As a growing number of factors at multiple spatial scales influence land use and land cover, and as these factors interact in chain-linked or nested ways (Hurni 1996), they produce dissimilar land cover/use outcomes and thereby reinforcing the uniqueness of any local context (Ostrom 2007; Turner et al. 2007).
The aim is to propose and evaluate a practical method that can account for the complex interactions of environmental covariates across multiple scales and their influence on soil formation.
An experimentally-validated lumped-parameters model of the bi-stable harvester is also introduced, and solved using the method of multiple scales to study the influence of the shape of the potential energy function on the output voltage.
Herein, we demonstrate an approach to VOI analysis, in which uncertainty about the biology of carcinogenesis and a proposed preventive intervention is propagated computationally across multiple scales to predict their influence on trial outcomes.
Our study highlights the need to determine patterns of environmental influence at multiple scales to conserve specialist species such as the brush-tailed rock-wallaby in naturally fragmented landscapes.
In addition, the random forest model results point to the multiple scales at which the environment influences forest communities.
These mechanisms can be defined spatially at the level of genome to neural circuitry and temporally at multiple scales ranging from milliseconds to years, influencing each other through systems of feedback loops [56].
We establish how monopolization, and more generally evolution-mediated priority effects, influence ecological patterns at multiple scales of space, time, and biological organization.
As a result pedogenesis and the spatial distribution of soil properties are both influenced by features emerging at multiple scales.
Species responses are influenced by processes operating at multiple scales, yet many conservation studies and management actions are focused on a single scale.
