National Forest Health Monitoring Research Articles

Status and future of the forest health indicators program of the USA

For two decades, the US Department of Agriculture, Forest Service, has been charged with implementing a nationwide field-based forest health monitoring effort. Given its extensive nature, the monitoring program has been gradually implemented across forest health indicators and inventoried states. Currently, the Forest Service's Forest Inventory and Analysis program has initiated forest health inventories in all states, and most forest health indicators are being documented in terms of sampling protocols, data management structures, and estimation procedures. Field data from most sample years and indicators are available on-line with numerous analytical examples published both internally and externally. This investment in national forest health monitoring has begun to yield dividends by allowing evaluation of state/regional forest health issues (e.g., pollution and invasive pests) and contributing substantially to national/international reporting efforts (e.g., National Report on Sustainability and US EPA Annual Greenhouse Gas Estimates). With the emerging threat of climate change, full national implementation and remeasurement of a forest health inventory should allow for more robust assessment of forest communities that are undergoing unprecedented changes, aiding future land management and policy decisions.

Development of a protocol for monitoring status and trends in forest soil carbon at a national level

The national Forest Health Monitoring (FHM) program requires protocols for monitoring soil carbon contents. In a pilot study, 30 FHM plots loblolly/shortleaf ( Pinus taeda L./ Pinus echinata Mill.) pine forests across Georgia were sampled by horizon and by depth increments. For total soil carbon, approximately 40% of the variance was between plots, 40% between subplots and 20% within subplots. Results by depth differed from those obtained by horizon primarily due to the rapid changes in carbon content from the top to the bottom of the A horizon. Published soil survey information overestimated bulk densities for these forest sites. The measurement of forest floor depths as a substitute to sampling did not provide reliable estimates of forest floor carbon. Precision of replicate samples was approximately 10–30% for field duplicates and 5–10% for laboratory duplicates. Based on national indicator evaluation criteria, sampling by depth using bulk density core samplers has been recommended for national implementation. Additional procedures are needed when sampling organic soils or soils with a high percentage of large rock fragments.

Using forest health monitoring data to integrate above and below ground carbon information

The national Forest Health Monitoring (FHM) program conducted a remeasurement study in 1999 to evaluate the usefulness and feasibility of collecting data needed for investigating carbon budgets in forests. This study indicated that FHM data are adequate for detecting a 20% change over 10 years (2% change per year) in percent total carbon and carbon content (MgC/ha) when sampling by horizon, with greater than 80% probability that a change in carbon content will be determined when a change has truly occurred ( P⩽0.33). The data were also useful in producing estimates of forest floor and soil carbon stocks by depth that were somewhat lower than literature values used for comparison. The scale at which the data were collected lends itself to producing standing stock estimates needed for carbon budget development and carbon cycle modeling. The availability of site-specific forest mensuration data enables the exploration of above ground and below ground linkages.

Forest Health Monitoring Protocol Applied to Roadside Trees in Maryland

The Maryland Roadside Tree Law places trees in all public road rights-of-way in the State of Maryland, U.S., under the jurisdiction of the Maryland Department of Natural Resources-Forest Service. Passed in 1914, this law is one of the oldest tree conservation laws in the United States. However, little statistical data have ever been generated related to Maryland's roadside trees. This paper provides a methodology for assessing the condition of roadside trees by combining GIS tools, rights-of-way definitions, and components of a national forest health monitoring program. The assessment of roadside trees was carried out in six of Maryland's most urbanized jurisdictions. Results indicate that 14% of Maryland's roadsides are tree lined and that the trees are in good health based on crown and damage indicators collected. Shannon-Weaver index and importance values were calculated to describe species diversity. Views on the efficacy of the law in protecting roadside trees in light of the findings, and the findings themselves, are discussed.

Sampling ozone exposure of Canadian forests at different scales: some case studies.

The use of passive samplers in extensive monitoring, such as that used in national forest health monitoring plots, indicates that these devices are able to determine both spatial and temporal differences in ozone exposure of the plots. This allows for categorisation of the plots and the potential for cause-effect analysis of certain forest health responses. Forest exposure along a gradient of air pollution deposition demonstrates large variation in accumulated exposures. The efficacy of using passive samplers for in situ monitoring of forest canopy exposure was also demonstrated. The sampler data produced weak relationships with ozone values from the nearest "continuous" monitor, even though data from colocated samplers showed strong relationships. This spatial variation and the apparent effect of elevation on ozone exposure demonstrate the importance of topography and tree canopy characteristics in plant exposure on a regional scale. In addition, passive sampling may identify the effects of local pollutant gases, such as NO, which may scavenge ozone locally only to increase the production of this secondary pollutant downwind, as atmospheric reactions redress the equilibrium between concentrations of this precursor and those of the generated ozone. The use of passive samplers at the stand level is able to resolve vertical profiles within the stand and edge effects that are important in exposure of understorey and ground flora. Recent case studies using passive samplers to determine forest exposure to ozone indicate a great potential for the development of spatial models on a regional, landscape, and stand level scale.

Estimating mapped-plot forest attributes with ratios of means

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% straddle multiple conditions. The ratio-of-means estimator is developed as a method to obtain estimates of forest attributes from mapped plots, along with measures of variability useful for constructing confidence intervals. Basic inventory statistics from North and South Carolina were examined to see if these data satisfied the conditions necessary to qualify the ratio of means as the best linear unbiased estimator. It is shown that the ratio-of-means estimator is equivalent to the Horwitz-Thompson, the mean-of-ratios, and the weighted-mean-of-ratios estimators under certain situations.

Estimating mapped-plot forest attributes with ratios of means

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% straddle multiple conditions. The ratio-of-means estimator is developed as a method to obtain estimates of forest attributes from mapped plots, along with measures of variability useful for constructing confidence intervals. Basic inventory statistics from North and South Carolina were examined to see if these data satisfied the conditions necessary to qualify the ratio of means as the best linear unbiased estimator. It is shown that the ratio-of-means estimator is equivalent to the Horwitz-Thompson, the mean-of-ratios, and the weighted-mean-of-ratios estimators under certain situations.

Correlated Observer Errors and their Effects on Survey Estimates of Needle-Leaf Loss

Abstract In Europe, crown transparency is one of the most important variables assessed for monitoring forest conditions. Though there are very strict international guidelines and intensive training programs for the evaluation of needle-leaf loss, there still exists a subjective component in the evaluation. This subjective component in the observation process can lead to a nonsampling error that can greatly reduce the precision of estimates of average needle-leaf loss. In this paper, methods for quantifying the potential loss in precision are presented and applied to data from the Swiss National Forest Health Monitoring Program. For. Sci. 41(4):758-776.

ARNEWS assesses the health of Canada's forests

In 1984 the Canadian Forest Service (CFS) established the Acid Rain National Early Warning System (ARNEWS) to monitor the state of health of Canada's forests. This program was implemented by the CFS Forest Insect and Disease Survey (FIDS) who survey the plots annually and determine the causes of observed damage. For the period, 1984-1994, the survey indicates that there has been no large-scale decline in the health of Canada's forests. Insects, diseases and abiotic conditions have impacted forests, and isolated cases of damage caused by air pollution have been observed. The presence of unknown damage is also being investigated to determine if pollution is involved. The results of this survey support the need for a national forest health monitoring network as part of sustainable management of Canadian forests. Key words: forest health, forest surveys, sustainable forestry, ecosystem monitoring

Monitoring the health of forest ecosystems in the United States: Role of information management∗

The Forest Resource group of the U.S. Environmental Protection Agency's Environmental Monitoring and Assessment program is working closely with the U.S. Forest Service and other government agencies to establish a national Forest Health Monitoring (FHM) program. The FHM information management system is a key component contributing to the success of this program. Field data are collected using portable data recorders which permit on‐site data verification and reduce field data collection errors by over 90 percent. A sample tracking system provides control of field samples from the time they are collected through laboratory analysis. Electronic communication between field crews and an FHM mainframe computer allows for near real time data validation as well as electronic mail communications. A national FHM data base containing data from the four FHM regions is designed to meet the needs of diverse groups of users from FHM program managers and scientists to researchers from other public agencies, universities,...