Improved methods for measuring forest landscape structure: LiDAR complements field-based habitat assessment

Conservation and monitoring of forest biodiversity requires reliable information about forest structure and composition at multiple spatial scales. However, detailed data about forest habitat characteristics across large areas are often incomplete due to difficulties associated with field sampling methods. To overcome this limitation we employed a nationally available light detection and ranging (LiDAR) remote sensing dataset to develop variables describing forest landscape structure across a large environmental gradient in Switzerland. Using a model species indicative of structurally rich mountain forests (hazel grouse Bonasa bonasia), we tested the potential of such variables to predict species occurrence and evaluated the additional benefit of LiDAR data when used in combination with traditional, sample plot-based field variables. We calibrated boosted regression trees (BRT) models for both variable sets separately and in combination, and compared the models’ accuracies. While both field-based and LiDAR models performed well, combining the two data sources improved the accuracy of the species’ habitat model. The variables retained from the two datasets held different types of information: field variables mostly quantified food resources and cover in the field and shrub layer, LiDAR variables characterized heterogeneity of vegetation structure which correlated with field variables describing the understory and ground vegetation. When combined with data on forest vegetation composition from field surveys, LiDAR provides valuable complementary information for encompassing species niches more comprehensively. Thus, LiDAR bridges the gap between precise, locally restricted field-data and coarse digital land cover information by reliably identifying habitat structure and quality across large areas.

Pedagogical field experiences in teacher education: Introduction to the research area

Research on pre-service teacher internships has become a dynamic area of investigation in teacher education whose growth seems to correspond with increased activity at the institutional level over the past two decades. Introducing or expanding field experiences has been a common strategy in nearly all teacher education programs for the last twenty years, and reforming teacher education with a focus on its practical aspects still ranks near the top of education policy agendas. This article provides an introduction to the research field, addressing five basic issues: (1) precision in the definition of the construct, (2) main sources of research literature, (3) elaboration of the construct in terms of effects and mediating variables, (4) the methodological challenges of empirical research, and (5) major areas of future research. Emphasis is placed on the often ignored aspect that internships elicit both intended and unintended effects, including not only positive but also adverse side effects.