Biodiversity

Title of the subproject:
Analysing the relationship between landscape and land-use parameters and High Nature Value farmland

Introduction:
Land-use strategies aimed at climate change mitigation or adaptation lead to changes in land use. Land-use change is currently one of most important drivers of biodiversity change. An increase in cultivation of biomass for energy production, for instance, could pose both substantial risks and prospects to biodiversity.

One the one hand, expanding agricultural biomass production may lead to a loss of biodiversity due to an intensification of land use, short crop rotations, reduction in crop diversity and the loss of linear landscape features (e.g. hedgerows, field margins). On the other hand, synergistic effects between climate change mitigation and the conservation of biodiversity may arise as a result of expanding agricultural biomass production, e. g. due to the reduced input of herbicides, diverse crop rotations and the increase in landscape diversity by introducing perennial crops into homogeneous landscapes.

In order to investigate the impact of various land-use strategies on biodiversity, we assess the relationship between landscape and land-use parameters and the percentage cover of species-rich farmland and landscape elements in Germany. 

Institution:
Thünen Institute of Biodiversity

The work package "Biodiversity" aims at analysing the relationship between agricultural and environmental parameters and the percentage cover of species-rich farmland and landscape elements in Germany. The modelled distribution of species-rich farmland and landscape elements facilitates the identification of priority areas for conservation actions and contributes to the evaluation of potential trade-offs between climate-optimized land-use strategies and the conservation of biodiversity in agricultural landscapes.

We use fine-scale data from a biological field survey that covered 915 1-km2 sample plots and comprise the area covered by species-rich farmland (defined by a minimum number of indicator plant species) and landscape elements (defined as hedgerows, ditches and patches of woodland or scrub that meet predefined quality criteria), respectively. Our approach involves two steps. Firstly, we derived 40 variables that are related to climate, topography, landscape, soil, agriculture and human population in order to ascertain relationships and provide a preliminary understanding of the possible underlying factors that have led to the current distribution of species-rich farmland and landscape elements within the sample plots. Secondly, we used these models to predict the spatial distribution of species-rich farmland and landscape elements at a national scale with a spatial resolution of 1-km.

Co-working with other subprojects in CC-LandStraD:

The subproject "Biodiversity" works closely with the subproject "Agricultural economics" (TP 1.1). Moreover, there is collaboration with the subproject "Socioeconomic Assessment" (TP 3).

From our geo-referenced database of 40 predictor variables covering climate, topography, landscape, soil, agriculture and human population, the factor analysis extracted five significant factors explaining 53 % of the variation. The factors describe independent gradients in arable farming, topography, low-input grassland farming, landscape structure and intensive husbandry, respectively.

The factors that were most strongly associated with the percentage cover of species-rich farmland and landscape elements were those describing low-input grassland farming, landscape structure and intensive livestock farming. The modelled distribution maps for Germany show clusters of areas with high percentage cover of species-rich farmland in the Bavarian Alpine foothills, the Black Forest and the Swabian Alb in the South of Germany; the Eifel and the Westerwald in the West; the Thuringian Forest and the Röhn in the Centre and the Spreewald and the Mecklenburg Lake District in the East. The regions with high percentage cover of landscape elements were predominately located along riparian and coastal zones, such as East and North Frisia in the North-West, the Münsterland in the West and the Palatinate Forest and its Rhine plains in the South-West of Germany.

In a policy context, the generated maps could be used as a tool to inform and guide strategic planning in farmland biodiversity conservation actions to prevent further intensification and/or abandonment of agriculture in these particular regions.