Explore the vast range of titles available.

Despite a long history of the study of tropical forests, uncertainty about the importance of different ecological processes in shaping tropical tree species distributions persists. Trait- and phylogenetic-based tests of community assembly provide a powerful way to detect community assembly processes but have seldom been applied to the same community. Both methods are well suited to testing how the relative importance of different ecological processes changes with spatial scale. Here we apply both methods to the Yasuní Forest Dynamics Plot, a 25-ha Amazonian forest with >1100 tree species. We found evidence for habitat filtering from both trait and phylogenetic methods from small (25 m 2 ) to intermediate (10 000 m 2 ) spatial scales. Trait-based methods detected even spacing of strategies, a pattern consistent with niche partitioning or enemy-mediated density dependence, at smaller spatial scales (25-400 m 2 ). Simulation modeling of community assembly processes suggests that low statistical power to detect even spacing of traits at larger spatial scales may contribute to the observed patterns. Trait and phylogenetic methods tended to identify the same areas of the forest as being subject to habitat filtering. Phylogenetic community tests, which are far less data-intensive than trait-based methods, captured much of the same filtering patterns detected by trait-based methods but often failed to detect even-spacing patterns apparent in trait data. Taken together, it appears that both habitat associations and niche differentiation shape species co-occurrence patterns in one of the most diverse forests in the world at a range of small and intermediate spatial scales.

Foundation species structure forest communities and ecosystems but are difficult to identify without long-term observations or experiments. We used statistical criteria—outliers from size-frequency distributions and scale-dependent negative effects on alpha diversity and positive effects on beta diversity—to identify candidate foundation woody plant species in 12 large forestdynamics plots spanning 26 degrees of latitude in China. We used these data (1) to identify candidate foundation species in Chinese forests, (2) to test the hypothesis—based on observations of a midlatitude peak in functional trait diversity and high local species richness but few numerically dominant species in tropical forests—that foundation woody plant species are more frequent in temperate than tropical or boreal forests, and (3) to compare these results with data from the Americas to suggest candidate foundation genera in northern hemisphere forests. Using the most stringent criteria, only two species of Acer, the canopy tree Acer ukurunduense and the shrubby treelet Acer barbinerve, were identified in temperate plots as candidate foundation species. Using more relaxed criteria, we identified four times more candidate foundation species in temperate plots (including species of Acer, Pinus, Juglans, Padus, Tilia, Fraxinus, Prunus, Taxus, Ulmus, and Corlyus) than in (sub)tropical plots (the treelets or shrubs Aporosa yunnanensis, Ficus hispida, Brassaiopsis glomerulata, and Orophea laui). Species diversity of co-occurring woody species was negatively associated with basal area of candidate foundation species more frequently at 5- and 10-m spatial grains (scale) than at a 20-m grain. Conversely, Bray-Curtis dissimilarity was positively associated with basal area of candidate foundation species more frequently at 5-m than at 10- or 20-m grains. Both stringent and relaxed criteria supported the hypothesis that foundation species are more common in mid-latitude temperate forests. Comparisons of candidate foundation species in Chinese and North American forests suggest that Acer be investigated further as a foundation tree genus

1. Many forests experience periodic, large-scale disturbances, such as hurricanes and cyclones, which open the forest canopy, causing dramatic changes in understorey light conditions and seedling densities. Thus, in hurricane-impacted forests, large variations in abiotic and biotic conditions likely shape seedling dynamics, which in turn will contribute to patterns of forest recovery. 2. We monitored 13 836 seedlings of 82 tree and shrub species over 10 years following Hurricane Georges in 1998 in a subtropical, montane forest in Puerto Rico. We quantified changes in the biotic and abiotic environment of the understorey and linked seedling dynamics to changes in canopy openness and seedling density, and to spatial variation in soil type, topography and tree density. 3. Canopy openness was highest when first measured after Hurricane Georges and dropped significantly within c. 3 years, while seedling densities remained high for c. 5 years post-hurricane. When all species and census intervals were analysed together, generalized linear mixed effects models revealed that canopy openness, seedling and adult tree densities were significant drivers of seedling survival. 4. The relative importance of abiotic and biotic factors changed over time. Separate analyses for each census interval revealed that canopy openness was a significant predictor of survival only for the first census interval, with lower survival at the highest levels of canopy openness. The effect of conspecific seedling density was significant in all intervals except the first, and soil type only in the final census interval. 5. When grouping species into life-history guilds based on adult tree susceptibility to hurricane damage, we found clear differences among guilds in the effects of biotic and abiotic factors on seedling survival. Seedlings of hurricane-susceptible and intermediate guilds were more strongly influenced by canopy openness, while seedlings of the hurricane-resistant group were less affected by conspecific seedling density. Individual species-level analyses for 12 common species, however, showed considerable variation among species within guilds. 6. Synthesis. Our results suggest that hurricanes shape species composition by altering understorey conditions that differentially influence the success of seedlings. Thus, predicted increases in the intensity and frequency of hurricanes in the Caribbean will likely alter seedling dynamics and ultimately the species composition in hurricane-impacted forests.

Tropical forests have long been thought to be in stable state, but recent insights indicate that global change is leading to shifts in forest dynamics and species composition. These shifts may be driven by environmental changes such as increased resource availability, increased drought stress, and/or recovery from past disturbances. The relative importance of these drivers can be inferred from analyzing changes in trait values of tree communities. Here, we evaluate a decade of change in species and trait composition across five old-growth Neotropical forests in Bolivia, Brazil, Guyana, and Costa Rica that cover large gradients in rainfall and soil fertility. To identify the drivers of compositional change, we used data from 29 permanent sample plots and measurements of 15 leaf, stem, and whole-plant traits that are important for plant performance and should respond to global change drivers. We found that forests differ strongly in their community-mean trait values, resulting from differences in soil fertility and annual rainfall seasonality. The abundance of deciduous species with high specific leaf area increases from wet to dry forests. The community-mean wood density is high in the driest forests to protect xylem vessels against drought cavitation, and is high in nutrient-poor forests to increase wood longevity and enhance nutrient residence time in the plant. Interestingly, the species composition changed over time in three of the forests, and the community-mean wood density increased and the specific leaf area decreased in all forests, indicating that these forests are changing toward later successional stages dominated by slow-growing, shade-tolerant species. We did not see changes in other traits that could reflect responses to increased drought stress, such as increased drought deciduousness or decreased maximum adult size, or that could reflect increased resource availability (CO2, rainfall, or nitrogen). Changes in species and trait composition in these forests are therefore most likely caused by recovery from past disturbances. These compositional changes may also lead to shifts in ecosystem processes, such as a lower carbon sequestration and \"slower\" forest dynamics.

Assessing the persistent impacts of fragmentation on aboveground structure of tropical forests is essential to understanding the consequences of land use change for carbon storage and other ecosystem functions. We investigated the influence of edge distance and fragment size on canopy structure, aboveground woody biomass (AGB), and AGB turnover in the Biological Dynamics of Forest Fragments Project (BDFFP) in central Amazon, Brazil, after 22+ yr of fragment isolation, by combining canopy variables collected with portable canopy profiling lidar and airborne laser scanning surveys with long-term forest inventories. Forest height decreased by 30% at edges of large fragments (>10 ha) and interiors of small fragments (<3 ha). In larger fragments, canopy height was reduced up to 40 m from edges. Leaf area density profiles differed near edges: the density of understory vegetation was higher and midstory vegetation lower, consistent with canopy reorganization via increased regeneration of pioneers following post-fragmentation mortality of large trees. However, canopy openness and leaf area index remained similar to control plots throughout fragments, while canopy spatial heterogeneity was generally lower at edges. AGB stocks and fluxes were positively related to canopy height and negatively related to spatial heterogeneity. Other forest structure variables typically used to assess the ecological impacts of fragmentation (basal area, density of individuals, and density of pioneer trees) were also related to lidar-derived canopy surface variables. Canopy reorganization through the replacement of edge-sensitive species by disturbance-tolerant ones may have mitigated the biomass loss effects due to fragmentation observed in the earlier years of BDFFP. Lidar technology offered novel insights and observational scales for analysis of theecological impacts of fragmentation on forest structure and function, specifically aboveground biomass storage.

Clustering at multiple critical scales may be common for plants since many different factors and processes may cause clustering. This is especially true for tropical rain forests for which theories explaining species coexistence and community structure rest heavily on spatial patterns. We used point pattern analysis to analyze the spatial structure of Shorea congestiflora, a dominant species in a 25-ha forest dynamics plot in a rain forest at Sinharaja World Heritage Site (Sri Lanka), which apparently shows clustering at several scales. We developed cluster processes incorporating two critical scales of clustering for exploring the spatial structure of S. congestiflora and interpret it in relation to factors such as competition, dispersal limitation, recruitment limitation, and Janzen-Connell effects. All size classes showed consistent large-scale clustering with a cluster radius of ∼25 m. Inside the larger clusters, small-scale clusters with a radius of 8 m were evident for recruits and saplings, weak for intermediates, and disappeared for adults. The pattern of all trees could be divided into two independent patterns: a random pattern (nearest neighbor distance > 8 m) comprising ∼12% of the trees and a nested double-cluster pattern. This finding suggests two independent recruitment and/or seed dispersal mechanisms. Saplings were several times as abundant as recruits and may accumulate several recruit generations. Recruits were only weakly associated with adults and occupied about half of the large-scale clusters, but saplings almost all. This is consistent with recruitment limitation. For ∼70% (95%) of all juveniles the nearest adult was less than 26 m away (53 m), suggesting a dispersal limitation that may also be related to the critical large-scale clustering. Our example illustrates the manner in which the use of a specific and complex null hypothesis of spatial structure in point pattern analysis can help us better understand the biology of a species and generate specific hypotheses to be further investigated in the field.

Questions: What drives individual species–area relationships in temperate coniferous forests? Location: Two 25.6-ha forest plots on the Pacific Slope of North America, one in California, and one in Washington State. Methods: We mapped all trees ≥1 cm in diameter and examined tree species diversity of their local neighbourhoods by calculating the individual species–area relationship for each species and for each of three diameter classes (saplings, mature trees and large-diameter trees). Results: In the California plot, small trees in four of the five major species occurred in neighbourhoods with higher levels of diversity than would be expected at random. In the Washington plot, small trees for four of five abundant species had neighbourhoods with lower than expected diversity at distances ≤5 m for small trees. However, at distances >5 m, all five species showed higher than expected diversity in their neighbourhoods. Larger trees at both plots tended to occur in neighbourhoods with lower than expected diversity, and no large-diameter focal species had neighbourhoods with higher than expected diversity. Conclusion: Diversity and co-existence in temperate conifer-dominated forests do not appear to be the result of random processes. Competitive interactions appear to dominate for the largest trees of most species, resulting in neighbourhoods with lower diversity. For smaller trees, we suggest that a positive response to environmental heterogeneity is the likely driver of neighbourhoods with higher than expected diversity, although we cannot rule out the possibility that facilitation or conspecific negative density dependence (CNDD) also play a role.

Dynamic forest models are a key tool to better understand, assess, and project decadal‐ to centennial‐scale forest dynamics. Despite their success, many questions regarding appropriate model formulations remain unresolved, and few models have found widespread application, for example, across a whole continent. We aimed to scrutinize the representation of ecological processes in dynamic forest models so as to rigorously test core assumptions underlying forest dynamics and the consistency of their interplay, taking the ForClim model as a case study. We developed a set of alternative representations for the main ecological processes, that is, tree establishment, growth, and mortality, and light extinction through the canopy, based on diverse sources of empirical data. We applied a pattern‐oriented modeling (POM) approach to test all combinations of the standard and alternative formulations (>500 model versions) against a comprehensive set of patterns for diverse model applications across a wide range of site conditions. We found that adapting one process in isolation can improve model performance for one specific application. However, the best model versions typically included more than one alternative formulation. Importantly, the best version for an individual application was generally not the best across multiple applications, emphasizing the varying influences of ecological processes. We conclude that the behavior and performance of complex models should not be analyzed for a few specific applications only. Rather, multiple applications, system states, and dynamics of interest should be scrutinized across a wide range of site conditions. This allows for avoiding overfitting and detecting and eliminating structural shortcomings and parameterization problems. We thus propose to make use of the ever‐increasing data availability and the POM framework to challenge the core processes of dynamic models in a holistic manner. For model applications, we propose that a set of alternative formulations (ensemble simulations) should be used to quantify the impacts of structural uncertainty, rather than to rely on the projections from one single model version.