Spatially-explicit modeling of multi-scale drivers of aboveground forest biomass and water yield in watersheds of the Southeastern United States

Understanding ecosystem processes and the influence of regional scale drivers can provide useful information for managing forest ecosystems. Examining more local scale drivers of forest biomass and water yield can also provide insights for identifying and better understanding the effects of climate...

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Veröffentlicht in:Journal of environmental management 2017-09, Vol.199, p.158-171
Hauptverfasser: Ajaz Ahmed, Mukhtar Ahmed, Abd-Elrahman, Amr, Escobedo, Francisco J., Cropper, Wendell P., Martin, Timothy A., Timilsina, Nilesh
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container_issue
container_start_page 158
container_title Journal of environmental management
container_volume 199
creator Ajaz Ahmed, Mukhtar Ahmed
Abd-Elrahman, Amr
Escobedo, Francisco J.
Cropper, Wendell P.
Martin, Timothy A.
Timilsina, Nilesh
description Understanding ecosystem processes and the influence of regional scale drivers can provide useful information for managing forest ecosystems. Examining more local scale drivers of forest biomass and water yield can also provide insights for identifying and better understanding the effects of climate change and management on forests. We used diverse multi-scale datasets, functional models and Geographically Weighted Regression (GWR) to model ecosystem processes at the watershed scale and to interpret the influence of ecological drivers across the Southeastern United States (SE US). Aboveground forest biomass (AGB) was determined from available geospatial datasets and water yield was estimated using the Water Supply and Stress Index (WaSSI) model at the watershed level. Our geostatistical model examined the spatial variation in these relationships between ecosystem processes, climate, biophysical, and forest management variables at the watershed level across the SE US. Ecological and management drivers at the watershed level were analyzed locally to identify whether drivers contribute positively or negatively to aboveground forest biomass and water yield ecosystem processes and thus identifying potential synergies and tradeoffs across the SE US region. Although AGB and water yield drivers varied geographically across the study area, they were generally significantly influenced by climate (rainfall and temperature), land-cover factor1 (Water and barren), land-cover factor2 (wetland and forest), organic matter content high, rock depth, available water content, stand age, elevation, and LAI drivers. These drivers were positively or negatively associated with biomass or water yield which significantly contributes to ecosystem interactions or tradeoff/synergies. Our study introduced a spatially-explicit modelling framework to analyze the effect of ecosystem drivers on forest ecosystem structure, function and provision of services. This integrated model approach facilitates multi-scale analyses of drivers and interactions at the local to regional scale. •Functional and geostatistical models integrated using multi-scale datasets.•Framework was used to model drivers of water yield and biomass at the watershed level.•Geographically Weighted Regression used to spatially analyze processes across the SE US.•Ecological and management drivers of ecosystem processes were identified at watershed level.•Positive/negative correlations were mapped to identify local ecosystem pr
doi_str_mv 10.1016/j.jenvman.2017.05.013
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source MEDLINE; Elsevier ScienceDirect Journals
subjects Biomass
climate
Climate Change
data collection
Drivers
Ecoregion
Ecosystem
Ecosystem services
forest ecosystems
forest management
Forests
Geographically weighted regression
geostatistics
land cover
leaf area index
organic matter
rain
Southeastern United States
spatial data
temperature
Trade-offs
Water
water content
water supply
Watershed
watersheds
wetlands
title Spatially-explicit modeling of multi-scale drivers of aboveground forest biomass and water yield in watersheds of the Southeastern United States
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