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Abstract: The Northwest Forest Plan (NWFP), which aims to conserve late-successional and old-growth forests (older forests) and associated species, established new policies on federal lands in the Pacific Northwest USA. As part of monitoring for the NWFP, we tested nearest-neighbor imputation for mapping change in older forest, defined by threshold values for forest attributes that vary with forest succession. We mapped forest conditions on >19millionha of forest for the beginning (Time 1) and end (Time 2) of a 13-year period using gradient nearest neighbor (GNN) imputation. Reference data were basal area by species and size class from 17,000 forest inventory plots measured from 1993 to 2008. Spatial predictors were from Landsat time-series and GIS data on climate, topography, parent material, and location. The Landsat data were temporally normalized at the pixel level using LandTrendr algorithms, which minimized year-to-year spectral variability and provided seamless multi-scene mosaics. We mapped older forest change by spatially differencing the Time 1 and Time 2 GNN maps for average tree size (MNDBH) and for old-growth structure index (OGSI), a composite index of stand age, large live trees and snags, down wood, and diversity of tree sizes. Forests with higher values of MNDBH and OGSI occurred disproportionately on federal lands. Estimates of older forest area and change varied with definition. About 10% of forest at Time 2 had OGSI >50, with a net loss of about 4% over the period. Considered spatially, gross gain and gross loss of older forest were much greater than net change. As definition threshold value increased, absolute area of mapped change decreased, but increased as a percentage of older forest at Time 1. Pixel-level change was noisy, but change summarized to larger spatial units compared reasonably to known changes. Geographic patterns of older forest loss coincided with areas mapped as disturbed by LandTrendr, including large wildfires on federal lands and timber harvests on nonfederal lands. The GNN distribution of older forest attributes closely represented the range of variation observed from a systematic plot sample. Validation using expert image interpretation of an independent plot sample in TimeSync corroborated forest changes from GNN. An advantage of imputed maps is their flexibility for post-classification, summary, and rescaling to address a range of objectives. Our methods for characterizing forest conditions and dynamics over large regions, and for describing the reliability of the information, should help inform the debate over conservation and management of older forest. [Copyright &y& Elsevier]

Landscape structure in the Eastern US experienced great changes in the last century with the expansion of forest cover into abandoned agricultural land and the clearing of secondary forest cover for urban development. In this paper, the spatial and temporal patterns of forest cover from 1914 to 2004 in the Gwynns Falls watershed in Baltimore, Maryland were quantified from historic maps and aerial photographs. Using a database of forest patches from six times-1914, 1938, 1957, 1971, 1999, and 2004-we found that forest cover changed, both temporally and spatially. While total forest area remained essentially constant, turnover in forest cover was very substantial. Less than 20% of initial forest cover remained unchanged. Forest cover became increasingly fragmented as the number, size, shape, and spatial distribution of forest patches within the watershed changed greatly. Forest patch change was also analyzed within 3-km distance bands extending from the urban core to the more suburban end of the watershed. This analysis showed that, over time, the location of high rates of forest cover change shifted from urban to suburban bands which coincides with the spatial shift of urbanization. Forest cover tended to be more stable in and near the urban center, whereas forest cover changed more in areas where urbanization was still in process. These results may have critical implications for the ecological functioning of forest patches and underscore the need to integrate multi-temporal data layers to investigate the spatial pattern of forest cover and the temporal variations of that spatial pattern. [ABSTRACT FROM AUTHOR]

The relative importance of macro- and micro-scale processes in the biosphere is controversial, with some researchers emphasizing micro-scale population dynamics and others macro-scale landscape dynamics. I hypothesize that there is spatial variation in the linkage between and importance of macro- and micro-environmental influences on vegetation, and explore this hypothesis in a case study of riparian vegetation in the mountains of western Colorado. I estimate percent cover, by species, in 115- 0.1 ha samples of riparian vegetation at relatively undisturbed sites. Environmental variables measured at each site include several channel characteristics, valley characteristics, geographical coordinates, and drainage basin characteristics. I determine major gradients in vegetation variation by Bray-Curtis ordination and interpret the gradients by correlating ordination axis scores with the values of environmental variables measured at each site. The first ordination axis is a complex gradient related to elevation, drainage basin variables, and channel width. The second axis correlates with stream gradient and sinuosity. When the overall data matrix is broken into four parts, by cluster analysis, separate ordinations of each part reveal that the vegetation varies along distinct gradients in each part, with macro-environmental variables important in some parts and micro-environmental variables important in others. The nature of the link between macro- and micro-environments varies spatially, as hypothesized, and may be temporally transient. [ABSTRACT FROM AUTHOR]