FRIBIO-Biologi og biomedisin

The availability and quality of field data is one of the most severe limitations to studies of spatio-temporal population processes such as cyclic dynamics and population synchrony. We propose here an approach that will overcome many limitations concernin g data adequacy and which can dramatically improve opportunities for future research and monitoring of population dynamics, and specifically so for Geometrid moths in northern birch-forest ecosystems. We will use recent advances in remote sensing data acq uisition and spatial modelling and confront our results with field data on population dynamic patterns and forest structure. Our research agenda includes: 1) identifying prime moth habitat and outbreak distribution and intensity based on remote sensing da ta, 2) evaluating moth dispersal characteristics using simulation models and observed patterns of outbreak spread, 3) an integrated analysis of the ability of different mechanisms (local trophic interactions, dispersal and environmental heterogeneity) to generate observed large-scale dynamical patterns such as travelling waves using spatially explicit simulation models, and 4) evaluating the consequences of data uncertainty for the spatial dynamical properties of the system and the relative importance of local dynamics, dispersal and environmental heterogeneity. The first two sub-projects deal with field data scarcity and explore the potential for generating large-scale distribution and dynamics information from remote sensing sources. The results would b e of immense value in research and monitoring of forest defoliators. The last two sub-projects aim at understanding the general mechanisms behind the complex spatio-temporal patterns observed in many cyclic species incl. geometrid moths. By focusing on la rge-scale patterns and processes and taking advantage of spatially explicit simulation modelling techniques, we will be able to significantly complement on-going research efforts on local- to meso-scale dynamics