DOI: 10.25829/bexis.31654-5
title: Biomass, species richness and environmental data from all three regions of the Biodiversity Exploratories, used in: Causal inference methods reveal weak reciprocal relationships between productivity and plant biodiversity in managed grasslands

description: To study the causal effects between biodiversity and productivity we collected seasonal data of both biodiversity and productivity and potential confounding variables (environmental and land-use related variables) in all 150 EP plots across the three regions of the Biodiversity Exploratories (i.e. Schorfheide-Chorin, Swabian Alb and Hainich-Dün) in both spring and summer of 2020 and 2021. This dataset comprises variables collected by the BEF-Loops project (funded by DFG: Nr. 433266560, Exploratories project phase Nr. PL 891/3-1) and other projects within the Biodiversity Exploratories.
description: Detailed description of study design: The grasslands are located within three German regions (north-east: Schorfheide-Chorin, central: Hainich-Dün, south-west: Swabian Alb) that are part of the Biodiversity Exploratories project (Fischer et al. 2010). All data was collected from permanently marked plots (1×1 m) within 50 grasslands per region (150 in total). These grasslands are managed, with plots selected to span a wide gradient of land-use intensity typical of Central European grasslands (Blüthgen et al. 2012).|Sampling design: In both the spring (April-May) and summer growing season (July-August) of 2020 and 2021, we estimated standing biomass (g m-2) and species-specific cover (in %) of vascular plant species in each of the 150 grassland plots. Standing biomass was non-destructively estimated using a rising plate meter, by taking vegetation density as a proxy for standing biomass. Biomass estimations were calibrated using data of actual biomass measurements from two additional, adjacent (~2 m distance) 1×1 m grassland plots (100 plots per region, 300 in total) collected in spring 2021. Land-use related information was derived from annual questionnaires of land-owners. Within each grassland, land-use intensity comprises the intensity of fertilization, mowing and grazing, which are used to generate an index of land-use intensity (LUI hereafter) as a composite variable of standardized measures of mowing (cuts year-1), grazing (Livestock units * day ha-1 year-1) and fertilization (kg N ha-1 year-1) intensity.|Equipment: Rising plate meter (Jenquip Manual Plate Meter)|Data preparation: To consider effects of past LUI (from previous year) on biodiversity and productivity, LUI was quantified for the years 2019 and 2020 using the LUI Tool (mean: global with ALB, HAI and SCH; separately for years 2019 and 2020) (see ID 31514).<br>To correct for confounding variables, we obtained existing project data from other project in the Biodiversity Exploratories on edaphic conditions (i.e. soil P, soil N, soil pH, sand/clay content, slope and elevation) (see ID 31210, 31074, 31340, 1000), climatic (i.e. mean temperature and precipitation in months before spring and summer) (see ID 24766) and hydrological variables (i.e. topographic wetness index) (see ID 31018 ).<br>To account for different resource acquisition strategies of plants that are known to influence biodiversity and productivity in managed grasslands, we additionally quantified community weighted means (CWM) of specific leaf area (SLA hereafter) for all plots, as the mean SLA of all species in a given plot weighted by relative cover of each species. All trait data was obtained from the TRY database. To quantify competition for light, we measured light availability as photosynthetically active radiation (in μmol sec-1 m-2) at ground level and 1.5 m.<br>The proportion of light reaching the ground (proxy for light competition at plot level) was calculated as the inverse ratio between the (average) light availability above canopy height and ground level (light availability hereafter; increases from 0 to 1).|Literature references: Blüthgen, Nico; Dormann, Carsten F.; Prati, Daniel; Klaus, Valentin H.; Kleinebecker, Till; Hölzel, Norbert et al. (2012): A quantitative index of land-use intensity in grasslands: Integrating mowing, grazing and fertilization. In Basic and Applied Ecology 13 (3), pp. 207–220. DOI: 10.1016/j.baae.2012.04.001.<br>Fischer, Markus; Bossdorf, Oliver; Gockel, Sonja; Hänsel, Falk; Hemp, Andreas; Hessenmöller, Dominik et al. (2010): Implementing large-scale and long-term functional biodiversity research: The Biodiversity Exploratories. In Basic and Applied Ecology 11 (6), pp. 473–485. DOI: 10.1016/j.baae.2010.07.009.|Data references:BExIS Datasets inlcuded in this data set (dataset ID - specific data extracted from the orginial dataset):<br>ID 31514 - LUI Tool (https://www.bexis.uni-jena.de/lui/LUICalculation/index, downloaded on the 04.11.2022)<br>ID 31180 - Calibration data for calibrating biomass estimations (measured via rising plate-meter)<br>ID 1000 - Slope, Elevation, Sand content, Clay content<br>ID 31210 - Soil carbon and nitrogen<br>ID 31074 - Soil pH<br>ID 31340 - Soil phosphorus<br>ID 24766 - Mean temperature and mean precipitation quantified based on climate data<br>ID 31018 - Topographic wetness index<br>TRY dataset included in this dataset:<br>Specific leaf area from TRY (https://www.try-db.org/TryWeb/Home.php, TraitID 3117, accessed on the 13.07.2020)