Lisa Paukner
Current Organizations / Institutes
The organizations/institutes from the scholar's latest article
Research Subjects
Lisa Paukner has a total of 2 co-authors. Here are the top co-authors by number of shared publications:
- Jolina Paulssen
Vegetation Ecology and Conservation Biology, Institute of Ecology University of Bremen Bremen Germany
1 shared publication - Martin Diekmann
Vegetation Ecology and Conservation Biology, Institute of Ecology University of Bremen Bremen Germany
1 shared publication
Latest Publications
- Open Access
- 13 January 2026
- Published by Springer Nature in European Journal of Forest Research
- Vol. 145 (1) , 17
Soil moisture and soil C/N ratio interactively affect plant species richness and composition in deciduous forests
To examine effects of local environmental conditions on the vegetation, measurements on the microhabitat level are highly relevant. Unlike most soil chemical variables, soil moisture is rarely considered in studies investigating the impact of local factors on plant species composition. Here, we conducted soil moisture measurements with TMS4 sensors over a two-month period in 25 deciduous forest plots in northern Germany, performed site-specific moisture calibrations and studied the quantitative effect of soil properties on the relationship between the TMS4 signal and gravimetric soil moisture. Moreover, we investigated the effect of measured microhabitat conditions (light availability, soil variables including soil moisture) on plant species richness and composition. We found that soil carbon significantly influenced the relationship between the TMS4 raw signal and gravimetric soil moisture. The number of herb layer species and ancient woodland indicators (AWI) increased with increasing soil moisture. For the herb layer, soil moisture and soil C/N ratio had an interactive effect: species richness increased more steeply with increasing soil moisture in plots with a low C/N ratio. AWI species richness was significantly higher in plots with a low C/N ratio. Herb layer species composition was shaped by two main gradients, reflecting (1) variation in C/N ratio and pH and (2) variation in soil moisture, other soil variables and light availability. Our findings indicate that soil carbon, a frequently measured variable in vegetation studies, could, with sufficiently good calibrations, be directly used to translate sensor raw signals into reliable soil moisture values for predicting plant species occurrence.
- 13 January 2026
- Published by Springer Nature in European Journal of Forest Research
- Vol. 145 (1) , 17
Open AccessSoil moisture and soil C/N ratio interactively affect plant species richness and composition in deciduous forests
To examine effects of local environmental conditions on the vegetation, measurements on the microhabitat level are highly relevant. Unlike most soil chemical variables, soil moisture is rarely considered in studies investigating the impact of local factors on plant species composition. Here, we conducted soil moisture measurements with TMS4 sensors over a two-month period in 25 deciduous forest plots in northern Germany, performed site-specific moisture calibrations and studied the quantitative effect of soil properties on the relationship between the TMS4 signal and gravimetric soil moisture. Moreover, we investigated the effect of measured microhabitat conditions (light availability, soil variables including soil moisture) on plant species richness and composition. We found that soil carbon significantly influenced the relationship between the TMS4 raw signal and gravimetric soil moisture. The number of herb layer species and ancient woodland indicators (AWI) increased with increasing soil moisture. For the herb layer, soil moisture and soil C/N ratio had an interactive effect: species richness increased more steeply with increasing soil moisture in plots with a low C/N ratio. AWI species richness was significantly higher in plots with a low C/N ratio. Herb layer species composition was shaped by two main gradients, reflecting (1) variation in C/N ratio and pH and (2) variation in soil moisture, other soil variables and light availability. Our findings indicate that soil carbon, a frequently measured variable in vegetation studies, could, with sufficiently good calibrations, be directly used to translate sensor raw signals into reliable soil moisture values for predicting plant species occurrence.