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Fiscal uncertainties can sometimes affect national continuous forest monitoring efforts. One solution of interest is to lengthen the time it takes to collect a "full set" of plot data from five to 10 years in order to reduce costs. Here, we investigate using ancillary information to partially offset this proposed solution's negative effects. We focus our discussion on the corresponding number of years between measurements of each plot while we investigate how thoroughly the detrimental effects of the reduced sampling effort can be ameliorated with change estimates obtained from temporally-dense remotely-sensed images. We simulate measured plot data under four sampling error structures, and we simulate remotely-sensed change estimates under three reliability assumptions, integrated with assumptions about the additional unobserved growth resulting from the lengthened observation window. We investigate a number of estimation systems with respect to their ability to provide compatible annual estimates of the components of change during years spanned by at least half of the full set of plot observations. We show that auxiliary data with shorter observation intervals can contribute to a significant improvement in estimation. [ABSTRACT FROM AUTHOR]

Simple methods for estimating the proportion of land changing from forest to nonforest are developed. Variance estimators are derived to facilitate significance tests. A power analysis indicates that 400 inventory plots are required to reliably detect small changes in net or gross forest loss. This is an important result because forest certification programs may require additional precautions when wood from areas where forestland area loss is occurring is harvested or purchased. Net and gross forest area loss must be clearly differentiated to avoid confusion. Estimates of gross forest cover loss from satellite data should not be equated with net forest area loss, which can be better determined from remeasured forest inventory plots. Simultaneous tests of net and gross forest area loss should use multiple comparison procedures to ensure that overall error rates are correct. Examples of applications demonstrate how to properly perform these tests. A simulated example is used to verify that the variance estimators are reliable. An application to USDA Forest Service inventory data indicates that neither net nor gross forest loss at the state level was statistically significant for states that had sufficien remeasured plot data publicly available when this analysis was done. [ABSTRACT FROM AUTHOR]

The transitioning of land from forest to other uses is of increasing interest as urban areas expand and the world's population continues to grow. Also of interest, but less recognized, is the transitioning of land from other uses into forest. In this paper, we show how rates of conversion from forest to non-forest and non-forest to forest can be estimated in the US from a continuously improving publicly available annual forest inventory database, under varying definitions of conversion. Two estimation approaches are considered and contrasted. The approaches are a simple ratio estimator and the weighted maximum likelihood estimator. The latter involves a statistical procedure that incorporates the binomial nature of the indicator variables, the transition of mapped plot conditions and an intuitively appealing way to combine data from varying remeasurement periods for a temporally dependent variable. [ABSTRACT FROM PUBLISHER]

Managing the forest to store carbon is a relatively new concept. Various regional greenhouse gas initiatives and new Federal legislation are providing financial incentives for forest owners to manage for carbon in addition to other forest products. These incentives are intended for landowners who engage in activities that go beyond business as usual practices. Managing for carbon will likely involve foregoing other investment alternatives and increasing rotation lengths. The analysis approach demonstrated here provides a relatively simple method for an owner to compare traditional forest management and regular harvests with letting the trees grow to accumulate more carbon in the forest. Several financial decision statistics are considered and demonstrated with examples. A derivative of land expectation value, called rotation equivalent value, is shown to be a useful decision tool for comparing carbon storage with other management options having different rotation lengths. L'aménagement de la forêt pour emmagasiner du carbone est un concept relativement nouveau. Diverses initiatives régionales portant sur les gaz à effet de serre et une nouvelle législation fédérale incitent les propriétaires de forêts à aménager en fonction du carbone en plus des autres produits forestiers. Ces mesures incitatives s'adressent aux propriétaires terriens qui s'engagent dans des activités qui vont au-delà des pratiques traditionnelles. Aménager pour le carbone impliquera probablement de laisser de côté d'autres choix d'investissement et d'allonger la durée des rotations. L'approche d'analyse présentée ici fournit une méthode relativement simple pour qu'un propriétaire puisse comparer l'aménagement forestier traditionnel et les coupes régulières avec le fait de laisser croître les arbres pour accumuler plus de carbone dans la forêt. Plusieurs statistiques associées à la prise de décisions financières sont prises en compte et illustrées par des exemples. Une dérivée de la valeur d'attente du fonds, appelée valeur équivalente de rotation, s'avère un outil utile pour comparer l'emmagasinage du carbone avec d'autres options d'aménagement qui ont différentes durées de rotation. [ABSTRACT FROM AUTHOR]

In the past decade, the United States Department of Agriculture Forest Service's Forest Inventory and Analysis Program (FIA) has replaced regionally autonomous, periodic, state-wide forest inventories using various probability proportional to tree size sampling designs with a nationally consistent annual forest inventory design utilizing systematically spaced clusters of fixed-area plots. This has resulted in significant changes in the spatial-temporal distribution of observations on the nation's forest resource. This paper discusses the resulting changes in the observation of the distribution of tree diameters measured at 1.37 m above ground level. We show that in three of the four FIA regions, a significant portion of the upper end of the diameter distribution has thus far gone unobserved by the new inventory design. We conclude that the reason is not that the larger diameter trees have become less common but rather that there is a low enough probability of observing these trees that they are not being observed. This postulate is supported by the observation that large-diameter trees are not missing from the data acquired by the fourth FIA region (the Pacific Northwest), which uses an additional sampling mechanism for large-diameter trees. We explore the implications of this effect in addition to potential solutions. [ABSTRACT FROM PUBLISHER]

Alternative definitions for growth and removals from a forest being monitored over time are discussed. It is shown that the definitions that are used in practice may not be what one would expect and estimates can vary substantially under alternative definitions. This can result in conclusions about forest sustainability that may be misleading. Alternative definitions are applied to selected states using US Department of Agriculture Forest Service inventory data. Standard errors of growth over removals ratios are used to indicate potential sustainability problems for selected forest types. [ABSTRACT FROM AUTHOR]

The rate of land-use conversion from forest to nonforest or natural forest to forest plantation is of interest for forest certification purposes and also as part of the process of assessing forest sustainability. Conversion rates can be estimated from remeasured inventory plots in general, but the emphasis here is on annual inventory data. A new estimator is proposed based on analysis of plot-level variables that indicate when a change in forest condition occurs between inventory remeasurements. A weighted maximum likelihood estimator is derived that incorporates the binomial nature of the indicator variables, mapped plot conditions, and varying remeasurement periods. Example applications demonstrate the utility of the proposed methodology. This approach is broadly useful for estimating the annual rate of change from an initial condition to another condition from annual forest inventory data. [ABSTRACT FROM AUTHOR]

Forest inventory data are often summarized in tabular format where rows and columns represent levels of categorical variables. It is generally desirable to constrain tables based on different categories to sum to common totals. It may also be desirable to develop a system that incorporates stratification. Weights can be assigned to inventory plots to achieve these goals with weighted estimators. The justification for weighting is presented here along with approaches for defining reasonable weights. A weighted estimator is developed to constrain tables derived from mapped plot data to add to common totals. [ABSTRACT FROM AUTHOR]