Burn severity can be mapped using satellite data to detect changes in forest structure and moisture content caused by fires. The 2001 Leroux fire on the Coconino National Forest, Arizona, burned over 18 pre-existing permanent 0.1 ha plots. Plots were re-measured following the fire. Landsat 7 ETM+ imagery and the Differenced Normalized Burn Ratio (ΔNBR) were used to map the fire into four severity levels immediately following the fire (July 2001) and 1 year after the fire (June 2002). Ninety-two Composite Burn Index (CBI) plots were compared to the fire severity maps. Pre- and post-fire plot measurements were also analysed according to their imagery classification. Ground measurements demonstrated differences in forest structure. Areas that were classified as severely burned on the imagery were predominantly Pinus ponderosa stands. Tree density and basal area, snag density and fine fuel accumulation were associated with severity levels. Tree mortality was not greatest in severely burned areas, indicating that the ΔNBR is comprehensive in rating burn severity by incorporating multiple forest strata. While the ΔNBR was less accurate at mapping perimeters, the method was reliable for mapping severely burned areas that may need immediate or long-term post-fire recovery.

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Summary1. Climatic constraints on plant distributions are well known, but predicting community composition through knowledge of trait-based environmental filtering remains an important empirical challenge. Here, we evaluate the maximum entropy (MaxEnt) model of trait-based community assembly using forest communities occurring along a 12°C gradient of mean annual temperature (MAT).We use independent cross-validation to evaluate model predictions from sites where trait constraints are predicted from environmental conditions. We also test whether orthogonal axes of trait variation can be used as predictors to improve model parsimony and explore MaxEnt forecasts of species distributions in a warmer climate. 2. Environmental factors explained between 31% and 74% of the community-weighted mean trait values, indicating moderate-to-strong selection of traits along the environmental gradients. A model with 10 traits explained 54% of the variation in observed relative abundances, which approached the upper limit of 57% given the available environmental information. Three orthogonal axes accounted for 81% of the trait variation among species, and environmental factors explained between 47% and 67% of the variation in these axes. However, the axes only explained 18% of the variation in relative abundances, suggesting that minor axes of functional variation may be important or that models with many traits may achieve good predictive capacity through overfitting. 3. Trait-environment relationships formed the basis for predicting vegetation change in a future scenario where MAT was increased by 2.5°C. The results suggested that up to 78% of Pinus ponderosa forest in Arizona may transition to dominance by Juniperus monosperma, but this forecast likely overestimates the rates of species migration. 4. Synthesis. MaxEnt is a mathematical translation of trait-based environmental filtering of the species pool and performs moderately well in predicting forest community structure using empirical trait-environment relationships. MaxEnt required many traits to achieve good fits, and three orthogonal axes of trait variation performed poorly as predictors of community structure. To be useful predictors, traits must vary strongly among species and community-weighted mean traits must vary predictably along environmental gradients.

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Summary 1.More than a century of forest management, including fire exclusion, livestock grazing and tree harvesting, may have affected forest structure and composition in south-western USA. Dendroecological techniques were used to reconstruct an 1876 baseline against which modern conditions could be compared. We assessed the magnitude of changes on the San Francisco Peaks in five distinct forest types: ponderosa, mixed conifer, aspen, spruce-fir and bristlecone. 2. We established a systematic grid of 135 plots, each 0·1 ha in size, over a 1117-m altitudinal band. 3. In the contemporary forest, density was greatest in spruce-fir and least in bristlecone whereas basal area was greatest in spruce-fir and lowest in ponderosa. In 1876, all forest types had significantly lower densities and basal areas. 4. The period since 1876 was associated with increased forest density, a shift in species composition as a result of invasion of shade-tolerant conifers, and a trend for mesic species to migrate to lower altitudes. Changes were least evident in the highest altitude forests. Climate and human-caused and natural biotic disturbance factors probably all played a role in forest change, but we argue that the most prominent factor was probably exclusion of the thinning effect of fire, especially on fire-susceptible mesic species. 5. Synthesis and applications. Mesic species have encroached to lower altitudes and forest density has increased since 1876. These changes have created to conditions opposite to those suitable for warmer, drier future climates that will display increased fire risk, setting the stage for sudden and severe change. Management is complex because of heavy fuel loading, administrative constraints and high public visibility. However, 'sky island' landscapes such as the Peaks represent protected ecosystems of great importance in arid regions. Testing of wildland fire use and other management interventions to restore composition and fuel structures more resilient to warmer climate should proceed.