Dr. Rico Fischer

Contact

until 2023: Helmholtz Centre for Environmental Research - UFZ Leipzig, Department of Ecological Modelling

since 11/2023:

Julius Kühn-Institute (JKI) - Federal Research Center for Cultivated Plants
Institute for Forest Protection
+49 3946 47-4017
rico.fischer@julius-kuehn.de
https://www.julius-kuehn.de/ws/personal/p/rico-fischer




Research Interests


Expert in Forest Modelling, Remote Sensing and Digital Forest Twins

  • modelling the dynamics of European forests
  • linking multi-sensor remote sensing with ecological modelling
  • developing digital forest twins
  • carbon cycle and disturbances in forest ecosystems
  • impact of fire, climate change and land use change on forests in Germany

Standsoftime
"Stands of Time" within the heart of the Malagasy Hauts-Plateaux. Credit: Trent Marwick

Projects


Forest Modeling

The forest gap model FORMIND is an individual-based vegetation model that simulates the growth of forests on the hectare scale. It allows to explore forest dynamics and forest structure including also processes like gap building (falling down of large trees).

Publication: Lessons learned from applying a forest gap model to understand ecosystem and carbon dynamics of complex tropical forests.

More details about FORMIND at www.formind.org

FORMIND at Wikipedia

Formind
FORMIND. An individual-based forest model.

Simulating the carbon stocks and fluxes of tropical and temperate forests in a changing world

Analyzing the carbon fluxes of a tropical forest in Tansania, Africa. We simulated biomass dynamics, forest productivity and carbon fluxes for a sub-montane forest at Mt. Kilimanjaro.

Publication: Simulating Carbon Stocks and Fluxes of an African Tropical Montane Forest with an Individual-Based Forest Model

We simulated with FORMIND the daily carbon fluxes for the forest site Hohes Holz in Germany, examining the influence of individual species and tree sizes on these fluxes.

Publication: Carbon sequestration in mixed deciduous forests: the influence of tree size and species composition derived from model experiments

Simulating the dynamics of lowland tropical forest in a changing world. Analyzing the impact of drought and logging on rainforest structure and dynamics.

Publication: Simulating the impacts of reduced rainfall on carbon stocks and net ecosystem exchange in a tropical forest


Evaluating the impact of fire and selective logging on forest dynamics

FORMIND was extended by a fire module, which was used to investigate how long a tropical forest in Africa needs to recover after a fire event. Depending on which forest variable is considered, it is more than 100 years.

Publication: The long-term consequences of forest fires on the carbon fluxes of a tropical forest in Africa.

Analyzing the mid- and long-term impacts of different management intensities on the dynamic and structure of a species-rich tropical lowland forest of French Guiana. High selective logging intensities prolong the recovery times of ecosystem functions such as biomass and productivity.

Publication: Simulation of succession in a neotropical forest: High selective logging intensities prolong the recovery times of ecosystem functions.


A multi-scaled analysis of forest structure and sampling strategies

Consideration of scale is essential when examining structural relationships in forests. Sampling strategy also plays a critical role in estimating forest characteristics. The scale as well as the sampling are crucial to correctly assess biomass in forests.

Publication: A multi-scaled analysis of forest structure using individual-based modeling in a costa rican rainforest.

Publication: An analysis of forest biomass sampling strategies across scales.

Formind the forest model
Visualisation of Formind the forest model. See www.formind.org for more details.

Remote Sensing

Emissions from the edge of the forest: global forest fragmentation

Deforestation has a fatal effect on the remaining forest fragments. The vegetation at the edges is exposed to an unfavorable microclimate: Direct sunlight and higher wind speeds cause these areas to dry out more quickly and tree mortality increases. We analyzed the state and dynamics of tropical forest fragmentation and its impact on the global carbon cycle using high-resolution remote sensing data. We found that fragmentation is accelerating with serve consequences for the global carbon cycle.

Fragmentation
The photo shows forest fragments of the Brazilian Atlantic rainforest in Northeastern Brazil. Photo: Mateus Dantas de Paula

Estimating forest structure from remote sensing

We investigated the potential of lidar and radar data to monitor forest biomass and forest structure and its temporal variations. Forest structure identification can be used to distinguish between different forest stages and different types induced by logging, natural disturbance, or forest management.

Publication: Remote Sensing Measurements of Forest Structure Types for Ecosystem Service Mapping

Publication: Monitoring of Forest Structure Dynamics by Means of L-Band SAR Tomography

Linking Remote Sensing with Ecological Modeling

An innovative research field is the combination of individual-based vegetation models with the latest remote sensing technology. For this purpose, the high degree of detail of the models in combination with the full-coverage measurement of the earth is used to determine the different ecosystem functions.

Estimating forest biomass and carbon fluxes from remote sensing

Forest models can help to better interpret remote sensing data. The linkage of models with remote sensing (e.g., lidar) allow to develop robust relationships between remote sensing metrics and forest variables like biomass. This can be done for local studies as well as for whole continents. Integrating more than 100 million GEDI measurements (see https://gedi.umd.edu/) into the forest model FORMIND, we have mapped forest productivity throughout the Amazon.

TandemX
Satellites TerraSAR-X and TanDEM-X 3D-scanning the earth surface. Image: EADS Astrium

The role of forest structure for biomass and productivity

Future remote sensing missions will have the capability to provide information on forest structure (e.g., from lidar or radar). By linking remote sensing techniques with vegetation modelling, the role of forest structure for ecosystem services of forests can be investigated. This will lead to more accurate assessments of forest biomass and productivity around the globe.

Publication: The Relevance of Forest Structure for Biomass and Productivity in Temperate Forests: New Perspectives for Remote Sensing

Forest Structure in Germany
Forest Structure in Germany. Estimated horizontal and vertical forest structure by linking remote sensing with a forest model.

Science in the News

Forest Fragmentation in the Tropics

press release, 06. September 2021

    Forest edges in the tropics increase carbon emissions

Press release, 14. February 2018

    Deforestation and Fragmentation in the tropics.

Press release, 30. March 2017

    Emissions from the edge of the forest.


Fires and Deforestation in the Amazon

Spiegel, Juni 2023

    "Bäume pflanzen fürs Klima – ist das wirklich so einfach?"

Spiegel, November 2022

    "Ist der Amazonas-Regenwald noch zu retten?"

Spiegel, November 2022

    "Waldschutzinitiative auf der Klimakonferenz - Einfach nur Geld zu verteilen, reicht nicht"

Federal Ministry of Education and Research, August 2019

    "Regenwälder sind mehr in Gefahr als je zuvor"

ZDF, August 2019

    Verheerende Brände weltweit - Zündquelle Mensch.

Spiegel Online, August 2019

    "Der Regenwald braucht mindestens hundert Jahre, um sich zu erholen"

Federal Ministry of Education and Research, Oktober 2019

    #Fragen4Future Amazonas Abholzung?

Press release, November 2019

    The forests of the Amazon are an important carbon sink.

Klimawald 2.0, July 2020, Bayerische Staatsforsten

    „Der Amazonas könnte von einer Kohlenstoff­senke zur ­-quelle werden.“


Zoo Leipzig and Visualization of Forests

Zoo Live, August 2012

    Baummessung in Gondwanaland (page 10).

Spiegel TV, 24. May 2012

    Virtueller Waldspaziergang: In 3D durch Sachsens Tropen.

Press release, 28. June 2011

    Gondwanaland hilft Wissenschaftlern, Waldmodelle zu verbessern.


Miscellaneous

Resonator - Der Forschungspodcast der Helmholtz-Gemeinschaft, 25. Oktober 2019

    Resonator Waldmodellierung

UFZ-Newsletter, February 2014

    Mathematik für den Regenwald (page 11)

German version: Video

2024 (2)

2022 (4)

  • Bahrami, B., Hildebrandt, A., Thober, S., Rebmann, C., Fischer, R., Samaniego, L., Rakovec, O., Kumar, R. (2022):
    Developing a parsimonious canopy model (PCM v1.0) to predict forest gross primary productivity and leaf area index of deciduous broad-leaved forest
    Geosci. Model Dev. 15 (18), 6957 - 6984
    full text (doi)
  • Bahrami, B., Hildebrandt, A., Thober, S., Rebmann, C., Fischer, R., Samaniego, L., Rakovec, O., Kumar, R. (2022):
    Parsimonious Canopy Model (PCM) v1.0
    Version: v1.0 Zenodo 10.5281/zenodo.6373776
  • Duncanson, L., Kellner, J.R., Armston, J., Dubayah, R., Minor, D.M., Hancock, S., Healey, S.P., Patterson, P.L., Saarela, S., Marselis, S., Silva, C.E., Bruening, J., Goetz, S.J., Tang, H., Hofton, M., Blair, B., Luthcke, S., Fatoyinbo, L., Abernethy, K., Alonso, A., Andersen, H.-E., Aplin, P., Baker, T.R., Barbier, N., Bastin, J.F., Biber, P., Boeckx, P., Bogaert, J., Boschetti, L., Brehm Boucher, P., Boyd, D.S., Burslem, D.F.R.P., Calvo-Rodriguez, S., Chave, J., Chazdon, R.L., Clark, D.B., Clark, D.A., Cohen, W.B., Coomes, D.A., Corona, P., Cushman, K.C., Cutler, M.E.J., Dalling, J.W., Dalponte, M., Dash, J., de-Miguel, S., Deng, S., Woods Ellis, P., Erasmus, B., Fekety, P.A., Fernandez-Landa, A., Ferraz, A., Fischer, R., Fisher, A.G., García-Abril, A., Gobakken, T., Hacker, J.M., Heurich, M., Hill, R.A., Hopkinson, C., Huang, H., Hubbell, S.P., Hudak, A.T., Huth, A., Imbach, B., Jeffery, K.J., Katoh, M., Kearsley, E., Kenfack, D., Kljun, N., Knapp, N., Král, K., Krůček, M., Labrière, N., Lewis, S.L., Longo, M., Lucas, R.M., Main, R., Manzanera, J.A., Vásquez Martínez, R., Mathieu, R., Memiaghe, H., Meyer, V., Monteagudo Mendoza, A., Monerris, A., Montesano, P., Morsdorf, F., Næsset, E., Naidoo, L., Nilus, R., O’Brien, M., Orwig, D.A., Papathanassiou, K., Parker, G., Philipson, C., Phillips, O.L., Pisek, J., Poulsen, J.R., Pretzsch, H., Rüdiger, C., Saatchi, S., Sanchez-Azofeifa, A., Sanchez-Lopez, N., Scholes, R., Silva, C.A., Simard, M., Skidmore, A., Stereńczak, K., Tanase, M., Torresan, C., Valbuena, R., Verbeeck, H., Vrska, T., Wessels, K., White, J.C., White, L.J.T., Zahabu, E., Zgraggen, C. (2022):
    Aboveground biomass density models for NASA’s Global Ecosystem Dynamics Investigation (GEDI) lidar mission
    Remote Sens. Environ. 270 , art. 112845
    full text (doi)
  • Hiltner, U., Huth, A., Fischer, R. (2022):
    Importance of the forest state in estimating biomass losses from tropical forests: combining dynamic forest models and remote sensing
    Biogeosciences 19 (7), 1891 - 1911
    full text (doi)

2021 (12)

2020 (4)

2019 (5)

2018 (10)

2017 (4)

2016 (3)

2015 (2)

2014 (3)


since 11/2023 Head of the Working Group "Digital Twins and Forest Modelling" at the Julius Kühn-Institut - Federal Research Centre for Cultivated Plants
2022 - 2023 Full member at the German Centre for Integrative Biodiversity Research (iDiv) Halle-Jena-Leipzig
2021 - 2023 Deputy Head of Department "Ecological Modelling" at the Helmholtz Centre for Environmental Research Leipzig.
2021 - 2023 Head of the Working Group "Forest Modelling" at the Helmholtz Centre for Environmental Research Leipzig.
2018 - 2021 Project leader at the Helmholtz Centre for Environmental Research Leipzig. Linking remote sensing and forest modeling.
2013 - 2017 Post Doc position at the Helmholtz Alliance “Remote Sensing and Earth System Dynamics"
2010 - 2013 PhD student within the DFG Research Unit "KiLi” Kilimanjaro ecosystems under global change - Linking biodiversity, biotic interactions and biogeochemical ecosystem processes
Thesis: "Modelling the dynamics of African tropical forests. Analysis of the influence of disturbances on tropical forests using the FORMIND forest model"
University of Osnabrück
2008 - 2010 Master in Applied Mathematics at the University of Applied Science (HTWK) Leipzig
Thesis: "Modelling the growth of rainforests. Investigation of the effects of drought stress and timber use on the tropical rainforest using the example of RNI Betampona, Madagascar"
2005 - 2008 Diploma in Business Mathematics at the University of Applied Science (HTWK) Leipzig
Thesis: "Modelling of non-linear dependencies with the help of copulas - application in the determination of value at risk"

Awards

2014 - UFZ Doctoral Award
2013 - Best Presentation HIGRADE Conference