Intraspecific variation in leaf traits facilitates the occurrence of trees at the Amazonia–Cerrado transition

The ability of plant species to adjust key functional traits through intraspecific variation may determine their success in persisting on our planet in the future, especially in unstable habitats, such as the Amazonia–Cerrado transition zone. We assessed intraspecific variation in 12 leaf morphological and anatomical traits for four tree species along a savanna–forest gradient, including rocky cerrado, typical cerrado and woodland savanna. Generally, all evaluated species showed great intraspecific variation. Our findings demonstrate that trees occurring in the woodland savanna are potentially more vulnerable to climate change, while in the cerrado the individuals presented higher tolerance to water deficit and high temperatures. Trees occurring in open-canopy habitats showed smaller stomata, higher stomata and trichome densities, compared to the same species growing in the woodland savanna. In contrast, the individuals in the woodland savanna shift leaf traits to increase resource acquisition (e.g. light), showing higher specific leaf area and larger stomata, compared to cerrado individuals. We have shown that vegetation-induced shifts in leaf morphological and anatomical traits are a major effect in within-species variability, with consequences for persistence and tolerance of species under future climatic conditions

Trees at the Amazonia-Cerrado transition are approaching high temperature thresholds

Land regions are warming rapidly. While in a warming world at extra-tropical latitudes vegetation adapted to higher temperatures may move in from lower latitudes this is not possible in the tropics. Thus, the limits of plant functioning will determine the nature and composition of future vegetation. The most temperature sensitive component of photosynthesis and a key component of plants is Photosystem II. Here we report the thermal safety margin (difference between Photosystem II thermotolerance (T50) and maximum leaf temperature) during the beginning of the dry season for four tree species co-occurring across the forest-savanna transition zone in Brazil, a region which has warmed particularly rapidly over the recent decades. The species selected are evergreen in forests but deciduous in savannas. We find that thermotolerance declines with growth temperature larger than >40 °C for individuals in the savannas. Current maximum leaf temperatures exceed T50 in some species and will exceed T50 in a 2.5 °C warmer world in most species evaluated. Despite plasticity in leaf thermal traits to increase leaf cooling in hotter environments, the results show this is not sufficient to maintain a safe thermal safety margin in hotter savannas. Overall, the results suggest that forest species may become increasingly deciduous and savanna-like in the future

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

Basin-wide variation in tree hydraulic safety margins predicts the carbon balance of Amazon forests

Tropical forests face increasing climate risk1,2, yet our ability to predict their response to climate change is limited by poor understanding of their resistance to water stress. Although xylem embolism resistance thresholds (for example, Ψ50) and hydraulic safety margins (for example, HSM50) are important predictors of drought-induced mortality risk3–5, little is known about how these vary across Earth’s largest tropical forest. Here, we present a pan-Amazon, fully standardized hydraulic traits dataset and use it to assess regional variation in drought sensitivity and hydraulic trait ability to predict species distributions and long-term forest biomass accumulation. Parameters Ψ50 and HSM50 vary markedly across the Amazon and are related to average long-term rainfall characteristics. Both Ψ50 and HSM50 influence the biogeographical distribution of Amazon tree species. However, HSM50 was the only significant predictor of observed decadal-scale changes in forest biomass. Old-growth forests with wide HSM50 are gaining more biomass than are low HSM50 forests. We propose that this may be associated with a growth–mortality trade-off whereby trees in forests consisting of fast-growing species take greater hydraulic risks and face greater mortality risk. Moreover, in regions of more pronounced climatic change, we find evidence that forests are losing biomass, suggesting that species in these regions may be operating beyond their hydraulic limits. Continued climate change is likely to further reduce HSM50 in the Amazon6,7, with strong implications for the Amazon carbon sink

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