Search Results
Variable tree rooting strategies are key for modelling the distribution, productivity and evapotranspiration of tropical evergreen forests
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, Kirsten
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.
Investigating potential transferability of place-based research in land system science
2016, Václavík, Tomáš, Langerwisch, Fanny, Cotter, Marc, Fick, Johanna, Häuser, Inga, Hotes, Stefan, Kamp, Johannes, Settele, Josef, Spangenberg, Joachim H., Seppelt, Ralf
Much of our knowledge about land use and ecosystem services in interrelated social-ecological systems is derived from place-based research. While local and regional case studies provide valuable insights, it is often unclear how relevant this research is beyond the study areas. Drawing generalized conclusions about practical solutions to land management from local observations and formulating hypotheses applicable to other places in the world requires that we identify patterns of land systems that are similar to those represented by the case study. Here, we utilize the previously developed concept of land system archetypes to investigate potential transferability of research from twelve regional projects implemented in a large joint research framework that focus on issues of sustainable land management across four continents. For each project, we characterize its project archetype, i.e. the unique land system based on a synthesis of more than 30 datasets of land-use intensity, environmental conditions and socioeconomic indicators. We estimate the transferability potential of project research by calculating the statistical similarity of locations across the world to the project archetype, assuming higher transferability potentials in locations with similar land system characteristics. Results show that areas with high transferability potentials are typically clustered around project sites but for some case studies can be found in regions that are geographically distant, especially when values of considered variables are close to the global mean or where the project archetype is driven by large-scale environmental or socioeconomic conditions. Using specific examples from the local case studies, we highlight the merit of our approach and discuss the differences between local realities and information captured in global datasets. The proposed method provides a blueprint for large research programs to assess potential transferability of place-based studies to other geographical areas and to indicate possible gaps in research efforts.
Deforestation in Amazonia impacts riverine carbon dynamics
2016, Langerwisch, Fanny, Walz, Ariane, Rammig, Anja, Tietjen, Britta, Thonicke, Kirsten, Cramer, Wolfgang
Fluxes of organic and inorganic carbon within the Amazon basin are considerably controlled by annual flooding, which triggers the export of terrigenous organic material to the river and ultimately to the Atlantic Ocean. The amount of carbon imported to the river and the further conversion, transport and export of it depend on temperature, atmospheric CO2, terrestrial productivity and carbon storage, as well as discharge. Both terrestrial productivity and discharge are influenced by climate and land use change. The coupled LPJmL and RivCM model system (Langerwisch et al., 2016) has been applied to assess the combined impacts of climate and land use change on the Amazon riverine carbon dynamics. Vegetation dynamics (in LPJmL) as well as export and conversion of terrigenous carbon to and within the river (RivCM) are included. The model system has been applied for the years 1901 to 2099 under two deforestation scenarios and with climate forcing of three SRES emission scenarios, each for five climate models. We find that high deforestation (business-as-usual scenario) will strongly decrease (locally by up to 90%) riverine particulate and dissolved organic carbon amount until the end of the current century. At the same time, increase in discharge leaves net carbon transport during the first decades of the century roughly unchanged only if a sufficient area is still forested. After 2050 the amount of transported carbon will decrease drastically. In contrast to that, increased temperature and atmospheric CO2 concentration determine the amount of riverine inorganic carbon stored in the Amazon basin. Higher atmospheric CO2 concentrations increase riverine inorganic carbon amount by up to 20% (SRES A2). The changes in riverine carbon fluxes have direct effects on carbon export, either to the atmosphere via outgassing or to the Atlantic Ocean via discharge. The outgassed carbon will increase slightly in the Amazon basin, but can be regionally reduced by up to 60% due to deforestation. The discharge of organic carbon to the ocean will be reduced by about 40% under the most severe deforestation and climate change scenario. These changes would have local and regional consequences on the carbon balance and habitat characteristics in the Amazon basin itself as well as in the adjacent Atlantic Ocean.
Tackling unresolved questions in forest ecology: The past and future role of simulation models
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.
A generic pixel-to-point comparison for simulated large-scale ecosystem properties and ground-based observations: An example from the Amazon region
2018, Rammig, Anja, Heinke, Jens, Hofhansl, Florian, Verbeeck, Hans, Baker, Timothy R., Christoffersen, Bradley, Ciais, Philippe, De Deurwaerder, Hannes, Fleischer, Katrin, Galbraith, David, Guimberteau, Matthieu, Huth, Andreas, Johnson, Michelle, Krujit, Bart, Langerwisch, Fanny, Meir, Patrick, Papastefanou, Phillip, Sampaio, Gilvan, Thonicke, Kirsten, von Randow, Celso, Zang, Christian, Rödig, Edna
Comparing model output and observed data is an important step for assessing model performance and quality of simulation results. However, such comparisons are often hampered by differences in spatial scales between local point observations and large-scale simulations of grid cells or pixels. In this study, we propose a generic approach for a pixel-to-point comparison and provide statistical measures accounting for the uncertainty resulting from landscape variability and measurement errors in ecosystem variables. The basic concept of our approach is to determine the statistical properties of small-scale (within-pixel) variability and observational errors, and to use this information to correct for their effect when large-scale area averages (pixel) are compared to small-scale point estimates. We demonstrate our approach by comparing simulated values of aboveground biomass, woody productivity (woody net primary productivity, NPP) and residence time of woody biomass from four dynamic global vegetation models (DGVMs) with measured inventory data from permanent plots in the Amazon rainforest, a region with the typical problem of low data availability, potential scale mismatch and thus high model uncertainty. We find that the DGVMs under- and overestimate aboveground biomass by 25% and up to 60%, respectively. Our comparison metrics provide a quantitative measure for model-data agreement and show moderate to good agreement with the region-wide spatial biomass pattern detected by plot observations. However, all four DGVMs overestimate woody productivity and underestimate residence time of woody biomass even when accounting for the large uncertainty range of the observational data. This is because DGVMs do not represent the relation between productivity and residence time of woody biomass correctly. Thus, the DGVMs may simulate the correct large-scale patterns of biomass but for the wrong reasons. We conclude that more information about the underlying processes driving biomass distribution are necessary to improve DGVMs. Our approach provides robust statistical measures for any pixel-to-point comparison, which is applicable for evaluation of models and remote-sensing products.
Combined effects of climate and land-use change on the provision of ecosystem services in rice agro-ecosystems
2017, Langerwisch, Fanny, Václavík, Tomáš, von Bloh, Werner, Vetter, Tobias, Thonicke, Kirsten
Irrigated rice croplands are among the world's most important agro-ecosystems. They provide food for more than 3.5 billion people and a range of other ecosystem services (ESS). However, the sustainability of rice agro-ecosystems is threatened by continuing climate and land-use changes. To estimate their combined effects on a bundle of ESS, we applied the vegetation and hydrology model LPJmL to seven study areas in the Philippines and Vietnam. We quantified future changes in the provision of four essential ESS (carbon storage, carbon sequestration, provision of irrigation water and rice production) under two climate scenarios (until 2100) and three site-specific land-use scenarios (until 2030), and examined the synergies and trade-offs in ESS responses to these drivers. Our results show that not all services can be provided in the same amounts in the future. In the Philippines and Vietnam the projections estimated a decrease in rice yields (by approximately 30%) and in carbon storage (by 15%) and sequestration (by 12%) towards the end of the century under the current land-use pattern. In contrast, the amount of available irrigation water was projected to increase in all scenarios by 10%–20%. However, the results also indicate that land-use change may partially offset the negative climate impacts in regions where cropland expansion is possible, although only at the expense of natural vegetation. When analysing the interactions between ESS, we found consistent synergies between rice production and carbon storage and trade-offs between carbon storage and provision of irrigation water under most scenarios. Our results show that not only the effects of climate and land-use change alone but also the interaction between ESS have to be considered to allow sustainable management of rice agro-ecosystems under global change.