669 The U.S. Forest Health Monitoring Program K. Riitters and B. Tkacz CONTENTS 30.1 Introduction 669 30.2 History and Management of FHM 669 30.3 Conceptual Approaches to FHM 671 30.4 Operation of FHM 673 30.5 Development Efforts in the FHM Program 675 30.6 FHM Reports 677 30.7 Conclusion 680 References 681 30.1 INTRODUCTION Historically, forest monitoring systems were built to meet the information needs for timber harvest scheduling, insect and disease control, and other forest management concerns. 1 In the past 25 years, the demand for new information has led to new monitoring systems. 2 Forests are increasingly viewed as holistic systems that can only be monitored through an integrated approach to sustainable forest management that considers the ecological and social aspects of forests. 3,4 Some of the new information requirements have been addressed through the FHM program, a coop- erative and integrated approach to collecting data and reporting on many aspects of forest health. Here we provide an overview of the FHM program, beginning with a brief history and summary of the conceptual approaches to forest health monitoring. We then describe current operations and development efforts, and give several examples of how the program is addressing forest health issues in the U.S. 30.2 HISTORY AND MANAGEMENT OF FHM Forest Health Monitoring grew from two related seeds that were sown in the 1980s in response to concern for the effects of air pollution on forest vegetation. As part of the National Acid Precipitation Assessment Program (NAPAP), the Forest Service established the National Vegetation Survey (NVS) to conduct field surveys of acid rain and ozone impacts on forests. 5 Several years later, the Environmental Protection 30 L1641_Frame_C30.fm Page 669 Tuesday, March 23, 2004 7:52 PM © 2004 by CRC Press LLC 670 Environmental Monitoring Agency established the Environmental Monitoring and Assessment Program (EMAP) 6 that included the EMAP-Forests component. 7 Within a few years, the NVS and EMAP-Forests were combined with additional federal and state partners to form the cooperative FHM program. 8 Early efforts focused on reviewing existing forest inventory programs, 9 candidate indicators, 10 sample designs, 11,12 and auxiliary data. 13 There were many field tests of proposed procedures. 14–21 The tests facilitated the development of field manuals, 22 quality assurance plans, 23,24 and information management systems. 25 The first implementation of FHM in 1990 was by six northeastern states: Maine, New Hampshire, Vermont, Massachusetts, Connecticut, and Rhode Island. 26,27 States in the southern region joined in the following year 28 and reports of tree and crown conditions were produced. 29–32 Today, with full implementation of FHM, the Forest Service (including the State and Private Forestry (S&PF) program, National Forest System (NFS), and Research and Development divisions) and states are the primary cooperators. The FHM program initially established plots and conducted surveys in parallel with existing Forest Service programs such as Forest Inventory and Analysis (FIA) and S&PF. In the mid-1990s, there was an effort to integrate FHM with those other programs, 3,33 and this was largely achieved by the year 2000. Since 1999, FIA is responsible for field plot establishment and most ground-based measurements. Forest health measurements are made on a plot network known as Phase 3 of an expanded FIA program. 34 Phase 3 consists of a subset of the FIA timber inventory plot network (Phase 2) where plots are visited to collect an extended suite of ecological data. As part of S&PF, the Forest Health Protection (FHP) program has long coordi- nated an extensive survey effort aimed at identifying forest health problems. 35 These surveys provide maps of problem areas, and they are supplemented by directed ground surveys in some cases. 36 The FHP program also conducts follow-up inves- tigations to evaluate changes in forest health that are observed on the plot network or in surveys. 37 Most of this survey work was integrated with FHM in 1998. The integration of FHM with other programs has resulted not only in efficiency for full implementation but also in the standardization of protocols across states and regions, which, in turn, has allowed the delivery of consistent databases for forest health assessments. While early FHM objectives addressed air pollution impacts on forests, subse- quent development has addressed new concerns including the goal of sustainable forest management as embodied in the Montréal Process Criteria and Indicators. 38,39 The Montréal Process is an agreed-upon national basis for strategic forest planning, 40 national resource assessments, 41 and forest health monitoring. 42,43 The criteria and indicators address social and economic goals as well as ecological goals. Together with FIA and FHP, the FHM program delivers data and assessments pertinent to three criteria — conservation of biodiversity, maintenance of forest ecosystem health, and conservation and maintenance of soil and water resources. Biodiversity indica- tors in the Montréal Process address forest extent, protected status, and fragmenta- tion. Forest ecosystem health indicators address air pollution impacts, forest distur- bance regimes, and biological functioning. Soil indicators include erosion, compaction, and other physical and chemical properties. Adoption of the Montréal L1641_Frame_C30.fm Page 670 Tuesday, March 23, 2004 7:52 PM © 2004 by CRC Press LLC The U.S. Forest Health Monitoring Program 671 Process with its set of common indicators has made it easier to assess and report on FHM data for a diverse set of stakeholders. The FHM program has three levels of internal management. A national Steering Committee is comprised of two state members appointed by the National Association of State Foresters and three federal members from the NFS, S&PF, and Research and Development divisions of the Forest Service. The Steering Committee sets broad strategic goals and directions to be implemented by the FHM National Program Manager. The National Program Manager is responsible for the overall management of the program budget and implementation of FHM. The second level of management is provided by the FHM Management Team which includes 15 rotating state and federal members with operational responsibil- ities in implementing various aspects of the program in different regions. The members provide a variety of expertise including data collection, research, and forest management. The FHM Management Team works closely with the National Program Manager to implement all aspects of the FHM program nationwide. The third level of management consists of ad hoc groups organized to address specialized needs— the design of a rapid-response field survey, for example, or the development of a new measurement protocol. The ad hoc groups typically include disciplinary spe- cialists and are closely coordinated with data collection specialists from FIA, FHP, and state agencies. 30.3 CONCEPTUAL APPROACHES TO FHM Forests are continually exposed to a changing array of natural and anthropogenic stresses, producing both normal and abnormal changes in forest health over time. The response to a given stress varies among biophysical regions and according to local circumstances with a region. Stresses also interact with each other and change over time, and forest responses to stresses can occur at multiple scales and may be delayed rather than immediate. These and other factors make it very difficult to establish baselines of forest health and to detect important departures from normal forest ecosystem functioning. The conceptual approach to forest health monitoring must also take into account the fact that many ecological processes are only poorly understood. The primary objective of monitoring is to identify ecological resources whose condition is deteriorating in subtle ways over large regions in response to cumulative stresses. This objective calls for consistent, large-scale, and long-term monitoring of key indicators of health status, change, and trend. A second objective is to define the extent of resources whose condition is deteriorating rapidly or is at risk of rapid deterioration, from specific stresses, and to develop mitigation and management strategies for those events. This objective calls for more focused surveys and monitoring. To address both objectives, the FHM program adopted a tiered strategy based on the detection of unusual conditions on a regional scale, followed by progressively more detailed studies to explore the causes and consequences of the observed changes. In the detection tier of monitoring, the forests are systematically sampled in space and time, and a small set of integrative health indicators is used to classify L1641_Frame_C30.fm Page 671 Tuesday, March 23, 2004 7:52 PM © 2004 by CRC Press LLC 672 Environmental Monitoring the status of forest resources and to gauge the stresses placed on those resources. Repetition of the indicator measurements provides a basis for periodic reporting of the health status and trends of forests and establishes a baseline for future compar- isons. Like a human health survey, the forest health survey provides statistically credible information about status and trends. It can suggest plausible mechanisms for observed changes, but by itself cannot resolve many important questions such as the causes of change or the ecological and social significance of change. The routine, long-term, and large-scale monitoring of selected indicators is supplemented by an evaluation tier that provides for intensive surveys and research when warranted by observations. The details naturally depend entirely on circum- stances and therefore the evaluation component is not fully defined in advance. Included in the evaluation tier are focused surveys to address the second objective of FHM. Sometimes a particular question about forest health must be answered in a very short period of time. An early example was the concern for air pollution impacts on forests, which eventually led to the inclusion of several field measurements of tree crown condition, lichen abundance, and ozone injury in the long-term monitoring design. A recent example that will be described in more detail later is the concern regarding the spread of sudden oak death, first observed in 1995 in the San Francisco Bay region. The potential impacts of some phenomena are so large that it makes sense to immediately conduct an evaluation of them, and not wait for signs and symptoms to be manifested through the detection tier of the monitoring system. An indicator-based approach to detection monitoring employs a multidimen- sional suite of indicators to monitor several aspects of forest health. Many measure- ments are needed to comprehensively characterize forest ecosystem structure, func- tion, and process, but only a few can be realistically employed in a long-term national program. Ideally, a small set of indicators addresses many dimensions of forest condition such as sustainability, productivity, aesthetics, contamination, utilization, diversity, and extent. If only a few aspects of forest condition are monitored, impor- tant changes could be overlooked. Another way to miss changes is to focus attention only on diagnosing known cause–effect relationships because that requires highly specific measures of conditions that are more appropriate for evaluating known problems than for detecting unknown health problems. The emphasis on detecting without necessarily explaining regional changes in health leads to the emphasis on integrative indicators of forest health. Detection monitoring accepts a high rate of false positives (i.e., a high Type I error rate) as the price of not overlooking change (i.e., a low Type II error rate) and resolves the false positive errors through closer evaluations of the observations. Whether or not a change will be detected depends partly on the scale of the indicator measurements and sample design relative to the scale of the change phe- nomena of interest. 44 The time and space scales of surveys should be linked 45 so that detection monitoring utilizes annual or longer measurement cycles and the measurements are sparsely distributed over very large areas. Knowledge of finer scale temporal or spatial variability typically contributes little information about long-term and large-scale changes. 46 For example, the long-term and regional impacts of climate change, air pollution, and urbanization are best monitored on a L1641_Frame_C30.fm Page 672 Tuesday, March 23, 2004 7:52 PM © 2004 by CRC Press LLC The U.S. Forest Health Monitoring Program 673 long-term and regional basis because model-based extrapolation from a few inten- sively studied research sites cannot reliably detect regional changes, and small-scale intensive surveys can say nothing about areas not included in the surveys. At the same time, research sites and intensive surveys are key elements of the evaluation tier of monitoring because they provide detailed information that cannot be provided by the detection tier of the system. In summary, the FHM strategy has a component to detect long-term regional changes, a component to assess the practical importance of observed changes and to develop options for mitigation and management, and a component to implement intensive surveys and research to rapidly deliver information about particular changes and concerns. Detection monitoring is largely statistical and relies on integrative indicators of condition that are expected to yield a high rate of false positives. Evaluation monitoring is designed to clarify the information, to increase the “signal- to-noise” ratio, and to focus attention on important health problems. The research tier is reserved for conditions that are known to affect large regions in a practical, important way when detailed information is needed about the causes and conse- quences of poor health and when options for prevention and mitigation are required. 30.4 OPERATION OF FHM This section will describe the data collection and processing for the detection tier of forest health monitoring. These procedures are more or less fixed and are con- ducted in a consistent fashion nationwide. In other tiers of monitoring, data that are collected for evaluation monitoring and research purposes are typically decided according to the specific project requirements. Detection monitoring includes field plot measurements, aerial surveys, and assessments of the data. Ancillary data obtained from supplemental sources are used to interpret the FHM measurements and to estimate some indicators. For example, tree crown condition information provided by FIA is interpreted in light of regional weather patterns as reported by the National Oceanic and Atmospheric Administration. Data from the U.S. Geolog- ical Survey are used to measure forest fragmentation, and the U.S. Environmental Protection Agency provides data to estimate air pollution exposure. The field plots that are measured by the FIA program are located according to a systematic national grid. A systematic grid is appropriate for sampling extensively distributed resources like forests and makes it easier to aggregate the resulting data according to states, ecological regions, or some other geographic partitioning required for particular reporting purposes. The basic design 34,47 identifies one Phase 2 (FIA timber inventory) sample plot location for every 6,000 acres with a total of about 125,000 possible plot locations in the lower 48 states. The Phase 3 forest health measurements are made on a 1/16 subset of the plots (~8,000 plots nation- wide). Depending on a schedule for each state, each plot is measured once every 5 field plots by state and federal field crews. 34 The measurements are supported by national training and quality assurance programs to ensure the quality and consistency L1641_Frame_C30.fm Page 673 Tuesday, March 23, 2004 7:52 PM © 2004 by CRC Press LLC Table 30.1 describes the measurements that are made in and around Phase 3 to 10 years through a rotating panel design (Figure 30.1). of the data. The field plot design (Figure 30.2) includes a cluster of four 0.042-acre 674 Environmental Monitoring circular subplots with subplot centers located 120 ft apart. All large trees are mea- sured within each of the subplots. Each subplot contains smaller fixed-area plots and line transects that are used for sampling smaller vegetation and woody material on the forest floor. Soils, lichens, and tree crowns are measured in the area between the subplots. Additional measurements of ozone injury are made at sample locations near the plot; the specific site and species required for such measurements may not occur in the plot. Aerial and ground-based surveys are conducted by federal and state forest health specialists. Each state and Forest Service administrative region is responsible for conducting an annual survey of forested lands within their jurisdiction. In most states, the data are collected by flying over the prescribed area in a systematic fashion, drawing polygons on a map to show the locations of affected areas, and making notes of the observed signs and symptoms. Maps are digitized into geographic information systems and the data are forwarded to a national processing center for automated sketch mapping system that allows observers to digitize polygons directly into a computer linked with the aircraft global positioning system. Like the plot measurements, the aerial survey data are supported by national training and assurance programs to ensure the quality and consistency of the data. FIGURE 30.1 The FIA sample design is based on a tiling of hexagons. A timber inventory plot is located within each hexagon, and a forest health plot is located within one of every sixteen hexagons. Plot measurements are scheduled according to a rotating panel design as indicated by the shading of hexagons. (From U.S. Forest Service, Sampling and Plot Design Fact Sheet, Forest Inventory and Analysis, Washington, D.C., 2003.) L1641_Frame_C30.fm Page 674 Tuesday, March 23, 2004 7:52 PM © 2004 by CRC Press LLC compilation and reporting (Figure 30.3). An increasing amount of sampling uses an The U.S. Forest Health Monitoring Program 675 Field plot measurements are reported with timber inventory statistics by the FIA program according to the schedules established in each FIA region. Similarly, the survey data are analyzed and reported by the FHP program for states and Forest Service administrative regions. Additional analysis and reporting conducted by the FHM program is focused on two topics. First, interpretive reports at state, regional, and national levels augment the routine reporting of status and trends statistics by FIA and FHP. Second, the FHM program compiles statistics from FIA, FHP, and other sources to produce annual forest health summaries at the national level. FHM is the only entity whose entire function is to integrate forest health information from many data collection agencies to produce reports of forest health. 30.5 DEVELOPMENT EFFORTS IN THE FHM PROGRAM The development of the FHM program is currently focused on five major themes: • Completing the implementation of plot measurements in all states through the FIA program • Completing the integration of information and reporting systems through the FHP survey program • Evaluating a possible expansion of FHM to urban forests, riparian forests, and other locations that are not included in FIA or FHP sample designs TABLE 30.1 Description of Forest Health Measurements on FIA Field Plots Indicator Measurements Included Crown condition Amount, condition, and distribution of foliage, branches, and growing tips of trees (crown ratio, crown density, foliar transparency, dieback, and crown width) Tree damage Type, location, and severity of injury caused by diseases, insects, storms, and human activities Tree mortality Type, location, and severity of injury caused by diseases, insects, storms, and human activities Vegetation diversity and structure Type, abundance, and vertical position of vascular plant species (includes an inventory of small trees, herbs, grasses, vines, ferns, and fern allies) Down woody material Species, size, and stage of decay of fallen trees, dead branches, and large fragments of wood on the forest floor Ozone injury Symptoms, species, and severity of foliar injury on ozone bioindicator species Lichen communities Lichen species abundance, diversity, and community composition Soil condition Physical and chemical soil properties of the litter, O-horizon, and mineral soil, including erosion and soil compaction L1641_Frame_C30.fm Page 675 Tuesday, March 23, 2004 7:52 PM © 2004 by CRC Press LLC 676 Environmental Monitoring FIGURE 30.2 Field plot layout for FIA forest health measurements. (From U.S. Forest Service, Sampling and Plot Design Fact Sheet, Forest Inventory and Analysis, Washington, D.C., 2003.) FIGURE 30.3 Example of the national integration of aerial survey data. The shades of gray indicate relative exposure of forests to defoliating agents (insects, diseases, etc.) for the years 1996–2000. Ecoregion boundaries are shown for comparison. (From Coulston, J.W. et al., 2002 Forest Health Monitoring National Technical Report, General Technical Report, U.S. Forest Service, Southern Research Station, Asheville, NC, in press.) L1641_Frame_C30.fm Page 676 Tuesday, March 23, 2004 7:52 PM © 2004 by CRC Press LLC The U.S. Forest Health Monitoring Program 677 • Evaluating additional forest health indicators for possible deployment and improving the efficiency of current indicators • Developing ways to use the field plot and aerial survey data along with supplemental data to produce state, regional, and national assessments of forest health As of 2003, the plot network is operational in 47 of the 50 states, and full implementation is expected by 2005. The FIA program is nearing completion of a transition to a common national system employing the same plot design, measure- ment protocols, and reporting standards. The survey component of FHP (including all states and territories) was linked with FHM in 1998, and integration of the resulting maps is now part of the normal reporting within FHP. Initiated at the same time, the evaluation tier of FHM now involves annual selection of follow-up studies in all regions of the nation. In response to growing information needs, FHM is evaluating an extension or intensification of the plot network and surveys in two special-interest populations. Recent concerns for the condition of the forest–urban interface surfaced mainly because of the catastrophic fire seasons from 1999 to 2002 when many homes were lost. At the same time, municipalities are placing increasing importance on reserves of forestland within their boundaries and are attempting to manage them in sustain- able ways. Since 2000, FHM has sponsored prototype tests of urban forest moni- toring in five states and is approaching a decision on operational deployment. There has also been a preliminary investigation of intensification of monitoring in riparian forests, the second special interest population. This effort is motivated by the require- ments of the NFS for integrated watershed-based monitoring of forest and water resources. Research continues to develop new indicators of forest health that directly address the Montréal Process framework for sustainable forest management. The initial focus of FHM was on air pollution, insects, and diseases, all of which are part of the framework, and the integration with timber inventory also made it possible to address indicators of forest extent and protected status. Research and prototype tests are underway for other criteria and indicators. Included are assessments of forest fragmentation as part of the biodiversity criterion and of invasive species and fire risk as part of the forest disturbance indicator. One research theme is to develop remotely sensed indicators of forest spatial patterns and fragmentation, and models for interpreting them. Other research is developing field procedures to survey and assess invasive species, and analytical procedures to estimate fuel loads and carbon sequestration from plot data. 30.6 FHM REPORTS The data flowing through the FHM program are now sufficient to produce meaningful statistical and interpretive reports for states, regions, and the nation. FHM cooper- ators including FIA and FHP are generally responsible for state and regional report- ing. In addition, the FHM program produces national level reports supporting the L1641_Frame_C30.fm Page 677 Tuesday, March 23, 2004 7:52 PM © 2004 by CRC Press LLC 678 Environmental Monitoring periodic Forest Service Strategic Planning and Resource Assessments, the Montréal Process, and a variety of other interagency and nongovernmental assessments. 42,43 We can give only a few examples of the many reports that have been developed using FHM data. The first two examples illustrate the operation of the detection and evaluation tiers of FHM. The 2001 FHM National Technical Report 42 used measurements from the plot network to identify apparently increased levels of dieback and mortality in some forests in Indiana in comparison to national averages. In a follow-up evaluation study, Stephen Krecik and Philip Marshall of the Indiana Department of Natural Resources analyzed the Indiana FHM data geographically, by species group and by forest type. 48 The changes in dieback were found to be inconsistent among forest types, and the increased mortality in some forest types was a false positive attributed to statistical estimation procedures and a small sample size. The index was high because of the mortality of a small number of relatively large trees, probably caused by known problems such as Dutch elm disease (fungus Ophiostoma ulmi ). The 2001 national FHM report also identified high levels of crown dieback on softwood tree species in northwest Wisconsin. Sally Dahir and Jane Cummings Carlson of the Wisconsin Department of Natural Resources combined historical information from aerial surveys and FIA timber inventories to evaluate the associ- ation among the current softwood dieback, the distribution of tree species, and six previous years of jack pine defoliation from the jack pine budworm ( Choristoneura pinus ). 49 The study concluded that the dieback observed on FHM plots was consistent with historical defoliation patterns and identified specific site and stand conditions to predict where future budworm outbreaks are most likely to occur. These two examples show that the first tier of monitoring is capable of detecting a strong signal of apparently unusual forest conditions, but also that baselines are not well estab- lished from only a few years of monitoring and that follow-up evaluations are critical to resolve whether the apparently unusual conditions are of concern or not. The studies also demonstrate the value of combining FHM data with supplemental data to interpret the information on a regional basis. FHM data are also combined with supplemental data to address national report- ing requirements. For example, the 2003 National Report on Sustainable Forests 50 required an assessment of the area of different forest types that are exposed to different levels of sulfate and nitrate deposition. The results are critical in assessing if air pollution is adversely affecting forests over large regions. FHM does not monitor air pollution exposure because that is done by the U.S. EPA. The FHM program prepared wet deposition maps from the EPA data and then combined them with a national forest type map. The map-based approach enabled the tabulation of the area of each forest type that was exposed to different levels of wet deposition, as required for national reporting purposes. 51 The next example demonstrates the ecological interpretation of FHM data with respect to a regional forest health issue. Over much of the Rocky Mountain region, there is a concern for the perpetuation of the aspen ( Populus tremuloides ) forest type. 52 A team of researchers in the Forest Service Interior West region used FHM and FIA plot data to document a regional pattern of aspen stand maturation and subsequent loss by natural succession. In-depth investigations suggested that the L1641_Frame_C30.fm Page 678 Tuesday, March 23, 2004 7:52 PM © 2004 by CRC Press LLC [...]... Sulfur 70 5 31.11.1.1 Sulfur Dioxide 70 6 31.11.1.2 Particulate Sulfate 70 7 31.11.2 Nitrogen 70 8 31.11.2.1 Nitric Acid 70 8 685 © 2004 by CRC Press LLC L1641_Frame_C31.fm Page 686 Tuesday, March 23, 2004 7: 53 PM 686 Environmental Monitoring 31.11.2.2 Particulate Nitrate 70 9 31.11.2.3 Total Nitrate 71 0 31.11.2.4 Particulate Ammonium 71 0 31.12 Deposition... L1641_Frame_C31.fm Page 70 5 Tuesday, March 23, 2004 7: 53 PM Clean Air Status and Trends Network (CASTNet) 70 5 0 .7 1.2 0.6 1 .7 0.6 1.3 1.8 2.2 1.3 2.2 2.0 0 2.8 2.5 2.8 3.1 3 .7 0.5 3.1 2 .7 4.8 4.3 4.8 4.2 4.6 4.6 4.9 5.4 5.1 4 .7 4.3 4.9 5.2 4.5 4 .7 4.5 4.5 5.1 4.5 4.8 4.9 5.9 0.5 0.6 0.5 0 .7 1.2 3.3 3.6 0.4 0.5 0.6 1.2 0.9 3.0 0 .7 0 .7 4 .7 4.6 1.1 3 .7 4.2 3.4 3.6 4.1 4.3 4.4 3.6 3 .7 4.2 1.0 3.2 Concentrations... CTH110 CAT 175 UVL124 MK G113 LAV410 STK138 LYK123 SAL133 R OM206 CAN4 07 QAK 172 R OM406 PIN414 GTH161 BVL130 KNZ184 OXF122 CDR119 VIN140 MC K131 ME V405 GRC 474 MA C426 CKT136 BEL116 ESP1 27 BWR139 SHN418 VPI120 PED108 CND1 25 CHE185 PET4 27 PAR1 07 MC K231 SPD1 11 PNF126 CDZ 171 JOT403 WSP144 AR E128 LRL1 17 DC P114 ALH1 57 DEV412 SEK402 ABT1 47 PSU106 CNT169 GRB411 KEF112 AN A115 YOS404 AC A416 HWF1 87 EGB181... (Continued) L1641_Frame_C31.fm Page 692 Tuesday, March 23, 2004 7: 53 PM 692 Environmental Monitoring TABLE 31.2 List of Active CASTNet Monitoring Stations (Continued ) Site ID Monitoring Station Agency State KEF112 LRL1 17 ARE128 MKG113 PSU106 ESP1 27 SPD111 PED108 VPI120 LYE145 PRK134 PAR1 07 CDR119 PND165 CNT169 DEN4 17 POF425 GRC 474 CHA4 67 JOT403 SEK402 PIN414 YOS404 LAV410 DEV412 MEV405 ROM406 EVE419... was prepared using an 0.2 1 .7 0.4 1.0 0.3 0 .7 1.3 1.9 1.0 1.2 1.2 0 .7 3 .7 2.2 3.0 3.6 6.3 0.3 10.2 8 .7 9.4 8.0 6.9 5.4 8.8 16.2 11.3 8.1 5.0 9.4 8.5 5.5 5.2 6.9 5.4 10.1 5.3 6.2 7. 3 6.1 3.0 0.3 0.5 0.2 0.5 0.4 4.0 4.4 4.1 0.2 0.2 0.5 0.9 0.4 1.3 0 .7 0.4 4.4 5.2 0.6 1.5 3.1 1.3 3.0 4.3 4.6 1 .7 1.2 2 .7 5.0 0.5 1.3 Concentrations 0 .7 12.0 6.0 4.0 1.0 0.5 0.2 1.8 1.0 0.4 0.4 0.4 27. 4 FIGURE 31.9 Annual mean... forest health monitoring program, Phytopathology, 82, 1152, 1992 17 Papp, M.L et al., FY91 Forest Health Monitoring Western Pilot Operations Report, EPA/600/X-92/009, U.S Environmental Protection Agency, Environmental Monitoring Systems Laboratory, Las Vegas, NV, 1992 18 Alexander, S.A et al., Forest Health Monitoring: 1991 Georgia Indicator Evaluation and Field Study, EPA/620/R-94/0 07, U.S Environmental. .. 71 0 31.12 Deposition of Sulfur and Nitrogen 71 0 31.13 Relative Contributions to Total Atmospheric Deposition .71 1 31.13.1 Sulfur Deposition 71 2 31.13.2 Nitrogen Deposition 71 2 31.14 Ozone Concentrations and Deposition 71 4 31.14.1 Eight-Hour Concentrations .71 4 31.15 Conclusion 71 5 References 71 7 31.1 INTRODUCTION The 1990 CAAA established the... 6 97 31.6.2 Deposition Flux Calculations and Aggregations 698 Quality Assurance 698 CASTNet Database 699 Limitations .699 Concentration Trends .70 0 31.10.1 Sulfur Dioxide 70 2 31.10.2 Particulate Sulfate 70 2 31.10.3 Nitric Acid 70 2 31.10.4 Particulate Ammonium 70 3 2002 Concentrations of Sulfur and Nitrogen 70 4 31.11.1... measuring tree height: an evaluation, Soc J Appl For., 18, 76 , 1994 21 Stapanian, M.A., Cline, S.P., and Cassell, D.L., Evaluation of a measurement method for forest vegetation in a large-scale ecological survey, Environ Monit Assess., 45, 2 37, 19 97 22 Tallent-Halsell, N.G., Ed., Forest Health Monitoring 1994 Field Methods Guide, EPA/620/R-94/0 27, U.S Environmental Protection Agency, Office of Research and... 691 TABLE 31.2 List of Active CASTNet Monitoring Stations Site ID Monitoring Station Agency SND152 CAD150 GTH161 ROM206 ABT1 47 IRL141 SUM156 GAS153 STK138 ALH1 57 BVL130 VIN140 SAL133 KNZ184 CKT136 MCK131 MCK231 BWR139 CDZ 171 BEL116 ASH135 HOW132 UVL124 HOX148 ANA115 CVL151 CND125 BFT142 COW1 37 PNF126 WST109 WSP144 CTH110 CAT 175 HWF1 87 CHE185 LYK123 OXF122 QAK 172 DCP114 EGB181 EGB281 Sand Mountain Caddo . Trends 70 0 31.10.1 Sulfur Dioxide 70 2 31.10.2 Particulate Sulfate 70 2 31.10.3 Nitric Acid 70 2 31.10.4 Particulate Ammonium 70 3 31.11 2002 Concentrations of Sulfur and Nitrogen 70 4 31.11.1 Sulfur 70 5 31.11.1.1. Deposition 71 1 31.13.1 Sulfur Deposition 71 2 31.13.2 Nitrogen Deposition 71 2 31.14 Ozone Concentrations and Deposition 71 4 31.14.1 Eight-Hour Concentrations 71 4 31.15 Conclusion 71 5 References 71 7 31.1. T1 47 WS P144 MK G113 PAR 1 07 AR E128 LR L1 17 C DR 119 HO W1 32 AS H135 C AT 175 WS T 109 HW F1 87 QAK 172 LY K123 OX F122 BF T142 PED108 DC P 1 1 4 AN A115 PNF126 IR L141 AL H1 57 E SP1 27 C DZ 171 CHE185 KNZ184 S