Forest biomass stocks and dynamics across the subtropical Andes

Forest biomass plays an important role in the global carbon cycle. Therefore, understanding the factors that control forest biomass stocks and dynamics is a key challenge in the context of global change. We analyzed data from 60 forest plots in the subtropical Andes (22–27.5° S and 300–2300 m asl) to describe patterns and identify drivers of aboveground biomass (AGB) stocks and dynamics. We found that AGB stocks remained roughly constant with elevation due to compensating changes in basal area (which increased with elevation) and plot-mean wood specific gravity (which decreased with elevation). AGB gain and loss rates both decreased with elevation and were explained mainly by temperature and rainfall (positive effects on both AGB gains and losses). AGB gain was also correlated with forest-use history and weakly correlated with forest structure. Mean annual temperature and rainfall showed minor effects on AGB stocks and AGB change (gains minus losses) over recent decades. Although AGB change was only weakly correlated with climate variables, increases in AGB gains and losses with increasing rainfall—together with observed increases in rainfall in the subtropical Andes—suggest that these forests may become increasingly dynamic in the future. Abstract in Spanish is available with online material.Fil: Blundo, Cecilia Mabel. Universidad Nacional de Tucumán. Instituto de Ecología Regional. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Tucumán. Instituto de Ecología Regional; ArgentinaFil: Malizia, Agustina. Universidad Nacional de Tucumán. Instituto de Ecología Regional. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Tucumán. Instituto de Ecología Regional; ArgentinaFil: Malizia, Lucio Ricardo. Universidad Nacional de Jujuy. Facultad de Ciencias Agrarias; ArgentinaFil: Lichstein, Jeremy W.. University of Florida; Estados Unido

Divergent drivers of leaf trait variation within species, among species, and among functional groups.

Understanding variation in leaf functional traits-including rates of photosynthesis and respiration and concentrations of nitrogen and phosphorus-is a fundamental challenge in plant ecophysiology. When expressed per unit leaf area, these traits typically increase with leaf mass per area (LMA) within species but are roughly independent of LMA across the global flora. LMA is determined by mass components with different biological functions, including photosynthetic mass that largely determines metabolic rates and contains most nitrogen and phosphorus, and structural mass that affects toughness and leaf lifespan (LL). A possible explanation for the contrasting trait relationships is that most LMA variation within species is associated with variation in photosynthetic mass, whereas most LMA variation across the global flora is associated with variation in structural mass. This hypothesis leads to the predictions that (i) gas exchange rates and nutrient concentrations per unit leaf area should increase strongly with LMA across species assemblages with low LL variance but should increase weakly with LMA across species assemblages with high LL variance and that (ii) controlling for LL variation should increase the strength of the above LMA relationships. We present analyses of intra- and interspecific trait variation from three tropical forest sites and interspecific analyses within functional groups in a global dataset that are consistent with the above predictions. Our analysis suggests that the qualitatively different trait relationships exhibited by different leaf assemblages can be understood by considering the degree to which photosynthetic and structural mass components contribute to LMA variation in a given assemblage

Estimation of pollen productivity and dispersal: How pollen assemblages in small lakes represent vegetation

Despite ongoing advances, quantitative understanding of vegetation dynamics over timespans beyond a century remains limited. In this regard, pollen-based reconstruction of past vegetation enables unique research opportunities by quantifying changes in plant community compositions over hundreds to thousands of years. Critically, the methodological basis for most reconstruction approaches rests upon estimates of pollen productivity and dispersal. However, previous studies have reached contrasting conclusions concerning these estimates, which may be perceived to challenge the applicability and reliability of pollen-based reconstruction. Here we show that conflicting estimates of pollen production and dispersal are, at least in part, artifacts of fixed assumptions of pollen dispersal and insufficient spatial resolution of vegetation data surrounding the pollen-collecting lake. We implemented a Bayesian statistical model that relates pollen assemblages in surface sediments of 33 small lakes (105 m from the lake margin. Our analysis reveals three key insights. First, pollen productivity is largely conserved within taxa and across forest types. Second, when local (within 1-km radius) vegetation abundances are not considered, pollen-source areas may be overestimated for a number of common taxa (Cupressaceae, Pinus, Quercus, and Tsuga). Third, pollen dispersal mechanisms may differ between local and regional scales, which is missed by pollen-dispersal models used in previous studies. These findings highlight the complex interactions between vegetation heterogeneity on the landscape and pollen dispersal. We suggest that, when estimating pollen productivity and dispersal, both detailed local and extended regional vegetation must be accounted for. Also, both deductive (mechanistic models) and inductive (statistical models) approaches are needed to better understand the emergent properties of pollen dispersal in heterogeneous landscapes

Demographic trade-offs predict tropical forest dynamics

Understanding tropical forest dynamics and planning for their sustainable management require efficient, yet accurate, predictions of the joint dynamics of hundreds of tree species. With increasing information on tropical tree life histories, our predictive understanding is no longer limited by species data but by the ability of existing models to make use of it. Using a demographic forest model, we show that the basal area and compositional changes during forest succession in a neotropical forest can be accurately predicted by representing tropical tree diversity (hundreds of species) with only five functional groups spanning two essential trade-offs—the growth-survival and stature-recruitment trade-offs. This data-driven modeling framework substantially improves our ability to predict consequences of anthropogenic impacts on tropical forests

Divergent drivers of leaf trait variation within species, among species, and among functional groups

Understanding variation in leaf functional traits—including rates of photosynthesis and respiration and concentrations of nitrogen and phosphorus—is a fundamental challenge in plant ecophysiology. When expressed per unit leaf area, these traits typically increase with leaf mass per area (LMA) within species but are roughly independent of LMA across the global flora. LMA is determined by mass components with different biological functions, including photosynthetic mass that largely determines metabolic rates and contains most nitrogen and phosphorus, and structural mass that affects toughness and leaf lifespan (LL). A possible explanation for the contrasting trait relationships is that most LMA variation within species is associated with variation in photosynthetic mass, whereas most LMA variation across the global flora is associated with variation in structural mass. This hypothesis leads to the predictions that (i) gas exchange rates and nutrient concentrations per unit leaf area should increase strongly with LMA across species assemblages with low LL variance but should increase weakly with LMA across species assemblages with high LL variance and that (ii) controlling for LL variation should increase the strength of the above LMA relationships. We present analyses of intra- and interspecific trait variation from three tropical forest sites and interspecific analyses within functional groups in a global dataset that are consistent with the above predictions. Our analysis suggests that the qualitatively different trait relationships exhibited by different leaf assemblages can be understood by considering the degree to which photosynthetic and structural mass components contribute to LMA variation in a given assemblage

The function-dominance correlation drives the direction and strength of biodiversity-ecosystem functioning relationships

Community composition is a primary determinant of how biodiversity change influences ecosystem functioning and, therefore, the relationship between biodiversity and ecosystem functioning (BEF). We examine the consequences of community composition across six structurally realistic plant community models. We find that a positive correlation between species' functioning in monoculture versus their dominance in mixture with regard to a specific function (the "function-dominance correlation") generates a positive relationship between realised diversity and ecosystem functioning across species richness treatments. However, because realised diversity declines when few species dominate, a positive function-dominance correlation generates a negative relationship between realised diversity and ecosystem functioning within species richness treatments. Removing seed inflow strengthens the link between the function-dominance correlation and BEF relationships across species richness treatments but weakens it within them. These results suggest that changes in species' identities in a local species pool may more strongly affect ecosystem functioning than changes in species richness

Crown Plasticity and Competition for Canopy Space: A New Spatially Implicit Model Parameterized for 250 North American Tree Species

BACKGROUND: Canopy structure, which can be defined as the sum of the sizes, shapes and relative placements of the tree crowns in a forest stand, is central to all aspects of forest ecology. But there is no accepted method for deriving canopy structure from the sizes, species and biomechanical properties of the individual trees in a stand. Any such method must capture the fact that trees are highly plastic in their growth, forming tessellating crown shapes that fill all or most of the canopy space. METHODOLOGY/PRINCIPAL FINDINGS: We introduce a new, simple and rapidly-implemented model--the Ideal Tree Distribution, ITD--with tree form (height allometry and crown shape), growth plasticity, and space-filling, at its core. The ITD predicts the canopy status (in or out of canopy), crown depth, and total and exposed crown area of the trees in a stand, given their species, sizes and potential crown shapes. We use maximum likelihood methods, in conjunction with data from over 100,000 trees taken from forests across the coterminous US, to estimate ITD model parameters for 250 North American tree species. With only two free parameters per species--one aggregate parameter to describe crown shape, and one parameter to set the so-called depth bias--the model captures between-species patterns in average canopy status, crown radius, and crown depth, and within-species means of these metrics vs stem diameter. The model also predicts much of the variation in these metrics for a tree of a given species and size, resulting solely from deterministic responses to variation in stand structure. CONCLUSIONS/SIGNIFICANCE: This new model, with parameters for US tree species, opens up new possibilities for understanding and modeling forest dynamics at local and regional scales, and may provide a new way to interpret remote sensing data of forest canopies, including LIDAR and aerial photography

Phylogenetic Constraints Do Not Explain the Rarity of Nitrogen-Fixing Trees in Late-Successional Temperate Forests

Symbiotic nitrogen (N)-fixing trees are rare in late-successional temperate forests, even though these forests are often N limited. Two hypotheses could explain this paradox. The 'phylogenetic constraints hypothesis' states that no late-successional tree taxa in temperate forests belong to clades that are predisposed to N fixation. Conversely, the 'selective constraints hypothesis' states that such taxa are present, but N-fixing symbioses would lower their fitness. Here we test the phylogenetic constraints hypothesis.Using U.S. forest inventory data, we derived successional indices related to shade tolerance and stand age for N-fixing trees, non-fixing trees in the 'potentially N-fixing clade' (smallest angiosperm clade that includes all N fixers), and non-fixing trees outside this clade. We then used phylogenetically independent contrasts (PICs) to test for associations between these successional indices and N fixation. Four results stand out from our analysis of U.S. trees. First, N fixers are less shade-tolerant than non-fixers both inside and outside of the potentially N-fixing clade. Second, N fixers tend to occur in younger stands in a given geographical region than non-fixers both inside and outside of the potentially N-fixing clade. Third, the potentially N-fixing clade contains numerous late-successional non-fixers. Fourth, although the N fixation trait is evolutionarily conserved, the successional traits are relatively labile.These results suggest that selective constraints, not phylogenetic constraints, explain the rarity of late-successional N-fixing trees in temperate forests. Because N-fixing trees could overcome N limitation to net primary production if they were abundant, this study helps to understand the maintenance of N limitation in temperate forests, and therefore the capacity of this biome to sequester carbon

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