Tuning stochastic matrix models with hydrologic data to predict the population dynamics of a riverine fish. 2010

Peter C Sakaris, and Elise R Irwin
Alabama Cooperative Fish and Wildlife Research Unit, 3301 Forestry and Wildlife Sciences Building, Auburn University, Auburn, Alabama 36849, USA psakaris@spsu.edu

We developed stochastic matrix models to evaluate the effects of hydrologic alteration and variable mortality on the population dynamics of a lotic fish in a regulated river system. Models were applied to a representative lotic fish species, the flathead catfish (Pylodictis olivaris), for which two populations were examined: a native population from a regulated reach of the Coosa River (Alabama, USA) and an introduced population from an unregulated section of the Ocmulgee River (Georgia, USA). Size-classified matrix models were constructed for both populations, and residuals from catch-curve regressions were used as indices of year class strength (i.e., recruitment). A multiple regression model indicated that recruitment of flathead catfish in the Coosa River was positively related to the frequency of spring pulses between 283 and 566 m3/s. For the Ocmulgee River population, multiple regression models indicated that year class strength was negatively related to mean March discharge and positively related to June low flow. When the Coosa population was modeled to experience five consecutive years of favorable hydrologic conditions during a 50-year projection period, it exhibited a substantial spike in size and increased at an overall 0.2% annual rate. When modeled to experience five years of unfavorable hydrologic conditions, the Coosa population initially exhibited a decrease in size but later stabilized and increased at a 0.4% annual rate following the decline. When the Ocmulgee River population was modeled to experience five years of favorable conditions, it exhibited a substantial spike in size and increased at an overall 0.4% annual rate. After the Ocmulgee population experienced five years of unfavorable conditions, a sharp decline in population size was predicted. However, the population quickly recovered, with population size increasing at a 0.3% annual rate following the decline. In general, stochastic population growth in the Ocmulgee River was more erratic and variable than population growth in the Coosa River. We encourage ecologists to develop similar models for other lotic species, particularly in regulated river systems. Successful management of fish populations in regulated systems requires that we are able to predict how hydrology affects recruitment and will ultimately influence the population dynamics of fishes.

UI MeSH Term Description Entries
D008962 Models, Theoretical Theoretical representations that simulate the behavior or activity of systems, processes, or phenomena. They include the use of mathematical equations, computers, and other electronic equipment. Experimental Model,Experimental Models,Mathematical Model,Model, Experimental,Models (Theoretical),Models, Experimental,Models, Theoretic,Theoretical Study,Mathematical Models,Model (Theoretical),Model, Mathematical,Model, Theoretical,Models, Mathematical,Studies, Theoretical,Study, Theoretical,Theoretical Model,Theoretical Models,Theoretical Studies
D011157 Population Dynamics The pattern of any process, or the interrelationship of phenomena, which affects growth or change within a population. Malthusianism,Neomalthusianism,Demographic Aging,Demographic Transition,Optimum Population,Population Decrease,Population Pressure,Population Replacement,Population Theory,Residential Mobility,Rural-Urban Migration,Stable Population,Stationary Population,Aging, Demographic,Decrease, Population,Decreases, Population,Demographic Transitions,Dynamics, Population,Migration, Rural-Urban,Migrations, Rural-Urban,Mobilities, Residential,Mobility, Residential,Optimum Populations,Population Decreases,Population Pressures,Population Replacements,Population Theories,Population, Optimum,Population, Stable,Population, Stationary,Populations, Optimum,Populations, Stable,Populations, Stationary,Pressure, Population,Pressures, Population,Replacement, Population,Replacements, Population,Residential Mobilities,Rural Urban Migration,Rural-Urban Migrations,Stable Populations,Stationary Populations,Theories, Population,Theory, Population,Transition, Demographic,Transitions, Demographic
D004784 Environmental Monitoring The monitoring of the level of toxins, chemical pollutants, microbial contaminants, or other harmful substances in the environment (soil, air, and water), workplace, or in the bodies of people and animals present in that environment. Monitoring, Environmental,Environmental Surveillance,Surveillance, Environmental
D005399 Fishes A group of cold-blooded, aquatic vertebrates having gills, fins, a cartilaginous or bony endoskeleton, and elongated bodies covered with scales.
D000818 Animals Unicellular or multicellular, heterotrophic organisms, that have sensation and the power of voluntary movement. Under the older five kingdom paradigm, Animalia was one of the kingdoms. Under the modern three domain model, Animalia represents one of the many groups in the domain EUKARYOTA. Animal,Metazoa,Animalia
D045483 Rivers Large natural streams of FRESH WATER formed by converging tributaries and which empty into a body of water (lake or ocean). Streams,River,Stream

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