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Volume 8, Number 1—January 2002

Perspective

Using a Dynamic Hydrology Model To Predict Mosquito Abundances in Flood and Swamp Water

Jeffrey ShamanComments to Author , Marc Stieglitz, Colin Stark, Sylvie Le Blancq, and Mark Cane
Author affiliations: Columbia University, Palisades, New York, USA;

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Figure 6

Figure 6 - a) Mass emergence forecast, Aedes vexans. Mass emergence is defined as a single-day collection of ≥128 mosquitoes. The probability of a mosquito mass emergence (lagged 10 days) increases with modeled surface wetness. b) Mass emergence forecast, Anopheles walkeri. Based on logistic regression analysis of the 15-year record of Great Swamp site An. walkeri. Mass emergence is defined as a single-day collection of ≥32 An. walkeri. As per Figure 6a, the probability of a mosquito m

Figure 6. a) Mass emergence forecast, Aedes vexans. Mass emergence is defined as a single-day collection of ≥128 mosquitoes. The probability of a mosquito mass emergence (lagged 10 days) increases with modeled surface wetness. b) Mass emergence forecast, Anopheles walkeri. Based on logistic regression analysis of the 15-year record of Great Swamp site An. walkeri. Mass emergence is defined as a single-day collection of ≥32 An. walkeri. As per Figure 6a, the probability of a mosquito mass emergence (lagged 10 days) increases with increasing modeled surface wetness. c) Mass emergence forecast, Culex pipiens. Based on logistic regression analysis of the 15-year record of Great Swamp site Cx. pipiens. Mass emergence is defined as a single-day colleciton of ≥32 Cx. pipiens. The probability of a mosquito mass emergence (lagged 10 days) decreases with increasing modeled surface wetness.

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