Recent global warming is acting across marine, freshwater, and terrestrial ecosystems to favor species adapted to warmer conditions and/or reduce the abundance of cold-adapted organisms (i.e., "thermophilization" of communities). Lack of community responses to increased temperature, however, has also been reported for several taxa and regions, suggesting that "climatic lags" may be frequent. Here we show that microclimatic effects brought about by forest canopy closure can buffer biotic responses to macroclimate warming, thus explaining an apparent climatic lag. Using data from 1,409 vegetation plots in European and North American temperate forests, each surveyed at least twice over an interval of 12-67 y, we document significant thermophilization of ground-layer plant communities. These changes reflect concurrent declines in species adapted to cooler conditions and increases in species adapted to warmer conditions. However, thermophilization, particularly the increase of warm-adapted species, is attenuated in forests whose canopies have become denser, probably reflecting cooler growing-season ground temperatures via increased shading. As standing stocks of trees have increased in many temperate forests in recent decades, local microclimatic effects may commonly be moderating the impacts of macroclimate warming on forest understories. Conversely, increases in harvesting woody biomass-e.g., for bioenergy-may open forest canopies and accelerate thermophilization of temperate forest biodiversity.climate change | forest management | understory | climatic debt | range shifts B iological signals of recent global warming are increasingly evident across a wide array of ecosystems (1-7). However, the temperature experienced by organisms at ground level (microclimate) can substantially differ from the atmospheric temperature due to local land cover and terrain variation in terms of vegetation structure, shading, topography, or slope orientation (8-15). The daytime or nighttime surface temperature in rough mountain terrain, for instance, can deviate by up to 9°C from the air temperature (10). Likewise, forest structure creates substantial temperature heterogeneity, with the interior daytime temperature in dense forests being commonly several degrees cooler than in more open habitats during the growing season (12-15). Spatial microclimatic temperature variation can thus be substantial relative to projected changes in average temperature over time, and biotic SignificanceAround the globe, climate warming is increasing the dominance of warm-adapted species-a process described as "thermophilization." However, thermophilization often lags behind warming of the climate itself, with some recent studies showing no response at all. Using a unique database of more than 1,400 resurveyed vegetation plots in forests across Europe and North America, we document significant thermophilization of understory vegetation. However, the response to macroclimate warming was attenuated in forests whose canopies have become denser. This microclima...

Questions: How can one explicitly quantify, and separately measure, stress and disturbance gradients? How do these gradients affect functional composition in early successional plant communities and to what extent? Can we accurately predict trait composition from knowledge of these gradients? Location: Southern Quebec, Canada. Methods: Using eight environmental variables measured in 48 early successional plant communities, we estimated stress and disturbance gradients through structural equation modelling. We then measured 10 functional traits on the most abundant species of these 48 communities and calculated their community-level mean and variance weighted by the relative abundance of each species. Finally, we related these community-weighted means and variances to the estimated stress and disturbance gradients using general linear models or generalized additive models. Results: We obtained a well-fitting measurement model of the stress and disturbance gradients existing in our sites. Of the 10 studied traits, only average plant reproductive height was strongly correlated with the stress (r 2 5 0.464) and disturbance (r 2 5 0.543) gradients. Leaf traits were not significantly related to either the stress or disturbance gradients. Conclusions: The well-fitting measurement model of the stress and disturbance gradients, combined with the generally weak trait-environment linkages, suggests that community assembly in these early successional plant communities is driven primarily by stochastic processes linked to the history of arrival of propagules and not to trait-based environmental filtering.

We evaluate the predictive power and generality of Shipley's maximum entropy (maxent) model of community assembly in the context of 96 quadrats over a 120-km2 area having a large (79) species pool and strong gradients. Quadrats were sampled in the herbaceous understory of ponderosa pine forests in the Coconino National Forest, Arizona, U.S.A. The maxent model accurately predicted species relative abundances when observed community-weighted mean trait values were used as model constraints. Although only 53% of the variation in observed relative abundances was associated with a combination of 12 environmental variables, the maxent model based only on the environmental variables provided highly significant predictive ability, accounting for 72% of the variation that was possible given these environmental variables. This predictive ability largely surpassed that of nonmetric multidimensional scaling (NMDS) or detrended correspondence analysis (DCA) ordinations. Using cross-validation with 1000 independent runs, the median correlation between observed and predicted relative abundances was 0.560 (the 2.5% and 97.5% quantiles were 0.045 and 0.825). The qualitative predictions of the model were also noteworthy: dominant species were correctly identified in 53% of the quadrats, 83% of rare species were correctly predicted to have a relative abundance of < 0.05, and the median predicted relative abundance of species actually absent from a quadrat was 5 x 10(-5).

Aim Biotic homogenization – the tendency for communities to converge in species composition – has occurred in many ecosystems, creating management challenges. The extent to which this convergence in species composition is related to convergence in trait composition (‘functional homogenization’), however, remains unresolved. Location North America, Wisconsin. Methods Using extensive plant community survey data from the 1950s and 2000s, and values for 11 traits measured on 169 species, we examined changes in functional beta diversity across 151 upland forest stands distributed across southern and northern Wisconsin. To estimate functional beta diversity, we used two recently developed pairwise functional dissimilarity metrics, plus an additive partitioning of functional diversity approach. Results Using pairwise functional dissimilarity metrics, we found no significant changes in functional beta diversity through time in either southern or northern upland forests. Under additive partitioning, species alpha diversity was lower than species beta diversity; whereas functional alpha diversity was much higher than functional beta diversity in both time periods and across all forest types. This suggests a high turnover of species but a low turnover of traits among communities. Main conclusions Although upland forests in Wisconsin have experienced taxonomic homogenization, they have not undergone functional homogenization, which may reflect a high functional redundancy among Wisconsin forest plants. As species decline further or disappear in response to habitat fragmentation and other global changes, functional redundancy may decline in a way that could diminish the functional diversity of Wisconsin's forests at both local and regional scales.

Summary 1.Although habitat fragmentation is recognized as a major threat to biodiversity, few studies have examined the relative importance of local, landscape and historical factors in controlling local species assemblages, and how these factors interact, in patchy ecosystems. We quantified the direct and indirect effects of patch size, patch heterogeneity, agricultural intensity and patch age on plant species richness and composition of forest patches embedded in agricultural landscapes. 2. In six 5 · 5 km-sampling landscape windows, we surveyed each forest patch for vascular plant species and collected three sets of independent variables, describing patch size and heterogeneity, landscape composition and history. The six windows were arranged along a gradient of agriculture intensity in rural landscapes of the Picardy region (N France). 3. We used non-metric multidimensional scaling (NMS) to detect major environmental gradients underlying variation in species composition among patches. We then constructed structural equation models (SEM) to quantify the direct and indirect effects of the three sets of variables on local plant diversity, which was successively incorporated as patch scores along the first three NMS axes, woody species richness, forest herb species richness, and non-forest herb species richness. 4. A major influence of the landscape matrix on local species composition was revealed by NMS and subsequent SEM, mainly through non-forest herb species, which explained most of the between patch floristic dissimilarity. Species richness increased with patch heterogeneity, whereas patch area never had a direct effect. Forest herbs were more responsive to patch age and connectivity than other species, whereas non-forest and woody species were more influenced by agriculture intensity in the surrounding matrix. 5. Synthesis. We used one of the largest data sets ever collected in temperate fragmented forests to build, for the first time, a structural model incorporating all suspected drivers of local plant communities. We showed that the number and identity of local species coexisting in successional fragments of a forest metacommunity at a given time is controlled by a unique combination of interacting local, landscape and historical factors. Preserving the largest, oldest fragments and favouring species movements in the surrounding matrix is the best way to conserve forest specialists in changing rural landscapes.

Questions: To what extent can Shipley et al.'s original maximum entropy model of trait‐based community assembly predict relative abundances of species over a large (3000 km2) landscape? How does variation in the species pool affect predictive ability of the model? How might the effects of missing traits be detected? How can non‐trait‐based processes be incorporated into the model? Location: Central England. Material and Methods: Using 10 traits measured on 506 plant species from 1308 1‐m2 plots collected over 3000 km2 in central England, we tested one aspect of Shipley et al.'s original maximum entropy model of “pure” trait‐based community assembly (S1), and modified it to represent both a neutral (S2) and a hybrid (S3) scenario of community assembly at the local level. Predictive ability of the three corresponding models was determined with different species pool sizes (30, 60, 100 and 506 species). Statistical significance was tested using a distribution‐free permutation test. Results: Predictive ability was high and significantly different from random expectations in S1. Predictive ability was low but significant in S2. Highest predictive ability occurred when both neutral and trait‐based processes were included in the model (S3). Increasing the pool size decreased predictive ability, but less so in S3. Incorporating habitat affinity (to indicate missing traits) increased predictive ability. Conclusions: The measured functional traits were significantly related to species relative abundance. Our results both confirm the generality of the original model but also highlight the importance of (i) taking into account neutral processes during assembly of a plant community, and (ii) properly defining the species pool.

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Plant traits are particularly important in determining plant community structure. However, how can one identify which traits are the most important in driving community assembly? Here we propose a method 1) to quantify the direction and strength of trait selection during community assembly and 2) to obtain parsimonious lists of traits that can predict species relative abundances in plant communities. We tested our method using floristic data from 32 plots experiencing different treatments (fertilisation and grazing) in southern France. Twelve functional traits were measured on 68 species. We determined the direction and strength of selection on these 12 traits using a metric derived from a maximum entropy model (i.e. lambda). We then determined our parsimonious list of traits using a backward selection of traits based on these lambda values (for all treatments and in each treatment separately). We finally compared our method to two other methods: one based on iterative RLQ and the other based on an entropy‐based forward selection of traits. We found major differences in the direction and strength of selection across the 12 traits and treatments. From the 12 traits, plant vegetative and reproductive heights, leaf dry matter content leaf nitrogen content, specific leaf area, and leaf phosphorus content were particularly important for predicting species relative abundances when considering all treatments together. Our method yielded results similar to those produced by the entropy‐based approach but differed from those produced by the iterative RLQ, whose selected traits could not significantly predict species relative abundances. Together these results suggest that the assembly of these communities is primarily driven by a small number of key functional traits. We argue that our method provides an objective way of determining a parsimonious list of traits that together accurately predict community structure and which, despite its complementarities with entropy‐based method, offers significant advantages.