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. 1992 Aug;2(3):248-261.
doi: 10.2307/1941859.

Gradient Analysis of Ecological Change in Time and Space: Implications for Forest Management

Gradient Analysis of Ecological Change in Time and Space: Implications for Forest Management

James R Gosz. Ecol Appl. 1992 Aug.

Abstract

Gradient analysis is a powerful technique to analyze for, and detect change in, the dynamics, structure, and function of ecosystems. Boundaries between zones or communities occur at distinctive locations along environmental gradients and are expected to be especially sensitive to environmental change. Gradient analysis can be performed at a range of scales, and allows integration and extrapolation of change across scales from those associated with communities to those of biomes. This review outlines the properties of gradients in space and time and uses an example of forests in the Rocky Mountain Physiographic Province to demonstrate constraints, the complex mosaics associated with distributional limits, transfers across boundaries, the role of disturbance, and threshold dynamics. A climate-change scenario is developed to hypothesize future changes in boundary movements, community mosaics, and ecosystem properties along elevational and latitudinal gradients in the Rocky Mountain Province. Mechanistic explanations of ecological phenomena that are necessary for management require information on: (1) the physical environmental constraints operating on the ecosystem; (2) the biota that operate within those constraints; and (3) the interactions among the biota and between the biota and environment. The relative importance of these three elements differs between environments and along environmental gradients. Biota and their interactions may account for much of the variance in system structure and function in mesic environments, while abiotic factors may limit biotic activity in less-favorable (arid) habitats. Plot studies that are analyzed as points along broader scale environmental gradients can provide quantitative information on the major driving variables, and broad-scale analyses of environmental factors along the gradient generate the information for extrapolating between sites and across scales. Modeling that includes such spatial gradients provides the foundation for local to regional management programs.

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