Predicting the spatial distribution of the invasive piscivorous chub (Opsariichthys uncirostris uncirostris) in the irrigation ditches of Kyushu, Japan: A tool for the risk management of biological invasions

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Abstract

The piscivorous chub (Opsariichthys uncirostris uncirostris) has widely invaded Kyushu Island in Japan, and its presence in irrigation ditches known as creeks around Ariake Bay has caused particular concern because various native freshwater fishes are also known to exist in the region. In order to examine the habitat characteristics that are related to its occurrence, we developed a species distribution model for piscivorous chub that inhabits creeks in the Kase river catchment by using geographic and habitat variables that were both biotic and abiotic. We then evaluated the model by using a different data set from the adjacent Chikugo river catchment. The resulting multiple logistic regression model, whose performance was supported by a high value of 0. 881 for the area under the receiver operating characteristics curve (AUC), indicated that the occurrence of piscivorous chub was strongly affected by the watercourse distance from the source populations in the Kase river. The model's performance was still high (AUC = 0. 792) when tested with the data set from the Chikugo river catchment. We also produced a GIS map that projects the predicted distribution of piscivorous chub across all creeks within the Kase river catchment. The result is likely to reflect the connectivity between static and lentic habitat and is not merely a question of the simple distance from the source populations. We also discuss how the potential distribution map can be applied to the management of piscivorous chub. © 2010 Springer Science+Business Media B.V.

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Sato, M., Kawaguchi, Y., Yamanaka, H., Okunaka, T., Nakajima, J., Mitani, Y., … Onikura, N. (2010). Predicting the spatial distribution of the invasive piscivorous chub (Opsariichthys uncirostris uncirostris) in the irrigation ditches of Kyushu, Japan: A tool for the risk management of biological invasions. Biological Invasions, 12(11), 3677–3686. https://doi.org/10.1007/s10530-010-9762-3

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