Development of Vegetation Models to Predict the Potential Effect of Groundwater Withdrawals on Forested Wetlands
We developed vegetation models that, when linked to groundwater-hydrology models and landscape-level applications, can be used to predict the potential effect of groundwater-level declines on the distribution of wetland-forest communities, individual wetland species, and wetland-indicator groups. An...
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| Veröffentlicht in: | Wetlands (Wilmington, N.C.) N.C.), 2010-06, Vol.30 (3), p.489-500 |
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| container_title | Wetlands (Wilmington, N.C.) |
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| creator | Laidig, Kim J. Zampella, Robert A. Brown, Allison M. Procopio, Nicholas A. |
| description | We developed vegetation models that, when linked to groundwater-hydrology models and landscape-level applications, can be used to predict the potential effect of groundwater-level declines on the distribution of wetland-forest communities, individual wetland species, and wetland-indicator groups. An upland-to-wetland vegetation gradient, comprising 201 forest plots located in five different study basins and classified as either upland pine-oak, pitch pine lowland, pine-hardwood lowland, hardwood swamp, or cedar swamp, paralleled variations in water-level. Water levels, woody-species composition, the percentage of wetland- and upland-indicator species, and soil properties varied among the five vegetation types. Because of the functional relationship of hydrology with its correlated soil variables, hydrology represented a good proxy for the complex hydrologic-edaphic gradient associated with the upland-to-wetland vegetation gradient. Two types of vegetation models were developed to predict potential changes in vegetation associated with water-level declines. Logistic regression models predicted the probability of encountering the different vegetation types and 29 community-indicator species in relation to water level. Simple regression models predicted the relative abundance and richness of wetland-and upland-indicator species as a function of water level. |
| doi_str_mv | 10.1007/s13157-010-0063-5 |
| format | Article |
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An upland-to-wetland vegetation gradient, comprising 201 forest plots located in five different study basins and classified as either upland pine-oak, pitch pine lowland, pine-hardwood lowland, hardwood swamp, or cedar swamp, paralleled variations in water-level. Water levels, woody-species composition, the percentage of wetland- and upland-indicator species, and soil properties varied among the five vegetation types. Because of the functional relationship of hydrology with its correlated soil variables, hydrology represented a good proxy for the complex hydrologic-edaphic gradient associated with the upland-to-wetland vegetation gradient. Two types of vegetation models were developed to predict potential changes in vegetation associated with water-level declines. Logistic regression models predicted the probability of encountering the different vegetation types and 29 community-indicator species in relation to water level. Simple regression models predicted the relative abundance and richness of wetland-and upland-indicator species as a function of water level.</description><identifier>ISSN: 0277-5212</identifier><identifier>EISSN: 1943-6246</identifier><identifier>DOI: 10.1007/s13157-010-0063-5</identifier><language>eng</language><publisher>Dordrecht: Springer Netherlands</publisher><subject>Aquifers ; Basins ; Biomedical and Life Sciences ; Classification ; Coastal Sciences ; Creeks & streams ; Ecology ; Environmental Management ; Flowers & plants ; Forest communities ; Forested wetlands ; Forests ; Freshwater & Marine Ecology ; Geographical distribution ; Groundwater ; Groundwater levels ; Hardwoods ; Hydrogeology ; Hydrologic models ; Hydrology ; Indicator species ; Landscape Ecology ; Life Sciences ; Original Paper ; Pine trees ; Regression analysis ; Regression models ; Relative abundance ; Soil properties ; Soils ; Species composition ; Statistical analysis ; Swamps ; Vegetation ; Water levels ; Wetlands</subject><ispartof>Wetlands (Wilmington, N.C.), 2010-06, Vol.30 (3), p.489-500</ispartof><rights>Society of Wetland Scientists 2010</rights><rights>Society of Wetland Scientists 2010.</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c316t-40460bf305331efa7f540b8a213282c755ece955bccbc0a9946e5dcd0b3b7a53</citedby><cites>FETCH-LOGICAL-c316t-40460bf305331efa7f540b8a213282c755ece955bccbc0a9946e5dcd0b3b7a53</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://link.springer.com/content/pdf/10.1007/s13157-010-0063-5$$EPDF$$P50$$Gspringer$$H</linktopdf><linktohtml>$$Uhttps://www.proquest.com/docview/2920175563?pq-origsite=primo$$EHTML$$P50$$Gproquest$$H</linktohtml><link.rule.ids>314,776,780,21367,27901,27902,33721,41464,42533,43781,51294</link.rule.ids></links><search><creatorcontrib>Laidig, Kim J.</creatorcontrib><creatorcontrib>Zampella, Robert A.</creatorcontrib><creatorcontrib>Brown, Allison M.</creatorcontrib><creatorcontrib>Procopio, Nicholas A.</creatorcontrib><title>Development of Vegetation Models to Predict the Potential Effect of Groundwater Withdrawals on Forested Wetlands</title><title>Wetlands (Wilmington, N.C.)</title><addtitle>Wetlands</addtitle><description>We developed vegetation models that, when linked to groundwater-hydrology models and landscape-level applications, can be used to predict the potential effect of groundwater-level declines on the distribution of wetland-forest communities, individual wetland species, and wetland-indicator groups. An upland-to-wetland vegetation gradient, comprising 201 forest plots located in five different study basins and classified as either upland pine-oak, pitch pine lowland, pine-hardwood lowland, hardwood swamp, or cedar swamp, paralleled variations in water-level. Water levels, woody-species composition, the percentage of wetland- and upland-indicator species, and soil properties varied among the five vegetation types. Because of the functional relationship of hydrology with its correlated soil variables, hydrology represented a good proxy for the complex hydrologic-edaphic gradient associated with the upland-to-wetland vegetation gradient. Two types of vegetation models were developed to predict potential changes in vegetation associated with water-level declines. Logistic regression models predicted the probability of encountering the different vegetation types and 29 community-indicator species in relation to water level. Simple regression models predicted the relative abundance and richness of wetland-and upland-indicator species as a function of water level.</description><subject>Aquifers</subject><subject>Basins</subject><subject>Biomedical and Life Sciences</subject><subject>Classification</subject><subject>Coastal Sciences</subject><subject>Creeks & streams</subject><subject>Ecology</subject><subject>Environmental Management</subject><subject>Flowers & plants</subject><subject>Forest communities</subject><subject>Forested wetlands</subject><subject>Forests</subject><subject>Freshwater & Marine Ecology</subject><subject>Geographical distribution</subject><subject>Groundwater</subject><subject>Groundwater levels</subject><subject>Hardwoods</subject><subject>Hydrogeology</subject><subject>Hydrologic models</subject><subject>Hydrology</subject><subject>Indicator species</subject><subject>Landscape Ecology</subject><subject>Life Sciences</subject><subject>Original Paper</subject><subject>Pine trees</subject><subject>Regression analysis</subject><subject>Regression models</subject><subject>Relative abundance</subject><subject>Soil properties</subject><subject>Soils</subject><subject>Species composition</subject><subject>Statistical analysis</subject><subject>Swamps</subject><subject>Vegetation</subject><subject>Water levels</subject><subject>Wetlands</subject><issn>0277-5212</issn><issn>1943-6246</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2010</creationdate><recordtype>article</recordtype><sourceid>BENPR</sourceid><recordid>eNp1kLFOwzAQhi0EEqXwAGyWmANnO06aEZW2IBXRoaKj5TiXNlUaF9ul4u1xCRIT0w33f9-dfkJuGdwzgPzBM8FkngCDBCATiTwjA1akIsl4mp2TAfA8TyRn_JJceb8FYBnnbED2T_iJrd3vsAvU1vQd1xh0aGxHX22FrafB0oXDqjGBhg3ShQ0x2uiWTuoazQ80c_bQVUcd0NFVEzaV00cd0SiZWoc-YEVXGFrdVf6aXNRxhze_c0iW08ly_JzM32Yv48d5YgTLQpJCmkFZC5BCMKx1XssUypHmTPARN7mUaLCQsjSmNKCLIs1QVqaCUpS5lmJI7nrt3tmPQ3xBbe3BdfGi4gUHFgWZiCnWp4yz3jus1d41O-2-FAN16lX1varYqzr1qk5m3jM-Zrs1uj_z_9A30XF79g</recordid><startdate>20100601</startdate><enddate>20100601</enddate><creator>Laidig, Kim J.</creator><creator>Zampella, Robert A.</creator><creator>Brown, Allison M.</creator><creator>Procopio, Nicholas A.</creator><general>Springer Netherlands</general><general>Springer Nature B.V</general><scope>AAYXX</scope><scope>CITATION</scope><scope>3V.</scope><scope>7X2</scope><scope>8FE</scope><scope>8FH</scope><scope>8FK</scope><scope>AEUYN</scope><scope>AFKRA</scope><scope>ATCPS</scope><scope>AZQEC</scope><scope>BBNVY</scope><scope>BENPR</scope><scope>BHPHI</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>GNUQQ</scope><scope>HCIFZ</scope><scope>LK8</scope><scope>M0K</scope><scope>M7P</scope><scope>PATMY</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PYCSY</scope></search><sort><creationdate>20100601</creationdate><title>Development of Vegetation Models to Predict the Potential Effect of Groundwater Withdrawals on Forested Wetlands</title><author>Laidig, Kim J. ; Zampella, Robert A. ; Brown, Allison M. ; Procopio, Nicholas A.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c316t-40460bf305331efa7f540b8a213282c755ece955bccbc0a9946e5dcd0b3b7a53</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2010</creationdate><topic>Aquifers</topic><topic>Basins</topic><topic>Biomedical and Life Sciences</topic><topic>Classification</topic><topic>Coastal Sciences</topic><topic>Creeks & streams</topic><topic>Ecology</topic><topic>Environmental Management</topic><topic>Flowers & plants</topic><topic>Forest communities</topic><topic>Forested wetlands</topic><topic>Forests</topic><topic>Freshwater & Marine Ecology</topic><topic>Geographical distribution</topic><topic>Groundwater</topic><topic>Groundwater levels</topic><topic>Hardwoods</topic><topic>Hydrogeology</topic><topic>Hydrologic models</topic><topic>Hydrology</topic><topic>Indicator species</topic><topic>Landscape Ecology</topic><topic>Life Sciences</topic><topic>Original Paper</topic><topic>Pine trees</topic><topic>Regression analysis</topic><topic>Regression models</topic><topic>Relative abundance</topic><topic>Soil properties</topic><topic>Soils</topic><topic>Species composition</topic><topic>Statistical analysis</topic><topic>Swamps</topic><topic>Vegetation</topic><topic>Water levels</topic><topic>Wetlands</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Laidig, Kim J.</creatorcontrib><creatorcontrib>Zampella, Robert A.</creatorcontrib><creatorcontrib>Brown, Allison M.</creatorcontrib><creatorcontrib>Procopio, Nicholas A.</creatorcontrib><collection>CrossRef</collection><collection>ProQuest Central (Corporate)</collection><collection>Agricultural Science Collection</collection><collection>ProQuest SciTech Collection</collection><collection>ProQuest Natural Science Collection</collection><collection>ProQuest Central (Alumni) (purchase pre-March 2016)</collection><collection>ProQuest One Sustainability</collection><collection>ProQuest Central UK/Ireland</collection><collection>Agricultural & Environmental Science Collection</collection><collection>ProQuest Central Essentials</collection><collection>Biological Science Collection</collection><collection>ProQuest Central</collection><collection>Natural Science Collection</collection><collection>ProQuest One Community College</collection><collection>ProQuest Central Korea</collection><collection>ProQuest Central Student</collection><collection>SciTech Premium Collection</collection><collection>ProQuest Biological Science Collection</collection><collection>Agricultural Science Database</collection><collection>Biological Science Database</collection><collection>Environmental Science Database</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>Environmental Science Collection</collection><jtitle>Wetlands (Wilmington, N.C.)</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Laidig, Kim J.</au><au>Zampella, Robert A.</au><au>Brown, Allison M.</au><au>Procopio, Nicholas A.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Development of Vegetation Models to Predict the Potential Effect of Groundwater Withdrawals on Forested Wetlands</atitle><jtitle>Wetlands (Wilmington, N.C.)</jtitle><stitle>Wetlands</stitle><date>2010-06-01</date><risdate>2010</risdate><volume>30</volume><issue>3</issue><spage>489</spage><epage>500</epage><pages>489-500</pages><issn>0277-5212</issn><eissn>1943-6246</eissn><abstract>We developed vegetation models that, when linked to groundwater-hydrology models and landscape-level applications, can be used to predict the potential effect of groundwater-level declines on the distribution of wetland-forest communities, individual wetland species, and wetland-indicator groups. An upland-to-wetland vegetation gradient, comprising 201 forest plots located in five different study basins and classified as either upland pine-oak, pitch pine lowland, pine-hardwood lowland, hardwood swamp, or cedar swamp, paralleled variations in water-level. Water levels, woody-species composition, the percentage of wetland- and upland-indicator species, and soil properties varied among the five vegetation types. Because of the functional relationship of hydrology with its correlated soil variables, hydrology represented a good proxy for the complex hydrologic-edaphic gradient associated with the upland-to-wetland vegetation gradient. Two types of vegetation models were developed to predict potential changes in vegetation associated with water-level declines. Logistic regression models predicted the probability of encountering the different vegetation types and 29 community-indicator species in relation to water level. Simple regression models predicted the relative abundance and richness of wetland-and upland-indicator species as a function of water level.</abstract><cop>Dordrecht</cop><pub>Springer Netherlands</pub><doi>10.1007/s13157-010-0063-5</doi><tpages>12</tpages></addata></record> |
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| subjects | Aquifers Basins Biomedical and Life Sciences Classification Coastal Sciences Creeks & streams Ecology Environmental Management Flowers & plants Forest communities Forested wetlands Forests Freshwater & Marine Ecology Geographical distribution Groundwater Groundwater levels Hardwoods Hydrogeology Hydrologic models Hydrology Indicator species Landscape Ecology Life Sciences Original Paper Pine trees Regression analysis Regression models Relative abundance Soil properties Soils Species composition Statistical analysis Swamps Vegetation Water levels Wetlands |
| title | Development of Vegetation Models to Predict the Potential Effect of Groundwater Withdrawals on Forested Wetlands |
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