Filling in the gaps: modelling native species richness and invasions using spatially incomplete data
Identifieur interne : 000835 ( Istex/Corpus ); précédent : 000834; suivant : 000836Filling in the gaps: modelling native species richness and invasions using spatially incomplete data
Auteurs : Catherine S. Jarnevich ; Thomas J. Stohlgren ; David Barnett ; John KarteszSource :
- Diversity and Distributions [ 1366-9516 ] ; 2006-09.
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Abstract
Detailed knowledge of patterns of native species richness, an important component of biodiversity, and non‐native species invasions is often lacking even though this knowledge is essential to conservation efforts. However, we cannot afford to wait for complete information on the distribution and abundance of native and harmful invasive species. Using information from counties well surveyed for plants across the USA, we developed models to fill data gaps in poorly surveyed areas by estimating the density (number of species km−2) of native and non‐native plant species. Here, we show that native plant species density is non‐random, predictable, and is the best predictor of non‐native plant species density. We found that eastern agricultural sites and coastal areas are among the most invaded in terms of non‐native plant species densities, and that the central USA appears to have the greatest ratio of non‐native to native species. These large‐scale models could also be applied to smaller spatial scales or other taxa to set priorities for conservation and invasion mitigation, prevention, and control efforts.
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DOI: 10.1111/j.1366-9516.2006.00278.x
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ISTEX:7861394A15C027749576696DDAE9F086CB69357FLe document en format XML
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Jarnevich <i>et al.</i></title><title type="short">Filling gaps</title></titleGroup><creators><creator creatorRole="author" xml:id="cr1" affiliationRef="#a1" corresponding="yes"><personName><givenNames>Catherine S.</givenNames><familyName>Jarnevich</familyName></personName></creator><creator creatorRole="author" xml:id="cr2" affiliationRef="#a1"><personName><givenNames>Thomas J.</givenNames><familyName>Stohlgren</familyName></personName></creator><creator creatorRole="author" xml:id="cr3" affiliationRef="#a2"><personName><givenNames>David</givenNames><familyName>Barnett</familyName></personName></creator><creator creatorRole="author" xml:id="cr4" affiliationRef="#a3"><personName><givenNames>John</givenNames><familyName>Kartesz</familyName></personName></creator></creators><affiliationGroup><affiliation xml:id="a1" countryCode="US"><unparsedAffiliation>Fort Collins Science Center, US Geological Survey, 2150 Centre Ave Bldg C, Fort Collins, Colorado 80526, USA,</unparsedAffiliation></affiliation><affiliation xml:id="a2" countryCode="US"><unparsedAffiliation>Natural Resource Ecology Laboratory, Colorado State University, Fort Collins, Colorado 80523, USA and</unparsedAffiliation></affiliation><affiliation xml:id="a3" countryCode="US"><unparsedAffiliation>Biota of North America Program, University of North Carolina, Chapel Hill, North Carolina 27599, USA</unparsedAffiliation></affiliation></affiliationGroup><keywordGroup xml:lang="en"><keyword xml:id="k1">biodiversity</keyword><keyword xml:id="k2">biological invasions</keyword><keyword xml:id="k3">modelling</keyword><keyword xml:id="k4">non‐native</keyword><keyword xml:id="k5">prediction.</keyword></keywordGroup><abstractGroup><abstract type="main" xml:lang="en"><title type="main">ABSTRACT</title><p>Detailed knowledge of patterns of native species richness, an important component of biodiversity, and non‐native species invasions is often lacking even though this knowledge is essential to conservation efforts. However, we cannot afford to wait for complete information on the distribution and abundance of native and harmful invasive species. Using information from counties well surveyed for plants across the USA, we developed models to fill data gaps in poorly surveyed areas by estimating the density (number of species km<sup>−2</sup>) of native and non‐native plant species. Here, we show that native plant species density is non‐random, predictable, and is the best predictor of non‐native plant species density. We found that eastern agricultural sites and coastal areas are among the most invaded in terms of non‐native plant species densities, and that the central USA appears to have the greatest ratio of non‐native to native species. 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However, we cannot afford to wait for complete information on the distribution and abundance of native and harmful invasive species. Using information from counties well surveyed for plants across the USA, we developed models to fill data gaps in poorly surveyed areas by estimating the density (number of species km−2) of native and non‐native plant species. Here, we show that native plant species density is non‐random, predictable, and is the best predictor of non‐native plant species density. We found that eastern agricultural sites and coastal areas are among the most invaded in terms of non‐native plant species densities, and that the central USA appears to have the greatest ratio of non‐native to native species. These large‐scale models could also be applied to smaller spatial scales or other taxa to set priorities for conservation and invasion mitigation, prevention, and control efforts.</abstract><subject lang="en"><genre>keywords</genre><topic>biodiversity</topic><topic>biological invasions</topic><topic>modelling</topic><topic>non‐native</topic><topic>prediction.</topic></subject><relatedItem type="host"><titleInfo><title>Diversity and Distributions</title></titleInfo><genre type="journal">journal</genre><identifier type="ISSN">1366-9516</identifier><identifier type="eISSN">1472-4642</identifier><identifier type="DOI">10.1111/(ISSN)1472-4642</identifier><identifier type="PublisherID">DDI</identifier><part><date>2006</date><detail type="volume"><caption>vol.</caption><number>12</number></detail><detail type="issue"><caption>no.</caption><number>5</number></detail><extent unit="pages"><start>511</start><end>520</end><total>10</total></extent></part></relatedItem><identifier type="istex">7861394A15C027749576696DDAE9F086CB69357F</identifier><identifier type="DOI">10.1111/j.1366-9516.2006.00278.x</identifier><identifier type="ArticleID">DDI278</identifier><recordInfo><recordContentSource>WILEY</recordContentSource><recordOrigin>Blackwell Publishing Ltd</recordOrigin></recordInfo></mods></metadata><serie></serie></istex></record>Pour manipuler ce document sous Unix (Dilib)
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