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Thomas C. Edwards

Publications and source records attributed to Thomas C. Edwards.

20 records · Page 2Linked to original sources

Co-occurrence patterns of trees along macro-climatic gradients and their potential influence on the present and future distribution of Fagus sylvatica L.

During recent and future climate change, shifts in large-scale species ranges are expected due to the hypothesized major role of climatic factors in regulating species distributions. The stress-gradient hypothesis suggests that biotic interactions may act as major constraints on species distributions under more favourable growing conditions, while climatic constraints may dominate under unfavourable conditions. We tested this hypothesis for one focal tree species having three major competitors using broad-scale environmental data. We evaluated the variation of species co-occurrence patterns in climate space and estimated the influence of these patterns on the distribution of the focal species for current and projected future climates. Location: Europe. Methods: We used ICP Forest Level 1 data as well as climatic, topographic and edaphic variables. First, correlations between the relative abundance of European beech (Fagus sylvatica) and three major competitor species (Picea abies, Pinus sylvestris and Quercus robur) were analysed in environmental space, and then projected to geographic space. Second, a sensitivity analysis was performed using generalized additive models (GAM) to evaluate where and how much the predicted F. sylvatica distribution varied under current and future climates if potential competitor species were included or excluded. We evaluated if these areas coincide with current species co-occurrence patterns. Results: Correlation analyses supported the stress-gradient hypothesis: towards favourable growing conditions of F. sylvatica, its abundance was strongly linked to the abundance of its competitors, while this link weakened towards unfavourable growing conditions, with stronger correlations in the south and at low elevations than in the north and at high elevations. The sensitivity analysis showed a potential spatial segregation of species with changing climate and a pronounced shift of zones where co-occurrence patterns may play a major role. Main conclusions: Our Results: demonstrate the importance of species co-occurrence patterns for calibrating improved species distribution models for use in projections of climate effects. The correlation approach is able to localize European areas where inclusion of biotic predictors is effective. The climateinduced spatial segregation of the major tree species could have ecological and economic consequences.

Journal of Biogeography↗

Use of generalized linear models and digital data in a forest inventory of northern Utah

Forest inventories, like those conducted by the Forest Service's Forest Inventory and Analysis Program (FIA) in the Rocky Mountain Region, are under increased pressure to produce better information at reduced costs. Here we describe our efforts in Utah to merge satellite-based information with forest inventory data for the purposes of reducing the costs of estimates of forest population totals and providing spatial depiction of forest resources. We illustrate how generalized linear models can be used to construct approximately unbiased and efficient estimates of population totals while providing a mechanism for prediction in space for mapping of forest structure. We model forest type and timber volume of five tree species groups as functions of a variety of predictor variables in the northern Utah mountains. Predictor variables include elevation, aspect, slope, geographic coordinates, as well as vegetation cover types based on satellite data from both the Advanced Very High Resolution Radiometer (AVHRR) and Thematic Mapper (TM) platforms. We examine the relative precision of estimates of area by forest type and mean cubic-foot volumes under six different models, including the traditional double sampling for stratification strategy. Only very small gains in precision were realized through the use of expensive photointerpreted or TM-based data for stratification, while models based on topography and spatial coordinates alone were competitive. We also compare the predictive capability of the models through various map accuracy measures. The models including the TM-based vegetation performed best overall, while topography and spatial coordinates alone provided substantial information at very low cost.

Utah↗