4.7 Article Proceedings Paper

Modeling water and ion fluxes in a highly structured, mixed-species stand

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FOREST ECOLOGY AND MANAGEMENT
卷 143, 期 1-3, 页码 27-37

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DOI: 10.1016/S0378-1127(00)00522-3

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modeling; spatial variability; mixed-species stand; nitrogen; water yield; watershed

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In the Convent Forest case study, the measuring plots were stratified by the following first- and second-order structure units. First-order structures were classified as treefall gaps, regeneration areas, and closed stand areas, whereas second-order structures were defined by tree species and the density of the crown layer. The measurements were taken in an experimental watershed (9.3 ha) in a mixed-species stand consisting of European beech (Fagus sylvatica L.), silver fir (Abies alba Mill.) and Norway spruce (Picea abies (L.) Karst.). Water fluxes were simulated by the one-dimensional Darcy model WHNSIM. The output was composed by the area-weighted sum of fluxes referring to the structural units. By this 'structural approach', we were able to demonstrate the spatial heterogeneity of canopy structures and tree species that cause a fine-scale patchwork of differing water and nutrient budgets. The different flux rates in the selected structural units were proved by statistical tools. The data generated with WHNSIM provided good estimates of soil-water fluxes that could then be linked with lysimeter concentration data. Evapotranspiration (ET) levels were within the range of values expected for this specific forest type. Crown density related ET differences appeared well-characterized. The simulation of the ecosystem output and its temporal structure can be improved by the following 'structured' modeling method: (1) dividing the ecosystem into representative structural units, (2) modeling these strata separately, and (3) putting the results together like a puzzle at the output end. Averaging the primary measured data resulted in a less sensitive shape of simulated streamflows. The results emphasize the importance of structural information for the recognition and prognostication of processes on the ecosystem level in forest stands. (C) 2001 Elsevier Science B.V. All rights reserved.

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