Future tree survival in European forests depends on understorey tree diversity

Climate change heavily threatens forest ecosystems worldwide and there is urgent need to understand what controls tree survival and forests stability. There is evidence that biodiversity can enhance ecosystem stability (Loreau and de Mazancourt in Ecol Lett 16:106–115, 2013; McCann in Nature 405:228–233, 2000), however it remains largely unclear whether this also holds for climate change and what aspects of biodiversity might be most important. Here we apply machine learning to outputs of a flexible-trait Dynamic Global Vegetation Model to unravel the effects of enhanced functional tree trait diversity and its sub-components on climate-change resistance of temperate forests (http://www.pik-potsdam.de/~billing/video/Forest_Resistance_LPJmLFIT.mp4). We find that functional tree trait diversity enhances forest resistance. We explain this with 1. stronger complementarity effects (~ 25% importance) especially improving the survival of trees in the understorey of up to + 16.8% (± 1.6%) and 2. environmental and competitive filtering of trees better adapted to future climate (40–87% importance). We conclude that forests containing functionally diverse trees better resist and adapt to future conditions. In this context, we especially highlight the role of functionally diverse understorey trees as they provide the fundament for better survival of young trees and filtering of resistant tree individuals in the future

Climate-induced hysteresis of the tropical forest in a fire-enabled Earth system model

Tropical rainforests are recognized as one of the terrestrial tipping elements which could have profound impacts on the global climate, once their vegetation has transitioned into savanna or grassland states. While several studies investigated the savannization of, e.g., the Amazon rainforest, few studies considered the influence of fire. Fire is expected to potentially shift the savanna-forest boundary and hence impact the dynamical equilibrium between these two possible vegetation states under changing climate. To investigate the climate-induced hysteresis in pan-tropical forests and the impact of fire under future climate conditions, we employed the Earth system model CM2Mc, which is biophysically coupled to the fire-enabled state-of-the-art dynamic global vegetation model LPJmL. We conducted several simulation experiments where atmospheric CO2 concentrations increased (impact phase) and decreased from the new state (recovery phase), each with and without enabling wildfires. We find a hysteresis of the biomass and vegetation cover in tropical forest systems, with a strong regional heterogeneity. After biomass loss along increasing atmospheric CO2 concentrations and accompanied mean surface temperature increase of about 4 ∘C (impact phase), the system does not recover completely into its original state on its return path, even though atmospheric CO2 concentrations return to their original state. While not detecting large-scale tipping points, our results show a climate-induced hysteresis in tropical forest and lagged responses in forest recovery after the climate has returned to its original state. Wildfires slightly widen the climate-induced hysteresis in tropical forests and lead to a lagged response in forest recovery by ca. 30 years

Improving the LPJmL4-SPITFIRE vegetation–fire model for South America using satellite data

Vegetation fires influence global vegetation distribution, ecosystem functioning, and global carbon cycling. Specifically in South America, changes in fire occurrence together with land-use change accelerate ecosystem fragmentation and increase the vulnerability of tropical forests and savannas to climate change. Dynamic global vegetation models (DGVMs) are valuable tools to estimate the effects of fire on ecosystem functioning and carbon cycling under future climate changes. However, most fire-enabled DGVMs have problems in capturing the magnitude, spatial patterns, and temporal dynamics of burned area as observed by satellites. As fire is controlled by the interplay of weather conditions, vegetation properties, and human activities, fire modules in DGVMs can be improved in various aspects. In this study we focus on improving the controls of climate and hence fuel moisture content on fire danger in the LPJmL4-SPITFIRE DGVM in South America, especially for the Brazilian fire-prone biomes of Caatinga and Cerrado. We therefore test two alternative model formulations (standard Nesterov Index and a newly implemented water vapor pressure deficit) for climate effects on fire danger within a formal model–data integration setup where we estimate model parameters against satellite datasets of burned area (GFED4) and aboveground biomass of trees. Our results show that the optimized model improves the representation of spatial patterns and the seasonal to interannual dynamics of burned area especially in the Cerrado and Caatinga regions. In addition, the model improves the simulation of aboveground biomass and the spatial distribution of plant functional types (PFTs). We obtained the best results by using the water vapor pressure deficit (VPD) for the calculation of fire danger. The VPD includes, in comparison to the Nesterov Index, a representation of the air humidity and the vegetation density. This work shows the successful application of a systematic model–data integration setup, as well as the integration of a new fire danger formulation, in order to optimize a process-based fire-enabled DGVM. It further highlights the potential of this approach to achieve a new level of accuracy in comprehensive global fire modeling and prediction

CM2Mc-LPJmL v1.0: biophysical coupling of a process-based dynamic vegetation model with managed land to a general circulation model

The terrestrial biosphere is exposed to land-use and climate change, which not only affects vegetation dynamics but also changes land–atmosphere feedbacks. Specifically, changes in land cover affect biophysical feedbacks of water and energy, thereby contributing to climate change. In this study, we couple the well-established and comprehensively validated dynamic global vegetation model LPJmL5 (Lund–Potsdam–Jena managed Land) to the coupled climate model CM2Mc, the latter of which is based on the atmosphere model AM2 and the ocean model MOM5 (Modular Ocean Model 5), and name it CM2Mc-LPJmL. In CM2Mc, we replace the simple land-surface model LaD (Land Dynamics; where vegetation is static and prescribed) with LPJmL5, and we fully couple the water and energy cycles using the Geophysical Fluid Dynamics Laboratory (GFDL) Flexible Modeling System (FMS). Several improvements to LPJmL5 were implemented to allow a fully functional biophysical coupling. These include a sub-daily cycle for calculating energy and water fluxes, conductance of the soil evaporation and plant interception, canopy-layer humidity, and the surface energy balance in order to calculate the surface and canopy-layer temperature within LPJmL5. Exchanging LaD with LPJmL5 and, therefore, switching from a static and prescribed vegetation to a dynamic vegetation allows us to model important biospheric processes, including fire, mortality, permafrost, hydrological cycling and the impacts of managed land (crop growth and irrigation). Our results show that CM2Mc-LPJmL has similar temperature and precipitation biases to the original CM2Mc model with LaD. The performance of LPJmL5 in the coupled system compared to Earth observation data and to LPJmL offline simulation results is within acceptable error margins. The historical global mean temperature evolution of our model setup is within the range of CMIP5 (Coupled Model Intercomparison Project Phase 5) models. The comparison of model runs with and without land-use change shows a partially warmer and drier climate state across the global land surface. CM2Mc-LPJmL opens new opportunities to investigate important biophysical vegetation–climate feedbacks with a state-of-the-art and process-based dynamic vegetation model

Variable tree rooting strategies are key for modelling the distribution, productivity and evapotranspiration of tropical evergreen forests

A variety of modelling studies have suggested tree rooting depth as a key variable to explain evapotranspiration rates, productivity and the geographical distribution of evergreen forests in tropical South America. However, none of those studies have acknowledged resource investment, timing and physical constraints of tree rooting depth within a competitive environment, undermining the ecological realism of their results. Here, we present an approach of implementing variable rooting strategies and dynamic root growth into the LPJmL4.0 (Lund-Potsdam-Jena managed Land) dynamic global vegetation model (DGVM) and apply it to tropical and sub-tropical South America under contemporary climate conditions. We show how competing rooting strategies which underlie the trade-off between above- and below-ground carbon investment lead to more realistic simulation of intra-annual productivity and evapotranspiration and consequently of forest cover and spatial biomass distribution. We find that climate and soil depth determine a spatially heterogeneous pattern of mean rooting depth and below-ground biomass across the study region. Our findings support the hypothesis that the ability of evergreen trees to adjust their rooting systems to seasonally dry climates is crucial to explaining the current dominance, productivity and evapotranspiration of evergreen forests in tropical South America.Fil: Sakschewski, Boris. Potsdam Institute for Climate Impact Research; AlemaniaFil: Von Bloh, Werner. Humboldt-Universität zu Berlin; AlemaniaFil: Drüke, Markus. Humboldt-Universität zu Berlin; AlemaniaFil: Sörensson, Anna. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Centro de Investigaciones del Mar y la Atmósfera. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Centro de Investigaciones del Mar y la Atmósfera; ArgentinaFil: Ruscica, Romina. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Centro de Investigaciones del Mar y la Atmósfera. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Centro de Investigaciones del Mar y la Atmósfera; ArgentinaFil: Langerwisch, Fanny. Universitat Potsdam; AlemaniaFil: Billing, Maik. Universidade Federal de Santa Catarina; BrasilFil: Bereswill, Sarah. Universidade Estadual de Campinas; BrasilFil: Hirota, Marina. Potsdam Institute for Climate Impact Research; AlemaniaFil: Oliveira, Rafael Silva. Potsdam Institute for Climate Impact Research; AlemaniaFil: Heinke, Jens. Potsdam Institute for Climate Impact Research; AlemaniaFil: Thonicke, Kirsten. Potsdam Institute for Climate Impact Research; Alemani

Variable tree rooting strategies are key for modelling the distribution, productivity and evapotranspiration of tropical evergreen forests

A variety of modelling studies have suggested tree rooting depth as a key variable to explain evapotranspiration rates, productivity and the geographical distribution of evergreen forests in tropical South America. However, none of those studies have acknowledged resource investment, timing and physical constraints of tree rooting depth within a competitive environment, undermining the ecological realism of their results. Here, we present an approach of implementing variable rooting strategies and dynamic root growth into the LPJmL4.0 (Lund-Potsdam-Jena managed Land) dynamic global vegetation model (DGVM) and apply it to tropical and sub-tropical South America under contemporary climate conditions. We show how competing rooting strategies which underlie the trade-off between above- and below-ground carbon investment lead to more realistic simulation of intra-annual productivity and evapotranspiration and consequently of forest cover and spatial biomass distribution. We find that climate and soil depth determine a spatially heterogeneous pattern of mean rooting depth and below-ground biomass across the study region. Our findings support the hypothesis that the ability of evergreen trees to adjust their rooting systems to seasonally dry climates is crucial to explaining the current dominance, productivity and evapotranspiration of evergreen forests in tropical South America

Elevated CO₂ does not increase eucalypt forest productivity on a low-phosphorus soil

Rising atmospheric CO2 stimulates photosynthesis and productivity of forests, offsetting CO2 emissions. Elevated CO2 experiments in temperate planted forests yielded ~23% increases in productivity over the initial years. Whether similar CO2 stimulation occurs in mature evergreen broadleaved forests on low-phosphorus (P) soils is unknown, largely due to lack of experimental evidence. This knowledge gap creates major uncertainties in future climate projections as a large part of the tropics is P-limited. Here,we increased atmospheric CO2 concentration in a mature broadleaved evergreen eucalypt forest for three years, in the first large-scale experiment on a P-limited site. We show that tree growth and other aboveground productivity components did not significantly increase in response to elevated CO2 in three years, despite a sustained 19% increase in leaf photosynthesis. Moreover, tree growth in ambient CO2 was strongly P-limited and increased by ~35% with added phosphorus. The findings suggest that P availability may potentially constrain CO2-enhanced productivity in P-limited forests; hence, future atmospheric CO2 trajectories may be higher than predicted by some models. As a result, coupled climate-carbon models should incorporate both nitrogen and phosphorus limitations to vegetation productivity in estimating future carbon sinks

Network dynamics of drought-induced tipping cascades in the Amazon rainforest

Tipping elements are nonlinear subsystems of the Earth system that can potentially abruptly and irreversibly shift if environmental change occurs. Among these tipping elements is the Amazon rainforest, which is threatened by anthropogenic activities and increasingly frequent droughts. Here, we assess how extreme deviations from climatological rainfall regimes may cause local forest-savanna transitions that cascade through the coupled forest-climate system. We develop a dynamical network model to uncover the role of atmospheric moisture recycling in such tipping cascades. We account for the heterogeneity in critical thresholds of the forest caused by adaptation to local climatic conditions. Our results reveal that, despite this adaptation, increased dry-season intensity may trigger tipping events particularly in the southeastern Amazon. Moisture recycling is responsible for one-fourth of the tipping events. If the rate of climate change exceeds the adaptive capacity of some parts of the forest, secondary effects through moisture recycling may exceed this capacity in other regions, increasing the overall risk of tipping across the Amazon rainforest

Frost and leaf-size gradients in forests: global patterns and experimental evidence

Explanations of leaf size variation commonly focus on water availability, yet leaf size also varies with latitude and elevation in environments where water is not strongly limiting. We provide the first conclusive test of a prediction of leaf energy balance theory that may explain this pattern: large leaves are more vulnerable to night-time chilling, because their thick boundary layers impede convective exchange with the surrounding air. Seedlings of New Zealand evergreens spanning 12-fold variation in leaf width were exposed to clear night skies, and leaf temperatures measured with thermocouples. We then used a global dataset to assess several climate variables as predictors of leaf size in forest assemblages. Leaf-minus-air temperature was strongly correlated with leaf width, ranging from -0.9 to -3.2 C in the smallest- and largest-leaved species, respectively. MAT and frost-free period were good predictors of evergreen angiosperm leaf size in forest assemblages, but no climate variable predicted deciduous leaf size. Although winter deciduousness makes large leaves possible in strongly seasonal climates, large-leaved evergreens are largely confined to frost-free climates because of their susceptibility to radiative cooling. Evergreen leaf size data can therefore be used to enhance vegetation models, and to infer palaeotemperatures from fossil leaf assemblages

Committed Global Warming Risks Triggering Multiple Climate Tipping Points

Many scenarios for limiting global warming to 1.5°C assume planetary-scale carbon dioxide removal sufficient to exceed anthropogenic emissions, resulting in radiative forcing falling and temperatures stabilizing. However, such removal technology may prove unfeasible for technical, environmental, political, or economic reasons, resulting in continuing greenhouse gas emissions from hard-to-mitigate sectors. This may lead to constant concentration scenarios, where net anthropogenic emissions remain non-zero but small, and are roughly balanced by natural carbon sinks. Such a situation would keep atmospheric radiative forcing roughly constant. Fixed radiative forcing creates an equilibrium “committed” warming, captured in the concept of “equilibrium climate sensitivity.” This scenario is rarely analyzed as a potential extension to transient climate scenarios. Here, we aim to understand the planetary response to such fixed concentration commitments, with an emphasis on assessing the resulting likelihood of exceeding temperature thresholds that trigger climate tipping points. We explore transients followed by respective equilibrium committed warming initiated under low to high emission scenarios. We find that the likelihood of crossing the 1.5°C threshold and the 2.0°C threshold is 83% and 55%, respectively, if today's radiative forcing is maintained until achieving equilibrium global warming. Under the scenario that best matches current national commitments (RCP4.5), we estimate that in the transient stage, two tipping points will be crossed. If radiative forcing is then held fixed after the year 2100, a further six tipping point thresholds are crossed. Achieving a trajectory similar to RCP2.6 requires reaching net-zero emissions rapidly, which would greatly reduce the likelihood of tipping events