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 |
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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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•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 process interactions.</description><identifier>ISSN: 0301-4797</identifier><identifier>EISSN: 1095-8630</identifier><identifier>DOI: 10.1016/j.jenvman.2017.05.013</identifier><identifier>PMID: 28531796</identifier><language>eng</language><publisher>England: Elsevier Ltd</publisher><subject>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</subject><ispartof>Journal of environmental management, 2017-09, Vol.199, p.158-171</ispartof><rights>2017 Elsevier Ltd</rights><rights>Copyright © 2017 Elsevier Ltd. All rights reserved.</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c445t-c0b7a87cb1089911d99364b42a58382bdeb6ea4c563539de6a0796cb066025993</citedby><cites>FETCH-LOGICAL-c445t-c0b7a87cb1089911d99364b42a58382bdeb6ea4c563539de6a0796cb066025993</cites><orcidid>0000-0001-7851-7382</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://dx.doi.org/10.1016/j.jenvman.2017.05.013$$EHTML$$P50$$Gelsevier$$H</linktohtml><link.rule.ids>314,777,781,3537,27905,27906,45976</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/28531796$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Ajaz Ahmed, Mukhtar Ahmed</creatorcontrib><creatorcontrib>Abd-Elrahman, Amr</creatorcontrib><creatorcontrib>Escobedo, Francisco J.</creatorcontrib><creatorcontrib>Cropper, Wendell P.</creatorcontrib><creatorcontrib>Martin, Timothy A.</creatorcontrib><creatorcontrib>Timilsina, Nilesh</creatorcontrib><title>Spatially-explicit modeling of multi-scale drivers of aboveground forest biomass and water yield in watersheds of the Southeastern United States</title><title>Journal of environmental management</title><addtitle>J Environ Manage</addtitle><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 process interactions.</description><subject>Biomass</subject><subject>climate</subject><subject>Climate Change</subject><subject>data collection</subject><subject>Drivers</subject><subject>Ecoregion</subject><subject>Ecosystem</subject><subject>Ecosystem services</subject><subject>forest ecosystems</subject><subject>forest management</subject><subject>Forests</subject><subject>Geographically weighted regression</subject><subject>geostatistics</subject><subject>land cover</subject><subject>leaf area index</subject><subject>organic matter</subject><subject>rain</subject><subject>Southeastern United States</subject><subject>spatial data</subject><subject>temperature</subject><subject>Trade-offs</subject><subject>Water</subject><subject>water content</subject><subject>water supply</subject><subject>Watershed</subject><subject>watersheds</subject><subject>wetlands</subject><issn>0301-4797</issn><issn>1095-8630</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2017</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><recordid>eNqFkcFu1DAQhi0EokvhEUA-ckkYx7GTnBCqoCBV4rD0bDn2bOuVEy-2s2Xfgkeut7tw7Wk0v76ZXzM_Ie8Z1AyY_LSttzjvJz3XDbCuBlED4y_IisEgql5yeElWwIFVbTd0F-RNSlsA4A3rXpOLphecdYNckb_rnc5Oe3-o8M_OO-MynYJF7-Y7GjZ0Wnx2VTLaI7XR7TGmo6zHsMe7GJbZ0k2ImDIdXZh0SlQX6UFnjPTg0Fvq5lOb7tE-zeZ7pOuwlKJT0Wd6O7uMlq5zwdJb8mqjfcJ353pJbr99_XX1vbr5ef3j6stNZdpW5MrA2Om-MyODfhgYs8PAZTu2jRY975vR4ihRt0ZILvhgUWoo95oRpIRGFPiSfDzt3cXweykHqMklg97rGcOSVHP8Fm96xp9F2VASaHvJZEHFCTUxpBRxo3bRTToeFAN1zE1t1Tk3dcxNgVDwZPHhbLGME9r_U_-CKsDnE4DlJ3uHUSXjcDZoXUSTlQ3uGYtHwu2uNw</recordid><startdate>20170901</startdate><enddate>20170901</enddate><creator>Ajaz Ahmed, Mukhtar Ahmed</creator><creator>Abd-Elrahman, Amr</creator><creator>Escobedo, Francisco J.</creator><creator>Cropper, Wendell P.</creator><creator>Martin, Timothy A.</creator><creator>Timilsina, Nilesh</creator><general>Elsevier Ltd</general><scope>CGR</scope><scope>CUY</scope><scope>CVF</scope><scope>ECM</scope><scope>EIF</scope><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7X8</scope><scope>7S9</scope><scope>L.6</scope><orcidid>https://orcid.org/0000-0001-7851-7382</orcidid></search><sort><creationdate>20170901</creationdate><title>Spatially-explicit modeling of multi-scale drivers of aboveground forest biomass and water yield in watersheds of the Southeastern United States</title><author>Ajaz Ahmed, Mukhtar Ahmed ; Abd-Elrahman, Amr ; Escobedo, Francisco J. ; Cropper, Wendell P. ; Martin, Timothy A. ; Timilsina, Nilesh</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c445t-c0b7a87cb1089911d99364b42a58382bdeb6ea4c563539de6a0796cb066025993</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2017</creationdate><topic>Biomass</topic><topic>climate</topic><topic>Climate Change</topic><topic>data collection</topic><topic>Drivers</topic><topic>Ecoregion</topic><topic>Ecosystem</topic><topic>Ecosystem services</topic><topic>forest ecosystems</topic><topic>forest management</topic><topic>Forests</topic><topic>Geographically weighted regression</topic><topic>geostatistics</topic><topic>land cover</topic><topic>leaf area index</topic><topic>organic matter</topic><topic>rain</topic><topic>Southeastern United States</topic><topic>spatial data</topic><topic>temperature</topic><topic>Trade-offs</topic><topic>Water</topic><topic>water content</topic><topic>water supply</topic><topic>Watershed</topic><topic>watersheds</topic><topic>wetlands</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Ajaz Ahmed, Mukhtar Ahmed</creatorcontrib><creatorcontrib>Abd-Elrahman, Amr</creatorcontrib><creatorcontrib>Escobedo, Francisco J.</creatorcontrib><creatorcontrib>Cropper, Wendell P.</creatorcontrib><creatorcontrib>Martin, Timothy A.</creatorcontrib><creatorcontrib>Timilsina, Nilesh</creatorcontrib><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>MEDLINE - Academic</collection><collection>AGRICOLA</collection><collection>AGRICOLA - Academic</collection><jtitle>Journal of environmental management</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Ajaz Ahmed, Mukhtar Ahmed</au><au>Abd-Elrahman, Amr</au><au>Escobedo, Francisco J.</au><au>Cropper, Wendell P.</au><au>Martin, Timothy A.</au><au>Timilsina, Nilesh</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Spatially-explicit modeling of multi-scale drivers of aboveground forest biomass and water yield in watersheds of the Southeastern United States</atitle><jtitle>Journal of environmental management</jtitle><addtitle>J Environ Manage</addtitle><date>2017-09-01</date><risdate>2017</risdate><volume>199</volume><spage>158</spage><epage>171</epage><pages>158-171</pages><issn>0301-4797</issn><eissn>1095-8630</eissn><abstract>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 process interactions.</abstract><cop>England</cop><pub>Elsevier Ltd</pub><pmid>28531796</pmid><doi>10.1016/j.jenvman.2017.05.013</doi><tpages>14</tpages><orcidid>https://orcid.org/0000-0001-7851-7382</orcidid><oa>free_for_read</oa></addata></record> |
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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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