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Institute
Understanding changes in biodiversity in agricultural landscapes in relation to land-use type and intensity is a major issue in current ecological research. In this context nutrient enrichment has been identified as a key mechanism inducing species loss in Central European grassland ecosystems. At the same time, insights into the linkage between agricultural land use and plant nutrient status are largely missing. So far, studies on the relationship between chemical composition of plant community biomass and biodiversity have mainly been restricted to wetlands and all these studies neglected the effects of land use. Therefore, we analyzed aboveground biomass of 145 grassland plots covering a gradient of land-use intensities in three regions across Germany. In particular, we explored relationships between vascular plant species richness and nutrient concentrations as well as fibre contents (neutral and acid detergent fibre and lignin) in the aboveground community biomass.
We found the concentrations of several nutrients in the biomass to be closely linked to plant species richness and land use. Whereas phosphorus concentrations increased with land-use intensity and decreased with plant species richness, nitrogen and potassium concentrations showed less clear patterns. Fibre fractions were negatively related to nutrient concentrations in biomass, but hardly to land-use measures and species richness. Only high lignin contents were positively associated with species richness of grasslands. The N:P ratio was strongly positively related to species richness and even more so to the number of endangered plant species, indicating a higher persistence of endangered species under P (co-)limited conditions. Therefore, we stress the importance of low P supply for species-rich grasslands and suggest the N:P ratio in community biomass to be a useful proxy of the conservation value of agriculturally used grasslands.
Many bryophytes may depend on epizoochorous dispersal by large mammals for maintaining their populations and colonizing new habitats. On dry grassland we investigated the transport of bryophyte diaspores by sheep, which are known to be effective epizoochorous dispersal vectors of seed plants. Twelve sheep of two breeds were examined by collecting gametophyte fragments from their fleece and hooves. Furthermore, microscopic diaspores from the soil adhering to the hooves were grown in a greenhouse. Species frequency and composition were compared to bryophyte vegetation on the pasture. Considerable amounts of unspecialized gametophyte fragments from 16 moss species, 40% of the species growing on the pasture, were transported by sheep, especially on the belly and the tail. Additionally, we provide first evidence of epizoochorous dispersal of thallus fragments from fruticose lichens. Sheep breeds differed in species spectrum and frequency, i.e. sheep with dense, curly fleece carried more fragments and larger species than those with smooth and fine hair. Among the dispersed bryophytes pleurocarps, certain taxa, sizes (small species) and life forms (mats) were overrepresented compared to the vegetation of the pasture, while large species, acrocarps, wefts and turfs were underrepresented, reflecting fragmentation and adhesion features of the species. In the hooves mostly acrocarpous colonist species were transported. We conclude that sheep are important dispersal vectors with the potential of long-range dispersal for bryophytes, especially for species without sexual reproduction, and that epizoochorous dispersal of microscopic diaspores might be underestimated in its importance so far.
Estimating large herbivore density has been a major area of research in recent decades. Previous studies monitoring ungulate density, however, focused mostly on determining animal abundance, and did not interpret animal distribution in relation to habitat parameters. We surveyed large ungulates in the Biodiversity Exploratory Schorfheide-Chorin using faecal pellet group counts. This allowed us to explore the link between relative ungulate abundance, habitat use, and browsing damage on trees in a region with several types of forest, including unharvested and age-class beech forests, as well as age-class pine forests. Our results demonstrate that roe deer and fallow deer relative abundance is negatively correlated with large tree cover, and positively correlated with the cover of small shrubs (Rubus spec., Vaccinium spec.), and winter food supply. Habitat use of roe deer and fallow deer, as estimated by counting faecal pellet groups, revealed a preference for mature pine forests, and avoidance of deciduous forests. This differential habitat use is explained by different distributions of high quality food resources during winter. The response of deer to understory cover differed between roe deer and fallow deer at high cover percentages. The amount of browsing damage we observed on coniferous trees was not consistent with the relative deer abundance. Browsing damage was consistently higher on most deciduous trees, except for beech saplings which sustained less damage when roe deer density was low. Because roe deer is a highly selective feeder, it was reported to affect tree diversity by feeding only on trees with high nutritional value. Consequently, we propose that managing the number of all deer species by hunting is necessary to allow successful forest regeneration. Such an adjustment to deer numbers would need to account for both current tree diversity and alternative food resources. Our findings may be applicable to other forest landscapes in northeastern Germany including mature pine stands and differently harvested deciduous forests.
Species distribution models are an important tool to predict the impact of global change on species distributional ranges and community assemblages. Although considerable progress has been made in the statistical modeling during the last decade, many approaches still ignore important features of species distributions, such as nonlinearity and interactions between predictors, spatial autocorrelation, and nonstationarity, or at most incorporate only some of these features. Ecologists, however, require a modeling framework that simultaneously addresses all these features flexibly and consistently. Here we describe such an approach that allows the estimation of the global effects of environmental variables in addition to local components dealing with spatiotemporal autocorrelation as well as nonstationary effects. The local components can be used to infer unknown spatiotemporal processes; the global component describes how the species is influenced by the environment and can be used for predictions, allowing the fitting of many well-known regression relationships, ranging from simple linear models to complex decision trees or from additive models to models inspired by machine learning procedures. The reliability of spatiotemporal predictions can be qualitatively predicted by separately evaluating the importance of local and global effects. We demonstrate the potential of the new approach by modeling the breeding distribution of the Red Kite (Milvus milvus), a bird of prey occurring predominantly in Western Europe, based on presence/absence data from two mapping campaigns using grids of 40 km 2 in Bavaria. The global component of the model selected seven environmental variables extracted from the CORINE and WorldClim databases to predict Red Kite breeding. The effect of altitude was found to be nonstationary in space, and in addition, the data were spatially autocorrelated, which suggests that a species distribution model that does not allow for spatially varying effects and spatial autocorrelation would have ignored important processes determining the distribution of Red Kite breeding across Bavaria. Thus, predictions from standard species distribution models that do not allow for real-world complexities may be considerably erroneous. Our analysis of Red Kite breeding exemplifies the potential of the innovative approach for species distribution models. The method is also applicable to modeling count data.
Edaphic fauna contributes to important ecosystem functions in grassland soils such as decomposition and nutrient mineralization. Since this functional role is likely to be altered by global change and associated shifts in plant communities, a thorough understanding of large scale drivers on below-ground processes independent of regional differences in soil type or climate is essential. We investigated the relationship between abiotic (soil properties, management practices) and biotic (plant functional group composition, vegetation characteristics, soil fauna abundance) predictors and feeding activity of soil fauna after accounting for sample year and study region. Our study was carried out over a period of two consecutive years in 92 agricultural grasslands in three regions of Germany, spanning a latitudinal gradient of more than 500 km. A structural equation model suggests that feeding activity of soil fauna as measured by the bait-lamina test was positively related to legume and grass species richness in both years. Most probably, a diverse vegetation promotes feeding activity of soil fauna via alterations of both microclimate and resource availability. Feeding activity of soil fauna also increased with earthworm biomass via a pathway over Collembola abundance. The effect of earthworms on the feeding activity in soil may be attributed to their important role as ecosystem engineers. As no additional effects of agricultural management such as fertilization, livestock density or number of cuts on bait consumption were observed, our results suggest that the positive effect of legume and grass species richness on the feeding activity in soil fauna is a general one that will not be overruled by regional differences in management or environmental conditions. We thus suggest that agri-environment schemes aiming at the protection of belowground activity and associated ecosystem functions in temperate grasslands may generally focus on maintaining plant diversity, especially with regard to the potential effects of climate change on future vegetation structure.