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Anthropogenic disturbance and streams: land use and land‐use change affect stream ecosystems via multiple pathways

Identifieur interne : 000F26 ( Istex/Corpus ); précédent : 000F25; suivant : 000F27

Anthropogenic disturbance and streams: land use and land‐use change affect stream ecosystems via multiple pathways

Auteurs : Kelly O. Maloney ; Donald E. Weller

Source :

RBID : ISTEX:833E9CB5A48F69C1E1355DAD55A0EF13F31A69C7

English descriptors

Abstract

1. Ecosystems are strongly influenced by land use practices. However, identifying the mechanisms behind these influences is complicated by the many potential pathways (often indirect) between land use and ecosystems and by the long‐lasting effects of past land use. To support ecosystem restoration and conservation efforts, we need to better understand these indirect and lasting effects. 2. We constructed structural equation models (SEM) to evaluate the direct and indirect effects of contemporary (2002) land use (agriculture and development) and change in land use from 1952 to 2002 on present‐day streams (n = 190) in Maryland, U.S.A. Additional variables examined included site location, system size, altitude, per cent sand in soils, riparian condition, habitat quality, stream water NO3‐N and benthic macroinvertebrate and fish measures of stream condition. Our first SEM (2002 Land Use) included the proportions of contemporary agriculture and development in catchments in the model. The second SEM (Land Use Change) included five measures of land use change (proportion agricultural in both times, developed in both times, agricultural in 1952 and developed in 2002, forested in 1952 and developed in 2002 and agricultural in 1952 and forested in 2002). 3. The data set fit both SEMs well. The 2002 Land Use model explained 71% of variation in NO3‐N and 55%, 42% and 38% of variation in riffle quality, macroinvertebrate condition and fish condition, respectively. The Land Use Change model explained similar amounts of variation in NO3‐N (R2 = 0.72), riffle quality (R2 = 0.57) and macroinvertebrate condition (R2 = 0.44) but slightly more variation in fish condition (R2 = 0.43). 4. Both models identified pathways through which landscape variables affect stream responses, including negative direct effects of latitude on macroinvertebrate and fish conditions and positive direct and indirect effects of altitude on NO3‐N, riffle quality and macroinvertebrate and fish conditions. The 2002 Land Use model showed contemporary development and agriculture had positive total effects on NO3‐N (both through direct pathways); contemporary development had negative effects on macroinvertebrate condition. The Land Use Change model showed that contemporary developed land that was forested in 1952 had no effects on NO3‐N; current developed land that was developed or agricultural in 1952 showed positive effects on NO3‐N. Forests that were agricultural in 1952 had negative effects on NO3‐N, suggesting reduced NO3‐N export with reforestation. The Land Use Change model also showed negative total effects of all types of contemporary developed land (developed, agricultural or forested in 1952) on benthic condition. Developed land that was forested in 1952 had negative effects on fish condition. Forest sites that were agricultural in 1952 had negative effects on fish and macroinvertebrate conditions, suggesting a long‐term imprint of abandoned agriculture in stream communities. 5. Our analyses (i) identified multiple indirect effects of contemporary land use on streams, (ii) showed that current land uses with different land use histories can exhibit different effects on streams and (iii) demonstrated an imprint of land use lasting >50 years. Knowledge of these indirect and long‐term effects of land use will help to conserve and restore streams.

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DOI: 10.1111/j.1365-2427.2010.02522.x

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ISTEX:833E9CB5A48F69C1E1355DAD55A0EF13F31A69C7

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<personName>
<givenNames>KELLY O.</givenNames>
<familyName>MALONEY</familyName>
</personName>
</creator>
<creator creatorRole="author" xml:id="cr2" affiliationRef="#aff-1-1">
<personName>
<givenNames>DONALD E.</givenNames>
<familyName>WELLER</familyName>
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<unparsedAffiliation>Smithsonian Environmental Research Center (SERC), Edgewater, MD, U.S.A.</unparsedAffiliation>
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<keywordGroup xml:lang="en">
<keyword xml:id="k1">benthic macroinvertebrates</keyword>
<keyword xml:id="k2">land use legacy</keyword>
<keyword xml:id="k3">past land use</keyword>
<keyword xml:id="k4">stream water chemistry</keyword>
<keyword xml:id="k5">structural equation modelling (SEM)</keyword>
</keywordGroup>
<supportingInformation>
<p>
<b>Table S1.</b>
Pearson correlation coefficients between land uses.</p>
<p>
<b>Table S2.</b>
Summary statistics for available variables.</p>
<p>
<b>Table S3.</b>
List of individual metrics used in multi‐metric indices of integrity.</p>
<p>
<b>Table S4.</b>
Structural equation model output from the 2002 Land Use model. ***
<i></i>
< 0.001.</p>
<p>
<b>Table S5.</b>
Structural equation model output from the Land Use Change model. ***
<i>P</i>
 < 0.001.</p>
<p>As a service to our authors and readers, this journal provides supporting information supplied by the authors. Such materials are peer‐reviewed and may be re‐organized for online delivery, but are not copy‐edited or typeset. Technical support issues arising from supporting information (other than missing files) should be addressed to the authors.</p>
<supportingInfoItem>
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<abstract type="main" xml:lang="en">
<title type="main">Summary</title>
<p>1. Ecosystems are strongly influenced by land use practices. However, identifying the mechanisms behind these influences is complicated by the many potential pathways (often indirect) between land use and ecosystems and by the long‐lasting effects of past land use. To support ecosystem restoration and conservation efforts, we need to better understand these indirect and lasting effects.</p>
<p>2. We constructed structural equation models (SEM) to evaluate the direct and indirect effects of contemporary (2002) land use (agriculture and development) and change in land use from 1952 to 2002 on present‐day streams (
<i>n</i>
 = 190) in Maryland, U.S.A. Additional variables examined included site location, system size, altitude, per cent sand in soils, riparian condition, habitat quality, stream water NO
<sub>3</sub>
‐N and benthic macroinvertebrate and fish measures of stream condition. Our first SEM (2002 Land Use) included the proportions of contemporary agriculture and development in catchments in the model. The second SEM (Land Use Change) included five measures of land use change (proportion agricultural in both times, developed in both times, agricultural in 1952 and developed in 2002, forested in 1952 and developed in 2002 and agricultural in 1952 and forested in 2002).</p>
<p>3. The data set fit both SEMs well. The 2002 Land Use model explained 71% of variation in NO
<sub>3</sub>
‐N and 55%, 42% and 38% of variation in riffle quality, macroinvertebrate condition and fish condition, respectively. The Land Use Change model explained similar amounts of variation in NO
<sub>3</sub>
‐N (
<i>R</i>
<sup>2</sup>
 = 0.72), riffle quality (
<i>R</i>
<sup>2</sup>
 = 0.57) and macroinvertebrate condition (
<i>R</i>
<sup>2</sup>
 = 0.44) but slightly more variation in fish condition (
<i>R</i>
<sup>2</sup>
 = 0.43).</p>
<p>4. Both models identified pathways through which landscape variables affect stream responses, including negative direct effects of latitude on macroinvertebrate and fish conditions and positive direct and indirect effects of altitude on NO
<sub>3</sub>
‐N, riffle quality and macroinvertebrate and fish conditions. The 2002 Land Use model showed contemporary development and agriculture had positive total effects on NO
<sub>3</sub>
‐N (both through direct pathways); contemporary development had negative effects on macroinvertebrate condition. The Land Use Change model showed that contemporary developed land that was forested in 1952 had no effects on NO
<sub>3</sub>
‐N; current developed land that was developed or agricultural in 1952 showed positive effects on NO
<sub>3</sub>
‐N. Forests that were agricultural in 1952 had negative effects on NO
<sub>3</sub>
‐N, suggesting reduced NO
<sub>3</sub>
‐N export with reforestation. The Land Use Change model also showed negative total effects of all types of contemporary developed land (developed, agricultural or forested in 1952) on benthic condition. Developed land that was forested in 1952 had negative effects on fish condition. Forest sites that were agricultural in 1952 had negative effects on fish and macroinvertebrate conditions, suggesting a long‐term imprint of abandoned agriculture in stream communities.</p>
<p>5. Our analyses (i) identified multiple indirect effects of contemporary land use on streams, (ii) showed that current land uses with different land use histories can exhibit different effects on streams and (iii) demonstrated an imprint of land use lasting >50 years. Knowledge of these indirect and long‐term effects of land use will help to conserve and restore streams.</p>
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<title>Anthropogenic disturbance and streams: land use and land‐use change affect stream ecosystems via multiple pathways</title>
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<titleInfo type="abbreviated" lang="en">
<title>Land use affects streams via multiple pathways</title>
</titleInfo>
<titleInfo type="alternative" contentType="CDATA" lang="en">
<title>Anthropogenic disturbance and streams: land use and land‐use change affect stream ecosystems via multiple pathways</title>
</titleInfo>
<name type="personal">
<namePart type="given">KELLY O.</namePart>
<namePart type="family">MALONEY</namePart>
<affiliation>Smithsonian Environmental Research Center (SERC), Edgewater, MD, U.S.A.</affiliation>
<role>
<roleTerm type="text">author</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">DONALD E.</namePart>
<namePart type="family">WELLER</namePart>
<affiliation>Smithsonian Environmental Research Center (SERC), Edgewater, MD, U.S.A.</affiliation>
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<dateIssued encoding="w3cdtf">2011-03</dateIssued>
<edition>(Manuscript accepted 3 October 2010)</edition>
<copyrightDate encoding="w3cdtf">2011</copyrightDate>
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<abstract lang="en">1. Ecosystems are strongly influenced by land use practices. However, identifying the mechanisms behind these influences is complicated by the many potential pathways (often indirect) between land use and ecosystems and by the long‐lasting effects of past land use. To support ecosystem restoration and conservation efforts, we need to better understand these indirect and lasting effects. 2. We constructed structural equation models (SEM) to evaluate the direct and indirect effects of contemporary (2002) land use (agriculture and development) and change in land use from 1952 to 2002 on present‐day streams (n = 190) in Maryland, U.S.A. Additional variables examined included site location, system size, altitude, per cent sand in soils, riparian condition, habitat quality, stream water NO3‐N and benthic macroinvertebrate and fish measures of stream condition. Our first SEM (2002 Land Use) included the proportions of contemporary agriculture and development in catchments in the model. The second SEM (Land Use Change) included five measures of land use change (proportion agricultural in both times, developed in both times, agricultural in 1952 and developed in 2002, forested in 1952 and developed in 2002 and agricultural in 1952 and forested in 2002). 3. The data set fit both SEMs well. The 2002 Land Use model explained 71% of variation in NO3‐N and 55%, 42% and 38% of variation in riffle quality, macroinvertebrate condition and fish condition, respectively. The Land Use Change model explained similar amounts of variation in NO3‐N (R2 = 0.72), riffle quality (R2 = 0.57) and macroinvertebrate condition (R2 = 0.44) but slightly more variation in fish condition (R2 = 0.43). 4. Both models identified pathways through which landscape variables affect stream responses, including negative direct effects of latitude on macroinvertebrate and fish conditions and positive direct and indirect effects of altitude on NO3‐N, riffle quality and macroinvertebrate and fish conditions. The 2002 Land Use model showed contemporary development and agriculture had positive total effects on NO3‐N (both through direct pathways); contemporary development had negative effects on macroinvertebrate condition. The Land Use Change model showed that contemporary developed land that was forested in 1952 had no effects on NO3‐N; current developed land that was developed or agricultural in 1952 showed positive effects on NO3‐N. Forests that were agricultural in 1952 had negative effects on NO3‐N, suggesting reduced NO3‐N export with reforestation. The Land Use Change model also showed negative total effects of all types of contemporary developed land (developed, agricultural or forested in 1952) on benthic condition. Developed land that was forested in 1952 had negative effects on fish condition. Forest sites that were agricultural in 1952 had negative effects on fish and macroinvertebrate conditions, suggesting a long‐term imprint of abandoned agriculture in stream communities. 5. Our analyses (i) identified multiple indirect effects of contemporary land use on streams, (ii) showed that current land uses with different land use histories can exhibit different effects on streams and (iii) demonstrated an imprint of land use lasting >50 years. Knowledge of these indirect and long‐term effects of land use will help to conserve and restore streams.</abstract>
<subject lang="en">
<genre>keywords</genre>
<topic>benthic macroinvertebrates</topic>
<topic>land use legacy</topic>
<topic>past land use</topic>
<topic>stream water chemistry</topic>
<topic>structural equation modelling (SEM)</topic>
</subject>
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<title>Freshwater Biology</title>
</titleInfo>
<genre type="journal">journal</genre>
<note type="content"> Table S1. Pearson correlation coefficients between land uses. Table S2. Summary statistics for available variables. Table S3. List of individual metrics used in multi‐metric indices of integrity. Table S4. Structural equation model output from the 2002 Land Use model. ***P < 0.001. Table S5. Structural equation model output from the Land Use Change model. ***P < 0.001. As a service to our authors and readers, this journal provides supporting information supplied by the authors. Such materials are peer‐reviewed and may be re‐organized for online delivery, but are not copy‐edited or typeset. Technical support issues arising from supporting information (other than missing files) should be addressed to the authors. Table S1. Pearson correlation coefficients between land uses. Table S2. Summary statistics for available variables. Table S3. List of individual metrics used in multi‐metric indices of integrity. Table S4. Structural equation model output from the 2002 Land Use model. ***P < 0.001. Table S5. Structural equation model output from the Land Use Change model. ***P < 0.001. As a service to our authors and readers, this journal provides supporting information supplied by the authors. Such materials are peer‐reviewed and may be re‐organized for online delivery, but are not copy‐edited or typeset. Technical support issues arising from supporting information (other than missing files) should be addressed to the authors. Table S1. Pearson correlation coefficients between land uses. Table S2. Summary statistics for available variables. Table S3. List of individual metrics used in multi‐metric indices of integrity. Table S4. Structural equation model output from the 2002 Land Use model. ***P < 0.001. Table S5. Structural equation model output from the Land Use Change model. ***P < 0.001. As a service to our authors and readers, this journal provides supporting information supplied by the authors. Such materials are peer‐reviewed and may be re‐organized for online delivery, but are not copy‐edited or typeset. Technical support issues arising from supporting information (other than missing files) should be addressed to the authors. Table S1. Pearson correlation coefficients between land uses. Table S2. Summary statistics for available variables. Table S3. List of individual metrics used in multi‐metric indices of integrity. Table S4. Structural equation model output from the 2002 Land Use model. ***P < 0.001. Table S5. Structural equation model output from the Land Use Change model. ***P < 0.001. As a service to our authors and readers, this journal provides supporting information supplied by the authors. Such materials are peer‐reviewed and may be re‐organized for online delivery, but are not copy‐edited or typeset. Technical support issues arising from supporting information (other than missing files) should be addressed to the authors. Table S1. Pearson correlation coefficients between land uses. Table S2. Summary statistics for available variables. Table S3. List of individual metrics used in multi‐metric indices of integrity. Table S4. Structural equation model output from the 2002 Land Use model. ***P < 0.001. Table S5. Structural equation model output from the Land Use Change model. ***P < 0.001. As a service to our authors and readers, this journal provides supporting information supplied by the authors. Such materials are peer‐reviewed and may be re‐organized for online delivery, but are not copy‐edited or typeset. Technical support issues arising from supporting information (other than missing files) should be addressed to the authors. Table S1. Pearson correlation coefficients between land uses. Table S2. Summary statistics for available variables. Table S3. List of individual metrics used in multi‐metric indices of integrity. Table S4. Structural equation model output from the 2002 Land Use model. ***P < 0.001. Table S5. Structural equation model output from the Land Use Change model. ***P < 0.001. As a service to our authors and readers, this journal provides supporting information supplied by the authors. Such materials are peer‐reviewed and may be re‐organized for online delivery, but are not copy‐edited or typeset. Technical support issues arising from supporting information (other than missing files) should be addressed to the authors.Supporting Info Item: Supporting info item - </note>
<identifier type="ISSN">0046-5070</identifier>
<identifier type="eISSN">1365-2427</identifier>
<identifier type="DOI">10.1111/(ISSN)1365-2427</identifier>
<identifier type="PublisherID">FWB</identifier>
<part>
<date>2011</date>
<detail type="volume">
<caption>vol.</caption>
<number>56</number>
</detail>
<detail type="issue">
<caption>no.</caption>
<number>3</number>
</detail>
<extent unit="pages">
<start>611</start>
<end>626</end>
<total>16</total>
</extent>
</part>
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<identifier type="DOI">10.1111/j.1365-2427.2010.02522.x</identifier>
<identifier type="ArticleID">FWB2522</identifier>
<accessCondition type="use and reproduction" contentType="copyright">© 2010 Blackwell Publishing Ltd</accessCondition>
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