Charles T. Scott

A GIS-derived integrated moisture index to predict forest composition and productivity of Ohio forests (U.S.A.)

A geographic information system (GIS) approach was used in conjunction with forest-plot data to develop an integrated moisture index (IMI), which was then used to predict forest productivity (site index) and species composition for forests in Ohio. In this region, typical of eastern hardwoods across the Midwest and southern Appalachians, topographic aspect and position (rather than elevation) change drastically at the fine scale and strongly influence many ecological functions. Elevational contours, soil series mapping units, and plot locations were digitized for the Vinton Furnace Experimental Forest in southeastern Ohio and gridded to 7.5-m cells for GIS modeling. Several landscape features (a slope-aspect shading index, cumulative flow of water downslope, curvature of the landscape, and water-holding capacity of the soil) were used to create the IMI, which was then statistically analyzed with site-index values and composition data for plots. On the basis of IMI values for forest land harvested in the past 30 years, we estimated oak site index and the percentage composition of two major species groups in the region: oak (Quercus spp.), and yellow poplar (Liriodendron tulipifera) plus black cherry (Prunus serotina). The derived statistical relationships were then applied in the GIS to create maps of site index and composition, and verified with independent data. The maps show the oaks will dominate on dry, ridge top positions (i.e., low site index), while the yellow poplar and black cherry will predominate on mesic sites. Digital elevation models with coarser resolution (1:24K, 1:100K, 1:250K) also were tested in the same manner. We had generally good success for 1:24K, moderate success for 1:100K, but no success for 1:250K data. This simple and portable approach has the advantage of using readily available GIS information which is time-invariant and requires no fieldwork. The IMI can be used to better manage forest resources where moisture is limiting and to predict how the resource will change under various forms of ecosystem management.

SAMPLING METHODS FOR ESTIMATING CHANGE IN FOREST RESOURCES

Changes in forest resources have been estimated in a variety of ways. This paper focuses on extensive forest surveys rather than on sentinel-site investigations. The sampling design and plot design used are key to precise estimates of change. Alternative sampling designs include temporary surveys, Continuous Forest Inventory, and Sampling with Partial Replacement. Each can be used in conjunction with stratified sampling or double sampling for stratification. Plot designs can involve variable-radius or Bitterlich sampling for trees, and fixed-area plots for most attributes. In extensive surveys, it is efficient to group plots into clusters. Plots must be sampled at a frequency that is commensurate with the rate of change, degree of interest, and funding available. Often, plots are less than a hectare in size and spaced widely across the population. Continuous Forest Inventory, with or without stratification, is efficient for estimating current values, net change, and components of change. Much work remains...

Implications of sampling design and sample size for national carbon accounting systems

BackgroundCountries willing to adopt a REDD regime need to establish a national Measurement, Reporting and Verification (MRV) system that provides information on forest carbon stocks and carbon stock changes. Due to the extensive areas covered by forests the information is generally obtained by sample based surveys. Most operational sampling approaches utilize a combination of earth-observation data and in-situ field assessments as data sources.ResultsWe compared the cost-efficiency of four different sampling design alternatives (simple random sampling, regression estimators, stratified sampling, 2-phase sampling with regression estimators) that have been proposed in the scope of REDD. Three of the design alternatives provide for a combination of in-situ and earth-observation data. Under different settings of remote sensing coverage, cost per field plot, cost of remote sensing imagery, correlation between attributes quantified in remote sensing and field data, as well as population variability and the percent standard error over total survey cost was calculated. The cost-efficiency of forest carbon stock assessments is driven by the sampling design chosen. Our results indicate that the cost of remote sensing imagery is decisive for the cost-efficiency of a sampling design. The variability of the sample population impairs cost-efficiency, but does not reverse the pattern of cost-efficiency of the individual design alternatives.Conclusions, brief summary and potential implicationsOur results clearly indicate that it is important to consider cost-efficiency in the development of forest carbon stock assessments and the selection of remote sensing techniques. The development of MRV-systems for REDD need to be based on a sound optimization process that compares different data sources and sampling designs with respect to their cost-efficiency. This helps to reduce the uncertainties related with the quantification of carbon stocks and to increase the financial benefits from adopting a REDD regime.

Use of space-filling curves to select sample locations in natural resource monitoring studies

The establishment of several large area monitoring networks over the past few decades has led to increased research into ways to spatially balance sample locations across the landscape. Many of these methods are well documented and have been used in the past with great success. In this paper, we present a method using geographic information systems (GIS) and fractals to create a sampling frame, superimpose a tessellation and draw a sample. We present a case study that illustrates the technique and compares results to those from other methods using data from Voyageurs National Park in Minnesota. Our method compares favorably with results from a popular plot selection method, Generalized Random Tessellation Stratified Design, and offers several additional advantages, including ease of implementation, intuitive appeal, and the ability to maintain spatial balance by adding new plots in the event of an inaccessible plot encountered in the field.

Evaluation of permanent sample surveys for growth and yield studies : a Swiss example

Abstract This paper compares experimental growth and yield study plots with sample plots from forest inventories. The difference in research objectives leads to a situation where sample plots are available that are representative of the total population, but give only limited information on site conditions and management history. However, detailed information on site condition and management history is available for growth and yield plots, but does not represent the total population. As an example, Swiss growth and yield plots are compared with survey plots in terms of species distribution, stem form, slope class and elevation. A critical review is given of the two most common sampling designs for regional forest surveys. Continuous forest inventory is recommended over the more efficient but more complex sampling with partial replacement design for use in conjunction with growth and yield studies. The limitations of both growth and yield plots and sample plots are discussed. Recommendations for linking both types of plots to close information gaps are given to improve both forest surveys and growth and yield studies.

Guidelines for documenting and reporting tree allometric equations

1 IntroductionGiven the pressing need to quantify carbon fluxes associatedwith terrestrial vegetation dynamics, an increasing number ofresearchers have sought to improve estimates of tree volume,biomass, and carbon stocks. Tree allometric equations arecritical tools for such purpose and have the potential toimprove our understanding about carbon sequestration inwoody vegetation, to support the implementation of policiesand mechanisms designed to mitigate climate change (e.g.CDM and REDD+; Agrawal et al. 2011), to calculate costsand benefits associated with forest carbon projects, and toimprove bioenergy systems and sustainable forest manage-ment (Henry et al. 2013).

Altered selection probabilities caused by avoiding the edge in field surveys

When field plots are prevented from overlapping the boundary of the tract being sampled, the selection probabilities of population elements near the edge differ from what they are when plots are permitted to overlap the boundary. In both situations, selection probabilities of edge elements differ from those of elements located far to the interior of the tract. An analytical expression and graphical depiction of the altered selection probabilities are presented, accompanied by an empirical study of the consequences on estimation for the situation where plots are pulled back from the edge until just tangent with the boundary.

An overview of existing and promising technologies for national forest monitoring

The main goal of national forest programs is to lead and steer forest policy development and implementation processes in an inter-sectoral way (FAO 2006). National forest monitoring systems contribute to forest programs through monitoring forest changes and forest services over time (FAO 2013). To do so, they generally collect and analyze forest-related data and provide knowledge and recommendations at regular intervals. The collection of forest-related data and their analyses have continually evolved with technological and computational advances (Kleinn 2002).

Inventory methods for trees in nonforest areas in the great plains states

The US Forest Service’s Forest Inventory and Analysis (FIA) program collects information on trees in areas that meet its definition of forest. However, the inventory excludes trees in areas that do not meet this definition, such as those found in urban areas, in isolated patches, in areas with sparse or predominantly herbaceous vegetation, in narrow strips (e.g., shelterbelts), or in riparian areas. In the Great Plains States, little is known about the tree resource in these noninventoried, nonforest areas, and there is a great deal of concern about the potential impact of invasive pests, such as the emerald ash borer. To address this knowledge gap, FIA’s National Inventory and Monitoring Applications Center has partnered with state cooperators and others in a project called the Great Plains Initiative to design and implement an inventory of trees in nonforest areas. The goal of the inventory is to characterize the nonforest tree resource using methods compatible with those of FIA so a holistic understanding of the resource can be obtained by integrating the two surveys. The goal of this paper is to describe the process of designing and implementing the survey, including plot and sample design, and to present some example results from a reporting tool we developed.

Recommendations for the use of tree models to estimate national forest biomass and assess their uncertainty

Key messageThree options are proposed to improve the accuracy of national forest biomass estimates and decrease the uncertainty related to tree model selection depending on available data and national contexts.IntroductionDifferent tree volume and biomass equations result in different estimates. At national scale, differences of estimates can be important while they constitute the basis to guide policies and measures, particularly in the context of climate change mitigation.MethodFew countries have developed national tree volume and biomass equation databases and have explored its potential to decrease uncertainty of volume and biomasttags estimates. With the launch of the GlobAllomeTree webplatform, most countries in the world could have access to country-specific databases. The aim of this article is to recommend approaches for assessing tree and forest volume and biomass at national level with the lowest uncertainty. The article highlights the crucial need to link allometric equation development with national forest inventory planning efforts.ResultsModels must represent the tree population considered. Data availability; technical, financial, and human capacities; and biophysical context, among other factors, will influence the calculation process.ConclusionThree options are proposed to improve accuracy of national forest assessment depending on identified contexts. Further improvements could be obtained through improved forest stratification and additional non-destructive field campaigns.