Schrumpf, M. | bioRxiv Science

bioRxiv2026

Water Stress Induces Diel Patterns of Root Growth

Growth and death of vegetation control both the amount of carbon held in living biomass and much of the flow between the atmosphere and soils, the largest terrestrial carbon reservoir. However, long-term field datasets on belowground growth dynamics are rare. Knowledge is lacking on how root growth patterns relate to the environment, fluctuating carbon and water availability, and internal plant physiological control, at both seasonal and diel scales. We imaged roots using automated minirhizotrons and interpreting root length density (RLD) automatically twice a day for nine months in a temperate grassland. From winter to autumn, we always observed some root growth in individual images, but with decreasing net RLD (indicative of net turnover) becoming predominant later in the season. Roots grew day-round except during a period of about one month in spring when root growth was only in daytime. This was a period without rain, during which soil moisture depleted rapidly, but not at its driest point. We discuss potential causes for both overall and short-term growth patterns, particularly the change in drivers of growth from internal storage to new photosynthates, or limits imposed by water availability - both soil moisture and rainfall - under shifting environmental conditions.

plant biology↗

bioRxiv2020

Landscape management for grassland multifunctionality

Land-use intensification has contrasting effects on different ecosystem services, often leading to land-use conflicts. While multiple studies have demonstrated how landscape-scale strategies can minimise the trade-off between agricultural production and biodiversity conservation, little is known about which land-use strategies maximise the landscape-level supply of multiple ecosystem services (landscape multifunctionality), a common goal of stakeholder communities. We combine comprehensive data collected from 150 German grassland sites with a simulation approach to identify landscape compositions, with differing proportions of low-, medium-, and high-intensity grasslands, that minimise trade-offs between the six main grassland ecosystem services prioritised by local stakeholders: biodiversity conservation, aesthetic value, productivity, carbon storage, foraging, and regional identity. Results are made accessible through an online tool that provides information on which compositions best meet any combination of user-defined priorities (https://neyret.shinyapps.io/landscape_composition_for_multifunctionality/). Results show that an optimal landscape composition can be identified for any pattern of ecosystem service priorities. However, multifunctionality was similar and low for all landscape compositions in cases where there are strong trade-offs between services (e.g. aesthetic value and fodder production), where many services were prioritised, and where drivers other than land use played an important role. We also found that if moderate service levels are deemed acceptable, then strategies in which both high and low intensity grasslands are present can deliver landscape multifunctionality. The tool presented can aid informed decision-making by predicting the impact of future changes in landscape composition, and by allowing for the relative roles of stakeholder priorities and biophysical trade-offs to be understood by scientists and practitioners alike. HighlightsO_LIAn online tool identifies optimal landscape compositions for desired ecosystem services C_LIO_LIWhen the desired services are synergic, the optimum is their common best landscape composition C_LIO_LIWhen the desired services trade-off, a mix of grassland intensity is most multifunctional C_LIO_LISuch tools could support decision-making processes and aid conflict resolution C_LI Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=111 SRC="FIGDIR/small/208199v5_ufig1.gif" ALT="Figure 1"> View larger version (27K): org.highwire.dtl.DTLVardef@3273f6org.highwire.dtl.DTLVardef@5b3a5aorg.highwire.dtl.DTLVardef@153f526org.highwire.dtl.DTLVardef@103cbea_HPS_FORMAT_FIGEXP M_FIG C_FIG

ecology↗