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Understanding of spatial pattern and scale has been identified as a key issue in ecology, yet ecology has traditionally lacked necessary tools for making inference about relationships between scale-specific patterns. We introduce wavelet-coefficient regression, in which the dependent and independent variables are wavelet transformed prior to analysis, as a means to formalize scale-specific relationships in ecological data. We apply this method to data on vegetation and environmental factors related to water availability from Sequoia-Kings Canyon National Park (California, USA). We find that the wavelet transform and wavelet-coefficient regression efficiently characterize scale-specific pattern in these data. We also find that different environmental factors show up as good predictors of vegetation growth at different scales and that these differences in scale greatly facilitate interpretation of the mechanisms relating water availability to vegetation growth.

The issue of scaling impinges on every aspect of landscape ecology and much of ecology in general. Consequently, the topic has invited a vast commentary. One result of scaling research is so-called scaling laws that describe how observations scale (e.g., as power laws). Importantly, such scaling rules seldom derive from a process-based understanding of why they emerge. Alternatively, the task of scaling is often addressed via simulation models. This is a scaling operation about which we are somewhat less confident, although recent advances in computing power and computational statistics provide for some promising new solutions. Here, I focus on methods for scaling simulations developed at fine grain and small extent, to their implications over much larger extent. The intent in scaling is to simplify the model while retaining those details essential for larger-scale applications. This approach should lead to scaling rules that are well founded in fine-scale ecological process and yet useful for making predictions at the larger scales of management and environmental policy.

Forest fragmentation is a common process in forests worldwide, with implications for tree species composition and abundance. In particular, the effects of forest– non-forest edges on microclimate are often profound, usually resulting in increased light available to plants along the forest–non-forest edge. Using dendrochronological techniques, we assessed the effect of edges on the growth rates of four overstory species common in the North Carolina Piedmont: Acer rubrum, Liriodendron tulipifera, Liquidambar styraciflua, and Pinus taeda. Transects from the edge into the forest interior were established on 62 edges of varying aspect and ages in the Duke Forest (Durham, North Carolina, USA). Within a transect, all stems >10 cm in diameter were cored, and their spatial positions relative to the edge were recorded. Along each transect, a set of environmental and edaphic variables was measured including soil texture, soil concentrations of plant nutrients, and percentage of canopy closure. All transects were geo...

Ecologists are familiar with two data structures commonly used to represent landscapes. Vector-based maps delineate land cover types as polygons, while raster lattices represent the landscape as a grid. Here we adopt a third lattice data structure, the graph. A graph represents a landscape as a set of nodes (e.g., habitat patches) connected to some degree by edges that join pairs of nodes functionally (e.g., via dispersal). Graph theory is well developed in other fields, including geography (transportation networks, routing ap- plications, siting problems) and computer science (circuitry and network optimization). We present an overview of basic elements of graph theory as it might be applied to issues of connectivity in heterogeneous landscapes, focusing especially on applications of metapo- pulation theory in conservation biology. We develop a general set of analyses using a hypothetical landscape mosaic of habitat patches in a nonhabitat matrix. Our results suggest that a simple graph construct, the minimum spanning tree, can serve as a powerful guide to decisions about the relative importance of individual patches to overall landscape con- nectivity. We then apply this approach to an actual conservation scenario involving the