Explore the vast range of titles available.

Aim: Tropical forests account for a quarter of the global carbon storage and a third of the terrestrial productivity. Few studies have teased apart the relative importance of environmental factors and forest attributes for ecosystem functioning, especially for the tropics. This study aims to relate aboveground biomass (AGB) and biomass dynamics (i.e., net biomass productivity and its underlying demographic drivers: biomass recruitment, growth and mortality) to forest attributes (tree diversity, community-mean traits and stand basal area) and environmental conditions (water availability, soil fertility and disturbance). Location: Neotropics. Methods: We used data from 26 sites, 201 1-ha plots and >92,000 trees distributed across the Neotropics. We quantified for each site water availability and soil total exchangeable bases and for each plot three key community-weighted mean functional traits that are important for biomass stocks and productivity. We used structural equation models to test the hypothesis that all drivers have independent, positive effects on biomass stocks and dynamics. Results: Of the relationships analysed, vegetation attributes were more frequently associated significantly with biomass stocks and dynamics than environmental conditions (in 67 vs. 33% of the relationships). High climatic water availability increased biomass growth and stocks, light disturbance increased biomass growth, and soil bases had no effect. Rarefied tree species richness had consistent positive relationships with biomass stocks and dynamics, probably because of niche complementarity, but was not related to net biomass productivity. Community-mean traits were good predictors of biomass stocks and dynamics. Main conclusions: Water availability has a strong positive effect on biomass stocks and growth, and a future predicted increase in (atmospheric) drought might, therefore, potentially reduce carbon storage. Forest attributes, including species diversity and community-weighted mean traits, have independent and important relationships with AGB stocks, dynamics and ecosystem functioning, not only in relatively simple temperate systems, but also in structurally complex hyper-diverse tropical forests.

Tropical forests are globally important, but it is not clear whether biodiversity enhances carbon storage and sequestration in them. We tested this relationship focusing on components of functional trait biodiversity as predictors. Data are presented for three rain forests in Bolivia, Brazil and Costa Rica. Initial above‐ground biomass and biomass increments of survivors, recruits and survivors + recruits (total) were estimated for trees ≥10 cm d.b.h. in 62 and 21 1.0‐ha plots, respectively. We determined relationships of biomass increments to initial standing biomass (AGBᵢ), biomass‐weighted community mean values (CWM) of eight functional traits and four functional trait variety indices (functional richness, functional evenness, functional diversity and functional dispersion). The forest continuum sampled ranged from ‘slow’ stands dominated by trees with tough tissues and high AGBᵢ, to ‘fast’ stands dominated by trees with soft, nutrient‐rich leaves, lighter woods and lower AGBᵢ. We tested whether AGBᵢand biomass increments were related to the CWM trait values of the dominant species in the system (the biomass ratio hypothesis), to the variety of functional trait values (the niche complementarity hypothesis), or in the case of biomass increments, simply to initial standing biomass (the green soup hypothesis). CWMs were reasonable bivariate predictors of AGBᵢand biomass increments, with CWM specific leaf area SLA, CWM leaf nitrogen content, CWM force to tear the leaf, CWM maximum adult height Hₘₐₓand CWM wood specific gravity the most important. AGBᵢwas also a reasonable predictor of the three measures of biomass increment. In best‐fit multiple regression models, CWMHₘₐₓwas the most important predictor of initial standing biomass AGBᵢ. Only leaf traits were selected in the best models for biomass increment; CWM SLA was the most important predictor, with the expected positive relationship. There were no relationships of functional variety indices to biomass increments, and AGBᵢwas the only predictor for biomass increments from recruits. Synthesis. We found no support for the niche complementarity hypothesis and support for the green soup hypothesis only for biomass increments of recruits. We have strong support for the biomass ratio hypothesis. CWMHₘₐₓis a strong driver of ecosystem biomass and carbon storage and CWM SLA, and other CWM leaf traits are especially important for biomass increments and carbon sequestration.

Significance Although forest succession has been approached as a predictable process, successional trajectories vary widely, even among nearby stands with similar environmental conditions and disturbance histories. We quantified predictability and uncertainty during tropical forest succession using dynamical models describing the interactions among stem density, basal area, and species density over time. We showed that the trajectories of these forest attributes were poorly predicted by stand age and varied significantly within and among sites. Our models reproduced the general successional trends observed, but high levels of noise were needed to increase model predictability. These levels of uncertainty call into question the premise that successional processes are consistent over space and time, and challenge the way ecologists view tropical forest regeneration. Although forest succession has traditionally been approached as a deterministic process, successional trajectories of vegetation change vary widely, even among nearby stands with similar environmental conditions and disturbance histories. Here, we provide the first attempt, to our knowledge, to quantify predictability and uncertainty during succession based on the most extensive long-term datasets ever assembled for Neotropical forests. We develop a novel approach that integrates deterministic and stochastic components into different candidate models describing the dynamical interactions among three widely used and interrelated forest attributes—stem density, basal area, and species density. Within each of the seven study sites, successional trajectories were highly idiosyncratic, even when controlling for prior land use, environment, and initial conditions in these attributes. Plot factors were far more important than stand age in explaining successional trajectories. For each site, the best-fit model was able to capture the complete set of time series in certain attributes only when both the deterministic and stochastic components were set to similar magnitudes. Surprisingly, predictability of stem density, basal area, and species density did not show consistent trends across attributes, study sites, or land use history, and was independent of plot size and time series length. The model developed here represents the best approach, to date, for characterizing autogenic successional dynamics and demonstrates the low predictability of successional trajectories. These high levels of uncertainty suggest that the impacts of allogenic factors on rates of change during tropical forest succession are far more pervasive than previously thought, challenging the way ecologists view and investigate forest regeneration.

We develop a novel statistical approach for classifying generalists and specialists in two distinct habitats. Using a multinomial model based on estimated species relative abundance in two habitats, our method minimizes bias due to differences in sampling intensities between two habitat types as well as bias due to insufficient sampling within each habitat. The method permits a robust statistical classification of habitat specialists and generalists, without excluding rare species a priori. Based on a user-defined specialization threshold, the model classifies species into one of four groups: (1) generalist; (2) habitat A specialist; (3) habitat B specialist; and (4) too rare to classify with confidence. We illustrate our multinomial classification method using two contrasting data sets: (1) bird abundance in woodland and heath habitats in southeastern Australia and (2) tree abundance in second-growth (SG) and old-growth (OG) rain forests in the Caribbean lowlands of northeastern Costa Rica. We evaluate the multinomial model in detail for the tree data set. Our results for birds were highly concordant with a previous nonstatistical classification, but our method classified a higher fraction (57.7%%) of bird species with statistical confidence. Based on a conservative specialization threshold and adjustment for multiple comparisons, 64.4%% of tree species in the full sample were too rare to classify with confidence. Among the species classified, OG specialists constituted the largest class (40.6%%), followed by generalist tree species (36.7%%) and SG specialists (22.7%%). The multinomial model was more sensitive than indicator value analysis or abundance-based phi coefficient indices in detecting habitat specialists and also detects generalists statistically. Classification of specialists and generalists based on rarefied subsamples was highly consistent with classification based on the full sample, even for sampling percentages as low as 20%%. Major advantages of the new method are (1) its ability to distinguish habitat generalists (species with no significant habitat affinity) from species that are simply too rare to classify and (2) applicability to a single representative sample or a single pooled set of representative samples from each of two habitat types. The method as currently developed can be applied to no more than two habitats at a time.

Connectivity of natural areas through biological corridors is essential for ecosystem resilience and biodiversity conservation. However, robust assessments of biodiversity in corridor areas are often hindered by logistical constraints and the statistical challenges of modeling data from multiple species. Herein, we used a hierarchical community occupancy model in a Bayesian framework to evaluate the status of medium and large-sized mammals in a critical link of the Mesoamerican Biological Corridor (MBC) in Costa Rica. We used camera traps deployed from 2013–2017 to detect 18 medium (1–15 kg) and 6 large (>15 kg) mammal species in a portion of two Jaguar Conservation Units (JCUs) and the Corridor linking them. Camera traps operated for 16,904 trap nights across 209 stations, covering an area of 880 km 2 . Forest cover was the most important driver of medium and large-sized mammal habitat use, with forest specialists such as jaguars ( Panthera onca ) and pumas ( Puma concolor ) strongly associated with high forest cover, while habitat generalists such as coyotes ( Canis latrans ) and raccoons ( Procyon lotor ) were associated with low forest cover. Medium and large-sized mammal species richness was lower in the Corridor area ( x ¯ = 9.78±1.84) than in the portions evaluated of the two JCUs ( x ¯ = 11.50±1.52). Puma and jaguar habitat use probabilities were strongly correlated with large prey species richness (jaguar, r = 0.59, p<0.001; puma, r = 0.72, p<0.001), and correlated to a lesser extent with medium prey species richness (jaguar, r = 0.36, p = 0.003; puma, r = 0.23, p = 0.064). Low estimated jaguar habitat use probability in one JCU (Central Volcanic Cordillera: x ¯ = 0.15±0.11) suggests that this is not the jaguar stronghold previously assumed. In addition, the western half of the Corridor has low richness of large mammals, making it necessary to take urgent actions to secure habitat connectivity for mammal populations.

Rates of change in tree communities following major disturbances are determined by a complex set of interactions between local site factors, landscape history and structure, regional species pools and species life histories. Our analysis focuses on vegetation change following abandonment of agricultural fields or pastures, as this is the most extensive form of major disturbance in Neotropical forests. We consider five tree community attributes: stem density, basal area, species density, species richness and species composition. We describe two case studies, in northeastern Costa Rica and Chiapas, Mexico, where both chronosequence and annual tree dynamics studies are being applied. These case studies show that the rates of change in tree communities often deviate from chronosequence trends. With respect to tree species composition, sites of different ages differ more than a single site followed over time through the same age range. Dynamic changes in basal area within stands, on the other hand, generally followed chronosequence trends. Basal area accumulation was more linked with tree growth rates than with net changes in tree density due to recruitment and mortality. Stem turnover rates were poor predictors of species turnover rates, particularly at longer time-intervals. Effects of the surrounding landscape on tree community dynamics within individual plots are poorly understood, but are likely to be important determinants of species accumulation rates and relative abundance patterns.

The crucial role of biodiversity in the links between ecosystems and societies has been repeatedly highlighted both as source of wellbeing and as a target of human actions, but not all aspects of biodiversity are equally important to different ecosystem services. Similarly, different social actors have different perceptions of and access to ecosystem services, and therefore, they have different wants and capacities to select directly or indirectly for particular biodiversity and ecosystem characteristics. Their choices feed back onto the ecosystem services provided to all parties involved and in turn, affect future decisions. Despite this recognition, the research communities addressing biodiversity, ecosystem services, and human outcomes have yet to develop frameworks that adequately treat the multiple dimensions and interactions in the relationship. Here, we present an interdisciplinary framework for the analysis of relationships between functional diversity, ecosystem services, and human actions that is applicable to specific social environmental systems at local scales. We connect the mechanistic understanding of the ecological role of diversity with its social relevance: ecosystem services. The framework permits connections between functional diversity components and priorities of social actors using land use decisions and ecosystem services as the main links between these ecological and social components. We propose a matrix-based method that provides a transparent and flexible platform for quantifying and integrating social and ecological information and negotiating potentially conflicting land uses among multiple social actors. We illustrate the applicability of our framework by way of land use examples from temperate to subtropical South America, an area of rapid social and ecological change.

Tropical forests are converted at an alarming rate for agricultural use and pastureland, but also regrow naturally through secondary succession. For successful forest restoration, it is essential to understand the mechanisms of secondary succession. These mechanisms may vary across forest types, but analyses across broad spatial scales are lacking. Here, we analyse forest recovery using 1,403 plots that differ in age since agricultural abandonment from 50 sites across the Neotropics. We analyse changes in community composition using species-specific stem wood density (WD), which is a key trait for plant growth, survival and forest carbon storage. In wet forest, succession proceeds from low towards high community WD (acquisitive towards conservative trait values), in line with standard successional theory. However, in dry forest, succession proceeds from high towards low community WD (conservative towards acquisitive trait values), probably because high WD reflects drought tolerance in harsh early successional environments. Dry season intensity drives WD recovery by influencing the start and trajectory of succession, resulting in convergence of the community WD over time as vegetation cover builds up. These ecological insights can be used to improve species selection for reforestation. Reforestation species selected to establish a first protective canopy layer should, among other criteria, ideally have a similar WD to the early successional communities that dominate under the prevailing macroclimatic conditions. Neotropical tree community composition shows opposing successional pathways for wet and dry forests, but as vegetation cover increases over time, trends converge. Selecting species that have similar wood density to early successional communities could improve reforestation prospects.

Identifying the environmental factors controlling litter decomposition is key to understanding the magnitude and rates of nutrient cycling in tropical forests, and how they may be influenced by climate variability and environmental change. We carried out a leaf litter translocation experiment in mature rain forest over a 2,520 m altitudinal gradient in Costa Rica. Leaf litter decomposition rates (k) of ten tree species, two dominant species from each ecosystem, plus two standard species, were calculated over 540 days in four life zones. k was lowest in montane with 0.83 per year and lower montane forests with 2.21 per year. k did not differ between lowland and premontane forests at 3.12 per year, in spite of the 3°c difference of mean annual temperature between these life zones. k varied fourfold among species. Species decomposition rates ranked as follows, and were predictably relatedto leaf economic spectrum traits of the species: Acalypha communis (standard, fast decomposer)» Hyeronima oblonga > Alchornea latifolia, Quercus bumelioides, Jarava ichu (standard, slow decomposer)> Minquartia guianensis > Magnolia sororum > Vochysia allenii > Pourouma bicolor, Carapa guianensis. These two slowest-decomposing species were native premontane and lowland forest dominants, respectively, with tough, low-nutrient leaves. The ranking of species by k varied very little among life zones suggesting that decomposer organisms in very different ecosystems and environments react in similar ways to the litter quality in general. We conclude that while k decreases with temperature in rain forests on tropical mountains, bioclimatic zones defined as premontane may be “functionally lowland.” The effects of species identity on decomposition rates on tropical mountains are consistent and independent of environment for both standard and native species. Under climate change on these mountains, if moisture regimes do not change, decomposition rates will increase due to rising temperatures. Soil carbon storage may therefore decrease. Changes in the altitudinal distributions of currently dominant species will also affect this critically important biogeochemical process.

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.