Search

Abstract: A basal area growth system for single-species, even-aged maritime pine (Pinus pinaster Ait.) stands in Galicia (northwestern Spain) was developed from data of 212 plots measured between one and [...]

Knowledge of the diameter distribution structures in forestry is an important metric for efficient management of forest resources. This study reports the fitting of empirical diameter frequency distributions in natural stands of Brutian pine in Southern Turkey. Johnson's SB function was used as the theoretical distribution. Two distinct methodologies were used to obtain all four parameters that define the SB distribution families: a parameter recovery method (4-PRM); and a new approach based on full nonconditioned (that is, without restrictions) maximum likelihood estimation (FMLE). The nonconditional FMLE uses all the available observations of individual diameters of the trees, whereas the 4-PRM is supported by summaries of the diameter data; such as mean, median, and basal area. To the best knowledge of the authors, the full maximum likelihood approach was never attempted for the SB distribution. Adequacy of reproducing the empirical diameter distributions with both methods was analyzed, and assessment for quantitative differences or similitude's of adequacy of fitting among the two approaches was performed. Results show good performance of both 4-parameter estimation methods. The differences in the error index were not statistically significant among FMLE and 4-PRM with respect to the total basal area estimates. When the analysis was accomplished by diameter classes, statistically significant differences were registered, with the nonconditional FMLE performing better than the parameter recovery approach. The selection of one method is dependent on the detail of the available data and on the objectives. The major advantage of the 4-PRM over the FMLE relies on the reduced level of input information required. For description of actual diameter structures, the FMLE is the preferable method, allowing better mimicking of the empirical distribution with less computational efforts. [ABSTRACT FROM AUTHOR]

Studies of spatial patterns of landscapes are useful to quantify human impact, predict wildlife effects, or describe various landscape features. A robust landscape index should quantify two components of landscape diversity: composition and configuration. One category of landscape index is the contagion index. Some landscape ecologists promote the use of relative contagion indices. It is demonstrated, using simulated landscapes, that relativized contagion indices are mathematically untenable. A new entropy contagion index (G) is developed. Distributional properties of G are derived. It is shown to be asymptotically unbiased, consistent, and asymptotically normally distributed. A variance formula for G is derived using the delta method. As an application, the pattern and changes in forest types across four soil-geologic landform strata were analyzed on the 80,000 ha Savannah River Site in South Carolina, USA. One-way analysis of variance was used for hypothesis testing of contagion among strata. The differences in contagion across the strata provide insight to managers to meet structural objectives. [ABSTRACT FROM AUTHOR]

Studies of spatial patterns of landscapes are useful to quantify human impact, predict wildlife effects, or describe variability of landscape features. A common approach to identify and quantify landscape structure is with a landscape scale model known as a contagion index. A contagion index quantifies two distinct components of landscape diversity: composition and configuration. Some landscape ecologists promote the use of relative contagion indices. It is demonstrated that relativized contagion indices are mathematically untenable. Two new theoretical contagion indices, and , are derived using a mean value approach (i.e., statistical expected value) instead of entropy. Behavior of and was investigated with simulated random, uniform, and aggregated landscapes. They are shown to be well-behaved and sensitive to composition and configuration. Distributional properties of and are derived. They are shown to be asymptotically unbiased, consistent, and asymptotically normally distributed. Variance formulas for and are developed using the delta method. The new index models are used to examine landscape diversity on three physiographic provinces in Alabama by analyzing the pattern and changes in forest cover types over the recent past. In comparing and , use of in analysis of variance gave a more conservative test of contagion. [ABSTRACT FROM AUTHOR]