Aparecido, L. M. T.; Santos, J. d.; Higuchi, N.; Kunert, N.: Relevance of wood anatomy and size of Amazonian trees in the determination and allometry of sapwood area. Acta Amazonica 49 (1), pp. 1 - 10 (2019)
Muhr, J.; Trumbore, S. E.; Higuchi, N.; Kunert, N.: Living on borrowed time – Amazonian trees use decade‐old storage carbon to survive for months after complete stem girdling. New Phytologist 220 (1), pp. 111 - 120 (2018)
Kunert, N.; Aparecido, L. M. T.; Wolff, S.; Higuchi, N.; Santos, J. d.; de Araujo, A. C.; Trumbore, S. E.: A revised hydrological model for the Central Amazon: The importance of emergent canopy trees in the forest water budget. Agricultural and Forest Meteorology 239, pp. 47 - 57 (2017)
Hilman, B.; Muhr, J.; Trumbore, S. E.; Kunert, N.; Carbone, M. S.; Yuval, P.; Wright, S. J.; Moreno, G.; Pérez‑Priego, O.; Migliavacca, M.et al.; Carrara, A.; Grünzweig, J. M.; Osem, Y.; Weiner, T.; Angert, A.: Comparison of CO2 and O2 fluxes demonstrate retention of respired CO2 in tree stems from a range of tree species. Biogeosciences 16 (1), pp. 177 - 191 (2017)
Kunert, N.: Curios relationship revealed by looking at long term data sets—The geometry and allometric scaling of diel xylem sap flux in tropical trees. Journal of Plant Physiology 205, pp. 80 - 83 (2016)
Aparecido, L. M. T.; dos Santos, J.; Higuchi, N.; Kunert, N.: Ecological applications of differences in the hydraulic efficiency of palms and broad leaved trees. Trees 29, pp. 1431 - 1445 (2015)
Da Silva, F.; Suwa, R.; Kajimoto, T.; Ishizuka, M.; Higuchi, N.; Kunert, N.: Allometric equations for estimating biomass of Euterpe precatoria, the most abundant palm species in the Amazon. Forests 6 (2), pp. 450 - 463 (2015)
Kunert, N.; Aparecido, L. M. T.; Barros, P.; Higuchi, N.: Modeling potential impacts of planting palms or tree in small holder fruit plantations on ecohydrological processes in the Central Amazon. Forests 6 (8), pp. 2530 - 2544 (2015)
Kunert, N.; Aparecido, L. M. T.; dos Santos, J.; Higuchi, N.; Trumbore, S. E.: Higher tree transpiration due to road-associated edge effects in a tropical moist lowland forest. Agricultural and Forest Meteorology 213, pp. 183 - 192 (2015)
Schwendenmann, L.; Pendall, E.; Sanchez-Bragado, R.; Kunert, N.; Hölscher, D.: Tree water uptake in a tropical plantation varying in tree diversity: interspecific differences, seasonal shifts and complementarity. Ecohydrology 8 (1), pp. 1 - 12 (2015)
Trumbore, S. E.; Angert, A.; Kunert, N.; Muhr, J.; Chambers, J. Q.: What's the flux? Unraveling how CO2 fluxes from trees reflect underlying physiological processes. New Phytologist 197 (2), pp. 353 - 355 (2013)
Kunert, N.; Mercado Cardenas, A.: Effects of xylem water transport on CO2 efflux of woody tissue in a tropical tree, Amazonas State. Hoehnea 39 (1), pp. 139 - 144 (2012)
Thanks to FLUXCOM-X, the next generation of data driven, AI-based earth system models, scientists can now see the Earth’s metabolism at unprecedented detail – assessed everywhere on land and every hour of the day.
David Hafezi Rachti was awarded twice: for his EGU poster with this year’s “Outstanding Student and PhD candidate Presentation” (OSPP) and for his Bachelor thesis, he received the 1st prize of the “Young Climate Scientist Award 2024”.
A recent study by scientists from the Max Planck Institute for Biogeochemistry and the University of Leipzig suggests that increasing droughts in the tropics and changing carbon cycle responses due to climate change are not primarily responsible for the strong tropical response to rising temperatures. Instead, a few particularly strong El Niño events could be the cause.
EU funds the international research project AI4PEX to further improve Earth system models and thus scientific predictions of climate change. Participating scientists from 9 countries met at the end of May 2024 to launch the project at the MPI for Biogeochemistry in Jena, which is leading the project.
From the Greek philosopher Aristotle to Charles Darwin to the present day, scientists have dealt with this fundamental question of biology. Contrary to public perception, however, it is still largely unresolved. Scientists have now presented a new approach for the identification and delimitation of species using artificial intelligence (AI).
When it comes to studying climate change, we generally assume that the total amount of carbon emissions determines how much the planet will warm. A new study suggests that not only the amount, but also the timing of those emissions controls the amount of surface warming that occurs on human time-scale.
Tropical forests are continuously being fragmented and damaged by human influences. Using remote sensing data and cutting-edge data analysis methods, researchers can now show for the first time that the impact of this damage is greater than previously estimated.
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.
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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.