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- ItemVariable tree rooting strategies are key for modelling the distribution, productivity and evapotranspiration of tropical evergreen forests(Katlenburg-Lindau : European Geosciences Union, 2021) Sakschewski, Boris; Bloh, Werner von; Drüke, Markus; Sörensson, Anna Amelia; Ruscica, Romina; Langerwisch, Fanny; Billing, Maik; Bereswill, Sarah; Hirota, Marina; Oliveira, Rafael Silva; Heinke, Jens; Thonicke, KirstenA 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.
- ItemUnderstanding the uncertainty in global forest carbon turnover(Katlenburg-Lindau [u.a.] : Copernicus, 2020) Pugh, Thomas A.M.; Rademacher, Tim; Shafer, Sarah L.; Steinkamp, Jörg; Barichivich, Jonathan; Beckage, Brian; Haverd, Vanessa; Harper, Anna; Heinke, Jens; Nishina, Kazuya; Rammig, Anja; Sato, Hisashi; Arneth, Almut; Hantson, Stijn; Hickler, Thomas; Kautz, Markus; Quesada, Benjamin; Smith, Benjamin; Thonicke, KirstenThe length of time that carbon remains in forest biomass is one of the largest uncertainties in the global carbon cycle, with both recent historical baselines and future responses to environmental change poorly constrained by available observations. In the absence of large-scale observations, models used for global assessments tend to fall back on simplified assumptions of the turnover rates of biomass and soil carbon pools. In this study, the biomass carbon turnover times calculated by an ensemble of contemporary terrestrial biosphere models (TBMs) are analysed to assess their current capability to accurately estimate biomass carbon turnover times in forests and how these times are anticipated to change in the future. Modelled baseline 1985-2014 global average forest biomass turnover times vary from 12.2 to 23.5 years between TBMs. TBM differences in phenological processes, which control allocation to, and turnover rate of, leaves and fine roots, are as important as tree mortality with regard to explaining the variation in total turnover among TBMs. The different governing mechanisms exhibited by each TBM result in a wide range of plausible turnover time projections for the end of the century. Based on these simulations, it is not possible to draw robust conclusions regarding likely future changes in turnover time, and thus biomass change, for different regions. Both spatial and temporal uncertainty in turnover time are strongly linked to model assumptions concerning plant functional type distributions and their controls. Thirteen model-based hypotheses of controls on turnover time are identified, along with recommendations for pragmatic steps to test them using existing and novel observations. Efforts to resolve uncertainty in turnover time, and thus its impacts on the future evolution of biomass carbon stocks across the world's forests, will need to address both mortality and establishment components of forest demography, as well as allocation of carbon to woody versus non-woody biomass growth. © 2020 SPIE. All rights reserved.
- ItemTree mortality submodels drive simulated long-term forest dynamics: assessing 15 models from the stand to global scale(Ithaca, NY : ESA, 2019) Bugmann, Harald; Seidl, Rupert; Hartig, Florian; Bohn, Friedrich; Bruna, Josef; Cailleret, Maxime; Francois, Louis; Heinke, Jens; Henrot, Alexandra-Jane; Hickler, Thomas; Huelsmann, Lisa; Huth, Andreas; Jacquemin, Ingrid; Kollas, Chris; Lasch-Born, Petra; Lexer, Manfred J.; Merganic, Jan; Merganicova, Katarna; Mette, Tobias; Miranda, Brian R.; Nadal-Sala, Daniel; Rammer, Werner; Rammig, Anja; Reineking, Bjoern; Roedig, Edna; Sabate, Santi; Steinkamp, Jorg; Suckow, Felicitas; Vacchiano, Giorgio; Wild, Jan; Xu, Chonggang; Reyer, Christopher P.O.Models are pivotal for assessing future forest dynamics under the impacts of changing climate and management practices, incorporating representations of tree growth, mortality, and regeneration. Quantitative studies on the importance of mortality submodels are scarce. We evaluated 15 dynamic vegetation models (DVMs) regarding their sensitivity to different formulations of tree mortality under different degrees of climate change. The set of models comprised eight DVMs at the stand scale, three at the landscape scale, and four typically applied at the continental to global scale. Some incorporate empirically derived mortality models, and others are based on experimental data, whereas still others are based on theoretical reasoning. Each DVM was run with at least two alternative mortality submodels. Model behavior was evaluated against empirical time series data, and then, the models were subjected to different scenarios of climate change. Most DVMs matched empirical data quite well, irrespective of the mortality submodel that was used. However, mortality submodels that performed in a very similar manner against past data often led to sharply different trajectories of forest dynamics under future climate change. Most DVMs featured high sensitivity to the mortality submodel, with deviations of basal area and stem numbers on the order of 10–40% per century under current climate and 20–170% under climate change. The sensitivity of a given DVM to scenarios of climate change, however, was typically lower by a factor of two to three. We conclude that (1) mortality is one of the most uncertain processes when it comes to assessing forest response to climate change, and (2) more data and a better process understanding of tree mortality are needed to improve the robustness of simulated future forest dynamics. Our study highlights that comparing several alternative mortality formulations in DVMs provides valuable insights into the effects of process uncertainties on simulated future forest dynamics. © 2019 The Authors.