Schaphoff, S.; von Bloh, W.; Rammig, A.; Thonicke, K.; Biemans, H.; Forkel, M.; Gerten, D.; Heinke, J.; Jägermeyr, J.; Knauer, J.et al.; Langerwisch, F.; Lucht, W.; Müller, C.; Rolinski, S.; Waha, K.: LPJmL4 – a dynamic global vegetation model with managed land – Part 1: Model description. Geoscientific Model Development 11 (4), pp. 1343 - 1375 (2018)
Knauer, J.; Zaehle, S.; Reichstein, M.; Medlyn, B. E.; Forkel, M.; Hagemann, S.; Werner, C.: The response of ecosystem water-use efficiency to rising atmospheric CO2 concentrations: sensitivity and large-scale biogeochemical implications. New Phytologist 213 (4), pp. 1654 - 1666 (2017)
Filippa, G.; Cremonese, E.; Migliavacca, M.; Galvagno, M.; Forkel, M.; Wingate, L.; Tomelleri, E.; di Cella, U. M.; Richardson, A. D.: Phenopix: A R package for image-based vegetation phenology. Agricultural and Forest Meteorology 220, pp. 141 - 150 (2016)
Sippel, S.; Otto, F. E. L.; Forkel, M.; Allen, M. R.; Guillod, B. P.; Heimann, M.; Reichstein, M.; Seneviratne, S. I.; Thonicke, K.; Mahecha, M. D.: A novel bias correction methodology for climate impact simulations. Earth System Dynamics 7 (1), pp. 71 - 88 (2016)
Thurner, M.; Beer, C.; Carvalhais, N.; Forkel, M.; Santoro, M.; Tum, M.; Schmullius, C.: Large-scale variation in boreal and temperate forest carbon turnover rate is related to climate. Geophysical Research Letters 43 (9), pp. 4576 - 4585 (2016)
Forkel, M.; Migliavacca, M.; Thonicke, K.; Reichstein, M.; Schaphoff, S.; Weber, U.; Carvalhais, N.: Codominant water control on global interannual variability and trends in land surface phenology and greenness. Global Change Biology 21 (9), pp. 3414 - 3435 (2015)
Forkel, M.; Carvalhais, N.; Schaphoff, S.; Bloh, W. v.; Migliavacca, M.; Thurner, M.; Thonicke, K.: Identifying environmental controls on vegetation greenness phenology through model-data integration. Biogeosciences 11 (23), pp. 7025 - 7050 (2014)
Urban, M.; Forkel, M.; Eberle, J.; Hüttich, C.; Schmullius, C.; Herold, M.: Pan-arctic climate and land cover trends derived from multi-variate and multi-scale analyses (1981–2012). Remote Sensing 6 (3), pp. 2296 - 2316 (2014)
Urban, M.; Forkel, M.; Schmullius, C.; Hese, S.; Hüttich, C.; Herold, M.: Identification of land surface temperature and albedo trends in AVHRR pathfinder data from 1982 to 2005 for northern Siberia. International Journal of Remote Sensing 34 (12), pp. 4491 - 4507 (2014)
Forkel, M.; Carvalhais, N.; Verbesselt, J.; Mahecha, M. D.; Neigh, C. S.R.; Reichstein, M.: Trend change detection in NDVI time series: Effects of inter-annual variability and methodology. Remote Sensing 5 (5), pp. 2113 - 2144 (2013)
Forkel, M.; Thonicke, K.; Beer, C.; Cramer, W.; Bartalev, S.; Schmullius, C.: Extreme fire events are related to previous-year surface moisture conditions in permafrost-underlain larch forests of Siberia. Environmental Research Letters 7, 044021 (2012)
Forkel, M.: Controls on Global Greening, Phenology and the Enhanced Seasonal CO2 Amplitude: Integrating Decadal Satellite Observations and Global Ecosystem Models. Dissertation, 323 pp., Friedrich Schiller University Jena, Jena (2015)
The new research project "PollenNet" aims to use artificial intelligence to accurately predict the spread of pollen. In order to improve allergy prevention, experts are bringing together the latest interdisciplinary findings from a wide range of fields.
If rivers overflow their banks, the consequences can be devastating. Using methods of explainable machine learning, researchers at the Helmholtz Centre for Environmental Research (UFZ) have shown that floods are more extreme when several factors are involved in their development.
Europe is the fastest warming continent in the world. According to the European Environment Agency’s assessment, many of these risks have already reached critical levels and could become catastrophic without urgent and decisive action.
Plant observations collected with plant identification apps such as Flora Incognita allow statements about the developmental stages of plants - both on a small scale and across Europe.
Global experts have unveiled the annual 10 New Insights in Climate Science report. The report equips policymakers with the latest and most pivotal climate science research from the previous 18 months, synthesised to help inform negotiations at COP28 and policy implementation through 2024 and beyond.
Vegetation can respond to drought through different mechanisms, including changes in the plants’ structure and physiology. By analyzing state-of-the-art satellite-derived datasets with explainable machine learning methods, an international team around Wantong Li and René Orth showed that the vegetation’s physiology in many ecosystems has deviated from its structure under drought on a global scale.
Carbon sinks on the land surface mitigate the greenhouse effect. An international team of scientists has now determined that the vast majority of Europe’s total above-ground carbon storage is provided by the forests of Eastern Europe. However, this carbon sink has declined, mainly due to changes in land use.
The world’s forests, grasslands, and other terrestrial ecosystems have played a substantial role in offsetting human carbon emissions—a capability that researchers say would be threatened by continued global change.
A new study shows that the efficiency of microbial carbon use is at least four times more influential than other biological factors or environmental conditions on the global storage and distribution of carbon in soil.
Germany's most popular plant identification app "Flora Incognita" has been further upgraded by a new artificial intelligence. This triples the number of plant species that can be identified up to 16,000. In addition, the app is now available in 20 different languages and also in offline mode.
Dr. Ana Bastos, group leader at Max Planck Institute for Biogeochemistry in Jena, was awarded the Beutenberg Campus science award in the category „outstanding junior research scientist”.