Statistical Test of Network Analysis: Can it Detect Differences in Food Web Properties

Ecological network analysis (ENA) is a modeling approach increasingly being used to examine food webs. However, most studies do not replicate networks, and a statistical evaluation of ENA is lacking. The major objectives of this study, therefore, were to evaluate statistically the effectiveness of E...

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Published inEcosystems (New York) Vol. 10; no. 6; pp. 906 - 923
Main Authors Dame, James K, Christian, Robert R
Format Journal Article
LanguageEnglish
Published New York, NY New York : Springer-Verlag 01.09.2007
Springer Science+Business Media
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Abstract Ecological network analysis (ENA) is a modeling approach increasingly being used to examine food webs. However, most studies do not replicate networks, and a statistical evaluation of ENA is lacking. The major objectives of this study, therefore, were to evaluate statistically the effectiveness of ENA in detecting differences in food web properties and to compare ENA output with established community level indices. Quantitative trophic networks (n = 12) representing four high salt marsh ponds during three times (corresponding to low stress, high stress, and post-disturbance) were constructed from an extensive field sampling program augmented by literature values. Food webs of salt marsh ponds were used because these systems contain relatively simple food webs, have well defined boundaries, and allow for adequate replication. A null hypothesis was tested to determine how values of 12 indices from ENA output differed among the three stress/disturbance conditions (H o: low stress = high stress = post-disturbance). Results of both ANOVA and Friedman's tests indicated most ENA indices were significantly different among the three stress/disturbance conditions. The amount of covariance among the indices was relatively low (7 of 66 were significant). Results were compared to differences in community indices (richness, evenness, and diversity) among the three stress/disturbance conditions. ENA output identified differences beyond those recognized by the community indices. Overall, networks were unique enough under different environmental conditions to provide statistically significant differences in ENA results. Our findings are supportive of the use of carefully constructed networks in food web analysis and for decision making in ecosystem-based management.
AbstractList Ecological network analysis (ENA) is a modeling approach increasingly being used to examine food webs. However, most studies do not replicate networks, and a statistical evaluation of ENA is lacking. The major objectives of this study, therefore, were to evaluate statistically the effectiveness of ENA in detecting differences in food web properties and to compare ENA output with established community level indices. Quantitative trophic networks (n = 12) representing four high salt marsh ponds during three times (corresponding to low stress, high stress, and post-disturbance) were constructed from an extensive field sampling program augmented by literature values. Food webs of salt marsh ponds were used because these systems contain relatively simple food webs, have well defined boundaries, and allow for adequate replication. A null hypothesis was tested to determine how values of 12 indices from ENA output differed among the three stress/disturbance conditions (Ho: low stress = high stress = post-disturbance). Results of both ANOVA and Friedman's tests indicated most ENA indices were significantly different among the three stress/disturbance conditions. The amount of covariance among the indices was relatively low (7 of 66 were significant). Results were compared to differences in community indices (richness, evenness, and diversity) among the three stress/disturbance conditions. ENA output identified differences beyond those recognized by the community indices. Overall, networks were unique enough under different environmental conditions to provide statistically significant differences in ENA results. Our findings are supportive of the use of carefully constructed networks in food web analysis and for decision making in ecosystem-based management.
Ecological network analysis (ENA) is a modeling approach increasingly being used to examine food webs. However, most studies do not replicate networks, and a statistical evaluation of ENA is lacking. The major objectives of this study, therefore, were to evaluate statistically the effectiveness of ENA in detecting differences in food web properties and to compare ENA output with established community level indices. Quantitative trophic networks (n = 12) representing four high salt marsh ponds during three times (corresponding to low stress, high stress, and post-disturbance) were constructed from an extensive field sampling program augmented by literature values. Food webs of salt marsh ponds were used because these systems contain relatively simple food webs, have well defined boundaries, and allow for adequate replication. A null hypothesis was tested to determine how values of 12 indices from ENA output differed among the three stress/disturbance conditions (H o: low stress = high stress = post-disturbance). Results of both ANOVA and Friedman's tests indicated most ENA indices were significantly different among the three stress/disturbance conditions. The amount of covariance among the indices was relatively low (7 of 66 were significant). Results were compared to differences in community indices (richness, evenness, and diversity) among the three stress/disturbance conditions. ENA output identified differences beyond those recognized by the community indices. Overall, networks were unique enough under different environmental conditions to provide statistically significant differences in ENA results. Our findings are supportive of the use of carefully constructed networks in food web analysis and for decision making in ecosystem-based management.
Ecological network analysis (ENA) is a modeling approach increasingly being used to examine food webs. However, most studies do not replicate networks, and a statistical evaluation of ENA is lacking. The major objectives of this study, therefore, were to evaluate statistically the effectiveness of ENA in detecting differences in food web properties and to compare ENA output with established community level indices. Quantitative trophic networks (n = 12) representing four high salt marsh ponds during three times (corresponding to low stress, high stress, and post-disturbance) were constructed from an extensive field sampling program augmented by literature values. Food webs of salt marsh ponds were used because these systems contain relatively simple food webs, have well defined boundaries, and allow for adequate replication. A null hypothesis was tested to determine how values of 12 indices from ENA output differed among the three stress/disturbance conditions (H ^sub o^: low stress = high stress = post-disturbance). Results of both ANOVA and Friedman's tests indicated most ENA indices were significantly different among the three stress/disturbance conditions. The amount of covariance among the indices was relatively low (7 of 66 were significant). Results were compared to differences in community indices (richness, evenness, and diversity) among the three stress/disturbance conditions. ENA output identified differences beyond those recognized by the community indices. Overall, networks were unique enough under different environmental conditions to provide statistically significant differences in ENA results. Our findings are supportive of the use of carefully constructed networks in food web analysis and for decision making in ecosystem-based management.[PUBLICATION ABSTRACT]
Ecological network analysis (ENA) is a modeling approach increasingly being used to examine food webs. However, most studies do not replicate networks, and a statistical evaluation of ENA is lacking. The major objectives of this study, therefore, were to evaluate statistically the effectiveness of ENA in detecting differences in food web properties and to compare ENA output with established community level indices. Quantitative trophic networks (n = 12) representing four high salt marsh ponds during three times (corresponding to low stress, high stress, and post-disturbance) were constructed from an extensive field sampling program augmented by literature values. Food webs of salt marsh ponds were used because these systems contain relatively simple food webs, have well defined boundaries, and allow for adequate replication. A null hypothesis was tested to determine how values of 12 indices from ENA output differed among the three stress/disturbance conditions (H sub(o): low stress = high stress = post-disturbance). Results of both ANOVA and Friedman's tests indicated most ENA indices were significantly different among the three stress/disturbance conditions. The amount of covariance among the indices was relatively low (7 of 66 were significant). Results were compared to differences in community indices (richness, evenness, and diversity) among the three stress/disturbance conditions. ENA output identified differences beyond those recognized by the community indices. Overall, networks were unique enough under different environmental conditions to provide statistically significant differences in ENA results. Our findings are supportive of the use of carefully constructed networks in food web analysis and for decision making in ecosystem-based management.
Author Dame, James K
Christian, Robert R
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Issue 6
Keywords ecopath
salt marsh pond
Ecology
ecosystem-based management
Environmental management
Stress
trophic network
Salt marsh
Statistical test
Salt pond
Food web
Ecosystem
ecological network analysis
Language English
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Snippet Ecological network analysis (ENA) is a modeling approach increasingly being used to examine food webs. However, most studies do not replicate networks, and a...
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SubjectTerms Animal and plant ecology
Animal, plant and microbial ecology
Applied ecology
Biological and medical sciences
Biomass
Conservation, protection and management of environment and wildlife
Disturbance
ecological network analysis
ecopath
Ecosystem management
Ecosystem models
ecosystem-based management
Ecosystems
Environmental conditions
Food chains
food web
Food webs
Fundamental and applied biological sciences. Psychology
General aspects
Insect larvae
Marine ecosystems
Network analysis
Ponds
salt marsh pond
Salt marshes
stress
Studies
Synecology
Taxa
Trophic levels
trophic network
Variance analysis
Title Statistical Test of Network Analysis: Can it Detect Differences in Food Web Properties
URI https://www.jstor.org/stable/27823732
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Volume 10
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