Predicting macrofaunal species distributions in estuarine gradients with the use of logistic regression and classification systems

J.L. Ellis, T. Ysebaert, T. Hume, A. Norkko, T.P. Bult, P. Herman, S. Thrush, J. Oldman

Research output: Contribution to journalArticleAcademicpeer-review

32 Citations (Scopus)

Abstract

There is a growing need to predict ecological responses to long-term habitat change. However, statistical models for marine soft-substratum ecosystems are limited, and consequently there is a need for the development of such models. In order to assess the utility of statistical modelling approaches for predicting likely changes in species distributions under varying environmental conditions, we tested the utility of logistic modelling and classification approaches. We successfully developed models relating the presence/absence of common intertidal macrofauna to changing environmental variables such as sediment characteristics, depth/elevation, tidal currents and wind-wave (i.e. wind-generated wave activity) disturbance. The final model for each species contained between 1 and 6 variables, where the percentage correctly predicted was moderate to high, ranging from 59 to 97 %. We were also able to identify relationships between higher level variables such as estuary type, basin morphometry and catchment-draining processes in driving macrobenthic community composition; however, we were unable to fully test the utility of the classification approach due to differences in the scale at which the macrobenthic data was collected and the scale of the higher level physical variables. These models were developed and tested using data that covered a range of environmental conditions in 5 estuaries in New Zealand. Such broad-scale statistical models play a critical role in our understanding of the likely effects of large-scale habitat change. However, a greater understanding of the fine-scale mechanistic controls on species distributions such as life-history characteristics, density information and biotic interactions would potentially lead to the development of more sensitive models.
Original languageEnglish
Pages (from-to)69-83
JournalMarine Ecology Progress Series
Volume316
DOIs
Publication statusPublished - 2006

Fingerprint

logistics
biogeography
statistical models
environmental factors
estuaries
environmental conditions
estuary
taxonomy
morphometry
wind wave
habitat
tidal current
distribution
habitats
modeling
community composition
tides
life history
catchment
basins

Keywords

  • canonical correspondence-analysis
  • macrobenthic communities
  • environmental-factors
  • sediment stability
  • sandflat
  • habitat
  • harbor

Cite this

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abstract = "There is a growing need to predict ecological responses to long-term habitat change. However, statistical models for marine soft-substratum ecosystems are limited, and consequently there is a need for the development of such models. In order to assess the utility of statistical modelling approaches for predicting likely changes in species distributions under varying environmental conditions, we tested the utility of logistic modelling and classification approaches. We successfully developed models relating the presence/absence of common intertidal macrofauna to changing environmental variables such as sediment characteristics, depth/elevation, tidal currents and wind-wave (i.e. wind-generated wave activity) disturbance. The final model for each species contained between 1 and 6 variables, where the percentage correctly predicted was moderate to high, ranging from 59 to 97 {\%}. We were also able to identify relationships between higher level variables such as estuary type, basin morphometry and catchment-draining processes in driving macrobenthic community composition; however, we were unable to fully test the utility of the classification approach due to differences in the scale at which the macrobenthic data was collected and the scale of the higher level physical variables. These models were developed and tested using data that covered a range of environmental conditions in 5 estuaries in New Zealand. Such broad-scale statistical models play a critical role in our understanding of the likely effects of large-scale habitat change. However, a greater understanding of the fine-scale mechanistic controls on species distributions such as life-history characteristics, density information and biotic interactions would potentially lead to the development of more sensitive models.",
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Predicting macrofaunal species distributions in estuarine gradients with the use of logistic regression and classification systems. / Ellis, J.L.; Ysebaert, T.; Hume, T.; Norkko, A.; Bult, T.P.; Herman, P.; Thrush, S.; Oldman, J.

In: Marine Ecology Progress Series, Vol. 316, 2006, p. 69-83.

Research output: Contribution to journalArticleAcademicpeer-review

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T1 - Predicting macrofaunal species distributions in estuarine gradients with the use of logistic regression and classification systems

AU - Ellis, J.L.

AU - Ysebaert, T.

AU - Hume, T.

AU - Norkko, A.

AU - Bult, T.P.

AU - Herman, P.

AU - Thrush, S.

AU - Oldman, J.

PY - 2006

Y1 - 2006

N2 - There is a growing need to predict ecological responses to long-term habitat change. However, statistical models for marine soft-substratum ecosystems are limited, and consequently there is a need for the development of such models. In order to assess the utility of statistical modelling approaches for predicting likely changes in species distributions under varying environmental conditions, we tested the utility of logistic modelling and classification approaches. We successfully developed models relating the presence/absence of common intertidal macrofauna to changing environmental variables such as sediment characteristics, depth/elevation, tidal currents and wind-wave (i.e. wind-generated wave activity) disturbance. The final model for each species contained between 1 and 6 variables, where the percentage correctly predicted was moderate to high, ranging from 59 to 97 %. We were also able to identify relationships between higher level variables such as estuary type, basin morphometry and catchment-draining processes in driving macrobenthic community composition; however, we were unable to fully test the utility of the classification approach due to differences in the scale at which the macrobenthic data was collected and the scale of the higher level physical variables. These models were developed and tested using data that covered a range of environmental conditions in 5 estuaries in New Zealand. Such broad-scale statistical models play a critical role in our understanding of the likely effects of large-scale habitat change. However, a greater understanding of the fine-scale mechanistic controls on species distributions such as life-history characteristics, density information and biotic interactions would potentially lead to the development of more sensitive models.

AB - There is a growing need to predict ecological responses to long-term habitat change. However, statistical models for marine soft-substratum ecosystems are limited, and consequently there is a need for the development of such models. In order to assess the utility of statistical modelling approaches for predicting likely changes in species distributions under varying environmental conditions, we tested the utility of logistic modelling and classification approaches. We successfully developed models relating the presence/absence of common intertidal macrofauna to changing environmental variables such as sediment characteristics, depth/elevation, tidal currents and wind-wave (i.e. wind-generated wave activity) disturbance. The final model for each species contained between 1 and 6 variables, where the percentage correctly predicted was moderate to high, ranging from 59 to 97 %. We were also able to identify relationships between higher level variables such as estuary type, basin morphometry and catchment-draining processes in driving macrobenthic community composition; however, we were unable to fully test the utility of the classification approach due to differences in the scale at which the macrobenthic data was collected and the scale of the higher level physical variables. These models were developed and tested using data that covered a range of environmental conditions in 5 estuaries in New Zealand. Such broad-scale statistical models play a critical role in our understanding of the likely effects of large-scale habitat change. However, a greater understanding of the fine-scale mechanistic controls on species distributions such as life-history characteristics, density information and biotic interactions would potentially lead to the development of more sensitive models.

KW - canonical correspondence-analysis

KW - macrobenthic communities

KW - environmental-factors

KW - sediment stability

KW - sandflat

KW - habitat

KW - harbor

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DO - 10.3354/meps316069

M3 - Article

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SP - 69

EP - 83

JO - Marine Ecology Progress Series

JF - Marine Ecology Progress Series

SN - 0171-8630

ER -