Predicting distributions of seven bitterling fishes in northern Kyushu, Japan

The distributions of seven bitterling species and subspecies—Tanakia lanceolata, T. limbata, Acheilognathus tabira nakamurae, A. rhombeus, Rhodeus ocellatus kurumeus, R. ocellatus ocellatus, and R. atremius atremius—in northern Kyushu were predicted using generalized linear models (GLMs) in order to...

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Veröffentlicht in:Ichthyological research 2012-04, Vol.59 (2), p.124-133
Hauptverfasser: Onikura, Norio, Nakajima, Jun, Miyake, Takuya, Kawamura, Kouichi, Fukuda, Shinji
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container_issue 2
container_start_page 124
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creator Onikura, Norio
Nakajima, Jun
Miyake, Takuya
Kawamura, Kouichi
Fukuda, Shinji
description The distributions of seven bitterling species and subspecies—Tanakia lanceolata, T. limbata, Acheilognathus tabira nakamurae, A. rhombeus, Rhodeus ocellatus kurumeus, R. ocellatus ocellatus, and R. atremius atremius—in northern Kyushu were predicted using generalized linear models (GLMs) in order to provide information helpful for conserving native bitterlings and preventing the expansion of alien bitterling species. Predictions were made according to the following procedure: (1) a set of GLMs for each species was formulated using environmental data from 710 sites that were derived using digital maps and GIS software, from which the best fit model for each species was selected using the Akaike information criterion for predicting the fish occurrence, (2) model performance was evaluated based on the receiver-operating characteristics (ROC) analysis using occurrence and environmental data from 362 sites, and (3) potential distributions of the bitterling were analyzed using the best fit models and environmental data for 1,272 sites, of which 200 data points without occurrence data were prepared. The best fit models revealed that 4–6 environmental factors were important in predicting seven bitterling distributions, which was supported by the area under the ROC curve (AUC) values of these fishes ranging from 0.753 to 0.927. The AUC values in model evaluation were significantly greater than 0.5 for six fishes, suggesting the moderate accuracies of these best fit models for predicting the fish distributions. These predictive models can be used for evaluating potential native bitterling richness and the potential distribution expansion of an alien subspecies.
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The AUC values in model evaluation were significantly greater than 0.5 for six fishes, suggesting the moderate accuracies of these best fit models for predicting the fish distributions. These predictive models can be used for evaluating potential native bitterling richness and the potential distribution expansion of an alien subspecies.</abstract><cop>Japan</cop><pub>Springer-Verlag</pub><doi>10.1007/s10228-011-0260-0</doi><tpages>10</tpages></addata></record>
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subjects Acheilognathus
Animal Systematics/Taxonomy/Biogeography
Biomedical and Life Sciences
computer software
Dispersal
Ecology
Environmental factors
Fish
Freshwater & Marine Ecology
geographic information systems
geographical distribution
indigenous species
introduced species
Life Sciences
linear models
Marine ecology
model validation
Pisces
prediction
Prediction models
Rhodeus ocellatus kurumeus
Zoology
title Predicting distributions of seven bitterling fishes in northern Kyushu, Japan
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