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 national reports that evaluate spatial pattern and temporal trends in forest biodiversity, air quality, and climate. Data collection and management follow standard national protocols. A lichen species richness index (the number of species per FIA plot) is available for all areas soon after data collection. Air quality and climate indexes (for defined regional gradients and based on lichen species composition at plots) are developed from an FIA lichen gradient model. Critical steps in standard data analysis include screening plots to exclude biased data, selection of appropriate populations, then analysis, presentation, and interpretation of data.

"Forest Inventory and Analysis. The Forest Service Forest Inventory and Analysis (FIA) Program is the Nations continuous forest census. Since 1930, we have collected, analyzed, and reported information on the status and trends of Americas forests: how much forest exists, where it exists, who owns it, and how it is changing growing, dying, or being harvested. In response to widening customer interests, the FIA Program is developing a core program that will be implemented in the same manner on all U.S. forest lands. It includes sampling an extended suite of forest health indicators. The purpose of this brochure is to describe these health indicators: what we are measuring, why we believe these measurements are important, how we collect and interpret the data, and examples of what we have found to date. The FIA indicators discussed in this brochure are: crown condition, ozone injury, tree damage, tree mortality, lichen communities, down woody debris, vegetation diversity and structure, soil condition.

The Forest Inventory and Analysis (FIA) program of the U.S. Forest Service collects vast amounts of field data to assess the condition and trends of the nations forest resources. A quality assurance (QA) program is implemented to assure that data are collected accurately with consistent protocols. A random subset of field plots is chosen to receive an additional, independent measurement by another field crew. This blind check approach allows for comparison of measurements between the two crews. The measurement differences are evaluated against measurement quality objectives (MQO), which specify a level of measurement precision for each attribute. In this report, differences in repeated measurements from blind check data are analyzed to assess the quality of forest health data nationwide. For the understory vegetation indicator, the ground cover variables attained the MQO or were slightly below the desired level. Variables related to canopy and species identifcation were substantially below the MQO. Tree crown attributes that effectively met the MQO include crown light exposure, crown dieback, and foliage transparency. The uncompacted crown ratio, vigor class, and crown density measurements did not attain the MQO standards. Quality assessment for the lichen indicator is evaluated using a second measurement by an expert and not an independent measurement by another field crew. Overall, the MQO was not attained, although compliance improved over time and western regions were close to achieving the standard. Most variables measured for the down woody material indicator were below MQO standards. Due to the sampling protocols for the ozone indicator, direct analyses of MQO attainment are not possible. Mean biosite index was not significantly different between crews, although there were some large discrepancies on individual plots. There was agreement on presence/absence of ozone damage for about 80 percent of the plots. For field measurements of forest soils, 10 of the 12 variables attained the MQO. Although MQOs are not specifically stated for laboratory analyses of soil properties, comparisons were performed to assess the variability of lab measurements.

Lichens are highly valued ecological indicators known for their sensitivity to a wide variety of environmental stressors like air quality and climate change. This report summarizes baseline results from the U.S. Department of Agriculture, Forest Service, Forest Inventory and Analysis (FIA) Lichen Community Indicator covering the first full cycle of data collection (1998-2001, 2003) for Washington, Oregon, and California. During this period, FIA conducted 972 surveys of epiphytic macrolichen communities for monitoring both spatial and long-term temporal trends in forest health. Major research findings are presented with emphasis on lichen biodiversity as well as bioindication of air quality and climate. Considerable effort is devoted to mapping geographic patterns and defining lichen indicator species suitable for estimating air quality and climate.

This annual Forest Inventory and Analysis (FIA) Fiscal Year 2015 business report (#18) will tell you, the taxpayers, partners, and clients what the program has accomplished with the financial resources provided and what the program will accomplish in the coming year with budgeted financial resources. This relationship with taxpayers, partners, and clients is integral to FIA's continued success, because accountability is their first priority. Some key findings of this annual report are: Annualized progress, Funding, Partners' support, Grants and agreements, Data availability, Five-year reports, Quality assurance, Users groups, Personnel, Other program features, New FIA Strategic Plan, Looking to 2016. This information can be used in many ways, such as evaluating wildlife habitat conditions, assessing sustainability of current ecosystem management practices, monitoring forest health, supporting planning and decision-making activities undertaken by public and private enterprises, and predicting the effects of climate change. Related products: Soil Manual Survey --New --2017 can be found here: https://bookstore.gpo.gov/products/soil-survey-manual-march-2017 Forest Health Monitoring: National Status, Trends, and Analysis, 2014 can be found here: https://bookstore.gpo.gov/products/sku/001-000-04768-0?ctid=819 National Individual Tree Species Atlas can be found at this link: https://bookstore.gpo.gov/products/sku/001-001-00703-0?ctid=819 Christmas Tree Pest Manual can be found at this link: https://bookstore.gpo.gov/products/sku/001-000-04764-7?ctid=819 Other products available from the United States Forest Service can be found at this link: https://bookstore.gpo.gov/agency/819 Environment & Nature publications can be found here: https://bookstore.gpo.gov/catalog/environment-nature Department of Agriculture (USDA) publications can be found here: https://bookstore.gpo.gov/agency/department-agriculture-usda

Lichens are highly valued ecological indicators known for their sensitivity to a wide variety of environmental stressors like air quality and climate change. This report summarizes baseline results from the U.S. Department of Agriculture, Forest Service, Forest Inventory and Analysis (FIA) Lichen Community Indicator covering the first full cycle of data collection (1998-2001, 2003) for Washington, Oregon, and California. During this period, FIA conducted 972 surveys of epiphytic macrolichen communities for monitoring both spatial and long-term temporal trends in forest health. Major research findings are presented with emphasis on lichen biodiversity as well as bioindication of air quality and climate. Considerable effort is devoted to mapping geographic patterns and defining lichen indicator species suitable for estimating air quality and climate.

Development of a regional lichen gradient model from community data is a powerful tool to derive lichen indexes of response to environmental factors for large-scale and long-term monitoring of forest ecosystems. The Forest Inventory and Analysis (FIA) Program of the U.S. Department of Agriculture Forest Service includes lichens in its national inventory of forests of the United States, to help monitor the status of forested ecosystems. Development of a model for a specific region to calculate lichen response indexes that are correlated with air quality and major climate factors, and are also independent of each other, is a critical step in achieving program goals. These indexes are the primary lichen bioindicators used in FIA for assessing regional patterns and monitoring trends of lichen response to environment over time. This general approach is also applicable to other monitoring efforts. A first step in the modeling process is to identify an appropriate geographic region for a model. Unconstrained ordination alone, or combined with indicator species analysis followed by regression analysis, are two approaches borrowed from plant ecology that have been shown to generate successful regional lichen gradient models. Calculation of lichen response indexes for new plots not part of the original model is necessary to support long-term monitoring. We explain the rationale for recommended approaches, describe in detail the recommended steps in the modeldevelopment process, and explain how to document and evaluate results, all to support successful application of a model for monitoring. A template is included for documenting a model and archiving all products necessary to understand and apply it, as is required for each FIA model.

The book embodies the detailed account about unique symbionts i.e. LICHENS in ecosystem monitoring. The first chapter deals with unique characteristics features of lichens which facilitate their survival in extreme climates and makes them an ideal organism for ecosystem monitoring. Biosynthesis of secondary metabolites are known to protect lichens against increasing environmental stresses therefore second chapter provides insight into various chromatographic and modern spectroscopic techniques involved in separation and characterization of lichen substances. The third chapter elaborates the criteria for selection of biomonitoring species and characters of host plant that influences lichen diversity and details about different lichen species utilized for biomonitoring. One can retrieve preliminary information about the air quality based on the lichen community structure and distribution of bioindicator species as lichen communities/indicator species provides valuable information about the natural/anthropogenic induced changes in the microclimate and land-use changes due to human activity. Therefore, for identification of species, a key to genera and species provides concise information to identify the lichen species based on their morphological and anatomical characters and chemicals present. Keys provided in Chapter 4 will help the beginners to identify some common lichen species based on the distribution in different climatic zones of India. The section also provides comprehensive information about the bioindicator communities and bioindicator species from India. Chapter 5 provides the details of factors affecting the ecosystem (natural as well as anthropogenic disturbances) and role of lichens in ecosystem monitoring in India has been discussed in detail. Chapter 6 discusses the need and utility of indicator species especially lichen biomonitoring data in sustainable forest management and conservation. The content about lichens in biomonitoring will be a valuable resource for researchers from different fields and will provide an essential reference for people interested in lichens and its role in ecosystem monitoring. The book will also hopefully popularize lichenological studies in India and will generate more active participation of lichen biomonitoring studies in management and conservation of natural resources in India.