest trees, especially in uneven-aged stands. Thus, the FIA stand age variable does not indicate whether the trees in the predominant size class established in response to severe fire, or established during the absence of fire. FIA stand age was not designed to measure the time since a stand-replacing disturbance. Quantification of historical “mixed-severity” fire regimes must be explicit about the spatial scale of high-severity fire effects, which is not possible using FIA stand age data. PMID:27196621

Diameter Growth Models Using Minnesota Forest Inventory and Analysis Data

Treesearch

Veronica C. Lessard; Ronald E. McRoberts; Margaret R. Holdaway

2001-01-01

The Forest Inventory and Analysis (FIA) program of the USDA Forest Service North Central Research Station (NCRS) has begun replacing the 12-to 13-yr periodic inventory cycles for the states in the North Central region with annual inventories featuring measurement of approximately 20% of all plots in each of the 11 states each year. State reports on summaries of the...

Do trees fall downhill? Relationship between treefall direction and slope-aspect and wind in eight old-growth oak stands in the central hardwood forest

Treesearch

James S. Rentch

2011-01-01

This study examined the relationship between direction of treefall and slope-aspect, and prevailing wind in eight old-growth stands where single-tree canopy gaps characterize the dominant disturbance regime. All live and downed trees were inventoried in 0.45-ha sample plots. To determine crown asymmetry, crown sizes of live trees were measured along two perpendicular...

Composition and Structure of a l930s-Era Pine-Hardwood Stand in Arkansas

Treesearch

Don C. Bragg

2004-01-01

This paper describes an unmanaged 1930s-era pine-hardwood stand on a minor stream terrace in Ashley County, AR. Probably inventoried as a part of an early growth and yield study, the sample plot was approximately 3.2 ha in size and contained at least 21 tree species. Loblolly pine comprised 39.1% of all stems, followed by willow oak (12.7%), winged elm (9.6%), sweetgum...

Precise FIA plot registration using field and dense LIDAR data

Treesearch

Demetrios Gatziolis

2009-01-01

Precise registration of forest inventory and analysis (FIA) plots is a prerequisite for an effective fusion of field data with ancillary spatial information, which is an approach commonly employed in the mapping of various forest parameters. Although the adoption of Global Positioning System technology has improved the precision of plot coordinates obtained during...

Refining FIA plot locations using LiDAR point clouds

Treesearch

Charlie Schrader-Patton; Greg C. Liknes; Demetrios Gatziolis; Brian M. Wing; Mark D. Nelson; Patrick D. Miles; Josh Bixby; Daniel G. Wendt; Dennis Kepler; Abbey Schaaf

2015-01-01

Forest Inventory and Analysis (FIA) plot location coordinate precision is often insufficient for use with high resolution remotely sensed data, thereby limiting the use of these plots for geospatial applications and reducing the validity of models that assume the locations are precise. A practical and efficient method is needed to improve coordinate precision. To...

Assessing the effect of snow/water obstructions on the measurement of tree seedlings in a large-scale temperate forest inventory

Treesearch

C.W. Woodall; J.A. Westfall; K. Zhu; D.J. Johnson

2013-01-01

National-scale forest inventories have endeavoured to include holistic measurements of forest health inclusive of attributes such as downed dead wood and tree regeneration that occur in the forest understory. Inventories may require year-round measurement of inventory plots with some of these measurements being affected by seasonal obstructions (e.g. snowpacks and...

Integrating LIDAR and forest inventories to fill the trees outside forests data gap.

PubMed

Johnson, Kristofer D; Birdsey, Richard; Cole, Jason; Swatantran, Anu; O'Neil-Dunne, Jarlath; Dubayah, Ralph; Lister, Andrew

2015-10-01

Forest inventories are commonly used to estimate total tree biomass of forest land even though they are not traditionally designed to measure biomass of trees outside forests (TOF). The consequence may be an inaccurate representation of all of the aboveground biomass, which propagates error to the outputs of spatial and process models that rely on the inventory data. An ideal approach to fill this data gap would be to integrate TOF measurements within a traditional forest inventory for a parsimonious estimate of total tree biomass. In this study, Light Detection and Ranging (LIDAR) data were used to predict biomass of TOF in all "nonforest" Forest Inventory and Analysis (FIA) plots in the state of Maryland. To validate the LIDAR-based biomass predictions, a field crew was sent to measure TOF on nonforest plots in three Maryland counties, revealing close agreement at both the plot and county scales between the two estimates. Total tree biomass in Maryland increased by 25.5 Tg, or 15.6%, when biomass of TOF were included. In two counties (Carroll and Howard), there was a 47% increase. In contrast, counties located further away from the interstate highway corridor showed only a modest increase in biomass when TOF were added because nonforest conditions were less common in those areas. The advantage of this approach for estimating biomass of TOF is that it is compatible with, and explicitly separates TOF biomass from, forest biomass already measured by FIA crews. By predicting biomass of TOF at actual FIA plots, this approach is directly compatible with traditionally reported FIA forest biomass, providing a framework for other states to follow, and should improve carbon reporting and modeling activities in Maryland.

Inventory-based landscape-scale simulation of management effectiveness and economic feasibility with BioSum

Treesearch

Jeremy S. Fried; Larry D. Potts; Sara M. Loreno; Glenn A. Christensen; R. Jamie Barbour

2017-01-01

The Forest Inventory and Analysis (FIA)-based BioSum (Bioregional Inventory Originated Simulation Under Management) is a free policy analysis framework and workflow management software solution. It addresses complex management questions concerning forest health and vulnerability for large, multimillion acre, multiowner landscapes using FIA plot data as the initial...

Forest resources of the Bighorn National Forest

Treesearch

Christopher Witt

2008-01-01

The Interior West Forest Inventory and Analysis (IWFIA) Program of the USDA Forest Service, Rocky Mountain Research Station, as part of our National Forest System cooperative inventories, conducted a forest resource inventory on the Bighorn National Forest (Bighorn) using a nationally standardized mapped-plot design. This report presents the highlights of this 2000...

Imputing forest carbon stock estimates from inventory plots to a nationally continuous coverage

PubMed Central

2013-01-01

The U.S. has been providing national-scale estimates of forest carbon (C) stocks and stock change to meet United Nations Framework Convention on Climate Change (UNFCCC) reporting requirements for years. Although these currently are provided as national estimates by pool and year to meet greenhouse gas monitoring requirements, there is growing need to disaggregate these estimates to finer scales to enable strategic forest management and monitoring activities focused on various ecosystem services such as C storage enhancement. Through application of a nearest-neighbor imputation approach, spatially extant estimates of forest C density were developed for the conterminous U.S. using the U.S.’s annual forest inventory. Results suggest that an existing forest inventory plot imputation approach can be readily modified to provide raster maps of C density across a range of pools (e.g., live tree to soil organic carbon) and spatial scales (e.g., sub-county to biome). Comparisons among imputed maps indicate strong regional differences across C pools. The C density of pools closely related to detrital input (e.g., dead wood) is often highest in forests suffering from recent mortality events such as those in the northern Rocky Mountains (e.g., beetle infestations). In contrast, live tree carbon density is often highest on the highest quality forest sites such as those found in the Pacific Northwest. Validation results suggest strong agreement between the estimates produced from the forest inventory plots and those from the imputed maps, particularly when the C pool is closely associated with the imputation model (e.g., aboveground live biomass and live tree basal area), with weaker agreement for detrital pools (e.g., standing dead trees). Forest inventory imputed plot maps provide an efficient and flexible approach to monitoring diverse C pools at national (e.g., UNFCCC) and regional scales (e.g., Reducing Emissions from Deforestation and Forest Degradation projects) while allowing timely incorporation of empirical data (e.g., annual forest inventory). PMID:23305341

Florida's forests-2005 update

Treesearch

Mark J. Brown

2007-01-01

This bulletin highlights principal findings of an annual inventory of Florida's forests. Data summaries are based on measurements of 60 percent of the plots in the State. Additional data summaries and bulletins will be published as the remaining plots are measured.

Corrections for Cluster-Plot Slop

Treesearch

Harry T. Valentine; Mark J. Ducey; Jeffery H. Gove; Adrian Lanz; David L.R. Affleck

2006-01-01

Cluster-plot designs, including the design used by the Forest Inventory and Analysis program of the USDA Forest Service (FIA), are attended by a complicated boundary slopover problem. Slopover occurs where inclusion zones of objects of interest cross the boundary of the area of interest. The dispersed nature of inclusion zones that arise from the use of cluster plots...

Analysis issues due to mapped conditions changing over time

Treesearch

Paul. Van Deusen

2015-01-01

Plot mapping is one of the innovations that were implemented when FIA moved to the annual forest inventory system. Mapped plots can improve the precision of estimates if the mapped conditions are carefully chosen and used judiciously. However, after plots are remeasured multiple times, it can be difficult to properly track changes in conditions and incorporate this...

Estimating number and size of forest patches from FIA plot data

Treesearch

Mark D. Nelson; Andrew J. Lister; Mark H. Hansen

2009-01-01

Forest inventory and analysis (FIA) annual plot data provide for estimates of forest area, type, volume, growth, and other attributes. Estimates of forest landscape metrics, such as those describing abundance, size, and shape of forest patches, however, typically are not derived from FIA plot data but from satellite image-based land cover maps. Associating image-based...

Boundary pint corrections for variable radius plots - simulation results

Treesearch

Margaret Penner; Sam Otukol

2000-01-01

The boundary plot problem is encountered when a forest inventory plot includes two or more forest conditions. Depending on the correction method used, the resulting estimates can be biased. The various correction alternatives are reviewed. No correction, area correction, half sweep, and toss-back methods are evaluated using simulation on an actual data set. Based on...

The 2002 RPA Plot Summary database users manual

Treesearch

Patrick D. Miles; John S. Vissage; W. Brad Smith

2004-01-01

Describes the structure of the RPA 2002 Plot Summary database and provides information on generating estimates of forest statistics from these data. The RPA 2002 Plot Summary database provides a consistent framework for storing forest inventory data across all ownerships across the entire United States. The data represents the best available data as of October 2001....

Estimating mapped-plot forest attributes with ratios of means

Treesearch

S.J. Zarnoch; W.A. Bechtold

2000-01-01

The mapped-plot design utilized by the U.S. Department of Agriculture (USDA) Forest Inventory and Analysis and the National Forest Health Monitoring Programs is described. Data from 2458 forested mapped plots systematically spread across 25 States reveal that 35 percent straddle multiple conditions. The ratio-of-means estimator is developed as a method to obtain...

Forest inventory with LiDAR and stereo DSM on Washington department of natural resources lands

Treesearch

Jacob L. Strunk; Peter J. Gould

2015-01-01

DNR’s forest inventory group has completed its first version of a new remote-sensing based forest inventory system covering 1.4 million acres of DNR forest lands. We use a combination of field plots, lidar, NAIP, and a NAIP-derived canopy surface DSM. Given that height drives many key inventory variables (e.g. height, volume, biomass, carbon), remote-sensing derived...

Improving Forest Inventory and Analysis efficiency with common land unit information

Treesearch

Greg C. Liknes; Mark D. Nelson

2009-01-01

The Forest Service, U.S. Department of Agriculture's (USDA's) Northern Research Station Forest Inventory and Analysis program (NRS-FIA) examines inventory locations on digital aerial imagery to determine if the land use at each plot location meets the FIA definition of forest and thereby becomes a field visit site. This manual image-interpretation effort...

Adding net growth, removals, and mortality estimates for biomass and carbon in FIADB

Treesearch

Jeffery A. Turner

2015-01-01

Traditional growth, removals, and mortality (GRM) estimates produced from Forest Inventory and Analysis (FIA) periodic inventories were limited to changes in volume on timberland. Estimates on forestland were added in the east as the first installment of annual inventory plots was remeasured. The western FIA units have begun annual remeasurement, precipitating the need...

A technique for conducting point pattern analysis of cluster plot stem-maps

Treesearch

C.W. Woodall; J.M. Graham

2004-01-01

Point pattern analysis of forest inventory stem-maps may aid interpretation and inventory estimation of forest attributes. To evaluate the techniques and benefits of conducting point pattern analysis of forest inventory stem-maps, Ripley`s K(t) was calculated for simulated tree spatial distributions and for over 600 USDA Forest Service Forest...

Using classified Landsat Thematic Mapper data for stratification in a statewide forest inventory

Treesearch

Mark H. Hansen; Daniel G. Wendt

2000-01-01

The 1998 Indiana/Illinois forest inventory (USDA Forest Service, Forest Inventory and Analysis (FIA)) used Landsat Thematic Mapper (TM) data for stratification. Classified images made by the National Gap Analysis Program (GAP) stratified FIA plots into four classes (nonforest, nonforest/ forest, forest/nonforest, and forest) based on a two pixel forest edge buffer zone...

Using Classified Landsat Thematic Mapper Data for Stratification in a Statewide Forest Inventory

Treesearch

Mark H. Hansen; Daniel G. Wendt

2000-01-01

The 1998 Indiana/Illinois forest inventory (USDA Forest Service, Forest Inventory and Analysis (FIA)) used Landsat Thematic Mapper (TM} data for stratification. Classified images made by the National Gap Analysis Program (GAP) stratified FIA plots into four classes (nonforest, nonforest/forest, forest/nonforest, and forest) based on a two pixel forest edge buffer zone...

Forest Inventory and Analysis Database of the United States of America (FIA)

Treesearch

Andrew N. Gray; Thomas J. Brandeis; John D. Shaw; William H. McWilliams; Patrick Miles

2012-01-01

Extensive vegetation inventories established with a probabilistic design are an indispensable tool in describing distributions of species and community types and detecting changes in composition in response to climate or other drivers. The Forest Inventory and Analysis Program measures vegetation in permanent plots on forested lands across the United States of America...

Increased uniformity by planting clones will likely have a minimal effect on inventory costs

Treesearch

Curtis L. VanderSchaaf; Dean W. Coble; David B. South

2012-01-01

When conducting inventories, reducing variability among tree diameters, heights, and ultimately volumes or biomass, can reduce the number of points/plots needed to obtain a desired level of precision. We present a simple analysis examining the potential reduction in discounted inventory costs when stand variability is decreased (via improved genetics and intensive...

The Effects of Removing Condition Boundaries on FIA Estimates

Treesearch

David Gartner; Gregory Reams

2005-01-01

When Forest Inventory and Analysis (FIA) changed to the national standards for the inventory system, plots with multiple condition codes were introduced to the Southern Station's FIA unit. FIA maps up to five different conditions on completely or partially forested 1/24-acre subplots. This change has made producing inventory estimates more complex because the data...

Forest inventory and management-based visual preference models of southern pine stands

Treesearch

Victor A. Rudis; James H. Gramann; Edward J. Ruddell; Joanne M. Westphal

1988-01-01

Statistical models explaining students' ratings of photographs of within stand forest scenes were constructed for 99 forest inventory plots in east Texas pine and oak-pine forest types. Models with parameters that are sensitive to visual preference yet compatible with forest management and timber inventories are presented. The models suggest that the density of...

A density management diagram for even-aged Sierra Nevada mixed-conifer stands

Treesearch

James N. Long; John D. Shaw

2012-01-01

We have developed a density management diagram (DMD) for even-aged mixed-conifer stands in the Sierra Nevada Mountains using forest inventory and analysis (FIA) data. Analysis plots were drawn from FIA plots in California, southern Oregon, and western Nevada which included those conifer species associated with the mixed-conifer forest type. A total of 204 plots met the...

Access and Use of FIA Data Through FIA Spatial Data Services

Treesearch

Elizabeth LaPoint

2005-01-01

Forest Inventory and Analysis (FIA) Spatial Data Services (SDS) was established in May 2002 to facilitate outside access to FIA data and allow use of georeferenced plot data while protecting the confidentiality of plot locations. Modification of the Food Security Act of 1985 legislated the protection of information on plot location and ownership. Penalties were put in...

Accuracy assessment of the vegetation continuous field tree cover product using 3954 ground plots in the southwestern USA

Treesearch

M. A. White; J. D. Shaw; R. D. Ramsey

2005-01-01

An accuracy assessment of the Moderate Resolution Imaging Spectroradiometer (MODIS) vegetation continuous field (VCF) tree cover product using two independent ground-based tree cover databases was conducted. Ground data included 1176 Forest Inventory and Analysis (FIA) plots for Arizona and 2778 Southwest Regional GAP (SWReGAP) plots for Utah and western Colorado....

Spatial Structure of Above-Ground Biomass Limits Accuracy of Carbon Mapping in Rainforest but Large Scale Forest Inventories Can Help to Overcome

PubMed Central

Guitet, Stéphane; Hérault, Bruno; Molto, Quentin; Brunaux, Olivier; Couteron, Pierre

2015-01-01

Precise mapping of above-ground biomass (AGB) is a major challenge for the success of REDD+ processes in tropical rainforest. The usual mapping methods are based on two hypotheses: a large and long-ranged spatial autocorrelation and a strong environment influence at the regional scale. However, there are no studies of the spatial structure of AGB at the landscapes scale to support these assumptions. We studied spatial variation in AGB at various scales using two large forest inventories conducted in French Guiana. The dataset comprised 2507 plots (0.4 to 0.5 ha) of undisturbed rainforest distributed over the whole region. After checking the uncertainties of estimates obtained from these data, we used half of the dataset to develop explicit predictive models including spatial and environmental effects and tested the accuracy of the resulting maps according to their resolution using the rest of the data. Forest inventories provided accurate AGB estimates at the plot scale, for a mean of 325 Mg.ha-1. They revealed high local variability combined with a weak autocorrelation up to distances of no more than10 km. Environmental variables accounted for a minor part of spatial variation. Accuracy of the best model including spatial effects was 90 Mg.ha-1 at plot scale but coarse graining up to 2-km resolution allowed mapping AGB with accuracy lower than 50 Mg.ha-1. Whatever the resolution, no agreement was found with available pan-tropical reference maps at all resolutions. We concluded that the combined weak autocorrelation and weak environmental effect limit AGB maps accuracy in rainforest, and that a trade-off has to be found between spatial resolution and effective accuracy until adequate “wall-to-wall” remote sensing signals provide reliable AGB predictions. Waiting for this, using large forest inventories with low sampling rate (<0.5%) may be an efficient way to increase the global coverage of AGB maps with acceptable accuracy at kilometric resolution. PMID:26402522

A baseline assessment of forest composition, structure, and health in the Hawai‘i experimental tropical forests

Treesearch

Robert R. Pattison; Andrew N. Gray; Lori Tango

2015-01-01

The US Forest Service’s Forest Inventory and Analysis (FIA) Program of the Pacific Northwest (PNW) Research Station has been working in the Hawaiian islands since 2010. During this time they have installed a base grid of field plots across all of the Hawaiian Islands and an intensified sample of two experimental forests, the Laupāhoehoe and Pu‘u Wa‘awa‘a units of the...

Terrestrial Biological Inventory Degognia and Fountain Bluff Levee and Drainage District and Grand Tower Drainage and Levee District, Jackson County, Illinois.

DTIC Science & Technology

1978-08-01

others. Unusual flowering herbs in the mesic woods community are sessile trillium (Trillium sessile), wild leek (Allium tricoccum), and the deli- cate...provided by herbs , vines, and woody plant seedlings is 40%. Although the South Woods is fairly uniform throughout most of its area, one extensive colony...encountered herbs and they provide the greatest per cent of ground cover. Each species occurred in every one of the sample plots. Rough bedstraw averaged 31.5

Species distribution models predict temporal but not spatial variation in forest growth.

PubMed

van der Maaten, Ernst; Hamann, Andreas; van der Maaten-Theunissen, Marieke; Bergsma, Aldo; Hengeveld, Geerten; van Lammeren, Ron; Mohren, Frits; Nabuurs, Gert-Jan; Terhürne, Renske; Sterck, Frank

2017-04-01

Bioclimate envelope models have been widely used to illustrate the discrepancy between current species distributions and their potential habitat under climate change. However, the realism and correct interpretation of such projections has been the subject of considerable discussion. Here, we investigate whether climate suitability predictions correlate to tree growth, measured in permanent inventory plots and inferred from tree-ring records. We use the ensemble classifier RandomForest and species occurrence data from ~200,000 inventory plots to build species distribution models for four important European forestry species: Norway spruce, Scots pine, European beech, and pedunculate oak. We then correlate climate-based habitat suitability with volume measurements from ~50-year-old stands, available from ~11,000 inventory plots. Secondly, habitat projections based on annual historical climate are compared with ring width from ~300 tree-ring chronologies. Our working hypothesis is that habitat suitability projections from species distribution models should to some degree be associated with temporal or spatial variation in these growth records. We find that the habitat projections are uncorrelated with spatial growth records (inventory plot data), but they do predict interannual variation in tree-ring width, with an average correlation of .22. Correlation coefficients for individual chronologies range from values as high as .82 or as low as -.31. We conclude that tree responses to projected climate change are highly site-specific and that local suitability of a species for reforestation is difficult to predict. That said, projected increase or decrease in climatic suitability may be interpreted as an average expectation of increased or reduced growth over larger geographic scales.

South Carolina's forest resources - 2000 update

Treesearch

Roger C. Conner; Raymond M. Sheffield

2001-01-01

This bulletin highlights the principal findings of an annual inventory of South Carolina's forest resources. Data summaries are based upon 60 percent of the plots in the State. Additional data summaries and bulletins will be published as the full set of plots are completed.

FIA Quality Assurance Program: Evaluation of a Tree Matching Algorithm for Paired Forest Inventory Data

Treesearch

James E. Pollard; James A. Westfall; Paul A. Patterson; David L. Gartner

2005-01-01

The quality of Forest Inventory and Analysis inventory data can be documented by having quality assurance crews remeasure plots originally measured by field crews within 2 to 3 weeks of the initial measurement, and assessing the difference between the original and remeasured data. Estimates of measurement uncertainty for the data are generated using paired data...

Estimating forest conversion rates with annual forest inventory data

Treesearch

Paul C. Van Deusen; Francis A. Roesch

2009-01-01

The rate of land-use conversion from forest to nonforest or natural forest to forest plantation is of interest for forest certification purposes and also as part of the process of assessing forest sustainability. Conversion rates can be estimated from remeasured inventory plots in general, but the emphasis here is on annual inventory data. A new estimator is proposed...

Use of USDA forest inventory and analysis data to assess oak tree health in Minnesota

Treesearch

Kathryn W. Kromroy; Jennifer Juzwik; Paul D. Castillo

2003-01-01

As a precursor to a regional assessment for the Upper Midwest, three variables were examined as measures of oak health in Minnesota between 1974 and 1990 using USDA Forest Service Inventory and Analysis data. Mortality was 6 percent in the 1986-1990 inventory based on numbers of dead oaks per total oaks on plots with...

The Finnish national forest inventory

Treesearch

Erkki Tomppo

2009-01-01

The National Forest Inventory (NFI) of Finland has produced large-area forest resource information since the beginning of 1920s (Ilvessalo 1927). When the 10th inventory (NFI10) started in 2004, the design was changed and the rotation shortened to 5 years. Measurements are done in the entire country each year through measuring one-fifth of the plots. About one-fifth of...

Attributes of down woody materials in hardwood forests of the Eastern United States

Treesearch

Christopher W. Woodall; Sonja N. Oswalt; Randall S. Morin

2007-01-01

The Forest Inventory and Analysis Program (FIA) of the USDA Forest Service conducts a national inventory of down woody materials (DWM) on forestland in the United States. Estimates of DWM for inventory plots occurring in eastern U.S. hardwood forests facilitate large-scale assessment of hardwood forest fuel loadings and wildlife habitat. Therefore, the objectives of...

Relative efficiency of anuran sampling methods in a restinga habitat (Jurubatiba, Rio de Janeiro, Brazil).

PubMed

Rocha, C F D; Van Sluys, M; Hatano, F H; Boquimpani-Freitas, L; Marra, R V; Marques, R V

2004-11-01

Studies on anurans in restinga habitats are few and, as a result, there is little information on which methods are more efficient for sampling them in this environment. Ten methods are usually used for sampling anuran communities in tropical and sub-tropical areas. In this study we evaluate which methods are more appropriate for this purpose in the restinga environment of Parque Nacional da Restinga de Jurubatiba. We analyzed six methods among those usually used for anuran samplings. For each method, we recorded the total amount of time spent (in min.), the number of researchers involved, and the number of species captured. We calculated a capture efficiency index (time necessary for a researcher to capture an individual frog) in order to make comparable the data obtained. Of the methods analyzed, the species inventory (9.7 min/searcher /ind.- MSI; richness = 6; abundance = 23) and the breeding site survey (9.5 MSI; richness = 4; abundance = 22) were the most efficient. The visual encounter inventory (45.0 MSI) and patch sampling (65.0 MSI) methods were of comparatively lower efficiency restinga, whereas the plot sampling and the pit-fall traps with drift-fence methods resulted in no frog capture. We conclude that there is a considerable difference in efficiency of methods used in the restinga environment and that the complete species inventory method is highly efficient for sampling frogs in the restinga studied and may be so in other restinga environments. Methods that are usually efficient in forested areas seem to be of little value in open restinga habitats.

Estimating Stand Height and Tree Density in Pinus taeda plantations using in-situ data, airborne LiDAR and k-Nearest Neighbor Imputation.

PubMed

Silva, Carlos Alberto; Klauberg, Carine; Hudak, Andrew T; Vierling, Lee A; Liesenberg, Veraldo; Bernett, Luiz G; Scheraiber, Clewerson F; Schoeninger, Emerson R

2018-01-01

Accurate forest inventory is of great economic importance to optimize the entire supply chain management in pulp and paper companies. The aim of this study was to estimate stand dominate and mean heights (HD and HM) and tree density (TD) of Pinus taeda plantations located in South Brazil using in-situ measurements, airborne Light Detection and Ranging (LiDAR) data and the non- k-nearest neighbor (k-NN) imputation. Forest inventory attributes and LiDAR derived metrics were calculated at 53 regular sample plots and we used imputation models to retrieve the forest attributes at plot and landscape-levels. The best LiDAR-derived metrics to predict HD, HM and TD were H99TH, HSD, SKE and HMIN. The Imputation model using the selected metrics was more effective for retrieving height than tree density. The model coefficients of determination (adj.R2) and a root mean squared difference (RMSD) for HD, HM and TD were 0.90, 0.94, 0.38m and 6.99, 5.70, 12.92%, respectively. Our results show that LiDAR and k-NN imputation can be used to predict stand heights with high accuracy in Pinus taeda. However, furthers studies need to be realized to improve the accuracy prediction of TD and to evaluate and compare the cost of acquisition and processing of LiDAR data against the conventional inventory procedures.

SPRUCE Deep Peat Heating (DPH) to Whole Ecosystem Warming (WEW) Metagenomes for Peat Samples Collected June 2016

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kluber, Laurel A; Yip, Daniel Z; Yang, Zamin K

This data set provides links to the results of metagenomic analyses of 44 peat samples collected on 13 June 2016 from SPRUCE experiment treatment and ambient plots. Experimental plots had received approximately 24 months of belowground warming (deep peat heating (DPH), Hanson et al. 2015) with the last 9 of those months including air warming for implementation of whole ecosystems warming (WEW – Hanson et al. 2016). WEW Metagenomes: Data from these metagenomes are archived in the U.S. Department of Energy Joint Genome Institute (DOE JGI) Integrated Microbial Genomes (IMG) system (http://img.jgi.doe.gov/) and are available at the accession numbers providedmore » below (Table 2) and in the accompanying inventory file. The easiest way to find results on IMG is at this link, https://img.jgi.doe.gov/cgi-bin/m/main.cgi, and then enter “June2016WEW” as a search term in the “Quick Genome Search:” box at the top of the page.« less

Predicted stand volume for Eucalyptus plantations by spatial analysis

NASA Astrophysics Data System (ADS)

Latifah, Siti; Teodoro, RV; Myrna, GC; Nathaniel, CB; Leonardo, M. F.

2018-03-01

The main objective of the present study was to assess nonlinear models generated by integrating the stand volume growth rate to estimate the growth and yield of Eucalyptus. The primary data was done for point of interest (POI) of permanent sample plots (PSPs) and inventory sample plots, in Aek Nauli sector, Simalungun regency,North Sumatera Province,Indonesia. from December 2008- March 2009. Today,the demand for forestry information has continued to grow over recent years. Because many forest managers and decision makers face complex decisions, reliable information has become the necessity. In the assessment of natural resources including plantation forests have been widely used geospatial technology.The yield of Eucalyptus plantations represented by merchantable volume as dependent variable while factors affecting yield namely stands variables and the geographic variables as independent variables. The majority of the areas in the study site has stand volume class 0 - 50 m3/ha with 16.59 ha or 65.85 % of the total study site.

Wisconsin's forest, 2004: statistics and quality assurance

Treesearch

Mark H. Hansen; Charles H. Perry; Gary Brand; Ronald E. McRoberts

2008-01-01

The first full, annualized inventory of Wisconsin's forests was completed in 2004 after 6,478 forested plots were visited. An earlier publication summarized the results and presented issue - driven analyses (Perry et al. 2008) . This report includes detailed information on forest inventory methods...

[A short version of the Narcissistic Personality Inventory (NPI-15): dimensionality and psychometric properties in a representative sample of the German population].

PubMed

Spangenberg, Lena; Romppel, Matthias; Bormann, Bianca; Hofmeister, Dirk; Brähler, Elmar; Strauß, Bernhard

2013-08-01

The Narcissistic Personality Inventory (NPI) is a commonly used measure of narcissism. This study administered a 15 item short version of the NPI (NPI-15). Central aims of the present study were to examine its dimensionality, and to provide data on its psychometric properties. NPI-15 and Hospital Anxiety and Depression Scale (HADS-D) were assessed in a representative sample of the German population (N=2,512). According to Scree-plot and model fit, a solution with 2 or 3 factors seemed feasible. Because of factor loadings and item-level associations to depression/anxiety we decided to favour a 2-factor-solution. 2 subscales reflecting different facets of narcissism were compiled (leadership ability/personality [LA/LP], grandiosity [G]). The psychometric properties of these scales were good (LA/LP) respectively unsatisfactory (G). The validity of the NPI-15 needs to be further studied. © Georg Thieme Verlag KG Stuttgart · New York.

The analysis of soil cores polluted with certain metals using the Box-Cox transformation.

PubMed

Meloun, Milan; Sánka, Milan; Nemec, Pavel; Krítková, Sona; Kupka, Karel

2005-09-01

To define the soil properties for a given area or country including the level of pollution, soil survey and inventory programs are essential tools. Soil data transformations enable the expression of the original data on a new scale, more suitable for data analysis. In the computer-aided interactive analysis of large data files of soil characteristics containing outliers, the diagnostic plots of the exploratory data analysis (EDA) often find that the sample distribution is systematically skewed or reject sample homogeneity. Under such circumstances the original data should be transformed. The Box-Cox transformation improves sample symmetry and stabilizes spread. The logarithmic plot of a profile likelihood function enables the optimum transformation parameter to be found. Here, a proposed procedure for data transformation in univariate data analysis is illustrated on a determination of cadmium content in the plough zone of agricultural soils. A typical soil pollution survey concerns the determination of the elements Be (16 544 values available), Cd (40 317 values), Co (22 176 values), Cr (40 318 values), Hg (32 344 values), Ni (34 989 values), Pb (40 344 values), V (20 373 values) and Zn (36 123 values) in large samples.

Abundance and Size Distribution of Cavity Trees in Second-Growth and Old-Growth Central Hardwood Forests

Treesearch

Zhaofei Fan; Stephen R. Shifley; Martin A. Spetich; Frank R. Thompson III; David R. Larsen

2005-01-01

In central hardwood forests, mean cavity-tree abundance increases with increasing standsize class (seedling/sapling, pole, sawtimber, old-growth). However, within a size class, the number of cavity trees is highly variable among 0.1-ha inventory plots. Plots in young stands are most likely to have no cavity trees, but some plots may have more than 50 cavity trees/ha....

Abundance and size distribution of cavity trees in second-growth and old-growth central hardwood forests

Treesearch

Zhaofei Fan; Stephen R. Shifley; Martin A. Spetich; Frank R. Thompson; David R. Larsen

2005-01-01

In central hardwood forests, mean cavity-tree abundance increases with increasing standsize class (seedling/sapling, pole, sawtimber, old-growth). However, within a size class, the number of cavity trees is highly variable among 0.1-ha inventory plots. Plots in young stands are most likely to have no cavity trees, but some plots may have more than 50 cavity trees/ha....

FIAMODEL: Users Guide Version 3.0.

Treesearch

Scott A. Pugh; David D. Reed; Kurt S. Pregitzer; Patrick D. Miles

2002-01-01

FIAMODEL is a geographic information system (GIS program used to summarize Forest Inventory and Analysis (FIA, USDA Forest Service) data such as volume. The model runs in ArcView and allows users to select FIA plots with heads-up-digitizing, overlays of digital map layers, or queries based on specific plot attributes.

Using SaTScanTM spatial-scan software with national forest inventory data: a case study in South Carolina

Treesearch

KaDonna Randolph

2017-01-01

The USDA Forest Service Forest Inventory and Analysis (FIA) program makes and keeps current an inventory of all forest land in the United States. To comply with privacy laws while at the same time offering its data to the public, FIA makes approximate plot locations available through a process known as perturbing ("fuzzing") and swapping. The free spatial...

The Southern Annual Forest Inventory System

Treesearch

Gregory A. Reams; Paul C. van Deusen

1999-01-01

The Southern Annual Forest Inventory System (SAFIS) is in various stages of implementation in 7 of the 13 southern states serviced by the Southern Research Station. The SAFIS design is an interpenetrating design where the n units (1/6 acre plots) are divided into k = 5 panels, each panel containing m = n...

Using forest inventory plot data and satellite imagery from MODIS and Landsat-TM to model spatial distribution patterns of honeysuckle and privet

Treesearch

Dumitru Salajanu; Dennis M. Jacobs

2009-01-01

Forest inventory and analysis data monitor the presence and extent of certain non-native invasive species. Onforestland, non-native species are considered part of the understory vegetation and can be found near canopyopenings as well as and...

Change in area and ownership of private timberland in western Oregon between 1961-1962 and 1973-1976.

Treesearch

Donald R. Gedney

1981-01-01

A reinventory in 1973-76 of permanent inventory plots established in 1961-62 on western Oregon's forest industry and other private timberland provides data by ownership of timberland losses to nonforest land uses and changes in private ownership of timberland between inventories.

Forests of Wisconsin, 2016

Treesearch

Cassandra M. Kurtz

2017-01-01

Publication updated February 9, 2018 to correct the number of forest field plots (page 1). This resource update provides an overview of forest resources in Wisconsin based on an inventory conducted by the U.S. Forest Service, Forest Inventory and Analysis (FIA) program at the Northern Research Station in cooperation with the Wisconsin Department of...

Supporting document for the historical tank content estimate for AY-tank farm

DOE Office of Scientific and Technical Information (OSTI.GOV)

Brevick, C H; Stroup, J L; Funk, J. W.

1997-03-12

This Supporting Document provides historical in-depth characterization information on AY-Tank Farm, such as historical waste transfer and level data, tank physical information, temperature plots, liquid observation well plots, chemical analyte and radionuclide inventories for the Historical Tank Content Estimate Report for the Southeast Quadrant of the Hanford 200 Areas.

Models for estimation and simulation of crown and canopy cover

Treesearch

John D. Shaw

2005-01-01

Crown width measurements collected during Forest Inventory and Analysis and Forest Health Monitoring surveys are being used to develop individual tree crown width models and plot-level canopy cover models for species and forest types in the Intermountain West. Several model applications are considered in the development process, including remote sensing of plot...

The great carbon push-pull: where science is pushing and policy is pulling the official forest carbon inventory of the US

Treesearch

C.W. Woodall; G.M. Domke; J. Coulston; M.B. Russell; J.A. Smith; C.H. Perry; S. Healey; A. Gray

2015-01-01

A national system of field inventory plots (FIA) is the primary data source for the annual assessment of US forest carbon (C) stocks and stock-change to meet reporting requirements under the United Nations Framework Convention on Climate Change (UNFCCC). The inventory data and their role in national carbon reporting continue to evolve. The framework of the previous C...

Assessing biomass and forest area classifications from modis satellite data while incrementing the number of FIA data panels

Treesearch

Dumitru Salajanu; Dennis M. Jacobs

2005-01-01

Our objective was to determine at what level biomass and forest area obtained from 2, 3, 4, or 5 panels of forest inventory data compares well with forested area and biomass estimates from the national inventory data. A subset of 2605 inventory plots (100% forested, 100% non-forested) was used to classify the land cover and model the biomass in South Carolina. Mixed...

Progress in adapting k-NN methods for forest mapping and estimation using the new annual Forest Inventory and Analysis data

Treesearch

Reija Haapanen; Kimmo Lehtinen; Jukka Miettinen; Marvin E. Bauer; Alan R. Ek

2002-01-01

The k-nearest neighbor (k-NN) method has been undergoing development and testing for applications with USDA Forest Service Forest Inventory and Analysis (FIA) data in Minnesota since 1997. Research began using the 1987-1990 FIA inventory of the state, the then standard 10-point cluster plots, and Landsat TM imagery. In the past year, research has moved to examine...

Estimating forestland area change from inventory data

Treesearch

Paul Van Deusen; Francis Roesch; Thomas Wigley

2013-01-01

Simple methods for estimating the proportion of land changing from forest to nonforest are developed. Variance estimators are derived to facilitate significance tests. A power analysis indicates that 400 inventory plots are required to reliably detect small changes in net or gross forest loss. This is an important result because forest certification programs may...

The effects of removing condition boundaries on FIA estimates

Treesearch

David Gartner; Gregory Reams

2002-01-01

When Forest Inverltory and Analysis (FIA) changed to the national standards for the inventory system, plots with lnultiplc condition codes were introduced to the Southern Station's FIA unit. FIA maps up to five different conditions on completely or partially forested 1124-acre subplots. This change has madc producing inventory estimates more complex because the...

The effect of blurred plot coordinates on interpolating forest biomass: a case study

Treesearch

J. W. Coulston

2004-01-01

Interpolated surfaces of forest attributes are important analytical tools and have been used in risk assessments, forest inventories, and forest health assessments. The USDA Forest Service Forest Inventory and Analysis program (FIA) annually collects information on forest attributes in a consistent fashion nation-wide. Users of these data typically perform...

The art and science of weed mapping

USGS Publications Warehouse

Barnett, David T.; Stohlgren, Thomas J.; Jarnevich, Catherine S.; Chong, Geneva W.; Ericson, Jenny A.; Davern, Tracy R.; Simonson, Sara E.

2007-01-01

Land managers need cost-effective and informative tools for non-native plant species management. Many local, state, and federal agencies adopted mapping systems designed to collect comparable data for the early detection and monitoring of non-native species. We compared mapping information to statistically rigorous, plot-based methods to better understand the benefits and compatibility of the two techniques. Mapping non-native species locations provided a species list, associated species distributions, and infested area for subjectively selected survey sites. The value of this information may be compromised by crude estimates of cover and incomplete or biased estimations of species distributions. Incorporating plot-based assessments guided by a stratified-random sample design provided a less biased description of non-native species distributions and increased the comparability of data over time and across regions for the inventory, monitoring, and management of non-native and native plant species.

[Estimation of Hunan forest carbon density based on spectral mixture analysis of MODIS data].

PubMed

Yan, En-ping; Lin, Hui; Wang, Guang-xing; Chen, Zhen-xiong

2015-11-01

With the fast development of remote sensing technology, combining forest inventory sample plot data and remotely sensed images has become a widely used method to map forest carbon density. However, the existence of mixed pixels often impedes the improvement of forest carbon density mapping, especially when low spatial resolution images such as MODIS are used. In this study, MODIS images and national forest inventory sample plot data were used to conduct the study of estimation for forest carbon density. Linear spectral mixture analysis with and without constraint, and nonlinear spectral mixture analysis were compared to derive the fractions of different land use and land cover (LULC) types. Then sequential Gaussian co-simulation algorithm with and without the fraction images from spectral mixture analyses were employed to estimate forest carbon density of Hunan Province. Results showed that 1) Linear spectral mixture analysis with constraint, leading to a mean RMSE of 0.002, more accurately estimated the fractions of LULC types than linear spectral and nonlinear spectral mixture analyses; 2) Integrating spectral mixture analysis model and sequential Gaussian co-simulation algorithm increased the estimation accuracy of forest carbon density to 81.5% from 74.1%, and decreased the RMSE to 5.18 from 7.26; and 3) The mean value of forest carbon density for the province was 30.06 t · hm(-2), ranging from 0.00 to 67.35 t · hm(-2). This implied that the spectral mixture analysis provided a great potential to increase the estimation accuracy of forest carbon density on regional and global level.

Evaluating uncertainty in 7Be-based soil erosion estimates: an experimental plot approach

NASA Astrophysics Data System (ADS)

Blake, Will; Taylor, Alex; Abdelli, Wahid; Gaspar, Leticia; Barri, Bashar Al; Ryken, Nick; Mabit, Lionel

2014-05-01

Soil erosion remains a major concern for the international community and there is a growing need to improve the sustainability of agriculture to support future food security. High resolution soil erosion data are a fundamental requirement for underpinning soil conservation and management strategies but representative data on soil erosion rates are difficult to achieve by conventional means without interfering with farming practice and hence compromising the representativeness of results. Fallout radionuclide (FRN) tracer technology offers a solution since FRN tracers are delivered to the soil surface by natural processes and, where irreversible binding can be demonstrated, redistributed in association with soil particles. While much work has demonstrated the potential of short-lived 7Be (half-life 53 days), particularly in quantification of short-term inter-rill erosion, less attention has focussed on sources of uncertainty in derived erosion measurements and sampling strategies to minimise these. This poster outlines and discusses potential sources of uncertainty in 7Be-based soil erosion estimates and the experimental design considerations taken to quantify these in the context of a plot-scale validation experiment. Traditionally, gamma counting statistics have been the main element of uncertainty propagated and reported but recent work has shown that other factors may be more important such as: (i) spatial variability in the relaxation mass depth that describes the shape of the 7Be depth distribution for an uneroded point; (ii) spatial variability in fallout (linked to rainfall patterns and shadowing) over both reference site and plot; (iii) particle size sorting effects; (iv) preferential mobility of fallout over active runoff contributing areas. To explore these aspects in more detail, a plot of 4 x 35 m was ploughed and tilled to create a bare, sloped soil surface at the beginning of winter 2013/2014 in southwest UK. The lower edge of the plot was bounded by a perforated pipe which fed into a collection bin for overland flow and associated sediment capture. At the same time, a flat area at the top of the slope was ploughed and tilled to create a reference site with same inventory baseline as the slope. Rain gauges were set up at the reference and slope site. The tilled surface had a low bulk density and high permeability at the start of the experiment (ksat > 100 mm hr-1). Hence, despite high rainfall in December 2013 (200 mm), notable runoff was observed only after intense rain storms during late 2013 and early January 2014 when the soil profile was saturated. Captured eroded sediment was analysed for 7Be and particle size. Subsequently, the plot soil surface was intensively sampled to quantify 7Be inventory patterns and develop a tracer budget. Preliminary results are discussed in the context of the above potential sources of uncertainty.

Using inventory-based tree-ring data as a proxy for historical climate: Investigating the Pacific decadal oscillation and teleconnections

Treesearch

J. DeRose; S. Wang; J. Shaw

2014-01-01

In 2009, the Interior West Forest Inventory and Analysis (FIA) program of the U.S. Forest Service started to archive approximately 11 000 increment cores collected in the Interior West states during the periodic inventories of the 1980s and 1990s. The two primary goals for use of the data were to provide a plot-linked database of radial growth to be used for growth...

Measurement of forest disturbance and regrowth with Landsat and forest inventory and analysis data: anticipated benefits from forest and inventory analysis' collaboration with the national aeronautics and space administration and university partners

Treesearch

Sean Healey; Gretchen Moisen; Jeff Masek; Warren Cohen; Sam Goward; < i> et al< /i>

2007-01-01

The Forest Inventory and Analysis (FIA) program has partnered with researchers from the National Aeronautics and Space Administration, the University of Maryland, and other U.S. Department of Agriculture Forest Service units to identify disturbance patterns across the United States using FIA plot data and time series of Landsat satellite images. Spatially explicit...

Down woody material, soil and tree core collection and analysis from the 2014 Tanana pilot plots

Treesearch

Robert R. Pattison; Andrew N. Gray; Patrick F. Sullivan; Kristen L. Manies

2015-01-01

In the summer of 2014 the US Forest Service’s Forest Inventory and Analysis (FIA) Program of the Pacific Northwest (PNW) Research Station in conjunction with NASA Goddard carried out a pilot inventory of the forests of interior Alaska. This inventory was conducted on the State of Alaska’s Tanana Valley State Forest and on the Tetlin National Wildlife Refuge. As part of...

Forest Resources of East Oklahoma, 2008

Treesearch

Richard A. Harper; Tony G. Johnson

2012-01-01

The Forest Inventory and Analysis Program conducted the seventh survey of east Oklahoma forests. This was the establishment of the annual plot methodology and closeout of the prism remeasurement plots. Forest land area remained stable at 5.7 million acres and covered almost 57 percent of the land area. About 5.1 million acres of forest land was considered timberland...

Supporting document for the historical tank content estimate for AX-tank farm

DOE Office of Scientific and Technical Information (OSTI.GOV)

Brevick, C.H., Westinghouse Hanford

This Supporting Document provides historical in-depth characterization information on AX-Tank Farm, such as historical waste transfer and level data, tank physical information,temperature plots, liquid observation well plots, chemical analyte and radionuclide inventories for the Historical Tank Content Estimate Report for the northeast quadrant of the Hanford 200 East Area.

Abundance and characteristics of snags in western Montana forests

Treesearch

Richard B. Harris

1999-01-01

Plot data from the U.S. Forest Service's Forest Inventory and Analysis program was used to characterize the abundance and selected characteristics of snags from forests in western Montana. Plots were grouped by whether they had a history of timber harvest, and the U.S. Forest Service classifications of forest type, habitat type, and potential vegetation group were...

Issues related to panel creep

Treesearch

Paul C. Van Deusen

2002-01-01

The annual inventory system was designed under the assumption that a fixed percentage of plots would be measured annually in each State. The initial plan was to assign plots to panels to provide systematic coverage of a State. One panel would be measured each year to allow for annual updates of each State using simple estimation procedures. The reality is that...

Effect of tree thinning and litter removal on the radiocesium (Cs-134, 137) discharge rates in the Kawauchi forest plantation (Fukushima Prefecture, northern Japan)

NASA Astrophysics Data System (ADS)

López-Vicente, Manuel; Onda, Yuichi; Takahashi, Junko; Kato, Hiroaki; Hisadome, Keigo

2016-04-01

On 11 March 2011 a 9.0 earthquake and the resulting tsunami occurred in central-eastern Japan triggering, one day after, the Fukushima Dai-ichi nuclear power plant (DNPP) accident. Despite the bulk of radionuclides (ca. 80%) were transported offshore and out over the Pacific Ocean, significant wet and dry deposits of those radionuclides occurred mainly in the Fukushima Prefecture and in a minor way in the Miyagi, Tochigi, Gunma and Ibaraki Prefectures. As a consequence and among other radionuclides, a total of 511,000 TBq of I-131, 13,500 TBq of Cs-134 and 13,600 TBq of Cs-137 were released into the atmosphere and the ocean, contaminating cultivated soils, rivers, settlements and forested areas. This accident caused severe environmental and economic damages. Several decontamination practices have done, including tree thinning and litter removal within the forests and tree plantations. In this study we analysed the effect of eight different management practices on the radiocesium (Cs-134 and Cs-137) discharge rates during 20 months (May'2013 - Dec'2014) in a Japanese cedar (Cryptomeria japonica) plantation (stand age of 57 years), located in a hillslope near the Kawauchi village, Fukushima Prefecture, northern Japan. This study area (37⁰ 20' 04" N, 140⁰ 53' 13.5" E) is located 16 km southwestern from the DNPP and within the evacuation area. The soils are Andosols. Ten runoff plots (5 x 2 meters) were installed and measurements started on May 2013. Two plots remained without any treatment as control plots and the other eight plots represented the following management practices: Mng1) Litter removal + clear-cutting (no sheet); Mng2) Litter removal + clear-cutting (no sheet); Mng3) Litter removal + clear-cutting (no sheet); Mng4) Litter removal; Mng5) Thinning (logged area); Mng6) Thinning (under remnant trees); Mng7) Litter removal + thinning (logged area); Mng8) Litter removal + thinning (under remnant trees). Each plot had a gauging station and sediment samples were collected every three weeks. Litter removal and tree thinning were done twice. The minimum of ground and vegetation coverages occurred in May and June 2013 and between February and April 2014. The maximum coverages appeared in September-October 2013 and between July and September 2014. The radioactivities of Cs-134 and Cs-137 were determined in the soil and litter fractions by gamma-ray spectrometry. Emissions were measured using a high purity n-type Ge coaxial detector coupled to an amplified and multichannel analyser at the CRiED laboratory of the University of Tsukuba. The activity concentration (Bq / kg) of Cs-134 and Cs-137 were calculated as well as the inventory (Bq / m2) and daily inventory (Bq / m2 day) of Cs-137. A total of 70 correlations were analysed: between the dry weight of the leaf and soil and the corresponding activity of Cs-134 and Cs-137 as well as between the total movement and total daily movement of leaf and soil and the inventory and daily inventory of Cs-137. The amount of soil and caesium movement in the experimental slopes was considerably decreased in the year 2014 than in 2013 due to the vegetation recovery after the operations in each plot.

Forest/non-forest mapping using inventory data and satellite imagery

Treesearch

Ronald E. McRoberts

2002-01-01

For two study areas in Minnesota, USA, one heavily forested and one sparsely forested, maps of predicted proportion forest area were created using Landsat Thematic Mapper imagery, forest inventory plot data, and two prediction techniques, logistic regression and a k-Nearest Neighbours technique. The maps were used to increase the precision of forest area estimates by...

Forest/Nonforest Classification of Landsat TM Data For Annual Inventory Phase One Stratification

Treesearch

Jim Rack

2001-01-01

Launch of Landsat 7 creates the opportunity to use relatively inexpensive and regularly acquired land cover data as an alternative to high altitude aerial photography. Creating a forest/nonforest mask from satellite imagery may offer a cost-effective alternative to interpretation of aerial photography for Phase One stratification of annual inventory plots. This paper...

Challenges of working with FIADB17 data: the SOLE experience

Treesearch

Michael Spinney; Paul Van Deusen

2007-01-01

The Southern On Line Estimator (SOLE) is an Internet-based Forest Inventory and Analysis (FIA) data analysis tool. SOLE is based on data downloaded from the publicly available FIA database (FIADB) and summarized by plot condition. The tasks of downloading, processing, and summarizing FIADB data require specialized expertise in inventory theory and data manipulation....

Implementing a land cover stratification on-the-fly

Treesearch

Ronald E. McRoberts; Daniel G. Wendt

2002-01-01

Stratified estimation is used by the Forest Inventory and Analysis program of the USDA Forest Service to increase the precision of county-level inventory estimates. Stratified estimation requires that plots be assigned to strata and that proportions of land area in each strata be determined. Classified satellite imagery has been found to be an efficient and effective...

Evaluating kriging as a tool to improve moderate resolution maps of forest biomass

Treesearch

Elizabeth A. Freeman; Gretchen G. Moisen

2007-01-01

The USDA Forest Service, Forest Inventory and Analysis program (FIA) recently produced a nationwide map of forest biomass by modeling biomass collected on forest inventory plots as nonparametric functions of moderate resolution satellite data and other environmental variables using Cubist software. Efforts are underway to develop methods to enhance this initial map. We...

Building the Forest Inventory and Analysis Tree-Ring Data set

Treesearch

Robert J. DeRose; John D. Shaw; James N. Long

2017-01-01

The Interior West Forest Inventory and Analysis (IW-FIA) program measures forestland conditions at great extent with relatively high spatial resolution, including the collection of tree-ring data. We describe the development of an unprecedented spatial tree-ring data set for the IW-FIA that enhances the baseline plot data by incorporating ring-width increment measured...

Amazonian landscapes and the bias in field studies of forest structure and biomass.

PubMed

Marvin, David C; Asner, Gregory P; Knapp, David E; Anderson, Christopher B; Martin, Roberta E; Sinca, Felipe; Tupayachi, Raul

2014-12-02

Tropical forests convert more atmospheric carbon into biomass each year than any terrestrial ecosystem on Earth, underscoring the importance of accurate tropical forest structure and biomass maps for the understanding and management of the global carbon cycle. Ecologists have long used field inventory plots as the main tool for understanding forest structure and biomass at landscape-to-regional scales, under the implicit assumption that these plots accurately represent their surrounding landscape. However, no study has used continuous, high-spatial-resolution data to test whether field plots meet this assumption in tropical forests. Using airborne LiDAR (light detection and ranging) acquired over three regions in Peru, we assessed how representative a typical set of field plots are relative to their surrounding host landscapes. We uncovered substantial mean biases (9-98%) in forest canopy structure (height, gaps, and layers) and aboveground biomass in both lowland Amazonian and montane Andean landscapes. Moreover, simulations reveal that an impractical number of 1-ha field plots (from 10 to more than 100 per landscape) are needed to develop accurate estimates of aboveground biomass at landscape scales. These biases should temper the use of plots for extrapolations of forest dynamics to larger scales, and they demonstrate the need for a fundamental shift to high-resolution active remote sensing techniques as a primary sampling tool in tropical forest biomass studies. The potential decrease in the bias and uncertainty of remotely sensed estimates of forest structure and biomass is a vital step toward successful tropical forest conservation and climate-change mitigation policy.

An assessment of autumn olive in northern U.S. forests

Treesearch

Cassandra M. Kurtz; Mark H. Hansen

2016-01-01

This publication is part of a series of research notes that provide an overview of the invasive plant species monitored on an extensive systematic network of plots measured by the Forest Inventory and Analysis (FIA) program of the U.S. Forest Service, Northern Research Station (NRS). Each research note features one of the invasive plants monitored on forested plots by...

Differences in forest area classification based on tree tally from variable- and fixed-radius plots

Treesearch

David Azuma; Vicente J. Monleon

2011-01-01

In forest inventory, it is not enough to formulate a definition; it is also necessary to define the "measurement procedure." In the classification of forestland by dominant cover type, the measurement design (the plot) can affect the outcome of the classification. We present results of a simulation study comparing classification of the dominant cover type...

Rapid classification of landsat TM imagery for phase 1 stratification using the automated NDVI threshold supervised classification (ANTSC) methodology

Treesearch

William H. Cooke; Dennis M. Jacobs

2002-01-01

FIA annual inventories require rapid updating of pixel-based Phase 1 estimates. Scientists at the Southern Research Station are developing an automated methodology that uses a Normalized Difference Vegetation Index (NDVI) for identifying and eliminating problem FIA plots from the analysis. Problem plots are those that have questionable land useiland cover information....

An assessment of nonnative bush honeysuckle in northern U.S. forests

Treesearch

Cassandra Kurtz; M.H. Hansen

2015-01-01

This publication is part of a series that provides an overview of the presence of invasive plant species monitored on an extensive systematic network of plots measured by the Forest Inventory and Analysis (FIA) program of the U.S. Forest Service, Northern Research Station (NRS). Each research note features one of the invasive plants monitored on forested plots by NRS...

An assessment of common buckthorn in northern U.S. forests

Treesearch

Cassandra M. Kurtz; Mark H. Hansen

2018-01-01

This publication is part of a series of that provides an overview of the presence of invasive plant species monitored on an extensive systematic network of plots measured by the Forest Inventory and Analysis (FIA) program of the USDA Forest Service, Northern Research Station (NRS). Each research note features one of the invasive plants monitored on forested plots by...

A comparison of FIA plot data derived from image pixels and image objects

Treesearch

Charles E. Werstak

2012-01-01

The use of Forest Inventory and Analysis (FIA) plot data for producing continuous and thematic maps of forest attributes (e.g., forest type, canopy cover, volume, and biomass) at the regional level from satellite imagery can be challenging due to differences in scale. Specifically, classification errors that may result from assumptions made between what the field data...

An assessment of Japanese honeysuckle in northern U.S. forests

Treesearch

Cassandra M. Kurtz; Mark H. Hansen

2015-01-01

This publication is part of a series that provides an overview of the presence of invasive plant species monitored on an extensive systematic network of plots measured by the Forest Inventory and Analysis (FIA) program of the U.S. Forest Service, Northern Research Station (NRS). Each research note features one of the invasive plants monitored on forested plots by NRS...

An assessment of garlic mustard in northern U.S. forests

Treesearch

Cassandra M. Kurtz; Mark H. Hansen

2014-01-01

This publication is part of a series that provides an overview of the presence of invasive plant species monitored on an extensive systematic network of plots measured by the Forest Inventory and Analysis (FIA) program of the U.S. Forest Service, Northern Research Station (NRS). Each research note features one of the invasive plants monitored on forested plots by FIA...

Isotopic Characterisation of Methane Emissions: use of Keeling-plot Methods to Identify Source Signatures in Boreal Wetlands and Other Settings

NASA Astrophysics Data System (ADS)

Fisher, R. E.; Lowry, D.; France, J.; Lanoiselle, M.; Zazzeri, G.; Nisbet, E. G.

2012-12-01

Different methane sources have different δ13CCH4 and δDCH4 signatures, which potentially provides a powerful constraint on models of methane emission budgets. However source signatures remain poorly known and need to be studied in more detail if isotopic measurements of ambient air are to be used to constrain regional and global emissions. The Keeling plot method (plotting δ13CCH4 or δDCH4 against 1/CH4 concentration in samples of ambient air in the close vicinity of known sources) directly assesses the source signature of the methane that is actually emitted to the air. This contrasts with chamber studies, measuring air within a chamber, where local micro-meteorological and microbiological processes are occurring. Keeling plot methods have been applied to a wide variety of settings in this study. The selection of appropriate background measurements for Keeling plot analysis is also considered. The method has been used on a local scale to identify the source signature of summer emissions from subarctic wetlands in Fennoscandia. Samples are collected from low height (0.3-3m) over the wetlands during 24-hour periods, to collect daily emissions maxima (warm late afternoons), inversion maxima (at the coldest time of the 24hr daylight: usually earliest morning), and ambient minima when mixing occurs (often mid afternoon). Some results are comparable to parallel chamber studies, but in other cases there are small but significant shifts between CH4 in chamber air and CH4 that is dispersing in the above-ground air. On a regional to continental scale the isotopic signature of bulk sources of emissions can be identified using Keeling plots. The methodology is very applicable for use in urban and urban-rural settings. For example, the winter SE monsoon sweeps from inland central Asia over China to Hong Kong. Application of back trajectory analysis and Keeling plot methods implied coal emissions may be a significant Chinese source of methane in January, although in other months biological sources dominate. Similarly, in London the method has been used to test the London methane emission inventory.

Where are the Walnut Trees in Minnesota? 1995.

Treesearch

J. Michael Vasievich; Neal P. Kingsley

1995-01-01

The forests of each state are inventoried by the USDA-Forest Service and the state?s forestry agency on a periodic basis. In the Midwest, the North Central Forest Experiment Station coordinates the inventory. The job takes a long time-- sometimes several years from start to finish -- because lots of trees are measured on lots of plots. For example, during the last...

Updating Indiana Annual Forest Inventory and Analysis Plot Data Using Eastern Broadleaf Forest Diameter Growth Models

Treesearch

Veronica C. Lessard

2001-01-01

The Forest Inventory and Analysis (FIA) program of the North Central Research Station (NCRS), USDA Forest Service, has developed nonlinear, individual-tree, distance-independent annual diameter growth models. The models are calibrated for species groups and formulated as the product of an average diameter growth component and a modifier component. The regional models...

Determining stocking, forest type and stand-size class from forest inventory data

Treesearch

Mark H. Hansen; Jerold T. Hahn

1992-01-01

This paper describes the procedures used by North Central Forest Experiment Station's Forest Inventory and Analysis Work Unit (NCFIA) in determining stocking, forest type, and stand-size class. The stocking procedure assigns a portion of the stocking to individual trees measured on NCFIA 10-point field plots. Stand size and forest type are determined as functions...

A Proposal for Phase 4 of the Forest Inventory and Analysis Program

Treesearch

Ronald E. McRoberts

2005-01-01

Maps of forest cover were constructed using observations from forest inventory plots, Landsat Thematic Mapper satellite imagery, and a logistic regression model. Estimates of mean proportion forest area and the variance of the mean were calculated for circular study areas with radii ranging from 1 km to 15 km. The spatial correlation among pixel predictions was...

A System to Derive Optimal Tree Diameter Increment Models from the Eastwide Forest Inventory Data Base (EFIDB)

Treesearch

Don C. Bragg

2002-01-01

This article is an introduction to the computer software used by the Potential Relative Increment (PRI) approach to optimal tree diameter growth modeling. These DOS programs extract qualified tree and plot data from the Eastwide Forest Inventory Data Base (EFIDB), calculate relative tree increment, sort for the highest relative increments by diameter class, and...

LiDAR based prediction of forest biomass using hierarchical models with spatially varying coefficients

Treesearch

Chad Babcock; Andrew O. Finley; John B. Bradford; Randy Kolka; Richard Birdsey; Michael G. Ryan

2015-01-01

Many studies and production inventory systems have shown the utility of coupling covariates derived from Light Detection and Ranging (LiDAR) data with forest variables measured on georeferenced inventory plots through regression models. The objective of this study was to propose and assess the use of a Bayesian hierarchical modeling framework that accommodates both...

Rapid assessment of wildfire damage using Forest Inventory data: A case in Georgia

Treesearch

Richard A. Harper; John W. Coulsten; Jeffery A. Turner

2009-01-01

The rapid assessment of damage caused by natural disasters is essential for planning the appropriate amount of disaster relief funds and public communication. Annual Forest Inventory and Analysis (FIA) data provided initial estimates of damage to timberland in a timely manner to State leaders during the 2007 Georgia Bay Complex Wildfire in southeast Georgia. FIA plots...

K-nearest neighbor imputation of forest inventory variables in New Hampshire

Treesearch

Andrew Lister; Michael Hoppus; Raymond L. Czaplewski

2005-01-01

The k-nearest neighbor (kNN) method was used to map stand volume for a mosaic of 4 Landsat scenes covering the state of New Hampshire. Data for gross cubic foot volume and trees per acre were summarized from USDA Forest Service Forest Inventory and Analysis (FIA) plots and used as training for kNN. Six bands of...

Assessing the Effects of Forest Fragmentation Using Satellite Imagery and Forest Inventory Data

Treesearch

Ronald E. McRoberts; Greg C. Liknes

2005-01-01

For a study area in the North Central region of the USA, maps of predicted proportion forest area were created using Landsat Thematic Mapper imagery, forest inventory plot data, and a logistic regression model. The maps were used to estimate quantitative indices of forest fragmentation. Correlations between the values of the indices and forest attributes observed on...

Assessing soil compaction on Forest Inventory & Analysis phase 3 field plots using a pocket penetrometer

Treesearch

Michael C. Amacher; Katherine P. O' Neill

2004-01-01

Soil compaction is an important indicator of soil quality, yet few practical methods are available to quantitatively measure this variable. Although an assessment of the areal extent of soil compaction is included as part of the soil indicator portion of the Forest Inventory & Analysis (FIA) program, no quantitative measurement of the degree of soil compaction...

A stem-map model for predicting tree canopy cover of Forest Inventory and Analysis (FIA) plots

Treesearch

Chris Toney; John D. Shaw; Mark D. Nelson

2009-01-01

Tree canopy cover is an important stand characteristic that affects understory light, fuel moisture, decomposition rates, wind speed, and wildlife habitat. Canopy cover also is a component of most definitions of forest land used by US and international agencies. The USDA Forest Service Forest Inventory and Analysis (FIA) Program currently does not provide a national...

Delaware Forests 2013

Treesearch

Tonya W. Lister; Brett J. Butler; Susan J. Crocker; Cassandra M. Kurtz; Andrew J. Lister; William G. Luppold; William H. McWilliams; Patrick D. Miles; Randall S. Morin; Mark D. Nelson; Ronald J. Piva; Rachel I. Riemann; James E. Smith; James A. Westfall; Richard H. Widmann; Christopher W. Woodall

2017-01-01

This report summarizes the 2013 results of the annualized inventory of Delaware’s forests conducted by the U.S. Forest Service, Forest Inventory and Analysis program. Results are based on data collected from 389 plots located across the State. There are an estimated 362,000 acres of forest land in Delaware with a total live- tree volume of 936 million cubic feet. There...

Using FIA inventory plot data to assess NTFP production possibilities

Treesearch

Jobriath Kauffman; James Chamberlain; Stephen Prisley

2015-01-01

The US Forest Service, Forest Inventory and Analysis (FIA) program collects data on a wealth of variables related to trees and understory species in forests. Some of these trees and plants produce non-timber forest products (NTFPs; e.g., seeds, fruit, bark, sap, roots) that are harvested for their culinary and medicinal values. As example, the cones of Pinus...

A Comparison of Various Estimators for Updating Forest Area Coverage Using AVHRR and Forest Inventory Data

Treesearch

Francis A. Roesch; Paul C. van Deusen; Zhiliang Zhu

1995-01-01

Various methods of adjusting low-cost and possibly biased estimates of percent forest coverage from AVHRR data with a subsample of higher-cost estimates from the USDA Forest Service's Forest Inventory and Analysis plots were investigated. Two ratio and two regression estimators were evaluated. Previous work (Zhu and Teuber, 1991) finding that the estimates from...

Rapid Classification of Landsat TM Imagery for Phase 1 Stratification Using the Automated NDVI Threshold Supervised Classification (ANTSC) Methodology

Treesearch

William H. Cooke; Dennis M. Jacobs

2005-01-01

FIA annual inventories require rapid updating of pixel-based Phase 1 estimates. Scientists at the Southern Research Station are developing an automated methodology that uses a Normalized Difference Vegetation Index (NDVI) for identifying and eliminating problem FIA plots from the analysis. Problem plots are those that have questionable land use/land cover information....

Forests of Vermont and New Hampshire 2012

Treesearch

Randall S. Morin; Chuck J. Barnett; Brett J. Butler; Susan J. Crocker; Grant M. Domke; Mark H. Hansen; Mark A. Hatfield; Jonathan Horton; Cassandra M. Kurtz; Tonya W. Lister; Patrick D. Miles; Mark D. Nelson; Ronald J. Piva; Sandy Wilmot; Richard H. Widmann; Christopher W. Woodall; Robert. Zaino

2015-01-01

The first full remeasurement of the annual inventory of the forests of Vermont and New Hampshire was completed in 2012 and covers nearly 9.5 million acres of forest land, with an average volume of nearly 2,300 cubic feet per acre. The data in this report are based on visits to 1,100 plots located across Vermont and 1,091 plots located across New Hampshire. Forest land...

A density management diagram for longleaf pine stands with application to red-cockaded woodpecker habitat

Treesearch

John D. Shaw; James N. Long

2007-01-01

We developed a density management diagram (DMD) for longleaf pine (Pinus palustris P. Mill.) using data from Forest Inventory and Analysis plots. Selection criteria were for purity, defined as longleaf pine basal area (BA) that is 90% or more of plot BA, and even-agedness, as defined by a ratio between two calculations of stand density index. The...

Preliminary Evaluation of Methods for Classifying Forest Site Productivity Based on Species Composition in Western North Carolina

Treesearch

W. Henry McNab; F. Thomas Lloyd; David L. Loftis

2002-01-01

The species indicator approach to forest site classification was evaluated for 210 relatively undisturbed plots established by the USDA Forest Service Forest Inventory and Analysis uni (FIA) in western North Carolina. Plots were classified by low, medium, and high levels of productivity based on 10-year individual tree basal area increment data standardized for initial...

A nearest-neighbor imputation approach to mapping tree species over large areas using forest inventory plots and moderate resolution raster data

Treesearch

B. Tyler Wilson; Andrew J. Lister; Rachel I. Riemann

2012-01-01

The paper describes an efficient approach for mapping multiple individual tree species over large spatial domains. The method integrates vegetation phenology derived from MODIS imagery and raster data describing relevant environmental parameters with extensive field plot data of tree species basal area to create maps of tree species abundance and distribution at a 250-...

A GIS-based tool for estimating tree canopy cover on fixed-radius plots using high-resolution aerial imagery

Treesearch

Sara A. Goeking; Greg C. Liknes; Erik Lindblom; John Chase; Dennis M. Jacobs; Robert. Benton

2012-01-01

Recent changes to the Forest Inventory and Analysis (FIA) Program's definition of forest land precipitated the development of a geographic information system (GIS)-based tool for efficiently estimating tree canopy cover for all FIA plots. The FIA definition of forest land has shifted from a density-related criterion based on stocking to a 10 percent tree canopy...

Thinning strategies to increase the regional availability of oak timber in the Mid-Appalachian Region

Treesearch

John R. Brooks; Jingxin Wang; Chris. LeDoux

2011-01-01

Plot data from 6,727 fully stocked oak-hickory stands were selected from Forest Inventory and Analysis data from five ecoregions common to West Virginia, Pennsylvania, Maryland, Virginia, Kentucky, and Ohio. Each plot was thinned from below using an existing thinning algorithm, where 30, 50, and 70 percent of the existing basal area was removed. These thinning...

Satellite inventory of Minnesota forest resources

NASA Technical Reports Server (NTRS)

Bauer, Marvin E.; Burk, Thomas E.; Ek, Alan R.; Coppin, Pol R.; Lime, Stephen D.; Walsh, Terese A.; Walters, David K.; Befort, William; Heinzen, David F.

1993-01-01

The methods and results of using Landsat Thematic Mapper (TM) data to classify and estimate the acreage of forest covertypes in northeastern Minnesota are described. Portions of six TM scenes covering five counties with a total area of 14,679 square miles were classified into six forest and five nonforest classes. The approach involved the integration of cluster sampling, image processing, and estimation. Using cluster sampling, 343 plots, each 88 acres in size, were photo interpreted and field mapped as a source of reference data for classifier training and calibration of the TM data classifications. Classification accuracies of up to 75 percent were achieved; most misclassification was between similar or related classes. An inverse method of calibration, based on the error rates obtained from the classifications of the cluster plots, was used to adjust the classification class proportions for classification errors. The resulting area estimates for total forest land in the five-county area were within 3 percent of the estimate made independently by the USDA Forest Service. Area estimates for conifer and hardwood forest types were within 0.8 and 6.0 percent respectively, of the Forest Service estimates. A trial of a second method of estimating the same classes as the Forest Service resulted in standard errors of 0.002 to 0.015. A study of the use of multidate TM data for change detection showed that forest canopy depletion, canopy increment, and no change could be identified with greater than 90 percent accuracy. The project results have been the basis for the Minnesota Department of Natural Resources and the Forest Service to define and begin to implement an annual system of forest inventory which utilizes Landsat TM data to detect changes in forest cover.

Inventory of montane-nesting birds in the Arctic Network of National Parks, Alaska

USGS Publications Warehouse

Tibbitts, T.L.; Ruthrauff, D.R.; Gill, Robert E.; Handel, Colleen M.

2006-01-01

The Alaska Science Center of the U.S. Geological Survey conducted an inventory of birds in montane areas of the four northern parks in the Arctic Network of National Parks, Alaska. This effort represents the first comprehensive assessment of breeding range and habitat associations for the majority of avian species in the Arctic Network. Ultimately, these data provide a framework upon which to design future monitoring programs.A stratified random sampling design was used to select sample plots (n = 73 plots) that were allocated in proportion to the availability of ecological subsections. Point counts (n = 1,652) were conducted to quantify abundance, distribution, and habitat associations of birds. Field work occurred over three years (2001 to 2003) during two-week-long sessions in late May through early June that coincided with peak courtship activity of breeding birds.Totals of 53 species were recorded in Cape Krusenstern National Monument, 91 in Noatak National Preserve, 57 in Kobuk Valley National Park, and 96 in Gates of the Arctic National Park and Preserve. Substantial proportions of species in individual parks are considered species of conservation concern (18 to 26%) or species of stewardship responsibility of the land managers in the region (8 to 18%). The most commonly detected passerines on point counts included Redpoll spp. (Carduelis flammea and C. hornemanni), Savannah Sparrow (Passerculus sandwichensis), and American Tree Sparrow (Spizella arborea). The most numerous shorebirds were American Golden-Plover (Pluvialis dominica), Wilson’s Snipe (Gallinago delicata), and Whimbrel (Numenius phaeopus). Most species were detected at low rates, reflecting the low breeding densities (and/or low detectabilities) of birds in the montane Arctic. Suites of species were associated with particular ranges of elevation and showed strong associations with particular habitat types.

How Much Can Remotely-Sensed Natural Resource Inventories Benefit from Finer Spatial Resolutions?

NASA Astrophysics Data System (ADS)

Hou, Z.; Xu, Q.; McRoberts, R. E.; Ståhl, G.; Greenberg, J. A.

2017-12-01

For remote sensing facilitated natural resource inventories, the effects of spatial resolution in the form of pixel size and the effects of subpixel information on estimates of population parameters were evaluated by comparing results obtained using Landsat 8 and RapidEye auxiliary imagery. The study area was in Burkina Faso, and the variable of interest was the stem volume (m3/ha) convertible to the woodland aboveground biomass. A sample consisting of 160 field plots was selected and measured from the population following a two-stage sampling design. Models were fit using weighted least squares; the population mean, mu, and the variance of the estimator of the population mean, Var(mu.hat), were estimated in two inferential frameworks, model-based and model-assisted, and compared; for each framework, Var(mu.hat) was estimated both analytically and empirically. Empirical variances were estimated with bootstrapping that for resampling takes clustering effects into account. The primary results were twofold. First, for the effects of spatial resolution and subpixel information, four conclusions are relevant: (1) finer spatial resolution imagery indeed contributes to greater precision for estimators of population parameter, but this increase is slight at a maximum rate of 20% considering that RapidEye data are 36 times finer resolution than Landsat 8 data; (2) subpixel information on texture is marginally beneficial when it comes to making inference for population of large areas; (3) cost-effectiveness is more favorable for the free of charge Landsat 8 imagery than RapidEye imagery; and (4) for a given plot size, candidate remote sensing auxiliary datasets are more cost-effective when their spatial resolutions are similar to the plot size than with much finer alternatives. Second, for the comparison between estimators, three conclusions are relevant: (1) model-based variance estimates are consistent with each other and about half as large as stabilized model-assisted estimates, suggesting superior effectiveness of model-based inference to model-assisted inference; (2) bootstrapping is an effective alternative to analytical variance estimators; and (3) prediction accuracy expressed by RMSE is useful for screening candidate models to be used for population inferences.

Stratified estimation of forest area using satellite imagery, inventory data, and the k-nearest neighbors technique

Treesearch

Ronald E. McRoberts; Mark D. Nelson; Daniel G. Wendt

2002-01-01

For two large study areas in Minnesota, USA, stratified estimation using classified Landsat Thematic Mapper satellite imagery as the basis for stratification was used to estimate forest area. Measurements of forest inventory plots obtained for a 12-month period in 1998 and 1999 were used as the source of data for within-stratum estimates. These measurements further...

Repeated measures from FIA data facilitates analysis across spatial scales of tree growth responses to nitrogen deposition from individual trees to whole ecoregions

Treesearch

Charles H. (Hobie) Perry; Kevin J. Horn; R. Quinn Thomas; Linda H. Pardo; Erica A.H. Smithwick; Doug Baldwin; Gregory B. Lawrence; Scott W. Bailey; Sabine Braun; Christopher M. Clark; Mark Fenn; Annika Nordin; Jennifer N. Phelan; Paul G. Schaberg; Sam St. Clair; Richard Warby; Shaun Watmough; Steven S. Perakis

2015-01-01

The abundance of temporally and spatially consistent Forest Inventory and Analysis data facilitates hierarchical/multilevel analysis to investigate factors affecting tree growth, scaling from plot-level to continental scales. Herein we use FIA tree and soil inventories in conjunction with various spatial climate and soils data to estimate species-specific responses of...

Using interpreted large scale aerial photo data to enhance satellite-based mapping and explore forest land definitions

Treesearch

Tracey S. Frescino; Gretchen G. Moisen

2009-01-01

The Interior-West, Forest Inventory and Analysis (FIA), Nevada Photo-Based Inventory Pilot (NPIP), launched in 2004, involved acquisition, processing, and interpretation of large scale aerial photographs on a subset of FIA plots (both forest and nonforest) throughout the state of Nevada. Two objectives of the pilot were to use the interpreted photo data to enhance...

Assessment of fire effects based on Forest Inventory and Analysis data and a long-term fire mapping data set

Treesearch

John D. Shaw; Sara A. Goeking; James Menlove; Charles E. Werstak

2017-01-01

Integration of Forest Inventory and Analysis (FIA) plot data with Monitoring Trends in Burn Severity (MTBS) data can provide new information about fire effects on forests. This integration allowed broad-scale assessment of the cover types burned in large fires, the relationship between prefire stand conditions and fire severity, and postfire stand conditions. Of the 42...

Errors in terrain-based model preditions caused by altered forest inventory plot locations in the Southern Appalachian Mountains, USA.

Treesearch

Huei-Jin Wang; Stephen Prisley; Philip Radtke; John Coulston

2012-01-01

Forest modeling applications that cover large geographic area can benefit from the use of widely-held knowledge about relationships between forest attributes and topographic variables. A noteworthy example involved the coupling of field survey data from the Forest Inventory Analysis (FIA) program of USDA Forest Service with digital elevation model (DEM) data in...

Mortality rates associated with crown health for eastern forest tree species

Treesearch

Randall S. Morin; KaDonna C. Randolph; Jim Steinman

2015-01-01

The condition of tree crowns is an important indicator of tree and forest health. Crown conditions have been evaluated during inventories of the US Forest Service Forest Inventory and Analysis (FIA) program since 1999. In this study, remeasured data from 55,013 trees on 2616 FIA plots in the eastern USA were used to assess the probability of survival among various tree...

Integrating forest inventory and analysis data into a LIDAR-based carbon monitoring system

Treesearch

Kristofer D. Johnson; Richard Birdsey; Andrew O Finley; Anu Swantaran; Ralph Dubayah; Craig Wayson; Rachel Riemann

2014-01-01

Forest Inventory and Analysis (FIA) data may be a valuable component of a LIDAR-based carbon monitoring system, but integration of the two observation systems is not without challenges. To explore integration methods, two wall-to-wall LIDAR-derived biomass maps were compared to FIA data at both the plot and county levels in Anne Arundel and Howard Counties in Maryland...

The relationship between diversity and productivity in selected forests of the Lake States Region (USA): relative impact of species versus structural diversity

Treesearch

W. Keith Moser; Mark Hansen

2009-01-01

Ecological theory suggests that diversity and productivity (at some measure) are positively correlated, presumably because individuals engage in niche partitioning to occupy any unclaimed growing space. We examined this theory using inventory information from the U.S. Department of Agriculture, Forest Service, Forest Inventory and Analysis program. The study uses plot-...

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

Treesearch

B. Ruefenacht; M.V. Finco; M.D. Nelson; R. Czaplewski; E.H. Helmer; J. A. Blackard; G.R. Holden; A.J. Lister; D. Salajanu; D. Weyermann; K. Winterberger

2008-01-01

Classification-trees were used to model forest type groups and forest types for the conterminous United States and Alaska. The predictor data were a geospatial data set with a spatial resolution of 250 m developed by the U.S. Department of Agriculture Forest Service (USFS). The response data were plot data from the USFS Forest Inventory and Analysis program. Overall...

Measuring and modeling carbon stock change estimates for US forests and uncertainties from apparent inter-annual variability

Treesearch

James E. Smith; Linda S. Heath

2015-01-01

Our approach is based on a collection of models that convert or augment the USDA Forest Inventory and Analysis program survey data to estimate all forest carbon component stocks, including live and standing dead tree aboveground and belowground biomass, forest floor (litter), down deadwood, and soil organic carbon, for each inventory plot. The data, which include...

New Mexico Forest Inventory and Analysis: American Recovery and Reinvestment Act Project, Field Report: 2010-2012

Treesearch

Mary Stuever; John Capuano

2014-01-01

For a 3-year period, from 2010-2012, the New Mexico Forestry Division utilized contractors to collect Forest Inventory and Analysis (FIA) data in New Mexico. Funded through the American Recovery and Reinvestment Act, the State partnered with the Interior West FIA Program. Together, both agencies collected data on approximately 6,450 plots. This effort represents the...

Long-term patterns in vegetation-site relationships in a southern Appalachian forest

Treesearch

Katherine J. Elliott; James M. Vose; Wayne T. Swank; Paul V. Bolstad

1999-01-01

The authors used permanent plot inventories from 1969-1973 and 1988-1993 to describe forest species distribution patterns of the Coweeta Hydrologic Laboratory, a 2,185 ha basin in Western North Carolina, USA. They used canonical correspondence analysis to explore the vegetation-site patterns for the 1970’s and 1990’s inventories combined. Site variables were determined...

Using US Forest Inventory (FIA) Data to Test for Growth Enhancement

NASA Astrophysics Data System (ADS)

Masek, J. G.; Collatz, G. J.; Williams, C. A.

2015-12-01

It is recognized that land ecosystems sequester a significant fraction of anthropogenic carbon emissions, and that the magnitude of the "land sink" appears to be increasing through time. This observation has led to the hypothesis that forest ecosystems are experiencing more rapid growth than their historical norm, due to some combination of CO2 fertilization, longer growing seasons, nitrogen deposition, and more intensive management. Direct evidence for growth enhancment has been reported from experimental plots, where long-term (historical) rates of biomass accumulation appear lower than contemporary rates derived from remeasurement of individual trees. However, the approach has not been pursued at a national scale. Since the late 1990's the US Forest Inventory and Analysis (FIA) program has standardized plot locations across the United States, and has systematically remeasured tree and plot attributes on 5-year (east) or 10-year (west) cycles. In principle, these remeasured plots provide a robust dataset for comparing contemporary and historical growth rates. In this talk we review approaches for performing this comparison at both plot and tree scales. We find that recent plot-level biomass accumulation rates from the eastern US do show more rapid growth than would be expected from historical biomass-age curves, with enhancement factors of up 2x. However, the implicit inclusion of "cryptic" or older disturbances in the historical curves hinders a definitive interpretation. Stand-level age-biomass simulations confirm that disturbance events must be included in the remeasured data set in order to provide comparability with historical curves. Remeasured DBH measurements from individual trees may provide a more robust approach for examining the issue.

Estimating Volume, Biomass, and Carbon in Hedmark County, Norway Using a Profiling LiDAR

NASA Technical Reports Server (NTRS)

Nelson, Ross; Naesset, Erik; Gobakken, T.; Gregoire, T.; Stahl, G.

2009-01-01

A profiling airborne LiDAR is used to estimate the forest resources of Hedmark County, Norway, a 27390 square kilometer area in southeastern Norway on the Swedish border. One hundred five profiling flight lines totaling 9166 km were flown over the entire county; east-west. The lines, spaced 3 km apart north-south, duplicate the systematic pattern of the Norwegian Forest Inventory (NFI) ground plot arrangement, enabling the profiler to transit 1290 circular, 250 square meter fixed-area NFI ground plots while collecting the systematic LiDAR sample. Seven hundred sixty-three plots of the 1290 plots were overflown within 17.8 m of plot center. Laser measurements of canopy height and crown density are extracted along fixed-length, 17.8 m segments closest to the center of the ground plot and related to basal area, timber volume and above- and belowground dry biomass. Linear, nonstratified equations that estimate ground-measured total aboveground dry biomass report an R(sup 2) = 0.63, with an regression RMSE = 35.2 t/ha. Nonstratified model results for the other biomass components, volume, and basal area are similar, with R(sup 2) values for all models ranging from 0.58 (belowground biomass, RMSE = 8.6 t/ha) to 0.63. Consistently, the most useful single profiling LiDAR variable is quadratic mean canopy height, h (sup bar)(sub qa). Two-variable models typically include h (sup bar)(sub qa) or mean canopy height, h(sup bar)(sub a), with a canopy density or a canopy height standard deviation measure. Stratification by productivity class did not improve the nonstratified models, nor did stratification by pine/spruce/hardwood. County-wide profiling LiDAR estimates are reported, by land cover type, and compared to NFI estimates.

Remeasured FIA plots reveal tree-level diameter growth and tree mortality impacts of nitrogen deposition on California’s forests

Treesearch

Mark E. Fenn; Jeremy S. Fried; Haiganoush K. Preisler; Andrzej Bytnerowicz; Susan Schilling; Sarah Jovan; Olaf Kuegler

2015-01-01

The air in California’s forests spans a broad range of purity, from virtually no locally generated pollutants to highly elevated levels of pollutants in forests downwind of urban and agricultural source areas. Ten-year remeasurement data from Forest Inventory and Analysis (FIA) plots in California were used in combination with modelled atmospheric nitrogen (N)...

A simulation of image-assisted forest monitoring for national inventories

Treesearch

Francis Roesch

2016-01-01

The efficiency of national forest monitoring efforts can be increased by the judicious incorporation of ancillary data. For instance, a fixed number of ground plots might be used to inform a larger set of annual estimates by observing a smaller proportion of the plots each year while augmenting each annual estimate with ancillary data in order to reduce overall costs...

Comparing the accuracy of terrestrial laser scanner in measuring forest inventory variables to enhance better decision making for potential fire hazards

NASA Astrophysics Data System (ADS)

Ghimire, Suman; Xystrakis, Fotios; Koutsias, Nikos

2017-04-01

Forest inventory variables are essential in accessing the potential of wildfire hazard, obtaining above ground biomass and carbon sequestration which helps developing strategies for sustainable management of forests. Effective management of forest resources relies on the accuracy of such inventory variables. This study aims to compare the accuracy in obtaining the forest inventory variables like diameter at breast height (DBH) and tree height from Terrestrial Laser Scanner (Faro Focus 3D X 330) with that from the traditional forest inventory techniques in the Mediterranean forests of Greece. The data acquisition was carried out on an area of 9,539.8 m2 with six plots each of radius 6 m. Computree algorithm was applied for automatic detection of DBH from terrestrial laser scanner data. Similarly, tree height was estimated manually using CloudCompare software for the terrestrial laser scanner data. The field estimates of DBH and tree height was carried out using calipers and Nikon Forestry 550 Laser Rangefinder. The comparison of DBH measured between field estimates and Terrestrial Laser Scanner (TLS), resulted in R squared values ranging from 0.75 to 0.96 at the plot level. An average R2 and RMSE value of 0.80 and 1.07 m respectively was obtained when comparing the tree height between TLS and field data. Our results confirm that terrestrial laser scanner can provide nondestructive, high-resolution, and precise determination of forest inventory for better decision making in sustainable forest management and assessing potential of forest fire hazards.

The impact of forest structure and spatial scale on the relationship between ground plot above ground biomass and GEDI lidar waveforms

NASA Astrophysics Data System (ADS)

Armston, J.; Marselis, S.; Hancock, S.; Duncanson, L.; Tang, H.; Kellner, J. R.; Calders, K.; Disney, M.; Dubayah, R.

2017-12-01

The NASA Global Ecosystem Dynamics Investigation (GEDI) will place a multi-beam waveform lidar instrument on the International Space Station (ISS) to provide measurements of forest vertical structure globally. These measurements of structure will underpin empirical modelling of above ground biomass density (AGBD) at the scale of individual GEDI lidar footprints (25m diameter). The GEDI pre-launch calibration strategy for footprint level models relies on linking AGBD estimates from ground plots with GEDI lidar waveforms simulated from coincident discrete return airborne laser scanning data. Currently available ground plot data have variable and often large uncertainty at the spatial resolution of GEDI footprints due to poor colocation, allometric model error, sample size and plot edge effects. The relative importance of these sources of uncertainty partly depends on the quality of ground measurements and region. It is usually difficult to know the magnitude of these uncertainties a priori so a common approach to mitigate their influence on model training is to aggregate ground plot and waveform lidar data to a coarser spatial scale (0.25-1ha). Here we examine the impacts of these principal sources of uncertainty using a 3D simulation approach. Sets of realistic tree models generated from terrestrial laser scanning (TLS) data or parametric modelling matched to tree inventory data were assembled from four contrasting forest plots across tropical rainforest, deciduous temperate forest, and sclerophyll eucalypt woodland sites. These tree models were used to simulate geometrically explicit 3D scenes with variable tree density, size class and spatial distribution. GEDI lidar waveforms are simulated over ground plots within these scenes using monte carlo ray tracing, allowing the impact of varying ground plot and waveform colocation error, forest structure and edge effects on the relationship between ground plot AGBD and GEDI lidar waveforms to be directly assessed. We quantify the sensitivity of calibration equations relating GEDI lidar structure measurements and AGBD to these factors at a range of spatial scales (0.0625-1ha) and discuss the implications for the expanding use of existing in situ ground plot data by GEDI.

An assessment of invasive plant species monitored by the Northern Research Station Forest Inventory and Analysis Program, 2005 through 2010

Treesearch

Cassandra M. Kurtz

2013-01-01

Invasive plant species are a worldwide concern due to the high ecological and economic costs associated with their presence. This document describes the plant characteristics and regional distribution of the 50 invasive plant species monitored from 2005 through 2010 on forested Phase 2 (P2) Forest Inventory and Analysis (FIA) plots in the 24 states of the Northern...

Oregon’s forest resources, 2001–2010: ten-year Forest Inventory and Analysis report

Treesearch

Sheel Bansal; Leslie Brodie; Sharon Stanton; Karen Waddell; Marin Palmer; Glenn Christensen; Olaf Kuegler; John Chase; Joel Thompson; Sarah Jovan; Andrew Gray; Morgan Todd

2017-01-01

This report highlights key findings from a comprehensive vegetation survey of all forested land across the state of Oregon. A total of 5,180 forested field plots in Oregon were visited by Forest Inventory and Analysis (FIA) crews over a 10-year period from 2001 to 2010. Oregon has 30 million acres of forest, covering nearly half the state. The structure and composition...

Searching for American chestnut: the estimation of rare species attributes in a national forest inventory

Treesearch

Francis A. Roesch; William H. McWilliams

2007-01-01

American chestnut, once a dominant tree species in forests of the Northeastern United States, has become extremely rare. It is so rare, in fact, that on completion of 80 percent of the plot measurements of the U.S. Department of Agriculture Forest Service's most recent inventory in Pennsylvania, only 33 American chestnut trees with a diameter at breast height !Y 1...

Searching for American chestnut: the estimation of rare species attributes in a national forest inventory

Treesearch

Francis A. Roesch; William H. McWilliams

2005-01-01

American chestnut, once a dominant tree species in forests of the Northeastern United States, has become extremely rare. It is so rare, in fact, that on completion of 80 percent of the plot measurements of the U.S. Department of Agriculture Forest Service's most recent inventory in Pennsylvania, only 33 American chestnut trees with a diameter at breast height 2: 1...

Utility of tree crown condition indicators to predict tree survival using remeasured Forest Inventory and Analysis data

Treesearch

Randall S. Morin; Jim Steinman; KaDonna C. Randolph

2012-01-01

The condition of tree crowns is an important indicator of tree and forest health. Crown conditions have been evaluated during surveys of Forest Inventory and Analysis (FIA) Phase 3 (P3) plots since 1999. In this study, remeasured data from 39,357 trees in the northern United States were used to assess the probability of survival among various tree species using the...

Current forest and woodland carbon storage and flux in California: An estimate for the 2010 statewide assessment

Treesearch

Timothy A. Robards

2012-01-01

This study used USDA Forest Service Forest Inventory and Analysis (FIA) plot data, forest growth models, wildland fire emission estimates and timber harvest data to estimate the live tree carbon storage and flux of California's forests and woodlands. Approximately 30 Tg C02e per year was estimated as the annual flux for all California forests. The forest inventory...

National-scale aboveground biomass geostatistical mapping with FIA inventory and GLAS data: Preparation for sparsely sampled lidar assisted forest inventory

NASA Astrophysics Data System (ADS)

Babcock, C. R.; Finley, A. O.; Andersen, H. E.; Moskal, L. M.; Morton, D. C.; Cook, B.; Nelson, R.

2017-12-01

Upcoming satellite lidar missions, such as GEDI and IceSat-2, are designed to collect laser altimetry data from space for narrow bands along orbital tracts. As a result lidar metric sets derived from these sources will not be of complete spatial coverage. This lack of complete coverage, or sparsity, means traditional regression approaches that consider lidar metrics as explanatory variables (without error) cannot be used to generate wall-to-wall maps of forest inventory variables. We implement a coregionalization framework to jointly model sparsely sampled lidar information and point-referenced forest variable measurements to create wall-to-wall maps with full probabilistic uncertainty quantification of all inputs. We inform the model with USFS Forest Inventory and Analysis (FIA) in-situ forest measurements and GLAS lidar data to spatially predict aboveground forest biomass (AGB) across the contiguous US. We cast our model within a Bayesian hierarchical framework to better model complex space-varying correlation structures among the lidar metrics and FIA data, which yields improved prediction and uncertainty assessment. To circumvent computational difficulties that arise when fitting complex geostatistical models to massive datasets, we use a Nearest Neighbor Gaussian process (NNGP) prior. Results indicate that a coregionalization modeling approach to leveraging sampled lidar data to improve AGB estimation is effective. Further, fitting the coregionalization model within a Bayesian mode of inference allows for AGB quantification across scales ranging from individual pixel estimates of AGB density to total AGB for the continental US with uncertainty. The coregionalization framework examined here is directly applicable to future spaceborne lidar acquisitions from GEDI and IceSat-2. Pairing these lidar sources with the extensive FIA forest monitoring plot network using a joint prediction framework, such as the coregionalization model explored here, offers the potential to improve forest AGB accounting certainty and provide maps for post-model fitting analysis of the spatial distribution of AGB.

VT0005 In Action: National Forest Biomass Inventory Using Airborne Lidar Sampling

NASA Astrophysics Data System (ADS)

Saatchi, S. S.; Xu, L.; Meyer, V.; Ferraz, A.; Yang, Y.; Shapiro, A.; Bastin, J. F.

2016-12-01

Tropical countries are required to produce robust and verifiable estimates of forest carbon stocks for successful implementation of climate change mitigation. Lack of systematic national inventory data due to access, cost, and infrastructure, has impacted the capacity of most tropical countries to accurately report the GHG emissions to the international community. Here, we report on the development of the aboveground forest carbon (AGC) map of Democratic Republic of Congo (DRC) by using the VCS (Verified Carbon Standard) methodology developed by Sassan Saatchi (VT0005) using high-resolution airborne LiDAR samples. The methodology provides the distribution of the carbon stocks in aboveground live trees of more than 150 million ha of forests at 1-ha spatial resolution in DRC using more than 430, 000 ha of systematic random airborne Lidar inventory samples of forest structure. We developed a LIDAR aboveground biomass allometry using more than 100 1-ha plots across forest types and power-law model with LIDAR height metrics and average landscape scale wood density. The methodology provided estimates of forest biomass over the entire country using two approaches: 1) mean, variance, and total carbon estimates for each forest type present in DRC using inventory statistical techniques, and 2) a wall-to-wall map of the forest biomass extrapolated using satellite radar (ALOS PALSAR), surface topography from SRTM, and spectral information from Landsat (TM) and machine learning algorithms. We present the methodology, the estimates of carbon stocks and the spatial uncertainty over the entire country. AcknowledgementsThe theoretical research was carried out partially at the Jet Propulsion Laboratory, California Institute of Technology, under a contract with the National Aeronautics and Space Administration, and the design and implementation in the Democratic Republic of Congo was carried out at the Institute of Environment and Sustainability at University of California Los Angeles through the support of the International Climate Initiative of the German Ministry of Environment, Conservation and Nuclear Security, and the KFW Development Bank.

Inventory of Amphibians and Reptiles in Southern Colorado Plateau National Parks

USGS Publications Warehouse

Persons, Trevor B.; Nowak, Erika M.

2006-01-01

In fiscal year 2000, the National Park Service (NPS) initiated a nationwide program to inventory vertebrates andvascular plants within the National Parks, and an inventory plan was developed for the 19 park units in the Southern Colorado Plateau Inventory & Monitoring Network. We surveyed 12 parks in this network for reptiles and amphibians between 2001 and 2003. The overall goals of our herpetofaunal inventories were to document 90% of the species present, identify park-specific species of special concern, and, based on the inventory results, make recommendations for the development of an effective monitoring program. We used the following standardized herpetological methods to complete the inventories: time-area constrained searches, visual encounter ('general') surveys, and nighttime road cruising. We also recorded incidental species sightings and surveyed existing literature and museum specimen databases. We found 50 amphibian and reptile species during fieldwork. These included 1 salamander, 11 anurans, 21 lizards, and 17 snakes. Literature reviews, museum specimen data records, and personal communications with NPS staff added an additional eight species, including one salamander, one turtle, one lizard, and five snakes. It was necessary to use a variety of methods to detect all species in each park. Randomly-generated 1-ha time-area constrained searches and night drives produced the fewest species and individuals of all the methods, while general surveys and randomly-generated 10-ha time-areas constrained searches produced the most. Inventory completeness was likely compromised by a severe drought across the region during our surveys. In most parks we did not come close to the goal of detecting 90% of the expected species present; however, we did document several species range extensions. Effective monitoring programs for herpetofauna on the Colorado Plateau should use a variety of methods to detect species, and focus on taxa-specific methods. Randomly-generated plots must take into account microhabitat and aquatic features to be effective at sampling for herpetofauna.

Implementing a national process for estimating growth, removals, and mortality at the Pacific Northwest’s Forest Inventory and Analysis’s Region: modeling diameter growth

Treesearch

Olaf. Kuegler

2015-01-01

The Pacific Northwest Research Station’s Forest Inventory and Analysis Unit began remeasurement of permanently located FIA plots under the annualized design in 2011. With remeasurement has come the need to implement the national FIA system for compiling estimates of forest growth, removals, and mortality. The national system requires regional diameter-growth models to...

Exploring the association of the Minnesota Department of Natural Resources' satellite-detected change with the Forest Inventory and Analysis system of observed removals and mortality

Treesearch

Dale D. Gormanson; Timothy J. Aunan; Mark H. Hansen; Michael Hoppus

2009-01-01

Since 2001, the Minnesota Department of Natural Resources (MN-DNR) has mapped forest change annually by comparison of Landsat satellite image pairs. Over the same timeframe, 1,761 U.S. Department of Agriculture, Forest Service, Forest Inventory and Analysis (FIA) plots in Minnesota have been remeasured on a 5-year cycle, providing field data on growth, removals, and...

Contrasting Patterns of Damage and Recovery in Logged Amazon Forests From Small Footprint LiDAR Data

NASA Technical Reports Server (NTRS)

Morton, D. C.; Keller, M.; Cook, B. D.; Hunter, Maria; Sales, Marcio; Spinelli, L.; Victoria, D.; Andersen, H.-E.; Saleska, S.

2012-01-01

Tropical forests ecosystems respond dynamically to climate variability and disturbances on time scales of minutes to millennia. To date, our knowledge of disturbance and recovery processes in tropical forests is derived almost exclusively from networks of forest inventory plots. These plots typically sample small areas (less than or equal to 1 ha) in conservation units that are protected from logging and fire. Amazon forests with frequent disturbances from human activity remain under-studied. Ongoing negotiations on REDD+ (Reducing Emissions from Deforestation and Forest Degradation plus enhancing forest carbon stocks) have placed additional emphasis on identifying degraded forests and quantifying changing carbon stocks in both degraded and intact tropical forests. We evaluated patterns of forest disturbance and recovery at four -1000 ha sites in the Brazilian Amazon using small footprint LiDAR data and coincident field measurements. Large area coverage with airborne LiDAR data in 2011-2012 included logged and unmanaged areas in Cotriguacu (Mato Grosso), Fiona do Jamari (Rondonia), and Floresta Estadual do Antimary (Acre), and unmanaged forest within Reserva Ducke (Amazonas). Logging infrastructure (skid trails, log decks, and roads) was identified using LiDAR returns from understory vegetation and validated based on field data. At each logged site, canopy gaps from logging activity and LiDAR metrics of canopy heights were used to quantify differences in forest structure between logged and unlogged areas. Contrasting patterns of harvesting operations and canopy damages at the three logged sites reflect different levels of pre-harvest planning (i.e., informal logging compared to state or national logging concessions), harvest intensity, and site conditions. Finally, we used multi-temporal LiDAR data from two sites, Reserva Ducke (2009, 2012) and Antimary (2010, 2011), to evaluate gap phase dynamics in unmanaged forest areas. The rates and patterns of canopy gap formation at these sites illustrate potential issues for separating logging damages from natural forest disturbances over longer time scales. Multi-temporal airborne LiDAR data and coincident field measurements provide complementary perspectives on disturbance and recovery processes in intact and degraded Amazon forests. Compared to forest inventory plots, the large size of each individual site permitted analyses of landscape-scale processes that would require extremely high investments to study using traditional forest inventory methods.

A general method for assessing the effects of uncertainty in individual-tree volume model predictions on large-area volume estimates with a subtropical forest illustration

Treesearch

Ronald E. McRoberts; Paolo Moser; Laio Zimermann Oliveira; Alexander C. Vibrans

2015-01-01

Forest inventory estimates of tree volume for large areas are typically calculated by adding the model predictions of volumes for individual trees at the plot level, calculating the mean over plots, and expressing the result on a per unit area basis. The uncertainty in the model predictions is generally ignored, with the result that the precision of the large-area...

Remeasurement of permanent vegetation plots in the Great Smoky Mountains National Park, Tennessee, USA, and the implications of climatic changes on vegetation. Environmental Sciences Division publication No. 1111

DOE Office of Scientific and Technical Information (OSTI.GOV)

Becking, R. W.; Olson, J. S.

1978-03-01

This report summarizes field work over two summers (1976 and 1977) to relocate, monument and reinventory permanent vegetation plots in the Great Smoky Mountains National Park. These plots were first established by the senior author and R.H. Whittaker in 1959-62. The inventory results are discussed in terms of vegetation changes in high-altitudinal forest ecosystems, in particular the spruce-fir forests, and the factors, climate shift and biotic and abiotic agents, bringing about vegetation change. A second aspect of the report summarizes experience and offers recommendations for establishment of permanent vegetation plots for the purpose of providing a monitoring tool with whichmore » to measure long-term ecological change.« less

Geoecological controls on net mercury retention in northern peatlands

NASA Astrophysics Data System (ADS)

Bindler, R.; Rydberg, J.

2010-12-01

Peatlands, which receive much or all of their element inputs (e.g. nutrients or trace metals) via the atmosphere, are considered an ideal archive for studying past changes in mercury (Hg) deposition. These archives potentially contain information not only on important anthropogenic contributions to the environment over the past few centuries, but also on the natural antecedent conditions over the past several millennia. However, the assumption that Hg accumulation rates in peat represent an absolute record of past atmospheric deposition has proved problematic. In on-going studies of Hg retention in northern peatlands (bogs and oligotrophic fens) we find that net Hg accumulation is influenced by a range of geoecological factors in addition to actual changes in atmospheric deposition. Factors that influence the interception and net retention of Hg include differences in vegetation and microtopography - both of which may enhance dry deposition, and properties and processes within the peat such as decomposition that might influence long-term retention. Wetness, too, may play an important role in net retention in the surface peat through increased evasive losses of Hg. Differences between Hg concentrations in vascular plants and mosses are well established (at our site: 5-15 ng/g for leaves/needles of cottongrass, heather, Labrador tea and pine; 15-45 ng/g for mosses Sphagnum centrale and S. rubellum), but we also measured significant differences between different mosses within the same plots (S. rubellum, 24±3 ng/g; S. centrale, 18±2 ng/g). Further differences in Hg concentrations occur for single moss species in different settings; for example, Hg concentrations in S. centrale in open Sphagnum-only plots relative to plots including a mixture of vascular plants that form a field-layer canopy are 18±2 and 32±6 ng/g, respectively. As a result, sampling sites consisting of both Sphagnum and vascular plants have long-term cumulative inventories of mercury in the peat that are >60% greater than in areas characterized only by a mixture of Sphagnum species (where the water table is also relatively highest). However, comparisons of Pb-210 inventories, an independent proxy for atmospheric deposition, indicate that this increase in interception should be ≤40%. Based on data also from other sites, where Hg inventories may vary between cores by 2-4 times, we have observed that wetter sites invariably have the lowest cumulative Hg inventories and hypothesize greater evasive loss from wetter sites, which has been shown for soils. We will investigate this during fall 2010. Although we have identified a number of factors that complicate the use of peat records as absolute records of mercury deposition, these problems can be circumvented by multi-core studies that provide a more robust estimate of mean net accumulation rates in peatlands.

A Computer Program for Displaying Forest Survey Type Information

Treesearch

B. Bruce Bare; Robert N. Stone

1968-01-01

Presents a computerized procedure for displaying forest type information from inventory plots. Although the development of general forest type maps in emphasized, the program can be used to display any locational data having rectangular coordinates

Data and animal management software for large-scale phenotype screening.

PubMed

Ching, Keith A; Cooke, Michael P; Tarantino, Lisa M; Lapp, Hilmar

2006-04-01

The mouse N-ethyl-N-nitrosourea (ENU) mutagenesis program at the Genomics Institute of the Novartis Research Foundation (GNF) uses MouseTRACS to analyze phenotype screens and manage animal husbandry. MouseTRACS is a Web-based laboratory informatics system that electronically records and organizes mouse colony operations, prints cage cards, tracks inventory, manages requests, and reports Institutional Animal Care and Use Committee (IACUC) protocol usage. For efficient phenotype screening, MouseTRACS identifies mutants, visualizes data, and maps mutations. It displays and integrates phenotype and genotype data using likelihood odds ratio (LOD) plots of genetic linkage between genotype and phenotype. More detailed mapping intervals show individual single nucleotide polymorphism (SNP) markers in the context of phenotype. In addition, dynamically generated pedigree diagrams and inventory reports linked to screening results summarize the inheritance pattern and the degree of penetrance. MouseTRACS displays screening data in tables and uses standard charts such as box plots, histograms, scatter plots, and customized charts looking at clustered mice or cross pedigree comparisons. In summary, MouseTRACS enables the efficient screening, analysis, and management of thousands of animals to find mutant mice and identify novel gene functions. MouseTRACS is available under an open source license at http://www.mousetracs.sourceforge.net.

The Computer Bulletin Board. Modified Gran Plots of Very Weak Acids on a Spreadsheet.

ERIC Educational Resources Information Center

Chau, F. T.; And Others

1990-01-01

Presented are two applications of computer technology to chemistry instruction: the use of a spreadsheet program to analyze acid-base titration curves and the use of database software to catalog stockroom inventories. (CW)

Predicting spatial distribution of privet (liguestrum spp.) in South Carolina from MODIS and forest inventory plot data

Treesearch

Dumitru Salajanu; Dennis M. Jacobs

2009-01-01

Privet's aggressive competitive behavior causes environmental harm to the ecosystem by degrading species diversity and wildlife habitat. Effective control of its spread requires high-quality spatial distribution information. Our...

Modelling individual tree height to crown base of Norway spruce (Picea abies (L.) Karst.) and European beech (Fagus sylvatica L.)

PubMed Central

Jansa, Václav

2017-01-01

Height to crown base (HCB) of a tree is an important variable often included as a predictor in various forest models that serve as the fundamental tools for decision-making in forestry. We developed spatially explicit and spatially inexplicit mixed-effects HCB models using measurements from a total 19,404 trees of Norway spruce (Picea abies (L.) Karst.) and European beech (Fagus sylvatica L.) on the permanent sample plots that are located across the Czech Republic. Variables describing site quality, stand density or competition, and species mixing effects were included into the HCB model with use of dominant height (HDOM), basal area of trees larger in diameters than a subject tree (BAL- spatially inexplicit measure) or Hegyi’s competition index (HCI—spatially explicit measure), and basal area proportion of a species of interest (BAPOR), respectively. The parameters describing sample plot-level random effects were included into the HCB model by applying the mixed-effects modelling approach. Among several functional forms evaluated, the logistic function was found most suited to our data. The HCB model for Norway spruce was tested against the data originated from different inventory designs, but model for European beech was tested using partitioned dataset (a part of the main dataset). The variance heteroscedasticity in the residuals was substantially reduced through inclusion of a power variance function into the HCB model. The results showed that spatially explicit model described significantly a larger part of the HCB variations [R2adj = 0.86 (spruce), 0.85 (beech)] than its spatially inexplicit counterpart [R2adj = 0.84 (spruce), 0.83 (beech)]. The HCB increased with increasing competitive interactions described by tree-centered competition measure: BAL or HCI, and species mixing effects described by BAPOR. A test of the mixed-effects HCB model with the random effects estimated using at least four trees per sample plot in the validation data confirmed that the model was precise enough for the prediction of HCB for a range of site quality, tree size, stand density, and stand structure. We therefore recommend measuring of HCB on four randomly selected trees of a species of interest on each sample plot for localizing the mixed-effects model and predicting HCB of the remaining trees on the plot. Growth simulations can be made from the data that lack the values for either crown ratio or HCB using the HCB models. PMID:29049391

Classification of forest land attributes using multi-source remotely sensed data

NASA Astrophysics Data System (ADS)

Pippuri, Inka; Suvanto, Aki; Maltamo, Matti; Korhonen, Kari T.; Pitkänen, Juho; Packalen, Petteri

2016-02-01

The aim of the study was to (1) examine the classification of forest land using airborne laser scanning (ALS) data, satellite images and sample plots of the Finnish National Forest Inventory (NFI) as training data and to (2) identify best performing metrics for classifying forest land attributes. Six different schemes of forest land classification were studied: land use/land cover (LU/LC) classification using both national classes and FAO (Food and Agricultural Organization of the United Nations) classes, main type, site type, peat land type and drainage status. Special interest was to test different ALS-based surface metrics in classification of forest land attributes. Field data consisted of 828 NFI plots collected in 2008-2012 in southern Finland and remotely sensed data was from summer 2010. Multinomial logistic regression was used as the classification method. Classification of LU/LC classes were highly accurate (kappa-values 0.90 and 0.91) but also the classification of site type, peat land type and drainage status succeeded moderately well (kappa-values 0.51, 0.69 and 0.52). ALS-based surface metrics were found to be the most important predictor variables in classification of LU/LC class, main type and drainage status. In best classification models of forest site types both spectral metrics from satellite data and point cloud metrics from ALS were used. In turn, in the classification of peat land types ALS point cloud metrics played the most important role. Results indicated that the prediction of site type and forest land category could be incorporated into stand level forest management inventory system in Finland.

Using (137)Cs to quantify the redistribution of soil organic carbon and total N affected by intensive soil erosion in the headwaters of the Yangtze River, China.

PubMed

Guoxiao, Wei; Yibo, Wang; Yan Lin, Wang

2008-12-01

Characteristics of soil organic carbon (SOC) and total nitrogen (total N) are important for determining the overall quality of soils. Studies on spatial and temporal variation in SOC and total N are of great importance because of global environmental concerns. Soil erosion is one of the major processes affecting the redistribution of SOC and total N in the test fields. To characterize the distribution and dynamics of SOC and N in the intensively eroded soil of the headwaters of the Yangtze River, China, we measured profiles of soil organic C, total N stocks, and (137)Cs in a control plot and a treatment plot. The amounts of SOC, (137)Cs of sampling soil profiles increased in the following order, lower>middle>upper portions on the control plot, and the amounts of total N of sampling soil profile increase in the following order: upper>middle>lower on the control plot. Intensive soil erosion resulted in a significant decrease of SOC amounts by 34.9%, 28.3% and 52.6% for 0-30cm soil layer at upper, middle and lower portions and (137)Cs inventory decreased by 68%, 11% and 85% at upper, middle and lower portions, respectively. On the treatment plot total N decreased by 50.2% and 14.6% at the upper and middle portions and increased by 48.9% at the lower portion. Coefficients of variation (CVs) of SOC decreased by 31%, 37% and 30% in the upper, middle and lower slope portions, respectively. Similar to the variational trend of SOC, CVs of (137)Cs decreased by 19.2%, 0.5% and 36.5%; and total N decreased by 45.7%, 65.1% and 19% in the upper, middle and lower slope portions, respectively. The results showed that (137)Cs, SOC and total N moved on the sloping land almost in the same physical mechanism during the soil erosion procedure, indicating that fallout of (137)Cs could be used directly for quantifying dynamic SOC and total N redistribution as the soil was affected by intensive soil erosion.

Beryllium-7 in vegetation, soil, sediment and runoff on the northern Loess Plateau.

PubMed

Zhang, Fengbao; Yang, Mingyi; Zhang, Jiaqiong

2018-06-01

Beryllium-7 ( 7 Be), as a potentially powerful tracer, was widely used to document soil redistribution and identify sediment sources in recent decades, but the quantity and distribution of 7 Be in vegetation, soil, sediment and runoff on the Loess Plateau have not been fully described. In this study, we measured 7 Be in vegetation, soil, sediment and runoff on the northern Loess Plateau of China and analyzed its variations during the rainy season to assess the potential of the 7 Be method for documenting soil redistribution and identifying sediment sources in a wide range of environments. The results indicated that vegetation, soil, and sediment samples showed higher levels and larger variations of 7 Be activities during the rainy season. The drying plants showed 7 Be mass activity that was more than three times higher than that of living and semi-decomposed plants. 7 Be mass activity in plants and sediment was much higher than in the soil. 7 Be activity in runoff water with a few submicron suspended particles varied slightly and was far lower than in plant, soil and sediment samples. The cumulative precipitation generally determined 7 Be inventory held by plants and soil. An inverse relationship was found between the 7 Be mass activity in sediment and the sediment amount. Globally, approximate 30% of the total 7 Be was held by plants in both the herbaceous and subshrub plots. Approximate 10% of the total 7 Be was lost with sediment from the bare plot. A very small proportion of 7 Be (1.18%-3.20%) was lost with runoff, and the vast majority of 7 Be was retained in the slope soil at the end of rainy season. Vegetation cover and soil erosion significantly affected the spatial distribution and variations of the 7 Be inventory in soil, providing a necessary condition for the development of a 7 Be method to document soil erosion on slopes with vegetation. Copyright © 2018 Elsevier B.V. All rights reserved.

Airborne Laser Scanning of Forest Stem Volume in a Mountainous Environment

PubMed Central

Hollaus, Markus; Wagner, Wolfgang; Maier, Bernhard; Schadauer, Klemens

2007-01-01

Airborne laser scanning (ALS) is an active remote sensing technique that uses the time-of-flight measurement principle to capture the three-dimensional structure of the earth's surface with pulsed lasers that transmit nanosecond-long laser pulses with a high pulse repetition frequency. Over forested areas most of the laser pulses are reflected by the leaves and branches of the trees, but a certain fraction of the laser pulses reaches the forest floor through small gaps in the canopy. Thus it is possible to reconstruct both the three-dimensional structure of the forest canopy and the terrain surface. For the retrieval of quantitative forest parameters such as stem volume or biomass it is necessary to use models that combine ALS with inventory data. One approach is to use multiplicative regression models that are trained with local inventory data. This method has been widely applied over boreal forest regions, but so far little experience exists with applying this method for mapping alpine forest. In this study the transferability of this approach to a 128 km2 large mountainous region in Vorarlberg, Austria, was evaluated. For the calibration of the model, inventory data as operationally collected by Austrian foresters were used. Despite these inventory data are based on variable sample plot sizes, they could be used for mapping stem volume for the entire alpine study area. The coefficient of determination R2 was 0.85 and the root mean square error (RMSE) 90.9 m3ha−1 (relative error of 21.4%) which is comparable to results of ALS studies conducted over topographically less complex environments. Due to the increasing availability, ALS data could become an operational part of Austrian's forest inventories.

Stand Table Construction from Relascope Plots.

Treesearch

Charles B. Briscoe

1957-01-01

When timber is cruised using relascope, basal area and volume figures are obtained without constructing a stand table, through the use of appropriate conversion factors. Although this saving in time is very desirable for most inventories, certain management purposes require stand tables.

An iterative and targeted sampling design informed by habitat suitability models for detecting focal plant species over extensive areas.

PubMed

Wang, Ophelia; Zachmann, Luke J; Sesnie, Steven E; Olsson, Aaryn D; Dickson, Brett G

2014-01-01

Prioritizing areas for management of non-native invasive plants is critical, as invasive plants can negatively impact plant community structure. Extensive and multi-jurisdictional inventories are essential to prioritize actions aimed at mitigating the impact of invasions and changes in disturbance regimes. However, previous work devoted little effort to devising sampling methods sufficient to assess the scope of multi-jurisdictional invasion over extensive areas. Here we describe a large-scale sampling design that used species occurrence data, habitat suitability models, and iterative and targeted sampling efforts to sample five species and satisfy two key management objectives: 1) detecting non-native invasive plants across previously unsampled gradients, and 2) characterizing the distribution of non-native invasive plants at landscape to regional scales. Habitat suitability models of five species were based on occurrence records and predictor variables derived from topography, precipitation, and remotely sensed data. We stratified and established field sampling locations according to predicted habitat suitability and phenological, substrate, and logistical constraints. Across previously unvisited areas, we detected at least one of our focal species on 77% of plots. In turn, we used detections from 2011 to improve habitat suitability models and sampling efforts in 2012, as well as additional spatial constraints to increase detections. These modifications resulted in a 96% detection rate at plots. The range of habitat suitability values that identified highly and less suitable habitats and their environmental conditions corresponded to field detections with mixed levels of agreement. Our study demonstrated that an iterative and targeted sampling framework can address sampling bias, reduce time costs, and increase detections. Other studies can extend the sampling framework to develop methods in other ecosystems to provide detection data. The sampling methods implemented here provide a meaningful tool when understanding the potential distribution and habitat of species over multi-jurisdictional and extensive areas is needed for achieving management objectives.

An Iterative and Targeted Sampling Design Informed by Habitat Suitability Models for Detecting Focal Plant Species over Extensive Areas

PubMed Central

Wang, Ophelia; Zachmann, Luke J.; Sesnie, Steven E.; Olsson, Aaryn D.; Dickson, Brett G.

2014-01-01

Prioritizing areas for management of non-native invasive plants is critical, as invasive plants can negatively impact plant community structure. Extensive and multi-jurisdictional inventories are essential to prioritize actions aimed at mitigating the impact of invasions and changes in disturbance regimes. However, previous work devoted little effort to devising sampling methods sufficient to assess the scope of multi-jurisdictional invasion over extensive areas. Here we describe a large-scale sampling design that used species occurrence data, habitat suitability models, and iterative and targeted sampling efforts to sample five species and satisfy two key management objectives: 1) detecting non-native invasive plants across previously unsampled gradients, and 2) characterizing the distribution of non-native invasive plants at landscape to regional scales. Habitat suitability models of five species were based on occurrence records and predictor variables derived from topography, precipitation, and remotely sensed data. We stratified and established field sampling locations according to predicted habitat suitability and phenological, substrate, and logistical constraints. Across previously unvisited areas, we detected at least one of our focal species on 77% of plots. In turn, we used detections from 2011 to improve habitat suitability models and sampling efforts in 2012, as well as additional spatial constraints to increase detections. These modifications resulted in a 96% detection rate at plots. The range of habitat suitability values that identified highly and less suitable habitats and their environmental conditions corresponded to field detections with mixed levels of agreement. Our study demonstrated that an iterative and targeted sampling framework can address sampling bias, reduce time costs, and increase detections. Other studies can extend the sampling framework to develop methods in other ecosystems to provide detection data. The sampling methods implemented here provide a meaningful tool when understanding the potential distribution and habitat of species over multi-jurisdictional and extensive areas is needed for achieving management objectives. PMID:25019621

The automated reference toolset: A soil-geomorphic ecological potential matching algorithm

USGS Publications Warehouse

Nauman, Travis; Duniway, Michael C.

2016-01-01

Ecological inventory and monitoring data need referential context for interpretation. Identification of appropriate reference areas of similar ecological potential for site comparison is demonstrated using a newly developed automated reference toolset (ART). Foundational to identification of reference areas was a soil map of particle size in the control section (PSCS), a theme in US Soil Taxonomy. A 30-m resolution PSCS map of the Colorado Plateau (366,000 km2) was created by interpolating ∼5000 field soil observations using a random forest model and a suite of raster environmental spatial layers representing topography, climate, general ecological community, and satellite imagery ratios. The PSCS map had overall out of bag accuracy of 61.8% (Kappa of 0.54, p < 0.0001), and an independent validation accuracy of 93.2% at a set of 356 field plots along the southern edge of Canyonlands National Park, Utah. The ART process was also tested at these plots, and matched plots with the same ecological sites (ESs) 67% of the time where sites fell within 2-km buffers of each other. These results show that the PSCS and ART have strong application for ecological monitoring and sampling design, as well as assessing impacts of disturbance and land management action using an ecological potential framework. Results also demonstrate that PSCS could be a key mapping layer for the USDA-NRCS provisional ES development initiative.

A wood density and aboveground biomass variability assessment using pre-felling inventory data in Costa Rica.

PubMed

Svob, Sienna; Arroyo-Mora, J Pablo; Kalacska, Margaret

2014-12-01

The high spatio-temporal variability of aboveground biomass (AGB) in tropical forests is a large source of uncertainty in forest carbon stock estimation. Due to their spatial distribution and sampling intensity, pre-felling inventories are a potential source of ground level data that could help reduce this uncertainty at larger spatial scales. Further, exploring the factors known to influence tropical forest biomass, such as wood density and large tree density, will improve our knowledge of biomass distribution across tropical regions. Here, we evaluate (1) the variability of wood density and (2) the variability of AGB across five ecosystems of Costa Rica. Using forest management (pre-felling) inventories we found that, of the regions studied, Huetar Norte had the highest mean wood density of trees with a diameter at breast height (DBH) greater than or equal to 30 cm, 0.623 ± 0.182 g cm -3 (mean ± standard deviation). Although the greatest wood density was observed in Huetar Norte, the highest mean estimated AGB (EAGB) of trees with a DBH greater than or equal to 30 cm was observed in Osa peninsula (173.47 ± 60.23 Mg ha -1 ). The density of large trees explained approximately 50% of EAGB variability across the five ecosystems studied. Comparing our study's EAGB to published estimates reveals that, in the regions of Costa Rica where AGB has been previously sampled, our forest management data produced similar values. This study presents the most spatially rich analysis of ground level AGB data in Costa Rica to date. Using forest management data, we found that EAGB within and among five Costa Rican ecosystems is highly variable. Combining commercial logging inventories with ecological plots will provide a more representative ground level dataset for the calibration of the models and remotely sensed data used to EAGB at regional and national scales. Additionally, because the non-protected areas of the tropics offer the greatest opportunity to reduce rates of deforestation and forest degradation, logging inventories offer a promising source of data to support mechanisms such as the United Nations REDD + (Reducing Emissions from Tropical Deforestation and Degradation) program.

Estimating vegetation biomass and cover across large plots in shrub and grass dominated drylands using terrestrial lidar and machine learning

USGS Publications Warehouse

Anderson, Kyle E.; Glenn, Nancy F.; Spaete, Lucas P.; Shinneman, Douglas; Pilliod, David S.; Arkle, Robert; McIlroy, Susan; Derryberry, DeWayne R.

2018-01-01

Terrestrial laser scanning (TLS) has been shown to enable an efficient, precise, and non-destructive inventory of vegetation structure at ranges up to hundreds of meters. We developed a method that leverages TLS collections with machine learning techniques to model and map canopy cover and biomass of several classes of short-stature vegetation across large plots. We collected high-definition TLS scans of 26 1-ha plots in desert grasslands and big sagebrush shrublands in southwest Idaho, USA. We used the Random Forests machine learning algorithm to develop decision tree models predicting the biomass and canopy cover of several vegetation classes from statistical descriptors of the aboveground heights of TLS points. Manual measurements of vegetation characteristics collected within each plot served as training and validation data. Models based on five or fewer TLS descriptors of vegetation heights were developed to predict the canopy cover fraction of shrubs (R2 = 0.77, RMSE = 7%), annual grasses (R2 = 0.70, RMSE = 21%), perennial grasses (R2 = 0.36, RMSE = 12%), forbs (R2 = 0.52, RMSE = 6%), bare earth or litter (R2 = 0.49, RMSE = 19%), and the biomass of shrubs (R2 = 0.71, RMSE = 175 g) and herbaceous vegetation (R2 = 0.61, RMSE = 99 g) (all values reported are out-of-bag). Our models explained much of the variability between predictions and manual measurements, and yet we expect that future applications could produce even better results by reducing some of the methodological sources of error that we encountered. Our work demonstrates how TLS can be used efficiently to extend manual measurement of vegetation characteristics from small to large plots in grasslands and shrublands, with potential application to other similarly structured ecosystems. Our method shows that vegetation structural characteristics can be modeled without classifying and delineating individual plants, a challenging and time-consuming step common in previous methods applying TLS to vegetation inventory. Improving application of TLS to studies of shrub-steppe ecosystems will serve immediate management needs by enhancing vegetation inventories, environmental modeling studies, and the ability to train broader datasets collected from air and space.

A universal airborne LiDAR approach for tropical forest carbon mapping.

PubMed

Asner, Gregory P; Mascaro, Joseph; Muller-Landau, Helene C; Vieilledent, Ghislain; Vaudry, Romuald; Rasamoelina, Maminiaina; Hall, Jefferson S; van Breugel, Michiel

2012-04-01

Airborne light detection and ranging (LiDAR) is fast turning the corner from demonstration technology to a key tool for assessing carbon stocks in tropical forests. With its ability to penetrate tropical forest canopies and detect three-dimensional forest structure, LiDAR may prove to be a major component of international strategies to measure and account for carbon emissions from and uptake by tropical forests. To date, however, basic ecological information such as height-diameter allometry and stand-level wood density have not been mechanistically incorporated into methods for mapping forest carbon at regional and global scales. A better incorporation of these structural patterns in forests may reduce the considerable time needed to calibrate airborne data with ground-based forest inventory plots, which presently necessitate exhaustive measurements of tree diameters and heights, as well as tree identifications for wood density estimation. Here, we develop a new approach that can facilitate rapid LiDAR calibration with minimal field data. Throughout four tropical regions (Panama, Peru, Madagascar, and Hawaii), we were able to predict aboveground carbon density estimated in field inventory plots using a single universal LiDAR model (r ( 2 ) = 0.80, RMSE = 27.6 Mg C ha(-1)). This model is comparable in predictive power to locally calibrated models, but relies on limited inputs of basal area and wood density information for a given region, rather than on traditional plot inventories. With this approach, we propose to radically decrease the time required to calibrate airborne LiDAR data and thus increase the output of high-resolution carbon maps, supporting tropical forest conservation and climate mitigation policy.

Observed effects of an exceptional drought on tree mortality in a tropical dry forest

NASA Astrophysics Data System (ADS)

Medvigy, D.; Vargas, G.; Xu, X.; Smith, C. M.; Becknell, J.; Brodribb, T.; Powers, J. S.

2016-12-01

Climate models predict that the coming century will bring reduced rainfall to Neotropical dry forests. It is unknown how tropical dry forest trees will respond to such rainfall reductions. Will there be increased mortality? If so, what will be the dominant mechanism of mortality? Will certain functional groups or size classes be more susceptible to unusually dry conditions and do functional traits underlie these patterns? With these questions in mind, we analyzed the response of trees from 18 Costa Rican tropical dry forest inventory plots and from additional transects to the exceptional 2015 drought that coincided with a strong ENSO event. We compared stand-level mortality rates observed during pre-drought years (2008-2014) and during the drought year of 2015 in the inventory plots. For both inventory plots and transects, we analyzed whether particular functional groups or size classes experienced exceptional mortality after the drought. We found that mortality rates were two to three times higher during the drought than before the drought. In contrast to observations at moist tropical forests, tree size had little influence on mortality. In terms of functional groups, mortality rates of evergreen oaks growing on nutrient-poor soils particularly increased during drought. Legumes seemed less affected by the drought than non-legumes. However, elevated mortality rates were not clearly correlated with commonly-measured traits like wood density or specific leaf area. Instead, hydraulic traits like P50 or turgor loss point may be better predictors of drought-driven mortality. In addition, trees that died during the drought tended to have smaller relative growth rate prior to the drought than trees that survived the drought.

Long-term tree inventory data from mountain forest plots in France.

PubMed

Fuhr, Marc; Cordonnier, Thomas; Courbaud, Benoît; Kunstler, Georges; Mermin, Eric; Riond, Catherine; Tardif, Pascal

2017-04-01

We present repeated tree measurement data from 63 permanent plots in mountain forests in France. Plot elevations range from 800 (lower limit of the montane belt) to 1942 m above sea level (subalpine belt). Forests mainly consist of pure or mixed stands dominated by European beech (Fagus sylvatica), Silver fir (Abies alba), and Norway spruce (Picea abies), in association with various broadleaved species at low elevation and with Arolla pine (Pinus cembra) at high elevation. The plot network includes 23 plots in stands that have not been managed for the last 40 years (at least) and 40 plots in plots managed according to an uneven-aged system with single-tree or small-group selection cutting. Plot sizes range from 0.2 to 1.9 ha. Plots were installed from 1994 to 2004 and remeasured two to five times during the 1994-2015 period. During the first census (installation), living trees more than 7.5 cm in dbh were identified, their diameter at breast height (dbh) was measured and their social status (strata) noted. Trees were spatially located, either with x, y, and z coordinates (40 plots) or within 0.25-ha square subplots (23 plots). In addition, in a subset of plots (58 plots), tree heights and tree crown dimensions were measured on a subset of trees and dead standing trees and stumps were included in the census. Remeasurements after installation include live tree diameters (including recruited trees), tree status (living, damaged, dead, stump), and for a subset of trees, height. At the time of establishment of the plots, plot densities range from 181 to 1328 stems/ha and plot basal areas range from 13.6 to 81.3 m 2 /ha. © 2017 by the Ecological Society of America.

Comparison of Precision of Biomass Estimates in Regional Field Sample Surveys and Airborne LiDAR-Assisted Surveys in Hedmark County, Norway

NASA Technical Reports Server (NTRS)

Naesset, Erik; Gobakken, Terje; Bollandsas, Ole Martin; Gregoire, Timothy G.; Nelson, Ross; Stahl, Goeran

2013-01-01

Airborne scanning LiDAR (Light Detection and Ranging) has emerged as a promising tool to provide auxiliary data for sample surveys aiming at estimation of above-ground tree biomass (AGB), with potential applications in REDD forest monitoring. For larger geographical regions such as counties, states or nations, it is not feasible to collect airborne LiDAR data continuously ("wall-to-wall") over the entire area of interest. Two-stage cluster survey designs have therefore been demonstrated by which LiDAR data are collected along selected individual flight-lines treated as clusters and with ground plots sampled along these LiDAR swaths. Recently, analytical AGB estimators and associated variance estimators that quantify the sampling variability have been proposed. Empirical studies employing these estimators have shown a seemingly equal or even larger uncertainty of the AGB estimates obtained with extensive use of LiDAR data to support the estimation as compared to pure field-based estimates employing estimators appropriate under simple random sampling (SRS). However, comparison of uncertainty estimates under SRS and sophisticated two-stage designs is complicated by large differences in the designs and assumptions. In this study, probability-based principles to estimation and inference were followed. We assumed designs of a field sample and a LiDAR-assisted survey of Hedmark County (HC) (27,390 km2), Norway, considered to be more comparable than those assumed in previous studies. The field sample consisted of 659 systematically distributed National Forest Inventory (NFI) plots and the airborne scanning LiDAR data were collected along 53 parallel flight-lines flown over the NFI plots. We compared AGB estimates based on the field survey only assuming SRS against corresponding estimates assuming two-phase (double) sampling with LiDAR and employing model-assisted estimators. We also compared AGB estimates based on the field survey only assuming two-stage sampling (the NFI plots being grouped in clusters) against corresponding estimates assuming two-stage sampling with the LiDAR and employing model-assisted estimators. For each of the two comparisons, the standard errors of the AGB estimates were consistently lower for the LiDAR-assisted designs. The overall reduction of the standard errors in the LiDAR-assisted estimation was around 40-60% compared to the pure field survey. We conclude that the previously proposed two-stage model-assisted estimators are inappropriate for surveys with unequal lengths of the LiDAR flight-lines and new estimators are needed. Some options for design of LiDAR-assisted sample surveys under REDD are also discussed, which capitalize on the flexibility offered when the field survey is designed as an integrated part of the overall survey design as opposed to previous LiDAR-assisted sample surveys in the boreal and temperate zones which have been restricted by the current design of an existing NFI.

Assessing Forest NPP: BIOME-BGC Predictions versus BEF Derived Estimates

NASA Astrophysics Data System (ADS)

Hasenauer, H.; Pietsch, S. A.; Petritsch, R.

2007-05-01

Forest productivity has always been a major issue within sustainable forest management. While in the past terrestrial forest inventory data have been the major source for assessing forest productivity, recent developments in ecosystem modeling offer an alternative approach using ecosystem models such as Biome-BGC to estimate Net Primary Production (NPP). In this study we compare two terrestrial driven approaches for assessing NPP: (i) estimates from a species specific adaptation of the biogeochemical ecosystem model BIOME-BGC calibrated for Alpine conditions; and (ii) NPP estimates derived from inventory data using biomass expansion factors (BEF). The forest inventory data come from 624 sample plots across Austria and consist of repeated individual tree observations and include growth as well as soil and humus information. These locations are covered with spruce, beech, oak, pine and larch stands, thus addressing the main Austrian forest types. 144 locations were previously used in a validating effort to produce species-specific parameter estimates of the ecosystem model. The remaining 480 sites are from the Austrian National Forest Soil Survey carried out at the Federal Research and Training Centre for Forests, Natural Hazards and Landscape (BFW). By using diameter at breast height (dbh) and height (h) volume and subsequently biomass of individual trees were calculated, aggregated for the whole forest stand and compared with the model output. Regression analyses were performed for both volume and biomass estimates.

Inventory simulation tools: Separating nuclide contributions to radiological quantities

NASA Astrophysics Data System (ADS)

Gilbert, Mark R.; Fleming, Michael; Sublet, Jean-Christophe

2017-09-01

The activation response of a material is a primary factor considered when evaluating its suitability for a nuclear application. Various radiological quantities, such as total (becquerel) activity, decay heat, and γ dose, can be readily predicted via inventory simulations, which numerically evolve in time the composition of a material under exposure to neutron irradiation. However, the resulting data sets can be very complex, often necessarily resulting in an over-simplification of the results - most commonly by just considering total response metrics. A number of different techniques for disseminating more completely the vast amount of data output from, in particular, the FISPACT-II inventory code system, including importance diagrams, nuclide maps, and primary knock-on atom (PKA) spectra, have been developed and used in scoping studies to produce database reports for the periodic table of elements. This paper introduces the latest addition to this arsenal - standardised and automated plotting of the time evolution in a radiological quantity for a given material separated by contributions from dominant radionuclides. Examples for relevant materials under predicted fusion reactor conditions, and for bench-marking studies against decay-heat measurements, demonstrate the usefulness and power of these radionuclide-separated activation plots. Note to the reader: the pdf file has been changed on September 22, 2017.

Avoiding treatment bias of REDD+ monitoring by sampling with partial replacement.

PubMed

Köhl, Michael; Scott, Charles T; Lister, Andrew J; Demon, Inez; Plugge, Daniel

2015-12-01

Implementing REDD+ renders the development of a measurement, reporting and verification (MRV) system necessary to monitor carbon stock changes. MRV systems generally apply a combination of remote sensing techniques and in-situ field assessments. In-situ assessments can be based on 1) permanent plots, which are assessed on all successive occasions, 2) temporary plots, which are assessed only once, and 3) a combination of both. The current study focuses on in-situ assessments and addresses the effect of treatment bias, which is introduced by managing permanent sampling plots differently than the surrounding forests. Temporary plots are not subject to treatment bias, but are associated with large sampling errors and low cost-efficiency. Sampling with partial replacement (SPR) utilizes both permanent and temporary plots. We apply a scenario analysis with different intensities of deforestation and forest degradation to show that SPR combines cost-efficiency with the handling of treatment bias. Without treatment bias permanent plots generally provide lower sampling errors for change estimates than SPR and temporary plots, but do not provide reliable estimates, if treatment bias occurs, SPR allows for change estimates that are comparable to those provided by permanent plots, offers the flexibility to adjust sample sizes in the course of time, and allows to compare data on permanent versus temporary plots for detecting treatment bias. Equivalence of biomass or carbon stock estimates between permanent and temporary plots serves as an indication for the absence of treatment bias while differences suggest that there is evidence for treatment bias. SPR is a flexible tool for estimating emission factors from successive measurements. It does not entirely depend on sample plots that are installed at the first occasion but allows for the adjustment of sample sizes and placement of new plots at any occasion. This ensures that in-situ samples provide representative estimates over time. SPR offers the possibility to increase sampling intensity in areas with high degradation intensities or to establish new plots in areas where permanent plots are lost due to deforestation. SPR is also an ideal approach to mitigate concerns about treatment bias.

Comparison of carbon uptake estimates from forest inventory and Eddy-Covariance for a montane rainforest in central Sulawesi

NASA Astrophysics Data System (ADS)

Heimsch, Florian; Kreilein, Heiner; Rauf, Abdul; Knohl, Alexander

2016-04-01

Rainforests in general and montane rainforests in particular have rarely been studied over longer time periods. We aim to provide baseline information of a montane tropical forest's carbon uptake over time in order to quantify possible losses through land-use change. Thus we conducted a re-inventory of 22 10-year old forest inventory plots, giving us a rare opportunity to quantify carbon uptake over such a long time period by traditional methods. We discuss shortfalls of such techniques and why our estimate of 1.5 Mg/ha/a should be considered as the lower boundary and not the mean carbon uptake per year. At the same location as the inventory, CO2 fluxes were measured with the Eddy-Covariance technique. Measurements were conducted at 48m height with an LI 7500 open-path infrared gas analyser. We will compare carbon uptake estimates from these measurements to those of the more conventional inventory method and discuss, which factors are probably responsible for differences.

How long is enough to detect terrestrial animals? Estimating the minimum trapping effort on camera traps

PubMed Central

Si, Xingfeng; Kays, Roland

2014-01-01

Camera traps is an important wildlife inventory tool for estimating species diversity at a site. Knowing what minimum trapping effort is needed to detect target species is also important to designing efficient studies, considering both the number of camera locations, and survey length. Here, we take advantage of a two-year camera trapping dataset from a small (24-ha) study plot in Gutianshan National Nature Reserve, eastern China to estimate the minimum trapping effort actually needed to sample the wildlife community. We also evaluated the relative value of adding new camera sites or running cameras for a longer period at one site. The full dataset includes 1727 independent photographs captured during 13,824 camera days, documenting 10 resident terrestrial species of birds and mammals. Our rarefaction analysis shows that a minimum of 931 camera days would be needed to detect the resident species sufficiently in the plot, and c. 8700 camera days to detect all 10 resident species. In terms of detecting a diversity of species, the optimal sampling period for one camera site was c. 40, or long enough to record about 20 independent photographs. Our analysis of evaluating the increasing number of additional camera sites shows that rotating cameras to new sites would be more efficient for measuring species richness than leaving cameras at fewer sites for a longer period. PMID:24868493

Analyzing the carbon dynamics in north western Portugal: calibration and application of Forest-BGC

NASA Astrophysics Data System (ADS)

Rodrigues, M. A.; Lopes, D. M.; Leite, S. M.; Tabuada, V. M.

2010-04-01

Net primary production (NPP) is an important variable that allows monitoring forestry ecosystems fixation of atmospheric Carbon. The importance of monitoring the sequestred carbon is related to the binding commitments established by the Kyoto Protocol. There are ecophysiologic models, as Forest-BGC that allow for estimating NPP. In a first stage, this study aims to analyze the climate evolution at the Vila Real administrative district during the last decades. The historical information will be observed in order to detect the past tendencies of evolution. Past will help us to predict future. In a next stage these tendencies will be used to infer the impact of these change scenarios on the net primary production of the forest ecosystems from this study area. For a parameterization and validation of the FOREST-BGC, this study was carried on based on 500 m2 sampling plots from the National Forest Inventory 2006 and are located in several County Halls of the district of Vila Real (Montalegre, Chaves, Valpaços, Boticas, Vila Pouca de Aguiar, Murça, Mondim de Basto, Alijó, Sabrosa and Vila Real). In order to quantify Biomass dinamics, we have selected 45 sampling plots: 19 from Pinus pinaster stands, 17 from Quercus pyrenaica and 10 from mixed of Quercus pyrenaica with Pinus pinaster. Adaptation strategies for climate change impacts can be proposed based on these research results.

Using variance components to estimate power in a hierarchically nested sampling design improving monitoring of larval Devils Hole pupfish

USGS Publications Warehouse

Dzul, Maria C.; Dixon, Philip M.; Quist, Michael C.; Dinsomore, Stephen J.; Bower, Michael R.; Wilson, Kevin P.; Gaines, D. Bailey

2013-01-01

We used variance components to assess allocation of sampling effort in a hierarchically nested sampling design for ongoing monitoring of early life history stages of the federally endangered Devils Hole pupfish (DHP) (Cyprinodon diabolis). Sampling design for larval DHP included surveys (5 days each spring 2007–2009), events, and plots. Each survey was comprised of three counting events, where DHP larvae on nine plots were counted plot by plot. Statistical analysis of larval abundance included three components: (1) evaluation of power from various sample size combinations, (2) comparison of power in fixed and random plot designs, and (3) assessment of yearly differences in the power of the survey. Results indicated that increasing the sample size at the lowest level of sampling represented the most realistic option to increase the survey's power, fixed plot designs had greater power than random plot designs, and the power of the larval survey varied by year. This study provides an example of how monitoring efforts may benefit from coupling variance components estimation with power analysis to assess sampling design.

Analysis And Assessment Of Forest Cover Change For The State Of Wisconsin

NASA Astrophysics Data System (ADS)

Perry, C. H.; Nelson, M. D.; Stueve, K.; Gormanson, D.

2010-12-01

The Forest Inventory and Analysis (FIA) program of the USDA Forest Service is charged with documenting the status and trends of forest resources of the United States. Since the 1930s, FIA has implemented an intensive field campaign that collects measurements on plots distributed across all ownerships, historically completing analyses which include estimates of forest area, volume, mortality, growth, removals, and timber products output in various ways, such as by ownership, region, or State. Originally a periodic inventory, FIA has been measuring plots on an annual basis since the passage of the Agriculture Research, Extension and Education Reform Act of 1998 (Farm Bill). The resulting change in sampling design and intensity presents challenges to establishing baseline and measuring changes in forest area and biomass. A project jointly sponsored by the Forest Service and the National Aeronautics and Space Agency (NASA) titled “Integrating Landscape-scale Forest Measurements with Remote Sensing and Ecosystem Models to Improve Carbon Management Decisions” seeks to improve estimates of landscape- and continental-scale carbon dynamics and causes of change for North American forest land, and to use this information to support land management decisions. Specifically, we are developing and applying methods to scale up intensive biomass and carbon measurements from the field campaign to larger land management areas while simultaneously estimating change in the above-ground forest carbon stocks; the State of Wisconsin is being used as the testbed for this large-scale integration remote sensing with field measurements. Once defined, the temporal and spatial patterns of forest resources by watershed for Lake Superior and Lake Michigan outputs are being integrated into water quality assessments for the Great Lakes.

[Effects of sampling plot number on tree species distribution prediction under climate change].

PubMed

Liang, Yu; He, Hong-Shi; Wu, Zhi-Wei; Li, Xiao-Na; Luo, Xu

2013-05-01

Based on the neutral landscapes under different degrees of landscape fragmentation, this paper studied the effects of sampling plot number on the prediction of tree species distribution at landscape scale under climate change. The tree species distribution was predicted by the coupled modeling approach which linked an ecosystem process model with a forest landscape model, and three contingent scenarios and one reference scenario of sampling plot numbers were assumed. The differences between the three scenarios and the reference scenario under different degrees of landscape fragmentation were tested. The results indicated that the effects of sampling plot number on the prediction of tree species distribution depended on the tree species life history attributes. For the generalist species, the prediction of their distribution at landscape scale needed more plots. Except for the extreme specialist, landscape fragmentation degree also affected the effects of sampling plot number on the prediction. With the increase of simulation period, the effects of sampling plot number on the prediction of tree species distribution at landscape scale could be changed. For generalist species, more plots are needed for the long-term simulation.

A multi-scale assessment of forest primary production across the eastern USA using Forest Inventory and Analysis (FIA) and MODIS data

NASA Astrophysics Data System (ADS)

Kwon, Youngsang

As evidence of global warming continues to increase, being able to predict the relationship between forest growth rate and climate factors will be vital to maintain the sustainability and productivity of forests. Comprehensive analyses of forest primary production across the eastern US were conducted using remotely sensed MODIS and field-based FIA datasets. This dissertation primarily explored spatial patterns of gross and net carbon uptake in the eastern USA, and addressed three objectives. 1) Examine the use of pixel- and plot-scale screening variables to validate MODIS GPP predictions with Forest Inventory and Analysis (FIA) NPP measures. 2) Assess the net primary production (NPP) from MODIS and FIA at increasing levels of spatial aggregation using a hexagonal tiling system. 3) Assess the carbon use efficiency (CUE) calculated using a direct ratio of MODIS NPP to MODIS GPP and a standardized ratio of FIA NPP to MODIS GPP. The first objective was analyzed using total of 54,969 MODIS pixels and co-located FIA plots to validate MODIS GPP estimates. Eight SVs were used to test six hypotheses about the conditions under which MODIS GPP would be most strongly validated. SVs were assessed in terms of the tradeoff between improved relations and reduced number of samples. MODIS seasonal variation and FIA tree density were the two most efficient SVs followed by basic quality checks for each data set. The sequential application of SVs provided an efficient dataset of 17,090 co-located MODIS pixels and FIA plots, that raised the Pearson's correlation coefficient from 0.01 for the complete dataset of 54,969 plots to 0.48 for this screened subset of 17,090 plots. The second objective was addressed by aggregating data over increasing spatial extents so as to not lose plot- and pixel-level information. These data were then analyzed to determine the optimal scale with which to represent the spatial pattern of NPP. The results suggested an optimal scale of 390 km2. At that scale MODIS and FIA were most strongly correlated while maximizing the number of observation. The maps conveyed both local-scale spatial structure from FIA and broad-scale climatic trends from MODIS. The third objective examined whether carbon use efficiency (CUE) was constant or variable in relation to forest types, and to geographic and climatic variables. The results indicated that while CUEs exhibited unclear patterns by forest types, CUEs are variable to other environmental variables. CUEs are most strongly related to the climatic factors of precipitation followed by temperature. More complex and weaker relationships were found for the geographic factors of latitude and altitude, as they reflected a combination of phenomenological driving forces. The results of the three objectives will help us to identify factors that control carbon cycles and to quantify forest productivity. This will help improve our knowledge about how forest primary productivity may change in relation to ongoing climate change.

The extent and characteristics of low-productivity aspen areas in Wisconsin.

Treesearch

Allen L. Lundgren; Jerold T. Hahn

1978-01-01

An analysis of inventory plots from Wisconsin's forest survey showed that 18% of the state's 3.7 million acres of aspen type was producing less than a quarter of potential volume yields and 47% was producing less than half of potential volume yields.

Field Testing New Plot Designs and Methods for Determining Hydrophytic Vegetation during Wetland Delineations in the United States

DTIC Science & Technology

2014-03-01

Trees and woody vines are sampled in large plots with 9 m (30 ft) radii. Saplings, shrubs , and herbs are sampled in nested smaller plots with 2 m (5 ft... woody vines in 9 m (30 ft) radius plots and saplings, shrubs , and herbaceous species in 2 m (5 ft) radius plots. In herbaceous meadows, only the 2 m (5...suggests stratifying vegetation by growth forms of trees, shrubs , herbs, and vines and sampling plant communities by using nested circular plots

Learning Style Scales: a valid and reliable questionnaire.

PubMed

Abdollahimohammad, Abdolghani; Ja'afar, Rogayah

2014-01-01

Learning-style instruments assist students in developing their own learning strategies and outcomes, in eliminating learning barriers, and in acknowledging peer diversity. Only a few psychometrically validated learning-style instruments are available. This study aimed to develop a valid and reliable learning-style instrument for nursing students. A cross-sectional survey study was conducted in two nursing schools in two countries. A purposive sample of 156 undergraduate nursing students participated in the study. Face and content validity was obtained from an expert panel. The LSS construct was established using principal axis factoring (PAF) with oblimin rotation, a scree plot test, and parallel analysis (PA). The reliability of LSS was tested using Cronbach's α, corrected item-total correlation, and test-retest. Factor analysis revealed five components, confirmed by PA and a relatively clear curve on the scree plot. Component strength and interpretability were also confirmed. The factors were labeled as perceptive, solitary, analytic, competitive, and imaginative learning styles. Cronbach's α was >0.70 for all subscales in both study populations. The corrected item-total correlations were >0.30 for the items in each component. The LSS is a valid and reliable inventory for evaluating learning style preferences in nursing students in various multicultural environments.

Defoliation potential of gypsy moth

Treesearch

David A. Gansner; David A. Drake; Stanford L. Arner; Rachel R. Hershey; Susan L. King; Susan L. King

1993-01-01

A model that uses forest stand characteristics to estimate the likelihood of gypsy moth (Lymantria dispar L.) defoliation has been developed. It was applied to recent forest inventory plot data to produce susceptibility ratings and maps showing current defoliation potential in a seven-state area where gypsy moth is an immediate threat.

Predicting the Probability of Stand Disturbance

Treesearch

Gregory A. Reams; Joseph M. McCollum

1999-01-01

Forest managers are often interested in identifying and scheduling future stand treatment opportunities. One of the greatest management opportunities is presented following major stand level disturbances that result from natural or anthropogenic forces. Remeasurement data from the Forest Inventory and Analysis (FIA) permanent plot system are used to fit a set of...

Mapping the defoliation potential of gypsy moth

Treesearch

David A. Gansner; Stanford L. Arner; Rachel Riemann Hershey; Susan L. King

1993-01-01

A model that uses forest stand characteristics to estimate the likelihood of gypsy moth (Lymantria dispar) defoliation has been developed. It was applied to recent forest inventory plot data to produce susceptibility ratings and a map showing defoliation potential for counties in Pennsylvania and six adjacent states on new frontiers of infestation.

Forest land area estimates from vegetation continuous fields

Treesearch

Mark D. Nelson; Ronald E. McRoberts; Matthew C. Hansen

2004-01-01

The USDA Forest Service's Forest Inventory and Analysis (FIA) program provides data, information, and knowledge about our Nation's forest resources. FIA regional units collect data from field plots and remotely sensed imagery to produce statistical estimates of forest extent (area); volume, growth, and removals; and health and condition. There is increasing...

Current and emerging operational uses of remote sensing in Swedish forestry

Treesearch

Hakan Olsson; Mikael Egberth; Jonas Engberg; Johan E.S. Fransson; Tina Granqvist Pahlen; < i> et al< /i>

2007-01-01

Satellite remote sensing is being used operationally by Swedish authorities in applications involving, for example, change detection of clear felled areas, use of k-Nearest Neighbour estimates of forest parameters, and post-stratification (in combination with National Forest Inventory plots). For forest management planning of estates, aerial...

Sampling Error in Relation to Cyst Nematode Population Density Estimation in Small Field Plots.

PubMed

Župunski, Vesna; Jevtić, Radivoje; Jokić, Vesna Spasić; Župunski, Ljubica; Lalošević, Mirjana; Ćirić, Mihajlo; Ćurčić, Živko

2017-06-01

Cyst nematodes are serious plant-parasitic pests which could cause severe yield losses and extensive damage. Since there is still very little information about error of population density estimation in small field plots, this study contributes to the broad issue of population density assessment. It was shown that there was no significant difference between cyst counts of five or seven bulk samples taken per each 1-m 2 plot, if average cyst count per examined plot exceeds 75 cysts per 100 g of soil. Goodness of fit of data to probability distribution tested with χ 2 test confirmed a negative binomial distribution of cyst counts for 21 out of 23 plots. The recommended measure of sampling precision of 17% expressed through coefficient of variation ( cv ) was achieved if the plots of 1 m 2 contaminated with more than 90 cysts per 100 g of soil were sampled with 10-core bulk samples taken in five repetitions. If plots were contaminated with less than 75 cysts per 100 g of soil, 10-core bulk samples taken in seven repetitions gave cv higher than 23%. This study indicates that more attention should be paid on estimation of sampling error in experimental field plots to ensure more reliable estimation of population density of cyst nematodes.

Cross-continental comparison of the functional composition and carbon allocation of two altitudinal forest transects in Ecuador and Rwanda.

NASA Astrophysics Data System (ADS)

Verbeeck, Hans; Bauters, Marijn; Bruneel, Stijn; Demol, Miro; Taveirne, Cys; Van Der Heyden, Dries; Kearsley, Elizabeth; Cizungu, Landry; Boeckx, Pascal

2017-04-01

Tropical forests are key actors in the global carbon cycle. Predicting future responses of these forests to global change is challenging, but important for global climate models. However, our current understanding of such responses is limited, due to the complexity of forest ecosystems and the slow dynamics that inherently form these systems. Our understanding of ecosystem ecology and functioning could greatly benefit from experimental setups including strong environmental gradients in the tropics, as found on altitudinal transects. We setup two such transects in both South-America and Central Africa, focussing on shifts in carbon allocation, forest structure, nutrient cycling and functional composition. The Ecuadorian transect has 16 plots (40 by 40 m) and ranges from 400 to 3000 m.a.s.l., and the Rwandan transect has 20 plots (40 by 40 m) from 1500 to 3000 m.a.s.l. All plots were inventoried and canopy, litter and soil were extensively sampled. By a cross-continental comparison of both transects, we will gain insight in how different or alike both tropical forests biomes are in their responses, and how universal the observed altitudinal adaption mechanisms are. This could provide us with vital information of the ecological responses of both biomes to future global change scenarios. Additionally, comparison of nutrient shifts and trait-based functional composition allows us to compare the biogeochemical cycles of African and South-American tropical forests.

Field strategies for the calibration and validation of high-resolution forest carbon maps: Scaling from plots to a three state region MD, DE, & PA, USA.

NASA Astrophysics Data System (ADS)

Dolan, K. A.; Huang, W.; Johnson, K. D.; Birdsey, R.; Finley, A. O.; Dubayah, R.; Hurtt, G. C.

2016-12-01

In 2010 Congress directed NASA to initiate research towards the development of Carbon Monitoring Systems (CMS). In response, our team has worked to develop a robust, replicable framework to quantify and map aboveground forest biomass at high spatial resolutions. Crucial to this framework has been the collection of field-based estimates of aboveground tree biomass, combined with remotely detected canopy and structural attributes, for calibration and validation. Here we evaluate the field- based calibration and validation strategies within this carbon monitoring framework and discuss the implications on local to national monitoring systems. Through project development, the domain of this research has expanded from two counties in MD (2,181 km2), to the entire state of MD (32,133 km2), and most recently the tri-state region of MD, PA, and DE (157,868 km2) and covers forests in four major USDA ecological providences. While there are approximately 1000 Forest Inventory and Analysis (FIA) plots distributed across the state of MD, 60% fell in areas considered non-forest or had conditions that precluded them from being measured in the last forest inventory. Across the two pilot counties, where population and landuse competition is high, that proportion rose to 70% Thus, during the initial phases of this project 850 independent field plots were established for model calibration following a random stratified design to insure the adequate representation of height and vegetation classes found across the state, while FIA data were used as an independent data source for validation. As the project expanded to cover the larger spatial tri-state domain, the strategy was flipped to base calibration on more than 3,300 measured FIA plots, as they provide a standardized, consistent and available data source across the nation. An additional 350 stratified random plots were deployed in the Northern Mixed forests of PA and the Coastal Plains forests of DE for validation.

Image matching as a data source for forest inventory - Comparison of Semi-Global Matching and Next-Generation Automatic Terrain Extraction algorithms in a typical managed boreal forest environment

NASA Astrophysics Data System (ADS)

Kukkonen, M.; Maltamo, M.; Packalen, P.

2017-08-01

Image matching is emerging as a compelling alternative to airborne laser scanning (ALS) as a data source for forest inventory and management. There is currently an open discussion in the forest inventory community about whether, and to what extent, the new method can be applied to practical inventory campaigns. This paper aims to contribute to this discussion by comparing two different image matching algorithms (Semi-Global Matching [SGM] and Next-Generation Automatic Terrain Extraction [NGATE]) and ALS in a typical managed boreal forest environment in southern Finland. Spectral features from unrectified aerial images were included in the modeling and the potential of image matching in areas without a high resolution digital terrain model (DTM) was also explored. Plot level predictions for total volume, stem number, basal area, height of basal area median tree and diameter of basal area median tree were modeled using an area-based approach. Plot level dominant tree species were predicted using a random forest algorithm, also using an area-based approach. The statistical difference between the error rates from different datasets was evaluated using a bootstrap method. Results showed that ALS outperformed image matching with every forest attribute, even when a high resolution DTM was used for height normalization and spectral information from images was included. Dominant tree species classification with image matching achieved accuracy levels similar to ALS regardless of the resolution of the DTM when spectral metrics were used. Neither of the image matching algorithms consistently outperformed the other, but there were noticeably different error rates depending on the parameter configuration, spectral band, resolution of DTM, or response variable. This study showed that image matching provides reasonable point cloud data for forest inventory purposes, especially when a high resolution DTM is available and information from the understory is redundant.

Lidar-Based Estimates of Above-Ground Biomass in the Continental US and Mexico Using Ground, Airborne, and Satellite Observations

NASA Technical Reports Server (NTRS)

Nelson, Ross; Margolis, Hank; Montesano, Paul; Sun, Guoqing; Cook, Bruce; Corp, Larry; Andersen, Hans-Erik; DeJong, Ben; Pellat, Fernando Paz; Fickel, Thaddeus;

Mortality trends and traits of hardwood advance regeneration following seasonal prescribed fires

Treesearch

Patrick Brose; David Van Lear

2003-01-01

Fire ecology studies in eastern hardwood forests generally use traditional, plot-based inventory methods and focus on sprouting stems to detect changes in vegetative composition and structure. Fire intensity often is not quantified or even subjectively classified and, if quantified, is not used in subsequent analysis. Consequently, reported responses of hardwood...

An assessment of multiflora rose in northern U.S. forests

Treesearch

Cassandra M. Kurtz; Mark H. Hansen

2013-01-01

This publication provides an overview of multiflora rose (Rosa multiflora) on forest land across the 24 states of the midwestern and northeastern United States based on an extensive systematic network of plots measured by the Forest Inventory and Analysis (FIA) program of the U.S. Forest Service, Northern Research Station (NRS).

An Analysis of Losses to the Southern Commercial Timberland Base

Treesearch

Ian A. Munn; David Cleaves

1998-01-01

Demographic and physical factors influencing the conversion of commercial timberland iu the south to non-forestry uses between the last two Forest Inventory Analysis (FIA) surveys were investigated. GIS techniques linked Census data and FIA plot level data. Multinomial logit regression identified factors associated with losses to the timberland base. Conversion to...

Estimates of the occurrence of dwarf mistletoe on the Deschutes National Forest.

Treesearch

Donald J. DeMars

1980-01-01

The proportion of forest area infested and of trees infected were calculated for the Deschutes National Forest by using 10-point plot inventory data. The proportion of commercial forest acres infested with dwarf mistletoe is 0.476, and the proportion of trees infected on these acres is 0.308.

Estimating white trunk rot in aspen stands

Treesearch

Alan C. Jones; Michael E. Ostry

1998-01-01

Advanced decay caused by Phellinus tremulae was estimated in 295 trembling aspen on 30 plots in 2 Minnesota counties using existing inventory guides, and then measured by felling and sectioning the trees. In standing trees, decay volume was underestimated by 38% compared to measured decay volume in felled trees. The most reliable external indicator...

Mapping and imputing potential productivity of Pacific Northwest forests using climate variables

Treesearch

Gregory Latta; Hailemariam Temesgen; Tara Barrett

2009-01-01

Regional estimation of potential forest productivity is important to diverse applications, including biofuels supply, carbon sequestration, and projections of forest growth. Using PRISM (Parameter-elevation Regressions on Independent Slopes Model) climate and productivity data measured on a grid of 3356 Forest Inventory and Analysis plots in Oregon and Washington, we...

K-Nearest Neighbor Estimation of Forest Attributes: Improving Mapping Efficiency

Treesearch

Andrew O. Finley; Alan R. Ek; Yun Bai; Marvin E. Bauer

2005-01-01

This paper describes our efforts in refining k-nearest neighbor forest attributes classification using U.S. Department of Agriculture Forest Service Forest Inventory and Analysis plot data and Landsat 7 Enhanced Thematic Mapper Plus imagery. The analysis focuses on FIA-defined forest type classification across St. Louis County in northeastern Minnesota. We outline...

Opportunities to improve monitoring of temporal trends with FIA panel data

Treesearch

Raymond Czaplewski; Michael Thompson

2009-01-01

The Forest Inventory and Analysis (FIA) Program of the Forest Service, Department of Agriculture, is an annual monitoring system for the entire United States. Each year, an independent "panel" of FIA field plots is measured. To improve accuracy, FIA uses the "Moving Average" or "Temporally Indifferent" method to combine estimates from...

Estimating dead wood during national forest inventories: a review of inventory methodologies and suggestions for harmonization.

PubMed

Woodall, Christopher W; Rondeux, Jacques; Verkerk, Pieter J; Ståhl, Göran

2009-10-01

Efforts to assess forest ecosystem carbon stocks, biodiversity, and fire hazards have spurred the need for comprehensive assessments of forest ecosystem dead wood (DW) components around the world. Currently, information regarding the prevalence, status, and methods of DW inventories occurring in the world's forested landscapes is scattered. The goal of this study is to describe the status, DW components measured, sample methods employed, and DW component thresholds used by national forest inventories that currently inventory DW around the world. Study results indicate that most countries do not inventory forest DW. Globally, we estimate that about 13% of countries inventory DW using a diversity of sample methods and DW component definitions. A common feature among DW inventories was that most countries had only just begun DW inventories and employ very low sample intensities. There are major hurdles to harmonizing national forest inventories of DW: differences in population definitions, lack of clarity on sample protocols/estimation procedures, and sparse availability of inventory data/reports. Increasing database/estimation flexibility, developing common dimensional thresholds of DW components, publishing inventory procedures/protocols, releasing inventory data/reports to international peer review, and increasing communication (e.g., workshops) among countries inventorying DW are suggestions forwarded by this study to increase DW inventory harmonization.

Integrated Sampling Strategy (ISS) Guide

Treesearch

Robert E. Keane; Duncan C. Lutes

2006-01-01

What is an Integrated Sampling Strategy? Simply put, it is the strategy that guides how plots are put on the landscape. FIREMON’s Integrated Sampling Strategy assists fire managers as they design their fire monitoring project by answering questions such as: What statistical approach is appropriate for my sample design? How many plots can I afford? How many plots do I...

QUANTIFYING FOREST ABOVEGROUND CARBON POOLS AND FLUXES USING MULTI-TEMPORAL LIDAR A report on field monitoring, remote sensing MMV, GIS integration, and modeling results for forestry field validation test to quantify aboveground tree biomass and carbon

DOE Office of Scientific and Technical Information (OSTI.GOV)

Lee Spangler; Lee A. Vierling; Eva K. Stand

2012-04-01

Sound policy recommendations relating to the role of forest management in mitigating atmospheric carbon dioxide (CO{sub 2}) depend upon establishing accurate methodologies for quantifying forest carbon pools for large tracts of land that can be dynamically updated over time. Light Detection and Ranging (LiDAR) remote sensing is a promising technology for achieving accurate estimates of aboveground biomass and thereby carbon pools; however, not much is known about the accuracy of estimating biomass change and carbon flux from repeat LiDAR acquisitions containing different data sampling characteristics. In this study, discrete return airborne LiDAR data was collected in 2003 and 2009 acrossmore » {approx}20,000 hectares (ha) of an actively managed, mixed conifer forest landscape in northern Idaho, USA. Forest inventory plots, established via a random stratified sampling design, were established and sampled in 2003 and 2009. The Random Forest machine learning algorithm was used to establish statistical relationships between inventory data and forest structural metrics derived from the LiDAR acquisitions. Aboveground biomass maps were created for the study area based on statistical relationships developed at the plot level. Over this 6-year period, we found that the mean increase in biomass due to forest growth across the non-harvested portions of the study area was 4.8 metric ton/hectare (Mg/ha). In these non-harvested areas, we found a significant difference in biomass increase among forest successional stages, with a higher biomass increase in mature and old forest compared to stand initiation and young forest. Approximately 20% of the landscape had been disturbed by harvest activities during the six-year time period, representing a biomass loss of >70 Mg/ha in these areas. During the study period, these harvest activities outweighed growth at the landscape scale, resulting in an overall loss in aboveground carbon at this site. The 30-fold increase in sampling density between the 2003 and 2009 did not affect the biomass estimates. Overall, LiDAR data coupled with field reference data offer a powerful method for calculating pools and changes in aboveground carbon in forested systems. The results of our study suggest that multitemporal LiDAR-based approaches are likely to be useful for high quality estimates of aboveground carbon change in conifer forest systems.« less

Effects of nutrient loading on the carbon balance of coastal wetland sediments

USGS Publications Warehouse

Morris, J.T.; Bradley, P.M.

1999-01-01

Results of a 12-yr study in an oligotrophic South Carolina salt marsh demonstrate that soil respiration increased by 795 g C m-2 yr-1 and that carbon inventories decreased in sediments fertilized with nitrogen and phosphorus. Fertilized plots became net sources of carbon to the atmosphere, and sediment respiration continues in these plots at an accelerated pace. After 12 yr of treatment, soil macroorganic matter in the top 5 cm of sediment was 475 g C m-2 lower in fertilized plots than in controls, which is equivalent to a constant loss rate of 40 g C m-2 yr-1. It is not known whether soil carbon in fertilized plots has reached a new equilibrium or continues to decline. The increase in soil respiration in the fertilized plots was far greater than the loss of sediment organic matter, which indicates that the increase in soil respiration was largely due to an increase in primary production. Sediment respiration in laboratory incubations also demonstrated positive effects of nutrients. Thus, the results indicate that increased nutrient loading of oligotrophic wetlands can lead to an increased rate of sediment carbon turnover and a net loss of carbon from sediments.

Double sampling for stratification: a forest inventory application in the Interior West

Treesearch

David C. Chojnacky

1998-01-01

This paper documents the use of double sampling for Forest Inventory and Analysis (Forest Service, U.S. Department of Agriculture) inventories in the Interior West. Results show 18 equations describe the entire inventory summarization process for estimating population totals and means, and respective variances. Most equations are for standard use of double sampling,...

43 CFR Appendix B to Part 10 - Sample Notice of Inventory Completion

Code of Federal Regulations, 2010 CFR

2010-10-01

... 43 Public Lands: Interior 1 2010-10-01 2010-10-01 false Sample Notice of Inventory Completion B... PROTECTION AND REPATRIATION REGULATIONS Pt. 10, App. B Appendix B to Part 10—Sample Notice of Inventory Completion The following is an example of a Notice of Inventory Completion published in the Federal Register...

The extent and characteristics of low productivity aspen areas in Minnesota.

Treesearch

Gerhard K. Raile; Jerold T. Hahn

1982-01-01

Plot data from 1977 Minnesota forest inventory were used to evaluate the productivity of Minnesota's aspen forest. Computer simulation was used to develop equations for evaluating the current and potential productivity of aspen forest stands. The analysis showed that 49% of the state's aspen forest type was producing less than half of potential volume yields...

Needs and Opportunities for Longleaf Pine Ecosystem Restoration in Florida

Treesearch

Kenneth W. Outcalt

1997-01-01

Data from permanent plots measured periodically by Forest Inventory and Analyses of the Southern Research Station, USDA Forest Service shows a continuing decline in the longleaf pine (Pinus pulustris Mill,) ecosystem in Florida from 1987 to 1995. Conversion to some other forest type resulted in a net loss of 58,000 ha natural stands of longleaf pine...

A comparison of several techniques for imputing tree level data

Treesearch

David Gartner

2002-01-01

As Forest Inventory and Analysis (FIA) changes from periodic surveys to the multipanel annual survey, new analytical methods become available. The current official statistic is the moving average. One alternative is an updated moving average. Several methods of updating plot per acre volume have been discussed previously. However, these methods may not be appropriate...

A framework for evaluating forest landscape model predictions using empirical data and knowledge

Treesearch

Wen J. Wang; Hong S. He; Martin A. Spetich; Stephen R. Shifley; Frank R. Thompson; William D. Dijak; Qia Wang

2014-01-01

Evaluation of forest landscape model (FLM) predictions is indispensable to establish the credibility of predictions. We present a framework that evaluates short- and long-term FLM predictions at site and landscape scales. Site-scale evaluation is conducted through comparing raster cell-level predictions with inventory plot data whereas landscape-scale evaluation is...

Michigan's forests 2004

Treesearch

Scott A. Pugh; Mark H. Hansen; Lawrence D. Pedersen; Douglas C. Heym; Brett J. Butler; Susan J. Crocker; Dacia Meneguzzo; Charles H. Perry; David E. Haugen; Christopher Woodall; Ed Jepsen

2009-01-01

The first annual inventory of Michigan's forests, completed in 2004, covers more than 19.3 million acres of forest land. The data in this report are based on visits to 10,355 forested plots from 2000 to 2004. In addition to detailed information on forest attributes, this report includes data on forest health, biomass, land-use change, and timber-product outputs....

Extrapolating intensified forest inventory data to the surrounding landscape using landsat

Treesearch

Evan B. Brooks; John W. Coulston; Valerie A. Thomas; Randolph H. Wynne

2015-01-01

In 2011, a collection of spatially intensified plots was established on three of the Experimental Forests and Ranges (EFRs) sites with the intent of facilitating FIA program objectives for regional extrapolation. Characteristic coefficients from harmonic regression (HR) analysis of associated Landsat stacks are used as inputs into a conditional random forests model to...

Maine's forests 2008

Treesearch

George L. McCaskill; William H. McWilliams; Charles J. Barnett; Brett J. Butler; Mark A. Hatfield; Cassandra M. Kurtz; Randall S. Morin; W. Keith Moser; Charles H. Perry; Christopher W. Woodall

2011-01-01

The second annual inventory of Maine's forests was completed in 2008 after more than 3,160 forested plots were measured. Forest land occupies almost 17.7 million acres, which represents 82 percent of the total land area of Maine. The dominant forest-type groups are maple/beech/yellow birch, spruce/fir, white/red/jack pine, and aspen/white birch. Statewide volume...

Michigan forests 2014

Treesearch

Scott A. Pugh; Douglas C. Heym; Brett J. Butler; David E. Haugen; Cassandra M. Kurtz; William H. McWilliams; Patrick D. Miles; Randall S. Morin; Mark D. Nelson; Rachel I. Riemann; James E. Smith; James A. Westfall; Christopher W. Woodall

2017-01-01

The eighth inventory of Michigan's forests, completed in 2014, describes more than 20.3 million acres of forest land. The data in this report are based on visits to 4,289 forested plots from 2009 to 2014. Timberland accounts for 95 percent of this forest land, and 62 percent is privately owned. The sugar maple/beech/yellow birch forest type accounts for 19 percent...

Michigan's Forests 2009

Treesearch

Scott A. Pugh; Lawrence D. Pedersen; Douglas C. Heym; Ronald J. Piva; Christopher W. Woodall; Charles J. Barnett; Cassandra M. Kurtz; W. Keith Moser

2012-01-01

The seventh inventory of Michigan's forests, completed in 2009, describes more than 19.9 million acres of forest land. The data in this report are based on visits to 7,516 forested plots from 2005 to 2009. Timberland accounts for 97 percent of this forest land, and 62 percent is privately owned. The sugar maple/beech/yellow birch forest type accounts for 18...

Federated States of Micronesia's forest resources, 2006

Treesearch

Joseph A. Donnegan; Sarah L. Butler; Olaf Kuegler; Bruce A. Hiserote

2011-01-01

The Forest Inventory and Analysis program collected, analyzed, and summarized field data on 73 forested field plots on the islands of Kosrae, Chuuk, Pohnpei, and Yap in the Federated States of Micronesia (FSM). Estimates of forest area, tree stem volume and biomass, the numbers of trees, tree damages, and the distribution of tree sizes were summarized for this...

Comparing Forest/Nonforest Classifications of Landsat TM Imagery for Stratifying FIA Estimates of Forest Land Area

Treesearch

Mark D. Nelson; Ronald E. McRoberts; Greg C. Liknes; Geoffrey R. Holden

2005-01-01

Landsat Thematic Mapper (TM) satellite imagery and Forest Inventory and Analysis (FIA) plot data were used to construct forest/nonforest maps of Mapping Zone 41, National Land Cover Dataset 2000 (NLCD 2000). Stratification approaches resulting from Maximum Likelihood, Fuzzy Convolution, Logistic Regression, and k-Nearest Neighbors classification/prediction methods were...

Landsat TM Classifications For SAFIS Using FIA Field Plots

Treesearch

William H. Cooke; Andrew J. Hartsell

2001-01-01

Wall-to-wall Landsat Thematic Mapper (TM) classification efforts in Georgia require field validation. We developed a new crown modeling procedure based on Forest Health Monitoring (FHM) data to test Forest Inventory and Analysis (FIA) data. These models simulate the proportion of tree crowns that reflect light on a FIA subplot basis. We averaged subplot crown...

A discrete global grid of photointerpretation

Treesearch

Joseph M McCollum; Jamie K. Cochran; Anita K. Rose

2008-01-01

The Forest Inventory and Analysis (FIA) Program of the Forest Service, U.S.Department of Agriculture, collects its data in three phases. The first phase is collection of photointerpretation data or dot counts, the second phase is field collection of FIA plot data, and the third phase is collection of Forest Health Monitoring data. This paper describes the development...

On FIA Variables For Ecological Use

Treesearch

David C. Chojnacky

2001-01-01

The Forest Inventory and Analysis (FIA) program collects or calculates over 300 variables for its national network of permanent forest plots. However, considerable ecological analysis can be done with only a few key variables. Two examples--Mexican spotted owl habitat in New Mexico and down deadwood in Maine--are used to illustrate the potential of FIA data for...

Fire effects assessment using FIA data in the northern and central Rocky Mountains

Treesearch

Theresa B. Jain; Ralph Their; Wilson Michael

2003-01-01

Wildfires of 2000 and 2001 burned thousands of hectares in the Northern Rocky Mountains. Within the fire parameters, 162 Forest Inventory and Analysis (FIA) plots burned in Idaho and Montana where pre-wildfire information on forest structure, vegetation composition, soil productivity, and surface fuels was documented; thus providing a unique opportunity to assess...

Preliminary results of spatial modeling of selected forest health variables in Georgia

Treesearch

Brock Stewart; Chris J. Cieszewski

2009-01-01

Variables relating to forest health monitoring, such as mortality, are difficult to predict and model. We present here the results of fitting various spatial regression models to these variables. We interpolate plot-level values compiled from the Forest Inventory and Analysis National Information Management System (FIA-NIMS) data that are related to forest health....

Wisconsin's forests, 2004

Treesearch

Charles H. (Hobie) Perry; Vern A. Everson; Ian K. Brown; Jane Cummings-Carlson; Sally E. Dahir; Edward A. Jepsen; Joe Kovach; Michael D. Labissoniere; Terry R. Mace; Eunice A. Padley; Richard B. Rideout; Brett J. Butler; Susan J. Crocker; Greg C. Liknes; Randall S. Morin; Mark D. Nelson; Barry T. (Ty) Wilson; Christopher W. Woodall

2008-01-01

The first full, annualized inventory of Wisconsin's forests was completed in 2004 after 6,478 forested plots were visited. There are more than 16.0 million acres of forest land in the Wisconsin, nearly half of the State's land area; 15.8 million acres meet the definition of timberland. The total area of both forest land and timberland continues an upward...

The role of remote sensing in process‐scaling studies of managed forest ecosystems

Treesearch

Jeffrey G. Masek; Daniel J. Hayes; M. Joseph Hughes; Sean P. Healey; David P. Turner

2015-01-01

Sustaining forest resources requires a better understanding of forest ecosystem processes, and how management decisions and climate change may affect these processes in the future. While plot and inventory data provide our most detailed information on forest carbon, energy, and water cycling, applying this understanding to broader spatial and temporal domains...

Commonwealth of the Northern Mariana Islands' forest resources, 2004

Treesearch

Joseph A. Donnegan; Sarah L. Butler; Olaf Kuegler; Bruce A. Hiserote

2011-01-01

The Forest Inventory and Analysis program collected, analyzed, and summarized field data on 37 field plots on the islands of Rota, Tinian, and Saipan in the Commonwealth of the Northern Mariana Islands (CNMI). Estimates of forest area, tree stem volume and biomass, the numbers of trees, tree damages, and the distribution of tree sizes were summarized for this...

Evaluating a model to predict timber harvesting in Austria

Treesearch

Hubert Sterba; Michael Golser; Klemens Schadauer

2000-01-01

Between 1981 and 1985, the Austrian National Forest Inventory (ANF) established a set of 5,500 clusters, each with four permanent plots, covering all Austrian forests. After the first remeasurement between 1986 and 1990, models were developed to predict tree growth, mortality, and the behavior of forest owners in harvesting timber. A set of logistic equations describes...

The effects of forest fragmentation on forest stand attributes

Treesearch

Ronald E. McRoberts; Greg C. Liknes

2002-01-01

For two study areas in Minnesota, USA, one heavily forested and one sparsely forested, maps of predicted proportion forest area were created using Landsat Thematic Mapper imagery, forest inventory plot data, and a logistic regression model. The maps were used to estimate quantitative indices of forest fragmentation. Correlations between the values of the indices and...

Image-based change estimation for land cover and land use monitoring

Treesearch

Jeremy Webb; C. Kenneth Brewer; Nicholas Daniels; Chris Maderia; Randy Hamilton; Mark Finco; Kevin A. Megown; Andrew J. Lister

2012-01-01

The Image-based Change Estimation (ICE) project resulted from the need to provide estimates and information for land cover and land use change over large areas. The procedure uses Forest Inventory and Analysis (FIA) plot locations interpreted using two different dates of imagery from the National Agriculture Imagery Program (NAIP). In order to determine a suitable...

Plotview Software For Retrieving Plot-Level Imagery and GIS Data Over The Web

Treesearch

Ken Boss

2001-01-01

The Minnesota Department of Natural Resources Division of Forestry Resource Assessment office has been cooperating with both the Forest Service's FIA and Natural Resource Conservation Services's NRI inventory programs in researching methods to more tightly integrate the two programs. One aspect of these ongoing efforts has been to develop a prototype intranet...

Forest Resources of Isle Royale National Park 2010

Treesearch

Wilfred J. Previant; Linda M. Nagel; Scott A. Pugh; Christopher W. Woodall

2012-01-01

This publication provides a baseline overview of forest resources for Isle Royale National Park (Isle Royale) using data from the Forest Inventory and Analysis (FIA) Program of the U.S. Department of Agriculture, Forest Service. The availability of permanent FIA plots allows for the first-ever comparison of Isle Royale's forest conditions (2006-2010) to reserved...

Long-term changes in fusiform rust incidence in the southeastern United States

Treesearch

KaDonna C. Randolph; Ellis B. Cowling; Dale A. Starkey

2015-01-01

Fusiform rust is the most devastating disease of slash pine (Pinus elliottii) and loblolly pine (Pinus taeda) in the southeastern United States. Since the 1970s, the USDA Forest Service Forest Inventory and Analysis (FIA) Program has assessed fusiform rust incidence on its network of ground plots in 13 states across the...

Diameter Growth, Survival, and Volume Estimates for Missouri Trees

Treesearch

Stephen R. Shifley; W. Brad Smith

1982-01-01

Measurements of more than 20,000 Missouri trees were summarized by species and diameter class into tables of mean annual diameter growth, annual probability of survival, net cubic foot volume, and net board foot volume. In the absence of better forecasting techniques, this information can be utilized to project short-term changes for Missouri trees, inventory plots,...

Development and applications of the LANDFIRE forest structure layers

Treesearch

Chris Toney; Birgit Peterson; Don Long; Russ Parsons; Greg Cohn

2012-01-01

The LANDFIRE program is developing 2010 maps of vegetation and wildland fuel attributes for the United States at 30-meter resolution. Currently available vegetation layers include ca. 2001 and 2008 forest canopy cover and canopy height derived from Landsat and Forest Inventory and Analysis (FIA) plot measurements. The LANDFIRE canopy cover layer for the conterminous...

Monitoring forest areas from continental to territorial levels using a sample of medium spatial resolution satellite imagery

NASA Astrophysics Data System (ADS)

Eva, Hugh; Carboni, Silvia; Achard, Frédéric; Stach, Nicolas; Durieux, Laurent; Faure, Jean-François; Mollicone, Danilo

A global systematic sampling scheme has been developed by the UN FAO and the EC TREES project to estimate rates of deforestation at global or continental levels at intervals of 5 to 10 years. This global scheme can be intensified to produce results at the national level. In this paper, using surrogate observations, we compare the deforestation estimates derived from these two levels of sampling intensities (one, the global, for the Brazilian Amazon the other, national, for French Guiana) to estimates derived from the official inventories. We also report the precisions that are achieved due to sampling errors and, in the case of French Guiana, compare such precision with the official inventory precision. We extract nine sample data sets from the official wall-to-wall deforestation map derived from satellite interpretations produced for the Brazilian Amazon for the year 2002 to 2003. This global sampling scheme estimate gives 2.81 million ha of deforestation (mean from nine simulated replicates) with a standard error of 0.10 million ha. This compares with the full population estimate from the wall-to-wall interpretations of 2.73 million ha deforested, which is within one standard error of our sampling test estimate. The relative difference between the mean estimate from sampling approach and the full population estimate is 3.1%, and the standard error represents 4.0% of the full population estimate. This global sampling is then intensified to a territorial level with a case study over French Guiana to estimate deforestation between the years 1990 and 2006. For the historical reference period, 1990, Landsat-5 Thematic Mapper data were used. A coverage of SPOT-HRV imagery at 20 m × 20 m resolution acquired at the Cayenne receiving station in French Guiana was used for year 2006. Our estimates from the intensified global sampling scheme over French Guiana are compared with those produced by the national authority to report on deforestation rates under the Kyoto protocol rules for its overseas department. The latter estimates come from a sample of nearly 17,000 plots analyzed from same spatial imagery acquired between year 1990 and year 2006. This sampling scheme is derived from the traditional forest inventory methods carried out by IFN (Inventaire Forestier National). Our intensified global sampling scheme leads to an estimate of 96,650 ha deforested between 1990 and 2006, which is within the 95% confidence interval of the IFN sampling scheme, which gives an estimate of 91,722 ha, representing a relative difference from the IFN of 5.4%. These results demonstrate that the intensification of the global sampling scheme can provide forest area change estimates close to those achieved by official forest inventories (<6%), with precisions of between 4% and 7%, although we only estimate errors from sampling, not from the use of surrogate data. Such methods could be used by developing countries to demonstrate that they are fulfilling requirements for reducing emissions from deforestation in the framework of an REDD (Reducing Emissions from Deforestation in Developing Countries) mechanism under discussion within the United Nations Framework Convention on Climate Change (UNFCCC). Monitoring systems at national levels in tropical countries can also benefit from pan-tropical and regional observations, to ensure consistency between different national monitoring systems.

Maintaining a permanent plot data base for growth and yield research: Solutions to some recurring problems

Treesearch

John C. Byrne

1993-01-01

Methods for solving some recurring problems of maintaining a permanent plot data base for growth and yield reseuch are described. These methods include documenting data from diverse sampling designs, changing sampling designs, changing field procedures, and coordinating activities in the plots with the land management agency. Managing a permanent plot data base (...

36 CFR 9.42 - Well records and reports, plots and maps, samples, tests and surveys.

Code of Federal Regulations, 2010 CFR

2010-07-01

... Well records and reports, plots and maps, samples, tests and surveys. Any technical data gathered... 36 Parks, Forests, and Public Property 1 2010-07-01 2010-07-01 false Well records and reports, plots and maps, samples, tests and surveys. 9.42 Section 9.42 Parks, Forests, and Public Property...

Field efficiency and bias of snag inventory methods

Treesearch

Robert S. Kenning; Mark J. Ducey; John C. Brissette; Jeffery H. Gove

2005-01-01

Snags and cavity trees are important components of forests, but can be difficult to inventory precisely and are not always included in inventories because of limited resources. We tested the application of N-tree distance sampling as a time-saving snag sampling method and compared N-tree distance sampling to fixed-area sampling and modified horizontal line sampling in...

Mapping aboveground woody biomass using forest inventory, remote sensing and geostatistical techniques.

PubMed

Yadav, Bechu K V; Nandy, S

2015-05-01

Mapping forest biomass is fundamental for estimating CO₂ emissions, and planning and monitoring of forests and ecosystem productivity. The present study attempted to map aboveground woody biomass (AGWB) integrating forest inventory, remote sensing and geostatistical techniques, viz., direct radiometric relationships (DRR), k-nearest neighbours (k-NN) and cokriging (CoK) and to evaluate their accuracy. A part of the Timli Forest Range of Kalsi Soil and Water Conservation Division, Uttarakhand, India was selected for the present study. Stratified random sampling was used to collect biophysical data from 36 sample plots of 0.1 ha (31.62 m × 31.62 m) size. Species-specific volumetric equations were used for calculating volume and multiplied by specific gravity to get biomass. Three forest-type density classes, viz. 10-40, 40-70 and >70% of Shorea robusta forest and four non-forest classes were delineated using on-screen visual interpretation of IRS P6 LISS-III data of December 2012. The volume in different strata of forest-type density ranged from 189.84 to 484.36 m(3) ha(-1). The total growing stock of the forest was found to be 2,024,652.88 m(3). The AGWB ranged from 143 to 421 Mgha(-1). Spectral bands and vegetation indices were used as independent variables and biomass as dependent variable for DRR, k-NN and CoK. After validation and comparison, k-NN method of Mahalanobis distance (root mean square error (RMSE) = 42.25 Mgha(-1)) was found to be the best method followed by fuzzy distance and Euclidean distance with RMSE of 44.23 and 45.13 Mgha(-1) respectively. DRR was found to be the least accurate method with RMSE of 67.17 Mgha(-1). The study highlighted the potential of integrating of forest inventory, remote sensing and geostatistical techniques for forest biomass mapping.

An Examination of Diameter Density Prediction with k-NN and Airborne Lidar

DOE PAGES

Strunk, Jacob L.; Gould, Peter J.; Packalen, Petteri; ...

2017-11-16

While lidar-based forest inventory methods have been widely demonstrated, performances of methods to predict tree diameters with airborne lidar (lidar) are not well understood. One cause for this is that the performance metrics typically used in studies for prediction of diameters can be difficult to interpret, and may not support comparative inferences between sampling designs and study areas. To help with this problem we propose two indices and use them to evaluate a variety of lidar and k nearest neighbor (k-NN) strategies for prediction of tree diameter distributions. The indices are based on the coefficient of determination ( R 2),more » and root mean square deviation (RMSD). Both of the indices are highly interpretable, and the RMSD-based index facilitates comparisons with alternative (non-lidar) inventory strategies, and with projects in other regions. K-NN diameter distribution prediction strategies were examined using auxiliary lidar for 190 training plots distribute across the 800 km 2 Savannah River Site in South Carolina, USA. In conclusion, we evaluate the performance of k-NN with respect to distance metrics, number of neighbors, predictor sets, and response sets. K-NN and lidar explained 80% of variability in diameters, and Mahalanobis distance with k = 3 neighbors performed best according to a number of criteria.« less

Class 1 overview of cultural resources for the Western Area Power Administration Salt Lake City Area Integrated Projects electric power marketing environmental impact statement

DOE Office of Scientific and Technical Information (OSTI.GOV)

Moeller, K.L.; Malinowski, L.M.; Hoffecker, J.F.

1993-11-01

Argonne National Laboratory conducted an inventory of known archaeological and historic sites in areas that could be affected by the hydropower operation alternatives under analysis in the power marketing environmental impact statement for the Western Area Power Administration`s Salt Lake City Area Integrated Projects. The study areas included portions of the Green River (Flaming Gorge Dam to Cub Creek) in Utah and Colorado and the Gunnison River (Blue Mesa Reservoir to Crystal Dam) in Colorado. All previous archaeological surveys and previously recorded prehistoric and historic sites, structures, and features were inventoried and plotted on maps (only survey area maps aremore » included in this report). The surveys were classified by their level of intensity, and the sites were classified according to their age, type, and contents. These data (presented here in tabular form) permit a general assessment of the character and distribution of archaeological remains in the study areas, as well as an indication of the sampling basis for such an assessment. To provide an adequate context for the descriptions of the archaeological and historic sites, this report also presents overviews of the environmental setting and the regional prehistory, history, and ethnography for each study area.« less

An Examination of Diameter Density Prediction with k-NN and Airborne Lidar

DOE Office of Scientific and Technical Information (OSTI.GOV)

Strunk, Jacob L.; Gould, Peter J.; Packalen, Petteri

While lidar-based forest inventory methods have been widely demonstrated, performances of methods to predict tree diameters with airborne lidar (lidar) are not well understood. One cause for this is that the performance metrics typically used in studies for prediction of diameters can be difficult to interpret, and may not support comparative inferences between sampling designs and study areas. To help with this problem we propose two indices and use them to evaluate a variety of lidar and k nearest neighbor (k-NN) strategies for prediction of tree diameter distributions. The indices are based on the coefficient of determination ( R 2),more » and root mean square deviation (RMSD). Both of the indices are highly interpretable, and the RMSD-based index facilitates comparisons with alternative (non-lidar) inventory strategies, and with projects in other regions. K-NN diameter distribution prediction strategies were examined using auxiliary lidar for 190 training plots distribute across the 800 km 2 Savannah River Site in South Carolina, USA. In conclusion, we evaluate the performance of k-NN with respect to distance metrics, number of neighbors, predictor sets, and response sets. K-NN and lidar explained 80% of variability in diameters, and Mahalanobis distance with k = 3 neighbors performed best according to a number of criteria.« less

SPRUCE Peat Physical and Chemical Characteristics from Experimental Plot Cores, 2012

DOE Data Explorer

Iversen, C. M. [Oak Ridge National Laboratory, U.S. Department of Energy, Oak Ridge, Tennessee, U.S.A.; Hanson, P. J. [Oak Ridge National Laboratory, U.S. Department of Energy, Oak Ridge, Tennessee, U.S.A.; Brice, D. J. [Oak Ridge National Laboratory, U.S. Department of Energy, Oak Ridge, Tennessee, U.S.A.; Phillips, J. R. [Oak Ridge National Laboratory, U.S. Department of Energy, Oak Ridge, Tennessee, U.S.A.; McFarlane, K. J. [Oak Ridge National Laboratory, U.S. Department of Energy, Oak Ridge, Tennessee, U.S.A.; Hobbie, E. A. [Oak Ridge National Laboratory, U.S. Department of Energy, Oak Ridge, Tennessee, U.S.A.; Kolka, R. K. [Oak Ridge National Laboratory, U.S. Department of Energy, Oak Ridge, Tennessee, U.S.A.

2012-01-01

This data set reports the results of physical and chemical analyses of peat core samples from the SPRUCE experimental study plots located in the S1-Bog. On August 13-15, 2012, a team of SPRUCE investigators and collaborators collected core samples of peat in the SPRUCE experimental plots. The goal was to characterize the biological, physical, and chemical characteristics of peat, and how those characteristics changed throughout the depth profile of the bog, prior to the initialization of the SPRUCE experimental warming and CO2 treatments. Cores were collected from 16 experimental plots; samples were collected from the hummock and hollow surfaces to depths of 200-300 cm in defined increments. Three replicate cores were collected from both hummock and hollow locations in each plot. The coring locations within each plot were mapped

Evaluating the efficiency of environmental monitoring programs

USGS Publications Warehouse

Levine, Carrie R.; Yanai, Ruth D.; Lampman, Gregory G.; Burns, Douglas A.; Driscoll, Charles T.; Lawrence, Gregory B.; Lynch, Jason; Schoch, Nina

2014-01-01

Statistical uncertainty analyses can be used to improve the efficiency of environmental monitoring, allowing sampling designs to maximize information gained relative to resources required for data collection and analysis. In this paper, we illustrate four methods of data analysis appropriate to four types of environmental monitoring designs. To analyze a long-term record from a single site, we applied a general linear model to weekly stream chemistry data at Biscuit Brook, NY, to simulate the effects of reducing sampling effort and to evaluate statistical confidence in the detection of change over time. To illustrate a detectable difference analysis, we analyzed a one-time survey of mercury concentrations in loon tissues in lakes in the Adirondack Park, NY, demonstrating the effects of sampling intensity on statistical power and the selection of a resampling interval. To illustrate a bootstrapping method, we analyzed the plot-level sampling intensity of forest inventory at the Hubbard Brook Experimental Forest, NH, to quantify the sampling regime needed to achieve a desired confidence interval. Finally, to analyze time-series data from multiple sites, we assessed the number of lakes and the number of samples per year needed to monitor change over time in Adirondack lake chemistry using a repeated-measures mixed-effects model. Evaluations of time series and synoptic long-term monitoring data can help determine whether sampling should be re-allocated in space or time to optimize the use of financial and human resources.

Where do the Field Plots Belong? A Multiple-Constraint Sampling Design for the BigFoot Project

NASA Astrophysics Data System (ADS)

Kennedy, R. E.; Cohen, W. B.; Kirschbaum, A. A.; Gower, S. T.

2002-12-01

A key component of a MODIS validation project is effective characterization of biophysical measures on the ground. Fine-grain ecological field measurements must be placed strategically to capture variability at the scale of the MODIS imagery. Here we describe the BigFoot project's revised sampling scheme, designed to simultaneously meet three important goals: capture landscape variability, avoid spatial autocorrelation between field plots, and minimize time and expense of field sampling. A stochastic process places plots in clumped constellations to reduce field sampling costs, while minimizing spatial autocorrelation. This stochastic process is repeated, creating several hundred realizations of plot constellations. Each constellation is scored and ranked according to its ability to match landscape variability in several Landsat-based spectral indices, and its ability to minimize field sampling costs. We show how this approach has recently been used to place sample plots at the BigFoot project's two newest study areas, one in a desert system and one in a tundra system. We also contrast this sampling approach to that already used at the four prior BigFoot project sites.

Radiological investigations at the "Taiga" nuclear explosion site, part II: man-made γ-ray emitting radionuclides in the ground and the resultant kerma rate in air.

PubMed

Ramzaev, V; Repin, V; Medvedev, A; Khramtsov, E; Timofeeva, M; Yakovlev, V

2012-07-01

Samples of soil and epigeic lichens were collected from the "Taiga" peaceful nuclear explosion site (61.30°N 56.60°E, the Perm region, Russia) in 2009 and analyzed using high resolution γ-ray spectrometry. For soil samples obtained at six different plots, two products of fission ((137)Cs and (155)Eu), five products of neutron activation ((60)Co, (94)Nb, (152)Eu, (154)Eu, (207)Bi) and (241)Am have been identified and quantified. The maximal activity concentrations of (60)Co, (137)Cs, and (241)Am for the soils samples were measured as 1650, 7100, and 6800 Bq kg(-1) (d.w.), respectively. The deposit of (137)Cs for the top 20 cm of soil on the tested plots at the "Taiga" site ranged from 30 to 1020 kBq m(-2); the maximal value greatly (by almost 3 orders of magnitude) exceeded the regional background (from global fallout) level of 1.4 kBq m(-2). (137)Cs contributes approximately 57% of the total ground inventory of the man-made γ-ray emitters for the six plots tested at the "Taiga" site. The other major radionuclides -(241)Am and (60)Co, constitute around 40%. Such radionuclides as (60)Co, (137)Cs, (241)Am, and (207)Bi have also been determined for the epigeic lichens (genera Cladonia) that colonized certain areas at the ground lip produced by the "Taiga" explosion. Maximal activity concentrations (up to 80 Bq kg(-1) for (60)Co, 580 Bq kg(-1) for (137)Cs, 200 Bq kg(-1) for (241)Am, and 5 Bq kg(-1) for (207)Bi; all are given in terms of d.w.) have been detected for the lower dead section of the organisms. The air kerma rates associated with the anthropogenic sources of gamma radiation have been calculated using the data obtained from the laboratory analysis. For the six plots tested, the kerma rates ranged from 50 to 1200 nGy h(-1); on average, 51% of the dose can be attributed to (137)Cs and 45% to (60)Co. These estimates agree reasonably well with the results of the in situ measurements made during our field survey of the "Taiga" site in August 2009. Copyright © 2011 Elsevier Ltd. All rights reserved.

Assessing impacts of roads: application of a standard assessment protocol

USGS Publications Warehouse

Duniway, Michael C.; Herrick, Jeffrey E.

2013-01-01

Adaptive management of road networks depends on timely data that accurately reflect the impacts those systems are having on ecosystem processes and associated services. In the absence of reliable data, land managers are left with little more than observations and perceptions to support management decisions of road-associated disturbances. Roads can negatively impact the soil, hydrologic, plant, and animal processes on which virtually all ecosystem services depend. The Interpreting Indicators of Rangeland Health (IIRH) protocol is a qualitative method that has been demonstrated to be effective in characterizing impacts of roads. The goal of this study were to develop, describe, and test an approach for using IIRH to systematically evaluate road impacts across large, diverse arid and semiarid landscapes. We developed a stratified random sampling approach to plot selection based on ecological potential, road inventory data, and image interpretation of road impacts. The test application on a semiarid landscape in southern New Mexico, United States, demonstrates that the approach developed is sensitive to road impacts across a broad range of ecological sites but that not all the types of stratification were useful. Ecological site and road inventory strata accounted for significant variability in the functioning of ecological processes but stratification based on apparent impact did not. Analysis of the repeatability of IIRH applied to road plots indicates that the method is repeatable but consensus evaluations based on multiple observers should be used to minimize risk of bias. Landscape-scale analysis of impacts by roads of contrasting designs (maintained dirt or gravel roads vs. non- or infrequently maintained roads) suggests that future travel management plans for the study area should consider concentrating traffic on fewer roads that are well designed and maintained. Application of the approach by land managers will likely provide important insights into minimizing impacts of road networks on key ecosystem services.

Role of sprouts in regeneration of a whole-tree clearcut in central hardwoods of Connecticut

Treesearch

C.W. Martin; L.M. Tritton

1991-01-01

Stump sprouts were the single most important type of regeneration in a central hardwood forest in Connecticut during the first 5 years after whole-tree clearcuttting. Herbs, shrubs, tree seedlings, and stump sprouts were inventoried using stratified permanent plots on a 6-ha watershed during the first, third, and fifth years after harvest.

Remotely sensed measurements of forest structure and fuel loads in the Pinelands of New Jersey

Treesearch

Nicholas Skowronski; Kenneth Clark; Ross Nelson; John Hom; Matt Patterson

2007-01-01

We used a single-beam, first return profiling LIDAR (Light Detection and Ranging) measurements of canopy height, intensive biometric measurements in plots, and Forest Inventory and Analysis (FIA) data to quantify forest structure and ladder fuels (defined as vertical fuel continuity between the understory and canopy) in the New Jersey Pinelands. The LIDAR data were...

The urban FIA inventory: plot design, data collection, data flow and processing

Treesearch

Tonya Lister; Mark Majewsky; Mark A. Hatfield; Angie Rowe; Bill Dunning; Chris Edgar; Tom Brandeis

2015-01-01

More than 80 percent of the U.S. population lives in urban areas and tree cover in these areas offers a wide range of environmental benefits including the provision of wildlife habitat, aesthetic appeal and visual barriers, microclimate control, water quality improvement, and air and noise pollution control. Recognizing the importance of urban forests, and with...

Potential relative increment (PRI): a new method to empirically derive optimal tree diameter growth

Treesearch

Don C Bragg

2001-01-01

Potential relative increment (PRI) is a new method to derive optimal diameter growth equations using inventory information from a large public database. Optimal growth equations for 24 species were developed using plot and tree records from several states (Michigan, Minnesota, and Wisconsin) of the North Central US. Most species were represented by thousands of...

Modeling forest mortality caused by drought stress: implications for climate change

Treesearch

Eric J Gustafson; Brian R. Sturtevant

2013-01-01

Climate change is expected to affect forest landscape dynamics in many ways, but it is possible that the most important direct impact of climate change will be drought stress. We combined data from weather stations and forest inventory plots (FIA) across the upper Great Lakes region (USA) to study the relationship between measures of drought stress and mortality for...

Dominant height-based height-diameter equations for trees in southern Indiana

Treesearch

John A., Jr. Kershaw; Robert C. Morrissey; Douglass F. Jacobs; John R. Seifert; James B. McCarter

2008-01-01

Height-diameter equations are developed based on dominant tree data collected in 1986 in 8- to 17-year-old clearcuts and the phase 2 Forest Inventory and Analysis plots on the Hoosier National Forest in south central Indiana. Two equation forms are explored: the basic, three-parameter Chapman-Richards function, and a modification of the three-parameter equation...

Maine Forests 2013

Treesearch

George L. McCaskill; Thomas Albright; Charles J. Barnett; Brett J. Butler; Susan J. Crocker; Cassandra M. Kurtz; William H. McWilliams; Patrick D. Miles; Randall S. Morin; Mark D. Nelson; Richard H. Widmann; Christopher W. Woodall

2016-01-01

The third 5-year annualized inventory of Maine's forests was completed in 2013 after more than 3170 forested plots were measured. Maine contains more than 17.6 million acres of forest land, an area that has been quite stable since 1960, covering more than 82 percent of the total land area. The number of live trees greater than 1 inch in diameter are approaching 24...

West Virginia Forests 2013

Treesearch

Randall S. Morin; Gregory W. Cook; Charles J. Barnett; Brett J. Butler; Susan J. Crocker; Mark A. Hatfield; Cassandra M. Kurtz; Tonya W. Lister; William G. Luppold; William H. McWilliams; Patrick D. Miles; Mark D. Nelson; Charles H. (Hobie) Perry; Ronald J. Piva; James E. Smith; Jim Westfall; Richard H. Widmann; Christopher W. Woodall

2016-01-01

The annual inventory of West Virginia's forests, completed in 2013, covers nearly 12.2 million acres of forest land with an average volume of more than 2,300 cubic feet per acre. This report is based data collected from 2,808 plots located across the State. Forest land is dominated by the oak/hickory forest-type group, which occupies 74 percent of total forest...

Controls on fallen leaf chemistry and forest floor element masses in native and novel forests across a tropical island

Treesearch

H.E. Erickson; E.H. Helmer; T.J. Brandeis; A.E. Lugo

2014-01-01

Litter chemistry varies across landscapes according to factors rarely examined simultaneously. We analyzed 11 elements in forest floor (fallen) leaves and additional litter components from 143 forest inventory plots systematically located across Puerto Rico, a tropical island recovering from large-scale forest clearing. We assessed whether three existing, independently...

An assessment of Japanese stiltgrass in northern U.S. forests

Treesearch

Cassandra M. Kurtz; Mark H. Hansen

2017-01-01

This publication is part of a series of research notes that provides an overview of the presence of invasive plant species monitored on an extensive systematic network of plots measured by the Forest Inventory and Analysis (FIA) program of the U.S. Forest Service, Northern Research Station (NRS). Each research note features one of the invasive plants monitored on...

Mapping forest vegetation for the western United States using modified random forests imputation of FIA forest plots

Treesearch

Karin Riley; Isaac C. Grenfell; Mark A. Finney

2016-01-01

Maps of the number, size, and species of trees in forests across the western United States are desirable for many applications such as estimating terrestrial carbon resources, predicting tree mortality following wildfires, and for forest inventory. However, detailed mapping of trees for large areas is not feasible with current technologies, but statistical...

Influence of elevation and site productivity on conifer distributions across Alaskan temperate rainforests

Treesearch

John P. Caouette; Ashley E. Steel; Paul E. Hennon; Pat G. Cunningham; Cathy A. Pohl; Barbara A. Schrader

2016-01-01

We investigated the influence of landscape factors on the distribution and life stage stability of coastal tree species near the northern limit of their ranges. Using data from 1465 forest inventory plots, we estimated probability of occurrence and basal area of six common conifer species across three broad latitudinal regions of coastal Alaska. By also comparing...

Assessing forest mortality patterns using climate and FIA data at multiple scales

Treesearch

Michael K. Crosby; Zhaofei Fan; Xingang Fan; Theodor D. Leininger; Martin A. Spetich

2012-01-01

Forest Inventory and Analysis (FIA) and PRISM climate data from 1991-2000 were obtained for 10 states in the southeastern United States. Mortality was calculated for each plot, and annual values for precipitation and maximum and minimum temperature were extracted from the PRISM data. Data were then stratified by upland/bottomland for red oak species, and classification...

Imputing forest carbon stock estimates from inventory plots to a nationally continuous coverage

Treesearch

Barry Tyler Wilson; Christopher W. Woodall; Douglas M. Griffith

2013-01-01

The U.S. has been providing national-scale estimates of forest carbon (C) stocks and stock change to meet United Nations Framework Convention on Climate Change (UNFCCC) reporting requirements for years. Although these currently are provided as national estimates by pool and year to meet greenhouse gas monitoring requirements, there is growing need to disaggregate these...

Distribution and occupancy of introduced species: a baseline inventory from Phase 3 plots across the country

Treesearch

Bethany K. Schulz; W. Keith Moser

2012-01-01

Invasive plant species have significant negative impacts in many ecosystems and are found in many forests around the world. Although not all introduced species become invasive, there are numerous examples of species escaping cultivation and invading natural ecosystems years or even decades after their initial introduction. Regional distributions of invasive species are...

From detection monitoring to evaluation monitoring - a case study involving crown dieback in northern white-cedar

Treesearch

KaDonna Randolph; William Bechtold; Randall Morin; Stanley Zarnoch

2009-01-01

The Forest Inventory and Analysis (FIA) Phase 3 plot network is a crucial part of the U.S. Forest Health Monitoring program's detection monitoring system, where select indicators are monitored for signals that may indicate deteriorating forest health. When a negative signal is identified, evaluation monitoring provides a mechanism whereby a potential problem can...

Size and frequency of natural forest disturbances and the Amazon forest carbon balance

Treesearch

F.D.B. Espirito-Santo; M. Gloor; M. Keller; Y. Malhi; S. Saatchi; B. Nelson; R.C. Oliveira Junior; C. Pereira; J. Lloyd; S. Frolking; M. Palace; Y.E. Shimabukuro; V. Duarte; A. Monteagudo Mendoza; G. Lopez-Gonzalez; T.R. Baker; T.R. Feldpausch; R.J.W. Brienen; G.P. Asner; D.S. Boyd; O.L. Phillips

2014-01-01

Forest inventory studies in the Amazon indicate a large terrestrial carbon sink. However, field plots may fail to represent forest mortality processes at landscape-scales of tropical forests. Here we characterize the frequency distribution of disturbance events in natural forests from 0.01 ha to 2,651 ha size throughout Amazonia using a novel...

Rate of value change in New England timber stands

Treesearch

Stanford L. Arner; David A. Gansner; Thomas W. Birch; Thomas W. Birch

1990-01-01

Analyses of remeasured plot data show that between the last two forest inventories of New England, compound rates of value change in timber stands averaged 4.2 percent and ranged from -26 to + 43 percent. Three key characteristics of stand condition (species composition, tree size, and stocking) can be used to estimate economic growth. For example, stands with (1) more...

Tracking changes in the susceptibility of forest land infested with gypsy moth

Treesearch

David A. Gansner; John W. Quimby; Susan L. King; Stanford L. Arner; David A. Drake

1994-01-01

Does forest land subject to intensive outbreaks of gypsy moth (Lymantria dispar L.) become less susceptible to defoliation? A model for estimating the likelihood of gypsy moth defoliation has been developed and validated. It was applied to forest-inventory plot data to quantify trends in the susceptibility of forest land in south-central Pennsylvania during a period of...

The spatial distribution of riparian ash: implications for the dispersal of the emerald ash borer

Treesearch

Susan J. Crocker; W. Keith Moser; Mark H. Hansen; Mark D. Nelson

2007-01-01

A pilot study to assess riparian ash connectivity and its implications for emerald ash borer dispersal was conducted in three subbasins in Michigan's Southern Lower Peninsula. Forest Inventory and Analysis data were used to estimate ash biomass. The nineteen percent of plots in riparian physiographic classes contained 40 percent of ash biomass. Connectivity of...

Status of the Longleaf Pine Forests of the West Gulf Coastal Plain

Treesearch

Kenneth W. Outcalt

1997-01-01

Datafrom the USDA Forest Service, forest inventory and analyses permanent field plot were used to track changes in longleaf pine (Pinuspalustris Mill.) communities in Texas and Louisiana between 1985 and 1995. The decline of longleaf forest has continued in Louisiana. Texas had much less longleaf type in 1985, but unlike Louisiana there has been a small increase in the...

Fuel load modeling from mensuration attributes in temperate forests in northern Mexico

Treesearch

Maricela Morales-Soto; Marín Pompa-Garcia

2013-01-01

The study of fuels is an important factor in defining the vulnerability of ecosystems to forest fires. The aim of this study was to model a dead fuel load based on forest mensuration attributes from forest management inventories. A scatter plot analysis was performed and, from explanatory trends between the variables considered, correlation analysis was carried out...

Successional changes in plant species diversity and composition after clearcutting a Southern Appalachian watershed

Treesearch

Katherine J. Elliott; Lindsay R. Boring; Wayne T. Swank; Bruce L. Haines

1997-01-01

Watershed 7, a southwest-facing watershed in the Coweeta Basin, western North Carolina, USA, was clearcut in 1977. Twenty-four permanent plots were inventoried in 1974 before cutting and in 1977, 1979, 1984, and 1993 after clearcutting. This study evaluates changes in species diversity during early succesion after clearcutting and differences in overstory tree and...

Development of forest regeneration imputation models using permanent plots in Oregon and Washington

Treesearch

Karin Kralicek; Andrew Sánchez Meador; Leah Rathbun

2015-01-01

Imputation models were developed and tested to estimate tree regeneration on Forest Service land in Oregon and Washington. The models were based on Forest Inventory and Analysis and Pacific Northwest Regional NFS Monitoring data. The data was processed into sets of tables containing estimates of regeneration by broad plant associations and spanning a large variety in...

Aboveground biomass variability across intact and degraded forests in the Brazilian Amazon

Treesearch

Marcos Longo; Michael Keller; Maiza N. dos-Santos; Veronika Leitold; Ekena R. Pinagé; Alessandro Baccini; Sassan Saatchi; Euler M. Nogueira; Mateus Batistella; Douglas C. Morton

2016-01-01

Deforestation rates have declined in the Brazilian Amazon since 2005, yet degradation from logging, fire, and fragmentation has continued in frontier forests. In this study we quantified the aboveground carbon density (ACD) in intact and degraded forests using the largest data set of integrated forest inventory plots (n = 359) and airborne lidar data (18,000 ha)...

Response of Scots pine stand vitality to changes in environmental factors in Poland, 1991-1995

Treesearch

Jerzy Wawrzoniak

1998-01-01

Vitality inventories of Scots pine stands, the most common species in Poland, have been done since 1991 by using the ICP-Forest methodology. In Scots pine stands older than 40 years, 1,040 observation plots were established. Defoliation was used as the primary indicator of stand vitality. During 1991 to 1995, SO2 and NOx...

Changes in area and ownership of timberland in western Oregon: 1961-86.

Treesearch

Colin D. MacLean

1990-01-01

This report notes the changes in timberland area and in timberland ownership that took place in western Oregon between 1961 and 1986. The data for the report were based on observations and measurements taken during three successive forest inventories of non-Federal lands in western Oregon. Estimates of change were based on repeat measurements of 1,465 permanent plots...

Quantifying forest fragmentation using Geographic Information Systems and Forest Inventory and Analysis plot data

Treesearch

Dacia M. Meneguzzo; Mark H. Hansen

2009-01-01

Fragmentation metrics provide a means of quantifying and describing forest fragmentation. The most common method of calculating these metrics is through the use of Geographic Information System software to analyze raster data, such as a satellite or aerial image of the study area; however, the spatial resolution of the imagery has a significant impact on the results....

Ecological impacts and management strategies for western larch in the face of climate-change

Treesearch

Gerald E. Rehfeldt; Barry C. Jaquish

2010-01-01

Approximately 185,000 forest inventory and ecological plots from both USA and Canada were used to predict the contemporary distribution of western larch (Larix occidentalis Nutt.) from climate variables. The random forests algorithm, using an 8-variable model, produced an overall error rate of about 2.9 %, nearly all of which consisted of predicting presence at...

Fusiform-Rust-Hazard Maps for Loblolly and Slash Pines

Treesearch

Robert L. Anderson; Thomas C. McCartney; Noel D. Cost; Hugh Devine; Martin Botkin

1988-01-01

Rust-hazard saps made from Forest Inventory and Analysis plot data show that fusiform rust on slash pine is most common in north-central Florida, in southeastern Georgia, and in areas north of slash pine's natural range. On loblolly pine, the disease is most common in central and southeastern Georgia and in portions of South Carolina. These maps show the general...

Multi-scale modeling of relationships between forest health and climatic factors

Treesearch

Michael K. Crosby; Zhaofei Fan; Xingang Fan; Martin A. Spetich; Theodor D. Leininger

2015-01-01

Forest health and mortality trends are impacted by changes in climate. These trends can vary by species, plot location, forest type, and/or ecoregion. To assess the variation among these groups, Forest Inventory and Analysis (FIA) data were obtained for 10 states in the southeastern United States and combined with downscaled climate data from the Weather Research and...

Rate of value change in Pennsylvania timber stands

Treesearch

Owen W. Herrick

1984-01-01

Data from remeasured Pennsylvania forest inventory plots revealed that during a 13-year period the compound rate of value change in uncut hardwood forest stands averaged 4.7 percent, and ranged from -5.5 to 18.8 percent. No well-defined means for predicting a stand's rate of value change could be identified, However, some measures of initial stand condition can be...

Calibration of the STEMS diameter growth model using FIA data

Treesearch

Veronica C. Lessard

2000-01-01

The diameter growth model used in STEMS, the Stand and Tree Evaluation and Modeling System, was originally calibrated using data from permanent growth plots in Minnesota, Wisconsin, and Michigan. Because the model has been applied in predicting growth using Forest Inventory and Analysis (FIA) data, it was appropriate to refit the model to FIA data. The model was...

A comparison of sample unit designs in the national inventory of the U.S.

Treesearch

B. E. Borders; G. H. Brister; N. Grahl; B. D. Shiver; C. J. Cieszewski

2000-01-01

The Forest Inventory and Analysis (FIA) program of the USDA Forest Service has adopted a new sampling unit for the national forest inventory of the U.S. We compared this new sampling unit with five other sampling units. Data from natural loblolly pine (Pinus taeda L.) stands in the Georgia piedmont show that all sample units produce reasonable...

Number of pins in two-stage stratified sampling for estimating herbage yield

Treesearch

William G. O' Regan; C. Eugene Conrad

1975-01-01

In a two-stage stratified procedure for sampling herbage yield, plots are stratified by a pin frame in stage one, and clipped. In stage two, clippings from selected plots are sorted, dried, and weighed. Sample size and distribution of plots between the two stages are determined by equations. A way to compute the effect of number of pins on the variance of estimated...

Standardized mean differences cause funnel plot distortion in publication bias assessments.

PubMed

Zwetsloot, Peter-Paul; Van Der Naald, Mira; Sena, Emily S; Howells, David W; IntHout, Joanna; De Groot, Joris Ah; Chamuleau, Steven Aj; MacLeod, Malcolm R; Wever, Kimberley E

2017-09-08

Meta-analyses are increasingly used for synthesis of evidence from biomedical research, and often include an assessment of publication bias based on visual or analytical detection of asymmetry in funnel plots. We studied the influence of different normalisation approaches, sample size and intervention effects on funnel plot asymmetry, using empirical datasets and illustrative simulations. We found that funnel plots of the Standardized Mean Difference (SMD) plotted against the standard error (SE) are susceptible to distortion, leading to overestimation of the existence and extent of publication bias. Distortion was more severe when the primary studies had a small sample size and when an intervention effect was present. We show that using the Normalised Mean Difference measure as effect size (when possible), or plotting the SMD against a sample size-based precision estimate, are more reliable alternatives. We conclude that funnel plots using the SMD in combination with the SE are unsuitable for publication bias assessments and can lead to false-positive results.

Standardized mean differences cause funnel plot distortion in publication bias assessments

PubMed Central

Van Der Naald, Mira; Sena, Emily S; Howells, David W; IntHout, Joanna; De Groot, Joris AH; Chamuleau, Steven AJ; MacLeod, Malcolm R

2017-01-01

Meta-analyses are increasingly used for synthesis of evidence from biomedical research, and often include an assessment of publication bias based on visual or analytical detection of asymmetry in funnel plots. We studied the influence of different normalisation approaches, sample size and intervention effects on funnel plot asymmetry, using empirical datasets and illustrative simulations. We found that funnel plots of the Standardized Mean Difference (SMD) plotted against the standard error (SE) are susceptible to distortion, leading to overestimation of the existence and extent of publication bias. Distortion was more severe when the primary studies had a small sample size and when an intervention effect was present. We show that using the Normalised Mean Difference measure as effect size (when possible), or plotting the SMD against a sample size-based precision estimate, are more reliable alternatives. We conclude that funnel plots using the SMD in combination with the SE are unsuitable for publication bias assessments and can lead to false-positive results. PMID:28884685