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Land use is increasingly recognized as a major driver of biodiversity and ecosystem functioning in many current research projects. In grasslands, land use is often classified by categorical descriptors such as pastures versus meadows or fertilized versus unfertilized sites. However, to account for the quantitative variation of multiple land-use types in heterogeneous landscapes, a quantitative, continuous index of land-use intensity (LUI) is desirable. Here we define such a compound, additive LUI index for managed grasslands including meadows and pastures. The LUI index summarizes the standardized intensity of three components of land use, namely fertilization, mowing, and livestock grazing at each site. We examined the performance of the LUI index to predict selected response variables on up to 150 grassland sites in the Biodiversity Exploratories in three regions in Germany(Alb, Hainich, Schorlheide). We tested the average Ellenberg nitrogen indicator values of the plant community, nitrogen and phosphorus concentration in the aboveground plant biomass, plant-available phosphorus concentration in the top soil, and soil C/N ratio, and the first principle component of these five response variables.
The LUI index significantly predicted the principal component of all five response variables, as well as some of the individual responses. Moreover, vascular plant diversity decreased significantly with LUI in two regions (Alb and Hainich).
Inter-annual changes in management practice were pronounced from 2006 to 2008, particularly due to variation in grazing intensity. This rendered the selection of the appropriate reference year(s) an important decision for analyses of land-use effects, whereas details in the standardization of the index were of minor importance. We also tested several alternative calculations of a LUI index, but all are strongly linearly correlated to the proposed index.
The proposed LUI index reduces the complexity of agricultural practices to a single dimension and may serve as a baseline to test how different groups of organisms and processes respond to land use. In combination with more detailed analyses, this index may help to unravel whether and how land-use intensities, associated disturbance levels or other local or regional influences drive ecological processes.
Ellenberg indicator values are widely used ecological tools to elucidate relationships between vegetation and environment in ecological research and environmental planning. However, they are mainly deduced from expert knowledge on plant species and are thus subject of ongoing discussion. We researched if Ellenberg indicator values can be directly extracted from the vegetation biomass itself. Mean Ellenberg "moisture" (mF) and "nitrogen" (mN) values of 141 grassland plots were related to nutrient concentrations, fibre fractions and spectral information of the aboveground biomass. We developed calibration models for the prediction of mF and mN using spectral characteristics of biomass samples with near-infrared reflectance spectroscopy (NIRS). Prediction goodness was evaluated with internal cross-validations and with an external validation data set. NIRS could accurately predict Ellenberg mN, and with less accuracy Ellenberg mF. Predictions were not more precise for cover-weighted Ellenberg values compared with un-weighted values. Both Ellenberg mN and mF showed significant and strong correlations with some of the nutrient and fibre concentrations in the biomass. Against expectations, Ellenberg mN was more closely related to phosphorus than to nitrogen concentrations, suggesting that this value rather indicates productivity than solely nitrogen. To our knowledge we showed for the first time that mean Ellenberg indicator values could be directly predicted from the aboveground biomass, which underlines the usefulness of the NIRS technology for ecological studies, especially in grasslands ecosystems.