Height-diameter allometry of tropical forest trees

Tropical tree height-diameter (H:D) relationships may vary by forest type and region making large-scale estimates of above-ground biomass subject to bias if they ignore these differences in stem allometry. We have therefore developed a new global tropical forest database consisting of 39 955 concurrent H and D measurements encompassing 283 sites in 22 tropical countries. Utilising this database, our objectives were: 1. to determine if H:D relationships differ by geographic region and forest type (wet to dry forests, including zones of tension where forest and savanna overlap). 2. to ascertain if the H:D relationship is modulated by climate and/or forest structural characteristics (e.g. stand-level basal area, A). 3. to develop H:D allometric equations and evaluate biases to reduce error in future local-to-global estimates of tropical forest biomass. Annual precipitation coefficient of variation (PV), dry season length (SD), and mean annual air temperature (TA) emerged as key drivers of variation in H:D relationships at the pantropical and region scales. Vegetation structure also played a role with trees in forests of a high A being, on average, taller at any given D. After the effects of environment and forest structure are taken into account, two main regional groups can be identified. Forests in Asia, Africa and the Guyana Shield all have, on average, similar H:D relationships, but with trees in the forests of much of the Amazon Basin and tropical Australia typically being shorter at any given D than their counterparts elsewhere. The region-environment-structure model with the lowest Akaike\u27s information criterion and lowest deviation estimated stand-level H across all plots to within amedian −2.7 to 0.9% of the true value. Some of the plot-to-plot variability in H:D relationships not accounted for by this model could be attributed to variations in soil physical conditions. Other things being equal, trees tend to be more slender in the absence of soil physical constraints, especially at smaller D. Pantropical and continental-level models provided less robust estimates of H, especially when the roles of climate and stand structure in modulating H:D allometry were not simultaneously taken into account

Functional trait variation among and within species and plant functional types in mountainous Mediterranean forests

Plant structural and biochemical traits are frequently used to characterise the life history of plants. Although some common patterns of trait covariation have been identified, recent studies suggest these patterns of covariation may differ with growing location and/or plant functional type (PFT). Mediterranean forest tree/shrub species are often divided into three PFTs based on their leaf habit and form, being classified as either needleleaf evergreen (Ne), broadleaf evergreen (Be), or broadleaf deciduous (Bd). Working across 61 mountainous Mediterranean forest sites of contrasting climate and soil type, we sampled and analysed 626 individuals in order to evaluate differences in key foliage trait covariation as modulated by growing conditions both within and between the Ne, Be, and Bd functional types. We found significant differences between PFTs for most traits. When considered across PFTs and by ignoring intraspecific variation, three independent functional dimensions supporting the Leaf-Height-Seed framework were identified. Some traits illustrated a common scaling relationship across and within PFTs, but others scaled differently when considered across PFTs or even within PFTs. For most traits much of the observed variation was attributable to PFT identity and not to growing location, although for some traits there was a strong environmental component and considerable intraspecific and residual variation. Nevertheless, environmental conditions as related to water availability during the dry season and to a smaller extend to soil nutrient status and soil texture, clearly influenced trait values. When compared across species, about half of the trait-environment relationships were species-specific. Our study highlights the importance of the ecological scale within which trait covariation is considered and suggests that at regional to local scales, common trait-by-trait scaling relationships should be treated with caution. PFT definitions by themselves can potentially be an important predictor variable when inferring one trait from another. These findings have important implications for local scale dynamic vegetation models

Predicting species dominance shifts across elevation gradients in mountain forests in Greece under a warmer and drier climate

The Mediterranean Basin is expected to face warmer and drier conditions in the future, following projected increases in temperature and declines in precipitation. The aim of this study is to explore how forests dominated by Abies borisii-regis, Abies cephalonica, Fagus sylvatica, Pinus nigra and Quercus frainetto will respond under such conditions. We combined an individual-based model (GREFOS), with a novel tree ring data set in order to constrain tree diameter growth and to account for inter- and intraspecific growth variability. We used wood density data to infer tree longevity, taking into account inter- and intraspecific variability. The model was applied at three 500-m-wide elevation gradients at Taygetos in Peloponnese, at Agrafa on Southern Pindos and at Valia Kalda on Northern Pindos in Greece. Simulations adequately represented species distribution and abundance across the elevation gradients under current climate. We subsequently used the model to estimate species and functional trait shifts under warmer and drier future conditions based on the IPCC A1B scenario. In all three sites, a retreat of less drought-tolerant species and an upward shift of more drought-tolerant species were simulated. These shifts were also associated with changes in two key functional traits, in particular maximum radial growth rate and wood density. Drought-tolerant species presented an increase in their average maximal growth and decrease in their average wood density, in contrast to less drought-tolerant species

Coordination of physiological and structural traits in Amazon forest trees

Many plant traits covary in a non-random manner reflecting interdependencies associated with "ecological strategy" dimensions. To understand how plants integrate their structural and physiological investments, data on leaf and leaflet size and the ratio of leaf area to sapwood area (Φ<sub>LS</sub>) obtained for 1020 individual trees (encompassing 661 species) located in 52 tropical forest plots across the Amazon Basin were incorporated into an analysis utilising existing data on species maximum height (<i>H</i><sub>max</sub>), seed size, leaf mass per unit area (<i>M</i><sub>A</sub>), foliar nutrients and δ<sup>13</sup>C, and branch xylem density (<i>ρ</i><sub>x</sub>). <br></br> Utilising a common principal components approach allowing eigenvalues to vary between two soil fertility dependent species groups, five taxonomically controlled trait dimensions were identified. The first involves primarily cations, foliar carbon and <i>M</i><sub>A</sub> and is associated with differences in foliar construction costs. The second relates to some components of the classic "leaf economic spectrum", but with increased individual leaf areas and a higher Φ<sub>LS</sub> newly identified components for tropical tree species. The third relates primarily to increasing <i>H</i><sub>max</sub> and hence variations in light acquisition strategy involving greater <i>M</i><sub>A</sub>, reductions in Φ<sub>LS</sub> and less negative δ<sup>13</sup>C. Although these first three dimensions were more important for species from high fertility sites the final two dimensions were more important for low fertility species and were associated with variations linked to reproductive and shade tolerance strategies. <br></br> Environmental conditions influenced structural traits with <i>ρ</i><sub>x</sub> of individual species decreasing with increased soil fertility and higher temperatures. This soil fertility response appears to be synchronised with increases in foliar nutrient concentrations and reductions in foliar [C]. Leaf and leaflet area and Φ<sub>LS</sub> were less responsive to the environment than <i>ρ</i><sub>x</sub>. <br></br> Thus, although genetically determined foliar traits such as those associated with leaf construction costs coordinate independently of structural characteristics such as maximum height, others such as the classical "leaf economic spectrum" covary with structural traits such as leaf size and Φ<sub>LS</sub>. Coordinated structural and physiological adaptions are also associated with light acquisition/shade tolerance strategies with several traits such as <i>M</i><sub>A</sub> and [C] being significant components of more than one ecological strategy dimension. This is argued to be a consequence of a range of different potential underlying causes for any observed variation in such "ambiguous" traits. Environmental effects on structural and physiological characteristics are also coordinated but in a different way to the gamut of linkages associated with genotypic differences

TRY plant trait database - enhanced coverage and open access

Plant traits-the morphological, anatomical, physiological, biochemical and phenological characteristics of plants-determine how plants respond to environmental factors, affect other trophic levels, and influence ecosystem properties and their benefits and detriments to people. Plant trait data thus represent the basis for a vast area of research spanning from evolutionary biology, community and functional ecology, to biodiversity conservation, ecosystem and landscape management, restoration, biogeography and earth system modelling. Since its foundation in 2007, the TRY database of plant traits has grown continuously. It now provides unprecedented data coverage under an open access data policy and is the main plant trait database used by the research community worldwide. Increasingly, the TRY database also supports new frontiers of trait-based plant research, including the identification of data gaps and the subsequent mobilization or measurement of new data. To support this development, in this article we evaluate the extent of the trait data compiled in TRY and analyse emerging patterns of data coverage and representativeness. Best species coverage is achieved for categorical traits-almost complete coverage for 'plant growth form'. However, most traits relevant for ecology and vegetation modelling are characterized by continuous intraspecific variation and trait-environmental relationships. These traits have to be measured on individual plants in their respective environment. Despite unprecedented data coverage, we observe a humbling lack of completeness and representativeness of these continuous traits in many aspects. We, therefore, conclude that reducing data gaps and biases in the TRY database remains a key challenge and requires a coordinated approach to data mobilization and trait measurements. This can only be achieved in collaboration with other initiatives

Regional and large-scale patterns in Amazon forest structure and function are mediated by variations in soil physical and chemical properties

Forest structure and dynamics have been noted to vary across the Amazon Basin in an east-west gradient in a pattern which coincides with variations in soil fertility and geology. This has resulted in the hypothesis that soil fertility may play an important role in explaining Basin-wide variations in forest biomass, growth and stem turnover rates. To test this hypothesis and assess the importance of edaphic properties in affect forest structure and dynamics, soil and plant samples were collected in a total of 59 different forest plots across the Amazon Basin. Samples were analysed for exchangeable cations, C, N, pH with various Pfractions also determined. Physical properties were also examined and an index of soil physical quality developed. Overall, forest structure and dynamics were found to be strongly and quantitatively related to edaphic conditions. Tree turnover rates emerged to be mostly influenced by soil physical properties whereas forest growth rates were mainly related to a measure of available soil phosphorus, although also dependent on rainfall amount and distribution. On the other hand, large scale variations in forest biomass could not be explained by any of the edaphic properties measured, nor by variation in climate. A new hypothesis of self-maintaining forest dynamic feedback mechanisms initiated by edaphic conditions is proposed. It is further suggested that this is a major factor determining forest disturbance levels, species composition and forest productivity on a Basin wide scale

Linking hydraulic traits to tropical forest function in a size-structured and trait-driven model (TFS v.1-Hydro)

Forest ecosystem models based on heuristic water stress functions poorly predict tropical forest response to drought partly because they do not capture the diversity of hydraulic traits (including variation in tree size) observed in tropical forests. We developed a continuous porous media approach to modeling plant hydraulics in which all parameters of the constitutive equations are biologically interpretable and measurable plant hydraulic traits (e.g., turgor loss point πtlp, bulk elastic modulus ϵ, hydraulic capacitance Cft, xylem hydraulic conductivity ks,max, water potential at 50% loss of conductivity for both xylem (P50,x) and stomata (P50,gs), and the leafg: sapwood area ratio Al: As). We embedded this plant hydraulics model within a trait forest simulator (TFS) that models light environments of individual trees and their upper boundary conditions (transpiration), as well as providing a means for parameterizing variation in hydraulic traits among individuals. We synthesized literature and existing databases to parameterize all hydraulic traits as a function of stem and leaf traits, including wood density (WD), leaf mass per area (LMA), and photosynthetic capacity (Amax), and evaluated the coupled model (called TFS v.1-Hydro) predictions, against observed diurnal and seasonal variability in stem and leaf water potential as well as stand-scaled sap flux. Our hydraulic trait synthesis revealed coordination among leaf and xylem hydraulic traits and statistically significant relationships of most hydraulic traits with more easily measured plant traits. Using the most informative empirical trait-trait relationships derived from this synthesis, TFS v.1-Hydro successfully captured individual variation in leaf and stem water potential due to increasing tree size and light environment, with model representation of hydraulic architecture and plant traits exerting primary and secondary controls, respectively, on the fidelity of model predictions. The plant hydraulics model made substantial improvements to simulations of total ecosystem transpiration. Remaining uncertainties and limitations of the trait paradigm for plant hydraulics modeling are highlighted

Solar radiation and functional traits explain the decline of forest primary productivity along a tropical elevation gradient

One of the major challenges in ecology is to understand how ecosystems respond to changes in environmental conditions, and how taxonomic and functional diversity mediate these changes. In this study, we use a trait-spectra and individual-based model, to analyse variation in forest primary productivity along a 3.3 km elevation gradient in the Amazon-Andes. The model accurately predicted the magnitude and trends in forest productivity with elevation, with solar radiation and plant functional traits (leaf dry mass per area, leaf nitrogen and phosphorus concentration, and wood density) collectively accounting for productivity variation. Remarkably, explicit representation of temperature variation with elevation was not required to achieve accurate predictions of forest productivity, as trait variation driven by species turnover appears to capture the effect of temperature. Our semi-mechanistic model suggests that spatial variation in traits can potentially be used to estimate spatial variation in productivity at the landscape scale