Alabama Cooperative Fish and Wildlife Research Unit, 3301 Forestry and Wildlife Sciences Building, Auburn University, Auburn, Alabama 36849, USA
Ecol Appl. 2010 Mar;20(2):483-96. doi: 10.1890/08-0305.1.
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.
我们开发了随机矩阵模型来评估水文变化和可变死亡率对受管制河流系统中洄游鱼类种群动态的影响。模型应用于两种平鳍𬶐种群进行研究，一种是来自阿拉巴马州库萨河受管制河段的本地种群，另一种是来自佐治亚州奥克穆尔吉河不受管制河段的引入种群。为这两个种群构建了按尺寸分类的矩阵模型，并使用渔获物曲线回归的残差作为年际强度（即补充）的指标。多元回归模型表明，库萨河平鳍𬶐的补充与 283 至 566 立方米/秒之间春季脉冲的频率呈正相关。对于奥克穆尔吉河种群，多元回归模型表明，年际强度与 3 月平均流量呈负相关，与 6 月低流量呈正相关。在 50 年预测期内，当假设库萨河种群连续 5 年经历有利的水文条件时，其大小会大幅增加，并以 0.2%的年增长率整体增长。当假设库萨河种群连续 5 年经历不利的水文条件时，种群大小最初会下降，但在下降后会稳定下来，并以 0.4%的年增长率增长。当假设奥克穆尔吉河种群连续 5 年经历有利条件时，其大小会大幅增加，并以 0.4%的年增长率整体增长。在奥克穆尔吉河种群经历 5 年不利条件后，预计其种群数量会急剧下降。然而，种群数量很快恢复，下降后以 0.3%的年增长率增长。一般来说，奥克穆尔吉河的随机种群增长比库萨河更为不稳定和多变。我们鼓励生态学家为其他洄游物种开发类似的模型，特别是在受管制的河流系统中。成功管理受管制系统中的鱼类种群需要我们能够预测水文如何影响补充，并最终影响鱼类的种群动态。
