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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.
- ItemPerformance evaluation of global hydrological models in six large Pan-Arctic watersheds(Dordrecht [u.a.] : Springer Science + Business Media B.V, 2020) Gädeke, Anne; Krysanova, Valentina; Aryal, Aashutosh; Chang, Jinfeng; Grillakis, Manolis; Hanasaki, Naota; Koutroulis, Aristeidis; Pokhrel, Yadu; Satoh, Yusuke; Schaphoff, Sibyll; Müller Schmied, Hannes; Stacke, Tobias; Tang, Qiuhong; Wada, Yoshihide; Thonicke, KirstenGlobal Water Models (GWMs), which include Global Hydrological, Land Surface, and Dynamic Global Vegetation Models, present valuable tools for quantifying climate change impacts on hydrological processes in the data scarce high latitudes. Here we performed a systematic model performance evaluation in six major Pan-Arctic watersheds for different hydrological indicators (monthly and seasonal discharge, extremes, trends (or lack of), and snow water equivalent (SWE)) via a novel Aggregated Performance Index (API) that is based on commonly used statistical evaluation metrics. The machine learning Boruta feature selection algorithm was used to evaluate the explanatory power of the API attributes. Our results show that the majority of the nine GWMs included in the study exhibit considerable difficulties in realistically representing Pan-Arctic hydrological processes. Average APIdischarge (monthly and seasonal discharge) over nine GWMs is > 50% only in the Kolyma basin (55%), as low as 30% in the Yukon basin and averaged over all watersheds APIdischarge is 43%. WATERGAP2 and MATSIRO present the highest (APIdischarge > 55%) while ORCHIDEE and JULES-W1 the lowest (APIdischarge ≤ 25%) performing GWMs over all watersheds. For the high and low flows, average APIextreme is 35% and 26%, respectively, and over six GWMs APISWE is 57%. The Boruta algorithm suggests that using different observation-based climate data sets does not influence the total score of the APIs in all watersheds. Ultimately, only satisfactory to good performing GWMs that effectively represent cold-region hydrological processes (including snow-related processes, permafrost) should be included in multi-model climate change impact assessments in Pan-Arctic watersheds. © 2020, The Author(s).
- 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.
- ItemCM2Mc-LPJmL v1.0: biophysical coupling of a process-based dynamic vegetation model with managed land to a general circulation model(Katlenburg-Lindau : Copernicus, 2021-7-1) Drüke, Markus; von Bloh, Werner; Petri, Stefan; Sakschewski, Boris; Schaphoff, Sibyll; Forkel, Matthias; Huiskamp, Willem; Feulner, Georg; Thonicke, KirstenThe 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.
- ItemSimulating functional diversity of European natural forests along climatic gradients(Oxford [u.a.] : Wiley-Blackwell, 2020) Thonicke, Kirsten; Billing, Maik; von Bloh, Werner; Sakschewski, Boris; Niinemets, Ülo; Peñuelas, Josep; Cornelissen, J. Hans C.; Onoda, Yusuke; van Bodegom, Peter; Schaepman, Michael E.; Schneider, Fabian D.; Walz, ArianeAim: We analyse how functional diversity (FD) varies across European natural forests to understand the effects of environmental and competitive filtering on plant trait distribution. Location: Forest ecosystems in Europe from 11°W to 36°E and 29.5°N to 62°N. Taxon: Pinaceae, Fagaceae and Betulaceae, Oleaceae, Tiliaceae, Aceraceae, Leguminosae (unspecific). Methods: We adopted the existing Dynamic Global Vegetation Model Lund-Potsdam-Jena managed Land of flexible individual traits (LPJmL-FIT) for Europe by eliminating both bioclimatic limits of plant functional types (PFTs) and replacing prescribed values of functional traits for PFTs with emergent values under influence of environmental filtering and competition. We quantified functional richness (FR), functional divergence (FDv) and functional evenness (FE) in representative selected sites and at Pan-European scale resulting from simulated functional and structural trait combinations of individual trees. While FR quantifies the amount of occupied trait space, FDv and FE describe the distribution and abundance of trait combinations, respectively, in a multidimensional trait space. Results: Lund-Potsdam-Jena managed Land of flexible individual traits reproduces spatial PFTs and local trait distributions and agrees well with observed productivity, biomass and tree height of European natural forests. The observed site-specific trait distributions and spatial gradients of traits of the leaf- and stem-resource economics spectra coincide with environmental filtering and the competition for light and water in environments with strong abiotic stress. Where deciduous and needle-leaved trees co-occur, for example, in boreal and mountainous forests, the potential niche space is wide (high FR), and extreme ends in the niche space are occupied (high FDv). We find high FDv in Mediterranean forests where drought increasingly limits tree growth, thus niche differentiation becomes more important. FDv decreases in temperate forests where a cold climate increasingly limits growth efficiency of broad-leaved summer green trees, thus reducing the importance of competitive exclusion. Highest FE was simulated in wet Atlantic and southern Europe which indicated relatively even niche occupation and thus high resource-use efficiency. Main Conclusions: We find FD resulting from both environmental and competitive filtering. Pan-European FR, FDv and FE demonstrate the influence of climate gradients and intra- and inter-PFT competition. The indices underline a generally high FD of natural forests in Europe. Co-existence of functionally diverse trees across PFTs emerges from alternative (life-history) strategies, disturbance and tree demography. © 2020 John Wiley & Sons Ltd
- ItemClimate change reduces winter overland travel across the Pan-Arctic even under low-end global warming scenarios(Bristol : IOP Publ., 2021-2-10) Gädeke, Anne; Langer, Moritz; Boike, Julia; Burke, Eleanor J.; Chang, Jinfeng; Head, Melissa; Reyer, Christopher P.O.; Schaphoff, Sibyll; Thiery, Wim; Thonicke, KirstenAmplified climate warming has led to permafrost degradation and a shortening of the winter season, both impacting cost-effective overland travel across the Arctic. Here we use, for the first time, four state-of-the-art Land Surface Models that explicitly consider ground freezing states, forced by a subset of bias-adjusted CMIP5 General Circulation Models to estimate the impact of different global warming scenarios (RCP2.6, 6.0, 8.5) on two modes of winter travel: overland travel days (OTDs) and ice road construction days (IRCDs). We show that OTDs decrease by on average −13% in the near future (2021–2050) and between −15% (RCP2.6) and −40% (RCP8.5) in the far future (2070–2099) compared to the reference period (1971–2000) when 173 d yr−1 are simulated across the Pan-Arctic. Regionally, we identified Eastern Siberia (Sakha (Yakutia), Khabarovsk Krai, Magadan Oblast) to be most resilient to climate change, while Alaska (USA), the Northwestern Russian regions (Yamalo, Arkhangelsk Oblast, Nenets, Komi, Khanty-Mansiy), Northern Europe and Chukotka are highly vulnerable. The change in OTDs is most pronounced during the shoulder season, particularly in autumn. The IRCDs reduce on average twice as much as the OTDs under all climate scenarios resulting in shorter operational duration. The results of the low-end global warming scenario (RCP2.6) emphasize that stringent climate mitigation policies have the potential to reduce the impact of climate change on winter mobility in the second half of the 21st century. Nevertheless, even under RCP2.6, our results suggest substantially reduced winter overland travel implying a severe threat to livelihoods of remote communities and increasing costs for resource exploration and transport across the Arctic.
- ItemTackling unresolved questions in forest ecology: The past and future role of simulation models([S.l.] : John Wiley & Sons, Inc., 2021) Maréchaux, Isabelle; Langerwisch, Fanny; Huth, Andreas; Bugmann, Harald; Morin, Xavier; Reyer, Christopher P.O.; Seidl, Rupert; Collalti, Alessio; Dantas de Paula, Mateus; Fischer, Rico; Gutsch, Martin; Lexer, Manfred J.; Lischke, Heike; Rammig, Anja; Rödig, Edna; Sakschewski, Boris; Taubert, Franziska; Thonicke, Kirsten; Vacchiano, Giorgio; Bohn, Friedrich J.Understanding the processes that shape forest functioning, structure, and diversity remains challenging, although data on forest systems are being collected at a rapid pace and across scales. Forest models have a long history in bridging data with ecological knowledge and can simulate forest dynamics over spatio-temporal scales unreachable by most empirical investigations.We describe the development that different forest modelling communities have followed to underpin the leverage that simulation models offer for advancing our understanding of forest ecosystems.Using three widely applied but contrasting approaches - species distribution models, individual-based forest models, and dynamic global vegetation models - as examples, we show how scientific and technical advances have led models to transgress their initial objectives and limitations. We provide an overview of recent model applications on current important ecological topics and pinpoint ten key questions that could, and should, be tackled with forest models in the next decade.Synthesis. This overview shows that forest models, due to their complementarity and mutual enrichment, represent an invaluable toolkit to address a wide range of fundamental and applied ecological questions, hence fostering a deeper understanding of forest dynamics in the context of global change.
- ItemClimate-induced hysteresis of the tropical forest in a fire-enabled Earth system model(Berlin ; Heidelberg : Springer, 2021) Drüke, Markus; Bloh, Werner von; Sakschewski, Boris; Wunderling, Nico; Petri, Stefan; Cardoso, Manoel; Barbosa, Henrique M.J.; Thonicke, KirstenTropical 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.
- ItemAccelerated photosynthesis routine in LPJmL4(Katlenburg-Lindau : Copernicus, 2023) Niebsch, Jenny; Bloh, Werner von; Thonicke, Kirsten; Ramlau, RonnyThe increasing impacts of climate change require strategies for climate adaptation. Dynamic global vegetation models (DGVMs) are one type of multi-sectorial impact model with which the effects of multiple interacting processes in the terrestrial biosphere under climate change can be studied. The complexity of DGVMs is increasing as more and more processes, especially for plant physiology, are implemented. Therefore, there is a growing demand for increasing the computational performance of the underlying algorithms as well as ensuring their numerical accuracy. One way to approach this issue is to analyse the routines which have the potential for improved computational efficiency and/or increased accuracy when applying sophisticated mathematical methods. In this paper, the Farquhar–Collatz photosynthesis model under water stress as implemented in the Lund–Potsdam–Jena managed Land DGVM (4.0.002) was examined. We additionally tested the uncertainty of most important parameter of photosynthesis as an additional approach to improve model quality. We found that the numerical solution of a nonlinear equation, so far solved with the bisection method, could be significantly improved by using Newton’s method instead. The latter requires the computation of the derivative of the underlying function which is presented. Model simulations show a significantly lower number of iterations to solve the equation numerically and an overall run time reduction of the model of about 16 % depending on the chosen accuracy. Increasing the parameters θ and αC3 by 10 %, respectively, while keeping all other parameters at their original value, increased global gross primary production (GPP) by 2.384 and 9.542 GtC yr−1, respectively. The Farquhar–Collatz photosynthesis model forms the core component in many DGVMs and land surface models. An update in the numerical solution of the nonlinear equation in connection with adjusting globally important parameters to best known values can therefore be applied to similar photosynthesis models. Furthermore, this exercise can serve as an example for improving computationally costly routines while improving their mathematical accuracy.
- ItemCharacterization of land cover-specific fire regimes in the Brazilian Amazon(Heidelberg : Springer, 2022) Cano-Crespo, Ana; Traxl, Dominik; Prat-Ortega, Genís; Rolinski, Susanne; Thonicke, KirstenHumans profoundly alter fire regimes both directly, by introducing changes in fuel dynamics and ignitions, and indirectly, by increasing the release of greenhouse gases and aerosols from fires, which can alter regional climate and, as a consequence, modify fuel moisture and availability. Interactions between vegetation dynamics, regional climate change and anthropogenic pressure lead to high heterogeneity in the spatio-temporal fire distribution. We use the new FireTracks Scientific Dataset that tracks the spatio-temporal development of individual fires to analyse fire regimes in the Brazilian Legal Amazon over the period 2002–2020. We analyse fire size, duration, intensity and rate of spread in six different land-cover classes. Particular combinations of fire features determine the dominant and characteristic fire regime in each of them. We find that fires in savannas and evergreen forests burn the largest areas and are the most long lasting. Forest fires have the potential for burning at the highest intensities, whereas higher rates of spread are found in savannas. Woody savanna and grassland fires are usually affected by smaller, shorter, less-intense fires compared with fires in evergreen forest and savanna. However, fires in grasslands can burn at rates of spread as high as savanna fires as a result of the easily flammable fuel. We observe that fires in deciduous forests and croplands are generally small, short and low intense, although the latter can sustain high rates of spread due to the dry post-harvest residuals. The reconstructed fire regimes for each land cover can be used to improve the simulated fire characteristics by models and, thus, future projections.