P3-5: Grid-Based Predictions of Biodiversity and Ecosystem Services at Different Spatial Scales

PhD Student: Felix Klaus
Supervisor: Dr. Ingo Grass
Department: Crop Sciences, Division of Agroecelogy

Project Description:
Recent studies have shown that biodiversity loss may be scale-dependent with greatest losses occurring at large spatial scales (Vellend et al., 2013). However, drawing the line between "large" and "small" scales is context-dependent and may be affected by organism size and mobility. In addition, ecological systems are characterized by interactions between local and landscape scales, and large-scale biodiversity loss may feedback to smaller spatial scales (Tscharntke et al., 2012), for example through landscape context effects or metacommunity dynamics.

At current, ecological studies mostly focus on particular habitats rather than on whole landscapes, and interpolated maps of biodiversity and associated ecosystem services across several spatial scales are lacking (Martin et al., 2012). There is still only a handful of studies covering several orders of magnitude, bridging the gap between small-scale systems and larger spatio-temporal scales. In this project, we propose to study biodiversity across scales by employing grid-based, i.e. systematic sampling approaches (Scherber et al., 2012) in replicated landscape grids. Based on experience from previous cohorts, we will extend the spatial and temporal sampling resolution and include habitat types such as forest and urban areas. Our project will therefore be among the first worldwide to perform grid-based sampling of whole landscapes. We will sample simultaneously at several spatial scales, allowing us to assess effects of spatial grain and extent on the response variables. Data on abundance and species richness of several taxonomic groups (plants, arthropods, birds) and associated ecosystem services (e.g. pollination, parasitism) will be collected repeatedly over time, providing spatio-temporal datasets that can be ideally analyzed using mixed model approaches that allow for spatio-temporal autocorrelation, hierarchical random effects, non-linear fixed effects and non-normal errors. Fine scale data on landscape structure and habitat composition will be collected using unmanned aerial vehicles (UAVs), allowing us to study also landscape changes (crop rotation) in real-time and at sufficient spatio-temporal resolution. In particular, the datasets generated in this project will be ideal candidates to test GAMLSS approaches, as organism abundances and species numbers will provide a wealth of non-normal response distributions, likely showing attributes such as zero-inflation, over- or underdispersion, skewed distributions and mixtures of distributions, and complex multidimensional patterning in space and time.

This project will be an essential link between theory-driven projects (e.g. P3-1), modeling projects (e.g. P3-4, P3-7), and other data-generating projects (e.g. P3-3, P3-4). Overall, we will combine grid-based sampling approaches with state-of-the-art statistical modelling to create predictions for biodiversity and ecosystem processes across scales (together with P3-6). Our approach will allow us to re-assess concepts such as landscape context using spatially explicit data. Such data and models are urgently needed in the face of biodiversity loss under increasing demands for agricultural land as the world's population grows.

Martin, L. J., Blossey, B. and Ellis, E. (2012), Mapping where ecologists work: biases in the global distribution of terrestrial ecological observations, Frontiers in Ecology and the Environment 10, 195-201.

Scherber, C., Lavandero, B., Meyer, K. M., Perovic, D., Visser, U., Wiegand, K. and Tscharntke, T. (2012), Scale effects in biodiversity and biological control: Methods and statistical analysis, in G. M. Gurr, S. D. Wratten, W. E. Snyder and D. M. Y. Read, eds, 'Biodiversity and Insect Pests', John Wiley & Sons, Ltd, Chichester, UK, pp. 121-138.

Tscharntke, T., Tylianakis, J. M., Rand, T. A., Didham, R. K., Fahrig, L., Batáry, P., Bengtsson, J., Clough, Y., Crist, T. O., Dormann, C. F., Ewers, R. M., Fru?nd, J., Holt, R. D., Holzschuh, A., Klein, A. M., Kleijn, D., Kremen, C., Landis, D. A., Laurance, W., Lindenmayer, D., Scherber, C., Sodhi, N., Ste_an-Dewenter, I., Thies, C., van der Putten, W. H. and Westphal, C. (2012), Landscape moderation of biodiversity patterns and processes - eight hypotheses, Biological Reviews 87, 661-685.

Vellend, M., Baeten, L., Myers-Smith, I. H., Elmendorf, S. C., Beauséjour, R., Brown, C. D., De Frenne, P., Verheyen, K. and Wipf, S. (2013), Global meta-analysis reveals no net change in local-scale plant biodiversity over time, Proceedings of the National Academy of Sciences 110, 19456-19459.