Artificial Intelligence

Modeling fish community dynamics in the Florida Everglades: role of temperature variation

Nov 01, 2002

DOI: https://doi.org/10.2166/wst.2002.0208

Published in: Water science and technology

/ Hussam Al Rabai'ah

Temperature variation is an important factor in Everglade wetlands ecology. A temperature fluctuation from 17°C to 32°C recorded in the Everglades may have significant impact on fish dynamics. The short life cycles of some of Everglade fishes has rendered this temperature variation to have even more impacts on the ecosystem. Fish population dynamic models, which do not explicitly consider seasonal oscillations in temperature, may fail to describe the details of such a population. Hence, a model for fish in freshwater marshes of the Florida Everglades that explicitly incorporates seasonal temperature variations is developed. The model's main objective is to assess the temporal pattern of fish population and densities through time subject to temperature variations. Fish population is divided into 2 functional groups (FGs) consisting of small fishes; each group is subdivided into 5-day age classes during their life cycles. Many governing sub-modules are set directly or indirectly to be temperature dependent. Growth, fecundity, prey availability, consumption rates and mortality are examples. Several mortality sub-modules are introduced in the model, of which starvation mortality is set to be proportional to the ratio of prey needed to prey available at that particular time step. As part of the calibration process, the model is run for 50 years to ensure that fish densities do not go to extinction, while the simulation period is about 8 years. The model shows that the temperature dependent starvation mortality is an important factor that influences fish population densities. It also shows high fish population densities at some temperature ranges when this consumption need is minimum. Several sensitivity analyses involving variations in temperature terms, food resources and water levels are conducted to ascertain the relative importance of temperature dependence terms.

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