Trait divergence and habitat specialization in tropical floodplain forests trees

Habitat heterogeneity of tropical forests is thought to lead to specialization in plants and contribute to the high diversity of tree species in Amazonia. One prediction of habitat specialization is that species specialized for resource-rich habitats will have traits associated with high resource acquisition and fast growth while species specialized for resource-poor habitats will have traits associated with high resource conservation and persistence but slow growth. We tested this idea for seven genera and for twelve families from nutrient-rich white-water floodplain forest (várzea) and nutrient-poor black-water (igapó) floodplain forest. We measured 11 traits that are important for the carbon and nutrient balance of the trees, and compared trait variation between habitat types (white- and black-water forests), and the effect of habitat and genus/family on trait divergence. Functional traits of congeneric species differed between habitat types, where white-water forest species invested in resource acquisition and productive tissues, whereas black-water forest species invested in resource conservation and persistent tissues. Habitat specialization is leading to the differentiation of floodplain tree species of white-water and black-water forests, thus contributing to a high diversity of plant species in floodplain forests

Estimating above ground net biomass change in tropical and subtropical forests: refinement of IPCC default values using forest plot data

As countries advance in greenhouse gas (GHG) accounting for climate change mitigation, consistent estimates of above ground biomass (AGB) net change are needed for the tropics and subtropics. Countries with limited forest monitoring capabilities rely on 2006 IPCC default AGB net change values, which are averages per ecological zone, per continent. These previous defaults come from single studies, provide no uncertainty indications, and aggregate old secondary forests and old-growth forests. In this study, we update these default values using forest plot data. In comparison with previous estimates, new values include data published from 2006 onwards, are derived from multiple sites per global ecological zone, provide measures of variation, and divide forests >20 years old into older secondary forests and old-growth forests. We compiled 176 AGB chronosequences in secondary forests and AGB net change rates from 536 permanent plots in old-growth and managed or logged forests. In this dataset, across all continents and ecozones, AGB net change rates in younger secondary forests (go years) are higher than rates in older secondary (>20 years and ≤100 years) forests and managed or logged forests, which in turn are higher than rates in old-growth forests (> 100 years). Data availability is highest for North and South America, followed by Asia then Africa. We provide a rigorous and traceable refinement of the IPCC 2006 AGB net change default rates, identify which areas in the tropics and subtropics require more research on AGB change, and reflect on possibilities for improvement as more data becomes available

Improved representation of plant functional types and physiology in the Joint UK Land Environment Simulator (JULES v4.2) using plant trait information

Dynamic global vegetation models are used to predict the response of vegetation to climate change. They are essential for planning ecosystem management, understanding carbon cycle–climate feedbacks, and evaluating the potential impacts of climate change on global ecosystems. JULES (the Joint UK Land Environment Simulator) represents terrestrial processes in the UK Hadley Centre family of models and in the first generation UK Earth System Model. Previously, JULES represented five plant functional types (PFTs): broadleaf trees, needle-leaf trees, C3 and C4 grasses, and shrubs. This study addresses three developments in JULES. First, trees and shrubs were split into deciduous and evergreen PFTs to better represent the range of leaf life spans and metabolic capacities that exists in nature. Second, we distinguished between temperate and tropical broadleaf evergreen trees. These first two changes result in a new set of nine PFTs: tropical and temperate broadleaf evergreen trees, broadleaf deciduous trees, needle-leaf evergreen and deciduous trees, C3 and C4 grasses, and evergreen and deciduous shrubs. Third, using data from the TRY database, we updated the relationship between leaf nitrogen and the maximum rate of carboxylation of Rubisco (Vcmax), and updated the leaf turnover and growth rates to include a trade-off between leaf life span and leaf mass per unit area. Overall, the simulation of gross and net primary productivity (GPP and NPP, respectively) is improved with the nine PFTs when compared to FLUXNET sites, a global GPP data set based on FLUXNET, and MODIS NPP. Compared to the standard five PFTs, the new nine PFTs simulate a higher GPP and NPP, with the exception of C3 grasses in cold environments and C4 grasses that were previously over-productive. On a biome scale, GPP is improved for all eight biomes evaluated and NPP is improved for most biomes – the exceptions being the tropical forests, savannahs, and extratropical mixed forests where simulated NPP is too high. With the new PFTs, the global present-day GPP and NPP are 128 and 62 Pg C year−1, respectively. We conclude that the inclusion of trait-based data and the evergreen/deciduous distinction has substantially improved productivity fluxes in JULES, in particular the representation of GPP. These developments increase the realism of JULES, enabling higher confidence in simulations of vegetation dynamics and carbon storage

Genetic diversity of Kenyan Prosopis populations based on random amplified polymorphic DNA markers

Several Prosopis species and provenances were introduced in Kenya, either as a single event or repeatedly. To date, naturally established Prosopis populations are described as pure species depending on site, despite the aforementioned introduction of several species within some sites. To determine whether naturally established stands consist of a single or mixture of species, six populations from Bamburi, Bura, Isiolo, Marigat, Taveta and Turkwel were compared for relatedness with reference to Prosopis chilensis, Prosopis juliflora and Prosopis pallida using random amplified polymorphic DNA markers. Cluster analysis based on Nei’s genetic distance clustered Kenyan populations as follows: Marigat, Bura and Isiolo with P. juliflora, Bamburi with P. pallida and Taveta with P. chilensis, whereas the Turkwel population is likely to be a hybrid between P. chileneis and P. juliflora. Four populations had private markers, revealing germplasm uniqueness. Expected heterozygosity tended to be larger for Kenyan populations (ranging from 0.091 to 0.191) than in the three reference (ranging from 0.065 to 0.144). For the six Kenyan populations and two P. juliflora provenances from the Middle East, molecular variation was larger within populations than between population. Higher molecular variance among populations is attributed to their geographical separation and the low variation within populations is due to gene flow between individuals within a population. Overall, this study shows that (1) the Kenyan Prosopis populations are genetically isolated, (2) multiple introductions enhanced genetic diversity within sites and (3) P. juliflora and its hybrid are the most aggressive invaders.Key words: Prosopis chilensis, Prosopis juliflora, Prosopis pallida, multiple introductions, genetic diversity

Plant functional traits have globally consistent effects on competition.

Phenotypic traits and their associated trade-offs have been shown to have globally consistent effects on individual plant physiological functions, but how these effects scale up to influence competition, a key driver of community assembly in terrestrial vegetation, has remained unclear. Here we use growth data from more than 3 million trees in over 140,000 plots across the world to show how three key functional traits--wood density, specific leaf area and maximum height--consistently influence competitive interactions. Fast maximum growth of a species was correlated negatively with its wood density in all biomes, and positively with its specific leaf area in most biomes. Low wood density was also correlated with a low ability to tolerate competition and a low competitive effect on neighbours, while high specific leaf area was correlated with a low competitive effect. Thus, traits generate trade-offs between performance with competition versus performance without competition, a fundamental ingredient in the classical hypothesis that the coexistence of plant species is enabled via differentiation in their successional strategies. Competition within species was stronger than between species, but an increase in trait dissimilarity between species had little influence in weakening competition. No benefit of dissimilarity was detected for specific leaf area or wood density, and only a weak benefit for maximum height. Our trait-based approach to modelling competition makes generalization possible across the forest ecosystems of the world and their highly diverse species composition.We are especially grateful to the researchers whose long-term commitment to establish and maintain forest plots and their associated databases made this study possible, and to those who granted us data access: forest inventories and permanent plots of New Zealand, Spain (MAGRAMA), France, Switzerland, Sweden, US and Canada (for the provinces of Quebec provided by the Ministère des Ressources Naturelles du Québec, Ontario provided by OnTAP’s Growth and Yield Program of the Ontario Ministry of Natural Resources, Saskatchewan, Manitoba, New Brunswick, Newfoundland and Labrador), CTFS (BCI and LTER-Luquillo), Taiwan (Fushan), Cirad (Paracou with funding by CEBA, ANR-10-LABX-25-01), Cirad, MEFCP and ICRA (M’Baïki) and Japan. We thank MPI-BGC Jena, who host TRY, and the international funding networks supporting TRY (IGBP, DIVERSITAS, GLP, NERC, QUEST, FRB and GIS Climate). G.K. was supported by a Marie Curie International Outgoing Fellowship within the 7th European Community Framework Program (Demo-Traits project, no. 299340). The working group that initiated this synthesis was supported by Macquarie University and by Australian Research Council through a fellowship to M.W.This is the author accepted manuscript. The final version is available from Nature Publishing Group via http://dx.doi.org/10.1038/nature1647

Leaf vein length per unit area is not intrinsically dependent on image magnification: avoiding measurement artifacts for accuracy and precision.

Leaf vein length per unit leaf area (VLA; also known as vein density) is an important determinant of water and sugar transport, photosynthetic function, and biomechanical support. A range of software methods are in use to visualize and measure vein systems in cleared leaf images; typically, users locate veins by digital tracing, but recent articles introduced software by which users can locate veins using thresholding (i.e. based on the contrasting of veins in the image). Based on the use of this method, a recent study argued against the existence of a fixed VLA value for a given leaf, proposing instead that VLA increases with the magnification of the image due to intrinsic properties of the vein system, and recommended that future measurements use a common, low image magnification for measurements. We tested these claims with new measurements using the software LEAFGUI in comparison with digital tracing using ImageJ software. We found that the apparent increase of VLA with magnification was an artifact of (1) using low-quality and low-magnification images and (2) errors in the algorithms of LEAFGUI. Given the use of images of sufficient magnification and quality, and analysis with error-free software, the VLA can be measured precisely and accurately. These findings point to important principles for improving the quantity and quality of important information gathered from leaf vein systems

Variation in stem mortality rates determines patterns of above-ground biomass in Amazonian forests: implications for dynamic global vegetation models

Understanding the processes that determine above-ground biomass (AGB) in Amazonian forests is important for predicting the sensitivity of these ecosystems to environmental change and for designing and evaluating dynamic global vegetation models (DGVMs). AGB is determined by inputs from woody productivity [woody net primary productivity (NPP)] and the rate at which carbon is lost through tree mortality. Here, we test whether two direct metrics of tree mortality (the absolute rate of woody biomass loss and the rate of stem mortality) and/or woody NPP, control variation in AGB among 167 plots in intact forest across Amazonia. We then compare these relationships and the observed variation in AGB and woody NPP with the predictions of four DGVMs. The observations show that stem mortality rates, rather than absolute rates of woody biomass loss, are the most important predictor of AGB, which is consistent with the importance of stand size structure for determining spatial variation in AGB. The relationship between stem mortality rates and AGB varies among different regions of Amazonia, indicating that variation in wood density and height/diameter relationships also influences AGB. In contrast to previous findings, we find that woody NPP is not correlated with stem mortality rates and is weakly positively correlated with AGB. Across the four models, basin-wide average AGB is similar to the mean of the observations. However, the models consistently overestimate woody NPP and poorly represent the spatial patterns of both AGB and woody NPP estimated using plot data. In marked contrast to the observations, DGVMs typically show strong positive relationships between woody NPP and AGB. Resolving these differences will require incorporating forest size structure, mechanistic models of stem mortality and variation in functional composition in DGVMs

Variation in stem mortality rates determines patterns of above-ground biomass in Amazonian forests: implications for dynamic global vegetation models

Understanding the processes that determine above-ground biomass (AGB) in Amazonian forests is important for predicting the sensitivity of these ecosystems to environmental change and for designing and evaluating dynamic global vegetation models (DGVMs). AGB is determined by inputs from woody productivity [woody net primary productivity (NPP)] and the rate at which carbon is lost through tree mortality. Here, we test whether two direct metrics of tree mortality (the absolute rate of woody biomass loss and the rate of stem mortality) and/or woody NPP, control variation in AGB among 167 plots in intact forest across Amazonia. We then compare these relationships and the observed variation in AGB and woody NPP with the predictions of four DGVMs. The observations show that stem mortality rates, rather than absolute rates of woody biomass loss, are the most important predictor of AGB, which is consistent with the importance of stand size structure for determining spatial variation in AGB. The relationship between stem mortality rates and AGB varies among different regions of Amazonia, indicating that variation in wood density and height/diameter relationships also influences AGB. In contrast to previous findings, we find that woody NPP is not correlated with stem mortality rates and is weakly positively correlated with AGB. Across the four models, basin-wide average AGB is similar to the mean of the observations. However, the models consistently overestimate woody NPP and poorly represent the spatial patterns of both AGB and woody NPP estimated using plot data. In marked contrast to the observations, DGVMs typically show strong positive relationships between woody NPP and AGB. Resolving these differences will require incorporating forest size structure, mechanistic models of stem mortality and variation in functional composition in DGVMs