IPB Halle: Leibniz-Institut für Pflanzenbiochemie Deutsch

Lange Nacht, die Wissen schafft

4. Juli 2025 am IPB
IPB-Newsletter | April 2025
Wir verstehen Pflanzen!

Der Film zum Institut
Molekulare Signalverarbeitung

Prof. Dr. Steffen Abel
Wie Pflanzen ihrer Umwelt trotzen.
Natur- und Wirkstoffchemie

Prof. Dr. Ludger Wessjohann
Die Chemie der Natur – Basis für Wirkstoffe zur Gesunderhaltung von Mensch und Pflanze.
Biochemie pflanzlicher Interaktionen

Prof. Dr. Tina Romeis
Wechselwirkungen in, von und mit Pflanzen.
Stoffwechsel- und Zellbiologie

Prof. Dr. Alain Tissier
Sekundär jedoch nicht zweitrangig - Die biologischen Funktionen pflanzlicher Sekundärmetaboliten.
Unabhängige Nachwuchsgruppe

Dr. Mariana Schuster

Aktuelles

Unser 10. Leibniz Plant Biochemistry Symposium am 7. und 8. Mai war ein großer Erfolg. Thematisch ging es in diesem Jahr um neue Methoden und Forschungsansätze der Naturstoffchemie. Die exzellenten Vorträge über Wirkstoffe…

Omanische Heilpflanze im Fokus der Phytochemie
IPB-Wissenschaftler und Partner aus Dhofar haben jüngst die omanische Heilpflanze Terminalia dhofarica unter die phytochemische Lupe genommen. Die Pflanze ist reich an…

Geschmack ist vorhersagbar: Mit FlavorMiner.
FlavorMiner heißt das Tool, das IPB-Chemiker und Partner aus Kolumbien jüngst entwickelt haben. Das Programm kann, basierend auf maschinellem Lernen (KI), anhand der…

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Datum: 14.05.2025 Referenznummer: 10/2025

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Rana, R.; Herz, K.; Bruelheide, H.; Dietz, S.; Haider, S.; Jandt, U.; Pena, R.; Leaf Attenuated Total Reflection Fourier Transform Infrared (ATR-FTIR) biochemical profile of grassland plant species related to land-use intensity Ecol. Indic. 84 803-810 (2017) DOI: 10.1016/j.ecolind.2017.09.047

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Herz, K.; Dietz, S.; Haider, S.; Jandt, U.; Scheel, D.; Bruelheide, H.; Predicting individual plant performance in grasslands Ecol. Evol. 7 8958-8965 (2017) DOI: 10.1002/ece3.3393

Plant functional traits are widely used to predict community productivity. However, they are rarely used to predict individual plant performance in grasslands. To assess the relative importance of traits compared to environment, we planted seedlings of 20 common grassland species as phytometers into existing grassland communities varying in land‐use intensity. After 1 year, we dug out the plants and assessed root, leaf, and aboveground biomass, to measure plant performance. Furthermore, we determined the functional traits of the phytometers and of all plants growing in their local neighborhood. Neighborhood impacts were analyzed by calculating community‐weighted means (CWM) and functional diversity (FD) of every measured trait. We used model selection to identify the most important predictors of individual plant performance, which included phytometer traits, environmental conditions (climate, soil conditions, and land‐use intensity), as well as CWM and FD of the local neighborhood. Using variance partitioning, we found that most variation in individual plant performance was explained by the traits of the individual phytometer plant, ranging between 19.30% and 44.73% for leaf and aboveground dry mass, respectively. Similarly, in a linear mixed effects model across all species, performance was best predicted by phytometer traits. Among all environmental variables, only including land‐use intensity improved model quality. The models were also improved by functional characteristics of the local neighborhood, such as CWM of leaf dry matter content, root calcium concentration, and root mass per volume as well as FD of leaf potassium and root magnesium concentration and shoot dry matter content. However, their relative effect sizes were much lower than those of the phytometer traits. Our study clearly showed that under realistic field conditions, the performance of an individual plant can be predicted satisfyingly by its functional traits, presumably because traits also capture most of environmental and neighborhood conditions.

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Herz, K.; Dietz, S.; Haider, S.; Jandt, U.; Scheel, D.; Bruelheide, H.; Drivers of intraspecific trait variation of grass and forb species in German meadows and pastures J. Veg. Sci. 28 705-716 (2017) DOI: 10.1111/jvs.12534

QuestionsTo what extent is trait variation in grasses and forbs driven by land‐use intensity, climate, soil conditions and plant diversity of the local neighbourhood? Do grass and forb species differ in the degree of intraspecific trait variation?LocationManaged grasslands in three regions of Germany.MethodsUsing a phytometer approach, we raised 20 common European grassland species (ten forbs and ten grasses) and planted them into 54 plots of different land‐use types (pasture, meadow, mown pasture). After 1 yr in the field, we measured above‐ and below‐ground plant functional traits. Linear mixed effects models (LMEM) were used to identify the most powerful predictors for every trait. Variation partitioning was applied to assess the amount of inter‐ and intraspecific trait variation in grasses and forbs explained by environmental conditions (land‐use intensity, climate and soil conditions) and plant species diversity of the local neighbourhood.ResultsFor 12 out of the 14 traits studied, either land‐use intensity or local neighbourhood diversity were predictors in the best LMEM. Land‐use intensity had considerably stronger effects than neighbourhood diversity. Root dry matter content and root phosphorus concentration of forbs were more affected by land‐use intensity than those of grasses. For almost all traits, intraspecific trait variation of grasses was much higher than that of forbs, while traits of forbs varied more among species. Overall, inter‐ and intraspecific variation was of the same magnitude.ConclusionThe similar magnitude of intra‐ and interspecific trait variation suggests that both sources should be considered in grassland studies at a scale similar to that of our study. The high amount of intraspecific trait variation that was explained by environmental factors and local neighbourhood diversity clearly demonstrates the high potential of species to adjust to local conditions, which would be ignored when only considering species mean trait values.

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Lange Nacht, die Wissen schafft

IPB-Newsletter | April 2025

Wir verstehen Pflanzen!

Molekulare Signalverarbeitung

Natur- und Wirkstoffchemie

Biochemie pflanzlicher Interaktionen

Stoffwechsel- und Zellbiologie

Unabhängige Nachwuchsgruppe

Aktuelles

Gelungenes Symposium

+++ Newsticker Wissenschaft #182 +++ Naturstoffe +++

+++ Newsticker Wissenschaft #181 +++ Maschinelles Lernen +++

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Referent*in der Geschäftsführung (m/w/d) (10/2025)

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