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Biology subjects

Klaus, V.

Publications and source records attributed to Klaus, V..

2 recordsLinked to original sources

Soil conditions drive belowground trait space in temperate agricultural grasslands

O_LIPlant belowground organs perform essential functions, including water and nutrient uptake, anchorage, vegetative reproduction and recruitment of mutualistic soil microbiota. Determining how belowground traits jointly determine dimensions of the trait space and how these dimensions are linked to environmental conditions would further advance our understanding of plant functioning and community assembly. C_LIO_LIHere, we investigated belowground plant-trait dimensionality and its variation along 10 soil and land-use parameters in 150 temperate grasslands plots. We used eight belowground traits collected in greenhouse and common garden experiments, as well as bud-bank size and specific leaf area from databases, for a total of 313 species, to calculate community weighted means (CWMs). C_LIO_LIUsing PCA, we found that about 55% of variance in CWMs was explained by two main dimensions, corresponding to a mycorrhizal collaboration and a resource conservation gradient. Frequently overlooked traits such as rooting depth, bud-bank size and root branching intensity were largely integrated in this bidimensional trait space. The two plant-strategy gradients were partially dependent on each other, with outsourcing communities along the collaboration gradient being more often slow. These outsourcing communities were also more often deep-rooting, and associated with soil parameters, such as low moisture and sand content, high topsoil pH, high C:N and low {delta}15N. Slow communities had large bud-banks and were associated with low land-use intensity, high topsoil pH, and low nitrate but high ammonium concentrations in the soil. We did not find a substantial role of phosphorus-availability as an indicator along the collaboration gradient. C_LIO_LIIn conclusion, the collaboration and conservation gradients previously identified at the species level scale up to community level in grasslands, encompass more traits than previously described, and vary with the environment. C_LI

ecology↗

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↗