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.     

Developing a National Indicator of Soil Quality on U.S Forestlands: Methods and Initial Results

The Montreal Process was formed in 1994 to develop an internationally agreed upon set of criteria and indicators for the conservation and sustainable management of temperate and boreal forests. In response to this initiative, the Forest Inventory and Analysis (FIA) and Forest Health Monitoring (FHM) programs of the United States Department of Agriculture Forest Service have implemented soil measurements as part of a national monitoring program to address specific questions related to the conservation of soil and water resources. Integration of soil assessments into the national FIA program provides for systematic monitoring of soil properties across all forested regions of the U.S. using standardized collection, laboratory, and statistical procedures that are compatible with existing forest inventory data. The resulting information will provide quantitative benchmarks for regional, national, and international reporting on sustainable forest management and enhance our understanding of management effects on soil quality. This paper presents an overview of the FIA soil monitoring program, outlines the field and laboratory protocols as currently implemented, and provides examples of how these data may be used to assess indicators of sustainable management as defined by the Montreal Process.     

A primer for nonresponse in the US forest inventory and analysis program

Nonresponse caused by denied access and hazardous conditions are a concern for the USDA Forest Service, Forest Inventory and Analysis (FIA) program, whose mission is to quantify status and trends in forest resources across the USA. Any appreciable amount of nonresponse can cause bias in FIA’s estimates of population parameters. This paper will quantify the magnitude of nonresponse and describe the mechanisms that result in nonresponse, describe and qualitatively evaluate FIA’s assumptions regarding nonresponse, provide a recommendation concerning plot replacement strategies, and identify appropriate strategies to pursue that minimize bias. The nonresponse rates ranged from 0% to 21% and differed by land owner group; with denied access to private land the leading cause of nonresponse. Current FIA estimators assume that nonresponse occurs at random. Although in most cases this assumption appears tenable, a qualitative assessment indicates a few situations where the assumption is not tenable. In the short-term, we recommend that FIA use stratification schemes that make the missing at random assumption tenable. We recommend the examination of alternative estimation techniques that use appropriate weighting and auxiliary information to mitigate the effects of nonresponse. We recommend the replacement of nonresponse sample locations not be used.     

Estimating the Number of Tree Species in a Forest Community using Survey Data

Using some large samples as actual populations we study a series of promising estimators for number of species in a population. We recommend a nonparametric estimator, CM2f = cs + fc1/(2c2) where cs is the number of species observed, c1 and c2 are the numbers of species occurring once and twice respectively on the sample plots, and f is the finite population correction for sampling, from such data as collected by Forest Inventory and Analysis (FIA) of the US Forest Service. For FIA samples, there are estimated to be 0, 4, 3, 1 and 6 rare tree species not sampled in Minnesota, Missouri, Pennsylvania, New, York, and Ohio respectively.     

Relative Costs and Benefits of a Continuous and a Periodic Forest Inventory in Minnesota

We show that the Annual Forest Inventory System (AFIS) being developed by the USDA Forest Service and tested in the state of Minnesota is no more costly than the periodic Minnesota forest inventory (12 year measurement cycle). Since very useful results could be generated with AFIS every 4 years in addition to the results from the periodic survey, a continuous inventory would be cost effective. Periodic surveys yield more precise estimates within the first few years of the full survey but afterwards the annual survey would be more precise. Where the changeover in precision occurs still needs to be determined. This cost-neutral advantage of AFIS is quite important to note since the USFS has decided to go to annualized inventories such as AFIS this year.     

Eight nonnative plants in western Oregon forests: Associations with environment and management

Nonnative plants have tremendous ecological and economic impacts on plant communities globally, but comprehensive data on the distribution and ecological relationships of individual species is often scarce or nonexistent. The objective of this study was to assess the influence of vegetation type, climate, topography, and management history on the distribution and abundance of eight selected nonnative plant taxa in forests in western Oregon. These eight taxa were selected as being reliably detected by a multi-resource inventory of 1127 systematically-placed plots on nonfederal forest lands from 1995 to 1997 by the USFS Forest Inventory and Analysis (FIA) program. One or more of the eight nonnative taxa studied were found on 20% of the sampled subplots in the study area, but relatively few stands were dominated by them. Overall abundance of nonnative taxa was likely much greater, because few composites and graminoids were identified to species in this general-purpose inventory. Distribution of most taxa was more closely associated with low density of overstory trees than with climate. Nonnative taxa were significantly more abundant in stands that had been recently clearcut or thinned than in stands that had not. Frequencies of several taxa decreased with elevation, which may reflect proximity to source populations and intensive land use rather than any climatic constraints. Although the greatest potential for displacement of native forest species appears to be in early-successional communities, the potential for spread of some shade-tolerant evergreen shrubs also seems high.     

Vulnerability of Mid-Atlantic Forested Watersheds to Timber Harvest Disturbance

Forested watersheds of the Mid-Atlantic Region are an important economic resource. They are also critical for maintaining water quality, sustaining important ecological services, and providing habitat to many animal and plant species of conservation concern. These forests are vulnerable to disturbance and fragmentation from changing patterns of land use in the Mid-Atlantic Region, and from harvests of commercially mature and relatively inexpensive timber. The U.S. Department of Agriculture Forest Service (USDA-FS) Forest Inventory and Analysis (FIA) compiles data on forest condition by state and county. We have transformed these FIA data to a U.S. Geological Survey (USGS) 6-digithdrologic unit code (HUC 6) watershed base, and projected trends in timber growth, inventory, and harvest to 2025 using a timber economics forecasting model (SRTS). We consider forest sustainability from the perspective of timber production, and from the perspective of landscape stability important to conservation values. Simulation data is combined with FIA planted pine acreage data to form a more complete picture of forest extent, composition, and silvicultural practice. Early recognition of prevailing economic trends which encourage the fragmentation of mature forests due to increasing timber harvests may provide managers and policy makers with a planning tool to mitigate undesirable impacts.     

Combining Accuracy Assessment of Land-Cover Maps with Environmental Monitoring Programs

A scientifically valid accuracy assessment of a large-area, land-cover map is expensive. Environmental monitoring programs offer a potential source of data to partially defray the cost of accuracy assessment while still maintaining the statistical validity. In this article, three general strategies for combining accuracy assessment and environmental monitoring protocols are described. These strategies range from a fully integrated accuracy assessment and environmental monitoring protocol, to one in which the protocols operate nearly independently. For all three strategies, features critical to using monitoring data for accuracy assessment include compatibility of the land-cover classification schemes, precisely co-registered sample data, and spatial and temporal compatibility of the map and reference data. Two monitoring programs, the National Resources Inventory (NRI) and the Forest Inventory and Monitoring (FIM), are used to illustrate important features for implementing a combined protocol.     

Optimising the sampling effort in riparian surveys

Riparian condition is commonly measured as part of stream health monitoring programs as riparian vegetation provides an intricate linkage between the terrestrial and aquatic ecosystems. Field surveys of a riparian zone provide comprehensive riparian attribute data but can be considerably intensive and onerous on resources and workers. Our objective was to assess the impact of reducing the sampling effort on the variation in key riparian health indicators. Subsequently, we developed a non-parametric approach to calculate an information retained (IR) statistic for comparing several constrained systematic sampling schemes to the original survey. The IR statistic is used to select a scheme that reduces the time taken to undertake riparian surveys (and thus potentially the costs) whilst maximising the IR from the original survey. Approximate bootstrap confidence intervals were calculated to improve the inferential capability of the IR statistic. The approach is demonstrated using riparian vegetation indicators collected as part of an aquatic ecosystem health monitoring program in Queensland, Australia. Of the nine alternative sampling designs considered, the sampling design that reduced the sampling intensity per site by sixfold without significantly comprising the quality of the IR, results in halving the time taken to complete a riparian survey at a site. This approach could also be applied to reducing sampling effort involved in monitoring other ecosystem health indicators, where an intensive systematic sampling scheme was initially employed.     

Non-detection errors in a survey of persistent, highly-detectable vegetation species

Rare, small or annual vegetation species are widely known to be imperfectly detected with single site surveys by most conventional vegetation survey methods. However, the detectability of common, persistent vegetation species is assumed to be high, but without supporting research. In this study, we evaluate the extent of false-negative errors of perennial vegetation species in a systematic vegetation survey in arid South Australia. Analysis was limited to the seven most easily detected persistent vegetation species and controlled for observer skill. By comparison of methodologies, we then predict the magnitude of non-detection error rates in a second survey. The analysis revealed that all but one highly detectable perennial vegetation species was imperfectly detected (detection probabilities ranged from 0.22 to 0.83). While focussed in the Australian rangelands, the implications of this study are far reaching. Inferences drawn from systematic vegetation surveys that fail to identify and account for non-detection errors should be considered potentially flawed. The identification of this problem in vegetation surveying is long overdue. By comparison, non-detection has been a widely acknowledged, and dealt with, problem in fauna surveying for decades. We recommend that, where necessary, vegetation survey methodology adopt the methods developed in fauna surveying to cope with non-detection errors.     

Evaluating Kriging as a Tool to Improve Moderate Resolution Maps of Forest Biomass

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 explored the possibility of modeling spatial structure to make such improvements. Spatial structure in the field biomass data as well as in residuals from the map was investigated across 18 ecological zones in the Interior Western U.S. Exploratory tools included directional graphs of summary statistics, three dimensional maps, Moran’s I correlograms, and variograms. Where spatial pattern was present, field and residual biomass were kriged, and predictions made for an independent test set were evaluated for improvement over predictions in the initial biomass map. While kriging has some potential benefit when analyzing the field data and exploring spatial structure, kriging residuals resulted in little or no improvement in the initial biomass map developed using Cubist software. Stationarity assumptions, variogram behavior, and appropriate model fitting strategies are discussed.     

Development history and bibliography of the US Forest Service crown-condition indicator for forest health monitoring

Comprehensive assessment of individual-tree crown condition by the US Department of Agriculture, Forest Service, Forest Inventory and Analysis (FIA) Program has its origins in the concerns about widespread forest decline in Europe and North America that developed in the late 1970s and early 1980s. Programs such as the US National Acid Precipitation Assessment Program, US National Vegetation Survey, Canadian Acid Rain National Early Warning System, and joint US–Canadian North American Sugar Maple Decline Project laid the groundwork for the development of the US Forest Service crown-condition indicator. The crown-condition assessment protocols were selected and refined through literature review, peer review, and field studies in several different forest types during the late 1980s and early 1990s. Between 1980 and 2011, 126 publications relating specifically to the crown-condition indicator were added to the literature. The majority of the articles were published by the US Department of Agriculture, Forest Service or other State or Federal government agency, and more than half were published after 2004.     

Combining mapped and statistical data in forest ecological inventory and monitoring – supplementing an existing system

A forest ecological inventory and monitoring system combining information derived from maps and samples is proposed based on ecosystem regions (Bailey, 1994). The system extends the design of the USDA Forest Service Region 6 Inventory and Monitoring System (R6IMS) in the Pacific Northwest of the United States. The key uses of the information are briefly discussed and expected results are illustrated with examples. The system is flexible, allowing regions based on ecological considerations to be modified. Sampling intensities that are affordable are likely to be insufficient to provide meaningful estimates for key parameters relating to rare and endangered species, watersheds, and other ecological units. Methods are proposed for collecting additional information in follow-up surveys and combining it with relevant information obtained in R6IMS. Near-continuous information on weather and possible pollution variables recorded by instruments at sampling sites is needed to develop meaningful models to understand what is happening in the ecoregions. R6IMS and the proposed additions constitute a dynamic system which will be modified further as data are analyzed.     

Analysis of the spatio-temporal and semantic aspects of land-cover/use change dynamics 1991–2001 in Albania at national and district levels

In the turmoil of a rapidly changing economy the Albanian government needs accurate and timely information for management of their natural resources and formulation of land-use policies. The transformation of the forestry sector has required major changes in the legal, regulatory and management framework. The World Bank financed Albanian National Forest Inventory project provides an analysis of spatially explicit land-cover/use change dynamics in the period 1991–2001 using the FAO/UNEP Land Cover Classification System for codification of classes, satellite remote sensing and field survey for data collection and elements of the object-oriented geo-database approach to handle changes as an evolution of land-cover/use objects, i.e. polygons, over time to facilitate change dynamics analysis.Analysis results at national level show the trend of natural resources depletion in the form of modifications and conversions that lead to a gradual shift from land-cover/use types with a tree cover to less dense tree covers or even a complete removal of trees. Policy failure (e.g., corruption, lack of law enforcement) is seen as the underlying cause. Another major trend is urbanisation of areas near large urban centres that change urban-rural linkages. Furthermore, after privatisation agricultural areas increased in the hills where environmental effects may be detrimental, while prime agricultural land in the plains is lost to urbanisation.At district level, the local variability of spatially explicit land-cover/use changes shows different types of natural resources depletion. The distribution of changes indicates a regional prevalence, thus a decentralised approach to the natural resources management could be advocated.     

Canada's National Forest Inventory (Responding to Current Information Needs)

Canada's current National Forest Inventory is a periodic compilation of existing inventory material from across the country. While the current approach has many advantages, it lacks information on the nature and rate of changes to the resource, and does not permit projections or forecasts. Beinga compilation of inventories of different dates, the current national forest inventory cannot reflect the current state ofthe forests and therefore cannot be used as a satisfactory baseline for monitoring change. The current format of Canada's National Forest Inventory has served its purpose by providingnational statistical compilations and reporting. However, itsuseful life is coming to a conclusion. To meet new demands, Canada is considering a new National Forest Inventory design consisting of a plot-based system of permanent observational units located on a national grid. The objective of the new inventory design is to assess and monitor the extent, state andsustainability of Canada's forests in a timely and accurate manner. Details of the new inventory design are described. A strategy to respond to Canada's national and international forest reporting commitments through a National Forest Information System is also discussed.     

Monitoring global change: Comparison of forest cover estimates using remote sensing and inventory approaches

Satellite-based remote sensing offers great potential for frequent assessment of forest cover over broad spatial scales, however, calibration and validation using ground-based surveys are needed. In this study, forest cover estimates for the United States from a recently developed land surface cover map generated from satellite remote sensing data were compared to state-level inventory data from the U.S. National Resources Planning Act Timber Database. The land cover map was produced at the U.S. Geological Survey EROS Data Center and is based on imagery from the AVHRR sensor (spatial resolution 1.1 km). Vegetation type was classified using the temporal signal in the Normalized Difference Vegetation Index derived from AVHRR data. Comparisons revealed close agreement in the estimate of forest cover for extensively forested states with large polygons of relatively similar vegetation such as Oregon. Larger forest cover differences were observed in other states with some regional patterns in the level of agreement apparent.Comparisons in inventory- and remote sensing-based estimates of current forested area with potential vegetation maps indicated the magnitude of past land use change and the potential for future changes. The remote sensing approach appears to hold promise for conducting surveys of forest cover where inventory data are limited or where rates of vegetation change, due to human or climatic factors, are rapid.     

Data,data everywhere but not a byte to read: Managing monitoring information

The problem of managing scientific information for widespread availability and use can be overwhelming. At Oregon State University, the Quantitative Sciences Group has found a workable solution. The group has developed a Forest Science Data Bank (FSDB) to house data generated by scientists and collaborating researchers in the Andrews Long-Term Ecological Research program. Today the FSDB houses some 2400 data sets from over 350 existing ecological studies and adds about 20 new studies yearly. This paper describes what we have learned in setting up the FSDB as a facility that can be used by researchers who both deposit information in and retrieve information from the FSDB.     

南通市开发区化工企业水环境污染源指纹图谱的构建与应用

以南通市开发区化工集中区为应用实施地,不同化工厂不同时间的污染物为研究对象,在GC-MS分析的基础下,联合GIS系统,建立指纹图谱数据库,探索以指纹图谱-GIS联用技术来锁定污染源的方法。结果表明,通过GC-MS初步分析和指纹特征峰的匹配,可快速缩小污染排查范围,为环境监督或污染事故的排查提供一定的技术支持。     

An integrated approach to assess broad-scale condition of coastal wetlands—the Gulf of Mexico Coastal Wetlands pilot survey

The Environmental Protection Agency (EPA) and U.S. Geological Survey (USGS) initiated a two-year regional pilot survey in 2007 to develop, test, and validate tools and approaches to assess the condition of northern Gulf of Mexico (GOM) coastal wetlands. Sampling sites were selected from estuarine and palustrine wetland areas with herbaceous, forested, and shrub/scrub habitats delineated by the US Fish and Wildlife Service National Wetlands Inventory Status and Trends (NWI S&T) program and contained within northern GOM coastal watersheds. A multi-level, stepwise, iterative survey approach is being applied to multiple wetland classes at 100 probabilistically-selected coastal wetlands sites. Tier 1 provides information at the landscape scale about habitat inventory, land use, and environmental stressors associated with the watershed in which each wetland site is located. Tier 2, a rapid assessment conducted through a combination of office and field work, is based on best professional judgment and on-site evidence. Tier 3, an intensive site assessment, involves on-site collection of vegetation, water, and sediment samples to establish an integrated understanding of current wetland condition and validate methods and findings from Tiers 1 and 2. The results from this survey, along with other similar regional pilots from the Mid-Atlantic, West Coast, and Great Lakes Regions will contribute to a design and implementation approach for the National Wetlands Condition Assessment to be conducted by EPA’s Office of Water in 2011.