Amazon forest responses to projected climate change, elevated CO2 and biodiversity loss

Rapid changes in the Earth's climate caused by the burning of fossil fuels and deforestation pose a severe threat to forests of the Amazon basin. Warmer temperatures and drier conditions are predicted to cause widespread forest die back, with associated threats to regional economies, social welfare, and natural capital through changes in agricultural output and hydropower supply. Nonetheless, the implications will be global as the Amazon forest provides substantial services to humankind by regulating the climate through the cycling of carbon, water, and energy; and harbouring a large part of the world's biodiversity. I will address some of the overarching questions of how climate change will affect the Amazon forest, the biodiversity it harbours, and the ecosystem services it provides to humanity

A high-­resolution monitoring network investigating stem growth of tropical forest trees.

Ref. B51D-0453

Modeling wildfire dynamics using FLAM coupled with deep learning methods

We improve the accuracy of modeling burned areas using the FLAM model by identifying the hidden relationships between human and natural impacts on wildfire suppression efficiency using the deep learning-based methods. The wildfire climate impacts and adaptation model (FLAM) is able to capture impacts of climate, population, and fuel availability on burned areas. FLAM uses a process-based fire parameterization algorithm with a daily time step. The model uses daily temperature, precipitation, relative humidity and wind speed to assess climate impacts on ignition probability and fire spread. The key features implemented in FLAM include fuel moisture computation based on the Fine Fuel Moisture Code (FFMC) of the Canadian Forest Fire Weather Index (FWI), and a procedure to calibrate spatial fire suppression efficiency. The coupled FLAM and deep learning approach consists in the following steps. First, using FLAM we calibrate the suppression efficiency map by comparing model output with observed burned area (satellite data). Secondly, we use deep learning methods to identify and assess the drivers behind the calibrated map. The features used in the analysis include several socio-economic factors, including accessibility, GPP, land use maps, as well as burned areas and other parameters modeled by FLAM. Our approach allows classifying those features by their importance and find correlations between them. Finally, we implement the output of deep learning network to estimate the spatial suppression efficiency within FLAM (instead of calibrating it), and validate the approach using observed burned area. The proposed approach is implemented using the Google Earth Engine platform that provides flexibility in terms of input data sets and visualization tools. We will present the case study for Indonesia at 0.083 arc degree spatial resolution. It is planned to consider climate change impacts in more detail. Modeling burned areas and suppression efficiency can help the implementation of fire prevention policies for decision maker and provide important information for building adequate and cost-efficient fire response infrastructure

Partitioning of plant functional trait variation into phenotypic plasticity and neutral components reveals functional differences among neotropical tree species

Background: Tropical plant communities exhibit extraordinary species richness and functional diversity in highly heterogeneous environments. Albeit the fact that such environmental filtering shapes local species composition and associated plant functional traits, it remains elusive to what extend tropical vegetation might be able to acclimate to environmental changes via phenotypic plasticity, which could be a critical determinant affecting the resistance and resilience of tropical vegetation to projected climate change. Methods: Based on a dataset compiled from 345 individuals and comprising 34 tropical tree species we here investigated the role of phenotypic plasticity versus non-plastic variation among key plant functional traits, i.e. wood density, maximum height, leaf thickness, leaf area, specific leaf area, leaf dry mass, nitrogen and phosphorus content. We hypothesized that trait variation due to plasticity is driven by environmental variability independently of spatial effects due to geographic distance between forest stands, whereas non-plastic variation increases with geographic distance due to adaption of the plant community to the local environment. Based on these hypotheses we partitioned total observed trait variation into phenotypic plasticity and neutral components and quantified respective amount of variation related to environmental filtering and neutral community assembly. Results: We found that trait variation was strongly related to spatial factors, thus often masking phenotypic plasticity in response to environmental cues. However, respective environmental factors differed among plant functional traits, such that leaf traits varied in association with light regime and soil nutrient content, whereas wood traits were related to topography and soil water content. Our results further suggest that phenotypic plasticity increased with the range size of congeneric tree species, indicating less plasticity within range restricted endemics compared to their widespread congeners. Conclusions: Differences in phenotypic trait plasticity affect stress tolerance and range size of tropical tree species, therefore endemic species could be especially prone to projected climate change

Topographical heterogeneity governs species distribution and regeneration potential by mediating soil attributes in Western Himalayan forests

The present study is an attempt to understand variation in species composition and diversity and soil properties along topographic gradients in Western Himalayan reserve forests (400-3000m asl). To analyze changes in floristic composition, diversity, and regeneration status, we measured woody vegetation in forest plots at different altitudinal levels and contrasting aspects (North and south). Trees (diameter at breast height (DBH) > 10cm) and saplings (3-10cm DBH) were sampled in 10m×10m plots, shrubs were sampled in 5m×5m plots and seedlings (0-3cm DBH) were sampled in 1m×1m plots. To study variation in soil properties, samples were collected from each forest stand in five replicates from layers of 0-10cm, 10-20cm, and 20-30cm in soil depths. Canonical Correspondence Analysis (CCA) was applied to identify important factors that govern species distribution. Variance partitioning was conducted to quantify the relative contribution of elevation, slope aspect, vegetation attributes, and soil properties on regeneration potential of tree species. We found that environmental filtering shapes local species composition and associated edaphic factors in the region. Species richness and diversity were found to decrease with elevation. Soil properties (Organic Carbon, pH, and texture) and associated vegetation parameters did not vary significantly between the aspects. CCA confirmed that species composition was positively related to moisture content and available phosphorous at higher elevations, while reduced weathering rates and bulk density at lower elevations might have caused relatively lower nutrient turnover rates. Our study concludes that topographical variation and increased sum of soil nutrients are highly favorable for growth and development of plant species

Optimal balancing of xylem efficiency and safety explains plant vulnerability to drought

In vast areas of the world, the growth of forests and vegetation is water-limited and plant survival depends on the ability to avoid catastrophic hydraulic failure. Therefore, it is remarkable that plants take high hydraulic risks by operating at water potentials (ψ) that induce partial failure of the water conduits (xylem). Here we present an eco-evolutionary optimality principle for xylem conduit design that explains this phenomenon. Based on the hypothesis that conductive efficiency and safety are optimally co-adapted to the environment, we derive a simple relationship between the intrinsic tolerance to negative water potential (ψ50) and the environmentally dependent minimum xylem, ψmin. This relationship is constrained by a physiological tradeoff between xylem conductivity and safety, which is relatively strong at the level of individual conduits although it may be weak at the whole sapwood level. The model explains observed variation in ψ50 both across a large number of species, and along the xylem path in two species. The larger hydraulic safety margin in gymnosperms compared to angiosperms is explained as an adaptation to the gymnosperms' lower capacity to recover from conductivity loss. The constant xylem safety factor provides a powerful principle for simplifying and improving plant and vegetation models

Optimal balancing of xylem efficiency and safety explains plant vulnerability to drought

In vast areas of the world, forests and vegetation are water limited and plant survival depends on the ability to avoid catastrophic hydraulic failure. Therefore, it is remarkable that plants take hydraulic risks by operating at water potentials (ψ) that induce partial failure of the water conduits (xylem). Here we present an eco-evolutionary optimality principle for xylem conduit design that explains this phenomenon based on the hypothesis that conductive efficiency and safety are optimally co-adapted to the environment. The model explains the relationship between the tolerance to negative water potential (ψ50) and the environmentally dependent minimum ψ (ψmin) across a large number of species, and along the xylem pathway within individuals of two species studied. The wider hydraulic safety margin in gymnosperms compared to angiosperms can be explained as an adaptation to a higher susceptibility to accumulation of embolism. The model provides a novel optimality-based perspective on the relationship between xylem safety and efficiency