Predictive modeling of spatial patterns of soil nutrients related to fertility islands
In arid shrublands, soil resources are patchily distributed around shrub canopies, forming well-studied “islands of fertility.” While soil nutrient patterns have previously been characterized quantitatively, we develop a predictive model that explicitly considers the distance from shrubs of varying...
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Veröffentlicht in: | Landscape ecology 2014-03, Vol.29 (3), p.491-505 |
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description | In arid shrublands, soil resources are patchily distributed around shrub canopies, forming well-studied “islands of fertility.” While soil nutrient patterns have previously been characterized quantitatively, we develop a predictive model that explicitly considers the distance from shrubs of varying canopy sizes. In 1-ha macroplots in both the Sonoran and Mojave Deserts, we used Plant Root Simulator™ probes to measure nutrient availability along transects extending north and south from creosote bushes (Larrea tridentata). We modeled the decline of nutrients with distance from focal shrubs using hierarchical mixed models that included the effects of transect direction and shrub canopy size. Of the nutrients considered, nitrogen and potassium had the strongest response to distance from focal shrubs. In the Sonora, both depended on canopy size and had different patterns to the north versus the south. In the Mojave, potassium depended on size and direction, but nitrogen only on canopy size. We used the fitted model equations and the location and canopy size of all Larrea shrubs within the macroplots to estimate nutrient concentrations at a 20 cm resolution. This produced maps showing nutrient “hotspots” centered on Larrea. Our models predicted up to 60 % of the variation in nutrient availability the following growing season. Our models efficiently used a moderate number of sample locations to predict nutrient concentrations over a large area, given easily measured values of shrub size and location. Our method can be applied to many systems with patchily distributed resources focused around major structural landscape features. |
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Our models predicted up to 60 % of the variation in nutrient availability the following growing season. Our models efficiently used a moderate number of sample locations to predict nutrient concentrations over a large area, given easily measured values of shrub size and location. Our method can be applied to many systems with patchily distributed resources focused around major structural landscape features.</description><identifier>ISSN: 0921-2973</identifier><identifier>EISSN: 1572-9761</identifier><identifier>DOI: 10.1007/s10980-013-9979-5</identifier><language>eng</language><publisher>Dordrecht: Springer-Verlag</publisher><subject>Animal, plant and microbial ecology ; Applied ecology ; Biological and medical sciences ; Biomedical and Life Sciences ; Canopies ; canopy ; creosote ; Desert plants ; deserts ; Ecology ; Environmental Management ; Fertility ; Fundamental and applied biological sciences. Psychology ; General aspects ; General aspects. 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In 1-ha macroplots in both the Sonoran and Mojave Deserts, we used Plant Root Simulator™ probes to measure nutrient availability along transects extending north and south from creosote bushes (Larrea tridentata). We modeled the decline of nutrients with distance from focal shrubs using hierarchical mixed models that included the effects of transect direction and shrub canopy size. Of the nutrients considered, nitrogen and potassium had the strongest response to distance from focal shrubs. In the Sonora, both depended on canopy size and had different patterns to the north versus the south. In the Mojave, potassium depended on size and direction, but nitrogen only on canopy size. We used the fitted model equations and the location and canopy size of all Larrea shrubs within the macroplots to estimate nutrient concentrations at a 20 cm resolution. This produced maps showing nutrient “hotspots” centered on Larrea. Our models predicted up to 60 % of the variation in nutrient availability the following growing season. Our models efficiently used a moderate number of sample locations to predict nutrient concentrations over a large area, given easily measured values of shrub size and location. Our method can be applied to many systems with patchily distributed resources focused around major structural landscape features.</description><subject>Animal, plant and microbial ecology</subject><subject>Applied ecology</subject><subject>Biological and medical sciences</subject><subject>Biomedical and Life Sciences</subject><subject>Canopies</subject><subject>canopy</subject><subject>creosote</subject><subject>Desert plants</subject><subject>deserts</subject><subject>Ecology</subject><subject>Environmental Management</subject><subject>Fertility</subject><subject>Fundamental and applied biological sciences. Psychology</subject><subject>General aspects</subject><subject>General aspects. Techniques</subject><subject>Growing season</subject><subject>Islands</subject><subject>Landscape Ecology</subject><subject>Landscape/Regional and Urban Planning</subject><subject>Larrea</subject><subject>Larrea tridentata</subject><subject>Life Sciences</subject><subject>Methods and techniques (sampling, tagging, trapping, modelling...)</subject><subject>Nature Conservation</subject><subject>Nitrogen</subject><subject>Nutrient availability</subject><subject>Nutrient concentrations</subject><subject>nutrient content</subject><subject>Nutrients</subject><subject>Plant ecology</subject><subject>potassium</subject><subject>Prediction models</subject><subject>Research Article</subject><subject>shrublands</subject><subject>Shrubs</subject><subject>Soil fertility</subject><subject>Soil nutrients</subject><subject>soil resources</subject><subject>Sustainable Development</subject><subject>Terrestrial ecosystems</subject><issn>0921-2973</issn><issn>1572-9761</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2014</creationdate><recordtype>article</recordtype><sourceid>BENPR</sourceid><recordid>eNp9kc1rVDEUxYNYcKz-Aa4MiODm2ZuveclSSq1CwUI_tiHzcjOkZF7GJCP0vzfTV0RcuLpw7-8cTk4IecfgMwMYzyoDo2EAJgZjRjOoF2TF1MgHM67ZS7ICw9nAzShekde1PgCAEAArcn9d0MepxV9Id9ljivOW5kDr3rXoEu2jYZnr0y7HROdDKxHnVmnB5Bp62jINWFpMsT3SWJObfX1DToJLFd8-z1Ny9_Xi9vzbcPXj8vv5l6thkiDasGFSwtoZzTdBI4QgfUBAdF6h9Mpt9ARGiE0wclKGBeMdSDZydEZ6359wSj4tvvuSfx6wNruLdcLUQ2A-VMuUkJprwaGjH_5BH_KhzD1dp4ApqbQYO8UWaiq51oLB7kvcufJoGdhj03Zp2vam7bFpq7rm47Ozq5NLobh5ivWPkGtl1mw8cnzhaj_NWyx_JfiP-ftFFFy2blu68d0NByb7F2oFhonfBeSX5Q</recordid><startdate>20140301</startdate><enddate>20140301</enddate><creator>Mudrak, Erika L</creator><creator>Schafer, Jennifer L</creator><creator>Fuentes-Ramirez, Andres</creator><creator>Holzapfel, Claus</creator><creator>Moloney, Kirk A</creator><general>Springer-Verlag</general><general>Springer Netherlands</general><general>Springer</general><general>Springer Nature B.V</general><scope>FBQ</scope><scope>IQODW</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>3V.</scope><scope>7SN</scope><scope>7ST</scope><scope>7XB</scope><scope>88I</scope><scope>8FE</scope><scope>8FH</scope><scope>8FK</scope><scope>ABUWG</scope><scope>AEUYN</scope><scope>AFKRA</scope><scope>ATCPS</scope><scope>AZQEC</scope><scope>BBNVY</scope><scope>BENPR</scope><scope>BHPHI</scope><scope>BKSAR</scope><scope>C1K</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>GNUQQ</scope><scope>HCIFZ</scope><scope>LK8</scope><scope>M2P</scope><scope>M7P</scope><scope>PATMY</scope><scope>PCBAR</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PYCSY</scope><scope>Q9U</scope><scope>SOI</scope></search><sort><creationdate>20140301</creationdate><title>Predictive modeling of spatial patterns of soil nutrients related to fertility islands</title><author>Mudrak, Erika L ; Schafer, Jennifer L ; Fuentes-Ramirez, Andres ; Holzapfel, Claus ; Moloney, Kirk A</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c403t-b14406a982bf8e0ff4dfe0eead5e4d5ab8c0933bf94c591f9da04172ea94dd033</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2014</creationdate><topic>Animal, plant and microbial ecology</topic><topic>Applied ecology</topic><topic>Biological and medical sciences</topic><topic>Biomedical and Life Sciences</topic><topic>Canopies</topic><topic>canopy</topic><topic>creosote</topic><topic>Desert plants</topic><topic>deserts</topic><topic>Ecology</topic><topic>Environmental Management</topic><topic>Fertility</topic><topic>Fundamental and applied biological sciences. Psychology</topic><topic>General aspects</topic><topic>General aspects. Techniques</topic><topic>Growing season</topic><topic>Islands</topic><topic>Landscape Ecology</topic><topic>Landscape/Regional and Urban Planning</topic><topic>Larrea</topic><topic>Larrea tridentata</topic><topic>Life Sciences</topic><topic>Methods and techniques (sampling, tagging, trapping, modelling...)</topic><topic>Nature Conservation</topic><topic>Nitrogen</topic><topic>Nutrient availability</topic><topic>Nutrient concentrations</topic><topic>nutrient content</topic><topic>Nutrients</topic><topic>Plant ecology</topic><topic>potassium</topic><topic>Prediction models</topic><topic>Research Article</topic><topic>shrublands</topic><topic>Shrubs</topic><topic>Soil fertility</topic><topic>Soil nutrients</topic><topic>soil resources</topic><topic>Sustainable Development</topic><topic>Terrestrial ecosystems</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Mudrak, Erika L</creatorcontrib><creatorcontrib>Schafer, Jennifer L</creatorcontrib><creatorcontrib>Fuentes-Ramirez, Andres</creatorcontrib><creatorcontrib>Holzapfel, Claus</creatorcontrib><creatorcontrib>Moloney, Kirk A</creatorcontrib><collection>AGRIS</collection><collection>Pascal-Francis</collection><collection>CrossRef</collection><collection>ProQuest Central (Corporate)</collection><collection>Ecology Abstracts</collection><collection>Environment Abstracts</collection><collection>ProQuest Central (purchase pre-March 2016)</collection><collection>Science Database (Alumni Edition)</collection><collection>ProQuest SciTech Collection</collection><collection>ProQuest Natural Science Collection</collection><collection>ProQuest Central (Alumni) (purchase pre-March 2016)</collection><collection>ProQuest Central (Alumni Edition)</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>Earth, Atmospheric & Aquatic Science Collection</collection><collection>Environmental Sciences and Pollution Management</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>Science Database</collection><collection>Biological Science Database</collection><collection>Environmental Science Database</collection><collection>Earth, Atmospheric & Aquatic 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><collection>ProQuest Central Basic</collection><collection>Environment Abstracts</collection><jtitle>Landscape ecology</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Mudrak, Erika L</au><au>Schafer, Jennifer L</au><au>Fuentes-Ramirez, Andres</au><au>Holzapfel, Claus</au><au>Moloney, Kirk A</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Predictive modeling of spatial patterns of soil nutrients related to fertility islands</atitle><jtitle>Landscape ecology</jtitle><stitle>Landscape Ecol</stitle><date>2014-03-01</date><risdate>2014</risdate><volume>29</volume><issue>3</issue><spage>491</spage><epage>505</epage><pages>491-505</pages><issn>0921-2973</issn><eissn>1572-9761</eissn><abstract>In arid shrublands, soil resources are patchily distributed around shrub canopies, forming well-studied “islands of fertility.” While soil nutrient patterns have previously been characterized quantitatively, we develop a predictive model that explicitly considers the distance from shrubs of varying canopy sizes. In 1-ha macroplots in both the Sonoran and Mojave Deserts, we used Plant Root Simulator™ probes to measure nutrient availability along transects extending north and south from creosote bushes (Larrea tridentata). We modeled the decline of nutrients with distance from focal shrubs using hierarchical mixed models that included the effects of transect direction and shrub canopy size. Of the nutrients considered, nitrogen and potassium had the strongest response to distance from focal shrubs. In the Sonora, both depended on canopy size and had different patterns to the north versus the south. In the Mojave, potassium depended on size and direction, but nitrogen only on canopy size. We used the fitted model equations and the location and canopy size of all Larrea shrubs within the macroplots to estimate nutrient concentrations at a 20 cm resolution. This produced maps showing nutrient “hotspots” centered on Larrea. Our models predicted up to 60 % of the variation in nutrient availability the following growing season. Our models efficiently used a moderate number of sample locations to predict nutrient concentrations over a large area, given easily measured values of shrub size and location. Our method can be applied to many systems with patchily distributed resources focused around major structural landscape features.</abstract><cop>Dordrecht</cop><pub>Springer-Verlag</pub><doi>10.1007/s10980-013-9979-5</doi><tpages>15</tpages></addata></record> |
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subjects | Animal, plant and microbial ecology Applied ecology Biological and medical sciences Biomedical and Life Sciences Canopies canopy creosote Desert plants deserts Ecology Environmental Management Fertility Fundamental and applied biological sciences. Psychology General aspects General aspects. Techniques Growing season Islands Landscape Ecology Landscape/Regional and Urban Planning Larrea Larrea tridentata Life Sciences Methods and techniques (sampling, tagging, trapping, modelling...) Nature Conservation Nitrogen Nutrient availability Nutrient concentrations nutrient content Nutrients Plant ecology potassium Prediction models Research Article shrublands Shrubs Soil fertility Soil nutrients soil resources Sustainable Development Terrestrial ecosystems |
title | Predictive modeling of spatial patterns of soil nutrients related to fertility islands |
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