Research Group

Impacts of future climate change on Biodiversity and Ecosystems

Ito, A., C. P. O. Reyer, A. Gadeke, P. Ciais, J. F. Chang, M. Chen, L. Francois, M. Forrest, T. Hickler, S. Ostberg, H. Shi, W. Thiery, and H. Q. Tian. 2020. Pronounced and unavoidable impacts of low-end global warming on northern high-latitude land ecosystems. Environmental Research Letters 15:11. doi: 10.1088/1748-9326/ab702b.

Takolander, A., T. Hickler, L. Meller, and M. Cabeza. 2019. Comparing future shifts in tree species distributions across Europe projected by statistical and dynamic process-based models. Regional Environmental Change 19:251-266. doi: 10.1007/s10113-018-1403-x

Baumbach, L., A. Niamir, T. Hickler, and R. Yousefpour. 2019. Regional adaptation of European beech (Fagus sylvatica) to drought in Central European conditions considering environmental suitability and economic implications. Regional Environmental Change 19:1159-1174. doi: 10.1007/s10113-019-01472-0.

Hof, C., A. Voskamp, M. F. Biber, K. Bohning-Gaese, E. K. Engelhardt, A. Niamir, S. G. Willis, and T. Hickler. 2018. Bioenergy cropland expansion may offset positive effects of climate change mitigation for global vertebrate diversity. Proceedings of the National Academy of Sciences of the United States of America 115:13294-13299. doi: 10.1073/pnas.1807745115.

Fire in the Earth System

Lasslop, G., S. Hantson, S. P. Harrison, D. Bachelet, C. Burton, M. Forkel, M. Forrest, F. Li, J. R. Melton, C. Yue, S. Archibald, S. Scheiter, A. Arneth, T. Hickler, and S. Sitch. 2020. Global ecosystems and fire: Multi-model assessment of fire-induced tree-cover and carbon storage reduction. Global Change Biology:15. doi: 10.1111/gcb.15160.

Teckentrup L, Harrison SP, Hantson S, Heil A, Melton JR, Forrest M, Li F, Yue C, Arneth A, Hickler T, Sitch S, Lasslop G. 2019. Response of simulated burned area to historical changes in environmental and anthropogenic factors: a comparison of seven fire models. Biogeosciences 16: 3883–3910 doi: 10.5194/bg-16-3883-2019.

Andela N, Morton DC, Giglio L, Chen Y, Werf GR van der, Kasibhatla PS, DeFries RS, Collatz GJ, Hantson S, Kloster S, Bachelet D, Forrest M, Lasslop G, Li F, Mangeon S, Melton JR, Yue C, Randerson JT. 2017. A human-driven decline in global burned area. Science 356: 1356–1362 doi: 10.1126/science.aal4108.

Hantson S, Arneth A, Harrison SP, Kelley DI, Prentice IC, Rabin SS, Archibald S, Mouillot F, Arnold SR, Artaxo P, Bachelet D, Ciais P, Forrest M, Friedlingstein P, Hickler T, Kaplan JO, Kloster S, Knorr W, Lasslop G, Li F, Mangeon S, Melton JR, Meyn A, Sitch S, Spessa A, van der Werf GR, Voulgarakis A, Yue C. 2016. The status and challenge of global fire modelling. Biogeosciences 13: 3359–3375 doi: 10.5194/bg-13-3359-2016.

Paleo-environmental Changes

Allen, J. R. M., Forrest, M., Hickler, T., Singarayer, J. S., Valdes, P. J., & Huntley, B. 2020. Global vegetation patterns of the past 140,000 years.  Journal of Biogeography, 18, doi: 10.1111/jbi.13930.

Feurdean A, …, Warren D,… , Forrest M, Liakka J,. .., Werner C, …, Naimar A ,  …, Pfeiffer M, … Hickler T. 2020. Fire hazard modulation by long-term dynamics in land cover and dominant forest type in eastern and central Europe. Biogeosciences 17: 1213–1230. doi: 10.5194/bg-17-1213-2020.

Ecological and Ecosystem Modelling

Forrest M, Tost H, Lelieveld J, Hickler T. 2020. Including vegetation dynamics in an atmospheric chemistry-enabled general circulation model: linking LPJ-GUESS (v4.0) with the EMAC modelling system (v2.53). Geoscientific Model Development 13: 1285–1309 doi: 10.5194/gmd-13-1285-2020.

Dantas de Paula, M, Gómez Giménez M, Niamir A, Thurner M,  and Hickler, T. 2020. Combining European Earth Observation products with Dynamic Global Vegetation Models for estimating Essential Biodiversity Variables. International Journal of Digital Earth 13:2 262-277 doi: 10.1080/17538947.2019.1597187.

Dantas de Paula M, Groeneveld J, Fischer R, Taubert F, Martins V F, and Huth A. 2018. Defaunation impacts on seed survival and its effect on the biomass of future tropical forests. OIKOS 00: 1-13 doi: 10.1111/oik.05084

Bagnara ,M, Silveyra Gonzalez R, Reifenberg S, Steinkamp J, Hickler T, Werner C, Dormann CF, and Hartig ,F. 2019. An R package facilitating sensitivity analysis, calibration and forward simulations with the LPJ-GUESS dynamic vegetation model. Environmental Modelling and Software 111: 55–60 doi: 10.1016/j.envsoft.2018.09.004

Invasive Species

Seebens, H; Bacher, S; Blackburn, T. 2020. Projecting the continental accumulation of alien species through to 2050. Global Change Biology (In press).

Seebens H, Blackburn TM, Dyer EE, Genovesi P, Hulme PE, Jeschke JM, Pagad S, Pyšek P, van Kleunen M, Winter M, Ansong M, Arianoutsou M, Bacher S, Blasius B, Brockerhoff EG, Brundu G, Capinha C, Causton CE, Celesti-Grapow L, Dawson W, Dullinger S, Economo EP, Fuentes N, Guénard B, Jäger H, Kartesz J, Kenis M, Kühn I, Lenzner B, Liebhold AM, Mosena A, Moser D, Nentwig W, Nishino M, Pearman D, Pergl J, Rabitsch W, Rojas-Sandoval J, Roques A, Rorke S, Rossinelli S, Roy HE, Scalera R, Schindler S, Štajerová K, Tokarska-Guzik B, Walker K, Ward DF, Yamanaka T, Essl F. 2018. Global rise in emerging alien species results from increased accessibility of new source pools. Proceedings of the National Academy of Sciences 115: E2264–E2273, doi: 10.1073/pnas.1719429115.

Seebens H, Blackburn TM, Dyer EE, Genovesi P, Hulme PE, Jeschke JM, Pagad S, Pyšek P, Winter M, Arianoutsou M, Bacher S, Blasius B, Brundu G, Capinha C, Celesti-Grapow L, Dawson W, Dullinger S, Fuentes N, Jäger H, Kartesz J, Kenis M, Kreft H, Kühn I, Lenzner B, Liebhold A, Mosena A, Moser D, Nishino M, Pearman D, Pergl J, Rabitsch W, Rojas-Sandoval J, Roques A, Rorke S, Rossinelli S, Roy HE, Scalera R, Schindler S, Štajerová K, Tokarska-Guzik B, van Kleunen M, Walker K, Weigelt P, Yamanaka T, Essl F. 2017. No saturation in the accumulation of alien species worldwide. Nature Communications 8: 14435, doi:10.1038/ncomms14435.

Currently two sets of simulations are available:

1. 1700-2013 historical simulation and sensitivity experiment

The baseline FireMIP simulation used historical climate, CO2, lightning, population density, and land use forcings from 1700 through 2013. Separate sensitivity simulations were conducted by keeping each of the main forcing variables constant to quantify the sensitivity to different forcings across models. A “World Without Fire” run is also performed to determine the importance of fire disturbance within each vegetation model. A detailed description of the protocol can be found in Rabin et al. (2017).

Part of the simulation output is available on Zenodo (https://zenodo.org/record/3555562, doi:10.5281/zenodo.3555562, https://zenodo.org/record/3386620, doi:10.5281/zenodo.3386620). Please see also CERA-Metadata for ‚FireMIPSensitivitySimulations‘

2. Last Glacial Maximum out-of-sample experiment

While most models are optimized to reproduce current day fire occurrence relatively well, it is unknown how well they are able to reproduce fire occurrence under very different environmental conditions (and therefore possibly under future climate change).
The Last Glacial Maximum (LGM) experiment will try to evaluate the model performance under a set of different environmental conditions. Model outputs will be evaluated using a set of paleofire proxies.

The comparisons within the Fire Model Intercomparison Project (FireMIP) showed that the models reproduce the spatial patterns and global totals of burned area (Figure 1) and emissions (Forkel et al., 2019; Li et al., 2019; Teckentrup et al., 2019; Hantson et al., 2020).

The simulations over the historical period show a strong divergence in simulated burned area trends for the recent two decades (Andela et al., 2017) and the last century (Teckentrup et al., 2019). This divergence in trends between models was attributed to anthropogenic factors based on the sensitivity simulations (Teckentrup et al., 2019; Li et al., 2019, Figure 2).

Models did not show a strong trend due to changes in climate over the 20th century; however, a strong influence of climate on the interannual variability was identified (Teckentrup et al., 2019). Anthropogenic fires influence seasonality, and explicitly including cropland fires improves the seasonality of fire in the Northern Hemisphere (Hantson et al., 2020).

A multivariate analysis using random forest showed that the response of mean burned area to climatic variables was reasonable; however, models did not reproduce the relationship between vegetation productivity and burned area well (Forkel et al., 2019, Figure 3).

Overall, the outcomes of FireMIP so far have shown that the models are able to reproduce present-day burned area and emission patterns and have revealed the human impacts and sensitivity to vegetation as major fields for model development.

As the models capture the spatial patterns well for the present day, we applied them to provide the first multi-model estimate of fire impacts on global tree cover and the carbon cycle under current climate and anthropogenic land use conditions. Fire reduces the tree covered area and vegetation carbon storage by 10%. Regionally the effects are much stronger, up to 20% for certain latitudinal bands, and 17% in savanna regions. The influence on vegetation productivity or total carbon storage is much lower (Lasslop et al., 2020, Figure 4).

FURNACES (Fire in the Future: Interactions with Ecosystems and Society) is an interdisciplinary project about the future interactions between fire, ecosystems and society.

FURNACES is funded by “Deutsche Forschungsgemeinschaft (DFG)” from Germany and “Fonds zur Förderung der wissenschaftlichen Forschung (FWF)”  from Austria.

In FURNACES we aim to
(1) improve our understanding how humans influence fires based on literature reviews and remote sensing data
(2) integrate an improved representation of humans and the associated uncertainty into vegetation models, and
(3) investigate the consequences of future changes in fire occurrence for ecosystems and societies.

This highly complex topic calls for an interdisciplinary approach. Scientists from Germany and Austria combine their expertise in fire ecology, social ecology, remote sensing, data science and vegetation modeling to better understand the local to global relationships between human, climate, vegetation and fire.

Project partners

• KIT, Garmisch-Partenkirchen (Prof. Dr. Almut Arneth, Dr. Sam Rabin)
• SBIK-F, Frankfurt (Prof. Dr. Thomas Hickler, Dr. Gitta Lasslop, Dr. Matthew Forest, Dr. Zahra Parsakhoo)
• TU Wien, Vienna (Prof. Dr. Wouter Dorigo, Dr. Stefan Schlaffer, Tichaona Mukunga, Ruxandra Zotta)
• TU Dresden, Dresden (JProf. Matthias Forkel)
• BOKU, Vienna (Prof. Dr. Karl-heinz Erb, Dr. Christian Lauk, Sarah Matej, Andreas Magerl)
• The University of Hong Kong, Hong Kong (Prof. Dr. Jed O. Kaplan)
• The University of Augsburg, Augsburg (Silvia Schrötter)

Collaborators

ISIMIP https://www.isimip.org/
FireMIP https://www.imk-ifu.kit.edu/deutsch/firemip.php
Leverhulme Wildfire https://centreforwildfires.org/

iCUE-Forest (“Improving tree carbon use efficiency for climate-adapted more productive forests”) is a EU H2020 Marie Skłodowska-Curie project exploring the effects of changes in climate and tree species distribution on wood productivity and carbon stocks.

Wood production depends on how effectively plants convert atmospheric carbon dioxide (CO₂) into wood. Moreover, forests mitigate climate change through their net carbon uptake from the atmosphere. Both these forest functions are crucially dependent on tree carbon use efficiency (CUE). Thus, within the iCUE-Forest project we will first identify the drivers of changes in CUE and then develop approaches to increase CUE to enhance wood productivity and carbon stocks under future climatic conditions.

We aim to inform forest managers on species that will be optimally adapted to future climate in northern boreal and temperate forests. For this purpose, we will:

1. Develop novel data-driven estimates of plant respiration (or autotrophic respiration; R_a), net primary production (NPP) and tree CUE based on recent satellite-driven maps of tree living biomass (Thurner et al., 2014; Thurner et al., 2019), extensive databases of field measurements on plant traits that allow to infer respiratory costs per unit biomass, and temperature datasets
2. Investigate the spatial patterns in CUE under current climate and forest management in order to quantify how CUE varies for different tree species and current environmental conditions
3. Apply a dynamic global vegetation model (DGVM) to predict temporal changes in CUE in response to climate change and tree species distribution scenarios

Tree CUE is defined as the ratio of net to gross primary production (NPP / GPP; Manzoni et al., 2018). In recent decades, vegetation productivity has been increasing. However, in view of the unknown response of plant respiration (R_a) to future climate conditions, a continued ncrease in NPP (= GPP – R_a) and CUE in forest vegetation is highly uncertain. Despite the urgent need to inform forest managers on the expected changes in these carbon fluxes and carbon cycle properties, estimates of current regional to global plant respiration levels are missing, since this carbon flux is hardly measurable in the field at such spatial scales. This shortcoming essentially contributes to the high uncertainty in NPP and its response to climate change simulated by DGVMs (Thurner et al., 2017).

The project’s concept and preliminary results have been presented at the GINKGO Workshop „Opportunities from New Data for Vegetation Modeling“ (UFZ Leipzig, October 2020) and will also be presented at the European Geosciences Union (EGU) General Assembly (Vienna, 30 April 2021, https://meetingorganizer.copernicus.org/EGU21/EGU21-10299.html).

Thurner, M., Beer, C., Crowther, T., Falster, D., Manzoni, S., Prokushkin, A., Schulze, E.-D. (2019): Sapwood biomass carbon in northern boreal and temperate forests. Global Ecology and Biogeography, 28, 5, 640-660. https://doi.org/10.1111/geb.12883

Manzoni, S., Čapek, P., Porada, P., Thurner, M., Winterdahl, M., Beer, C., Brüchert, V., Frouz, J., Herrmann, A.M., Lindahl, B.D., Lyon, S.W., Santruckova, H., Vico, G., Way, D. (2018) Reviews and syntheses: Carbon use efficiency from organisms to ecosystems – Definitions, theories, and empirical evidence. Biogeosciences, 15, 5929–5949, https://doi.org/10.5194/bg-15-5929-2018

Thurner, M., Beer, C., Ciais, P., Friend, A.D., Ito, A., Kleidon, A., Lomas, M.R., Quegan, S., Rademacher, T.T., Schaphoff, S., Tum, M., Wiltshire, A., Carvalhais, N. (2017): Evaluation of climate-related carbon turnover processes in global vegetation models for boreal and temperate forests. Global Change Biology, 23, 8, 3076-3091. https://doi.org/10.1111/gcb.13660

Thurner, M., Beer, C., Santoro, M., Carvalhais, N., Wutzler, T., Schepaschenko, D., Shvidenko, A., Kompter, E., Ahrens, B., Levick, S.R., Schmullius, C. (2014): Carbon stock and density of northern boreal and temperate forests. Global Ecology and Biogeography, 23, 3, 297-310. https://doi.org/10.1111/geb.12125

This project has received funding from the European Union’s Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie grant agreement No 891402.

GEOEssential

EarthShape: Earth Surface Shaping by Biota

Ecosystem Management Support for Climate Change in Southern Africa (EMSAfrica)

The open Climate Impacts Encyclopedia (ISIpedia)

Past warm periods as natural analogues of our „high CO₂“ climate future (VeWA Project)

Environmental changes in biodiversity hotspot ecosystems of South Ecuador: RESPonse and feedback effECTs (FOR2730)

Fire in the Future: Interactions with Ecosystems and Society – FURNACES

Multisectoral analysis of climate and land use change impacts on pollinators, plant diversity and crops yields – MAPPY

BioDiv-Support: Scenario-based decision support for policy planning and adaptation to future changes in biodiversity and ecosystem services

Developing a holististic, risk-wise strategy for European wildfire management – FireEUrisk

Impacts of future climate change on Biodiversity and Ecosystems

Ito, A., C. P. O. Reyer, A. Gadeke, P. Ciais, J. F. Chang, M. Chen, L. Francois, M. Forrest, T. Hickler, S. Ostberg, H. Shi, W. Thiery, and H. Q. Tian. 2020. Pronounced and unavoidable impacts of low-end global warming on northern high-latitude land ecosystems. Environmental Research Letters 15:11. doi: 10.1088/1748-9326/ab702b.

Takolander, A., T. Hickler, L. Meller, and M. Cabeza. 2019. Comparing future shifts in tree species distributions across Europe projected by statistical and dynamic process-based models. Regional Environmental Change 19:251-266. doi: 10.1007/s10113-018-1403-x

Baumbach, L., A. Niamir, T. Hickler, and R. Yousefpour. 2019. Regional adaptation of European beech (Fagus sylvatica) to drought in Central European conditions considering environmental suitability and economic implications. Regional Environmental Change 19:1159-1174. doi: 10.1007/s10113-019-01472-0.

Hof, C., A. Voskamp, M. F. Biber, K. Bohning-Gaese, E. K. Engelhardt, A. Niamir, S. G. Willis, and T. Hickler. 2018. Bioenergy cropland expansion may offset positive effects of climate change mitigation for global vertebrate diversity. Proceedings of the National Academy of Sciences of the United States of America 115:13294-13299. doi: 10.1073/pnas.1807745115.

Fire in the Earth System

Lasslop, G., S. Hantson, S. P. Harrison, D. Bachelet, C. Burton, M. Forkel, M. Forrest, F. Li, J. R. Melton, C. Yue, S. Archibald, S. Scheiter, A. Arneth, T. Hickler, and S. Sitch. 2020. Global ecosystems and fire: Multi-model assessment of fire-induced tree-cover and carbon storage reduction. Global Change Biology:15. doi: 10.1111/gcb.15160.

Teckentrup L, Harrison SP, Hantson S, Heil A, Melton JR, Forrest M, Li F, Yue C, Arneth A, Hickler T, Sitch S, Lasslop G. 2019. Response of simulated burned area to historical changes in environmental and anthropogenic factors: a comparison of seven fire models. Biogeosciences 16: 3883–3910 doi: 10.5194/bg-16-3883-2019.

Andela N, Morton DC, Giglio L, Chen Y, Werf GR van der, Kasibhatla PS, DeFries RS, Collatz GJ, Hantson S, Kloster S, Bachelet D, Forrest M, Lasslop G, Li F, Mangeon S, Melton JR, Yue C, Randerson JT. 2017. A human-driven decline in global burned area. Science 356: 1356–1362 doi: 10.1126/science.aal4108.

Hantson S, Arneth A, Harrison SP, Kelley DI, Prentice IC, Rabin SS, Archibald S, Mouillot F, Arnold SR, Artaxo P, Bachelet D, Ciais P, Forrest M, Friedlingstein P, Hickler T, Kaplan JO, Kloster S, Knorr W, Lasslop G, Li F, Mangeon S, Melton JR, Meyn A, Sitch S, Spessa A, van der Werf GR, Voulgarakis A, Yue C. 2016. The status and challenge of global fire modelling. Biogeosciences 13: 3359–3375 doi: 10.5194/bg-13-3359-2016.

Paleo-environmental Changes

Allen, J. R. M., Forrest, M., Hickler, T., Singarayer, J. S., Valdes, P. J., & Huntley, B. 2020. Global vegetation patterns of the past 140,000 years.  Journal of Biogeography, 18, doi: 10.1111/jbi.13930.

Feurdean A, …, Warren D,… , Forrest M, Liakka J,. .., Werner C, …, Naimar A ,  …, Pfeiffer M, … Hickler T. 2020. Fire hazard modulation by long-term dynamics in land cover and dominant forest type in eastern and central Europe. Biogeosciences 17: 1213–1230. doi: 10.5194/bg-17-1213-2020.

Ecological and Ecosystem Modelling

Forrest M, Tost H, Lelieveld J, Hickler T. 2020. Including vegetation dynamics in an atmospheric chemistry-enabled general circulation model: linking LPJ-GUESS (v4.0) with the EMAC modelling system (v2.53). Geoscientific Model Development 13: 1285–1309 doi: 10.5194/gmd-13-1285-2020.

Dantas de Paula, M, Gómez Giménez M, Niamir A, Thurner M,  and Hickler, T. 2020. Combining European Earth Observation products with Dynamic Global Vegetation Models for estimating Essential Biodiversity Variables. International Journal of Digital Earth 13:2 262-277 doi: 10.1080/17538947.2019.1597187.

Dantas de Paula M, Groeneveld J, Fischer R, Taubert F, Martins V F, and Huth A. 2018. Defaunation impacts on seed survival and its effect on the biomass of future tropical forests. OIKOS 00: 1-13 doi: 10.1111/oik.05084

Bagnara ,M, Silveyra Gonzalez R, Reifenberg S, Steinkamp J, Hickler T, Werner C, Dormann CF, and Hartig ,F. 2019. An R package facilitating sensitivity analysis, calibration and forward simulations with the LPJ-GUESS dynamic vegetation model. Environmental Modelling and Software 111: 55–60 doi: 10.1016/j.envsoft.2018.09.004

Invasive Species

Seebens, H; Bacher, S; Blackburn, T. 2020. Projecting the continental accumulation of alien species through to 2050. Global Change Biology (In press).

Seebens H, Blackburn TM, Dyer EE, Genovesi P, Hulme PE, Jeschke JM, Pagad S, Pyšek P, van Kleunen M, Winter M, Ansong M, Arianoutsou M, Bacher S, Blasius B, Brockerhoff EG, Brundu G, Capinha C, Causton CE, Celesti-Grapow L, Dawson W, Dullinger S, Economo EP, Fuentes N, Guénard B, Jäger H, Kartesz J, Kenis M, Kühn I, Lenzner B, Liebhold AM, Mosena A, Moser D, Nentwig W, Nishino M, Pearman D, Pergl J, Rabitsch W, Rojas-Sandoval J, Roques A, Rorke S, Rossinelli S, Roy HE, Scalera R, Schindler S, Štajerová K, Tokarska-Guzik B, Walker K, Ward DF, Yamanaka T, Essl F. 2018. Global rise in emerging alien species results from increased accessibility of new source pools. Proceedings of the National Academy of Sciences 115: E2264–E2273, doi: 10.1073/pnas.1719429115.

Seebens H, Blackburn TM, Dyer EE, Genovesi P, Hulme PE, Jeschke JM, Pagad S, Pyšek P, Winter M, Arianoutsou M, Bacher S, Blasius B, Brundu G, Capinha C, Celesti-Grapow L, Dawson W, Dullinger S, Fuentes N, Jäger H, Kartesz J, Kenis M, Kreft H, Kühn I, Lenzner B, Liebhold A, Mosena A, Moser D, Nishino M, Pearman D, Pergl J, Rabitsch W, Rojas-Sandoval J, Roques A, Rorke S, Rossinelli S, Roy HE, Scalera R, Schindler S, Štajerová K, Tokarska-Guzik B, van Kleunen M, Walker K, Weigelt P, Yamanaka T, Essl F. 2017. No saturation in the accumulation of alien species worldwide. Nature Communications 8: 14435, doi:10.1038/ncomms14435.