Effects of density dependence on diel vertical migration of populations of northern krill: a genetic algorithm model
Effects of density dependence on diel vertical migration of populations of northern krill: a genetic algorithm model
复制标题
密度依赖性对北方磷虾种群昼夜垂直迁移的影响：遗传算法模型
DOI：
10.3354/meps277209
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发表时间：
2004
影响因子：
2.5
通讯作者：
G. Tarling
中科院分区：
文献类型：
--
作者：
M. Burrows;G. Tarling
对磷虾Diel垂直迁徙(DVM)的净研究和声学研究往往表明，在平均种群深度附近存在一定程度的分散，这种分散程度在夜间变得更大。权衡模型可以预测饮食周期的最佳深度，但很少解释为什么会有垂直分散，为什么聚集在特定的时间分散。我们考察了密度相关因素作为对这些现象的潜在解释。开发了一个遗传算法模型，该模型基于磷虾种群的内部状态(即能量储备水平)、捕食风险和同种生物的位置来预测DVM。建模方法的设计是动态的，因为最佳政策可以随着时间的推移对不断变化的情况作出反应。模型的参数化是通过在克莱德海地区对北部磷虾Meganyctiphane Norveica及其环境进行的测量实现的。深度光强度被用来评估视觉捕食的风险水平。食物供应是垂直分层的浮游植物和垂直迁徙的桡足类动物的混合物。用负指数函数模拟各深度食物回报的密度依赖关系。敏感性分析涉及密度依赖程度和代谢率的变化。在所有敏感性分析中都预测了DVm，并且每一项都与净渔获量和声学观测呈正相关。取食成功率对密度的依赖程度增加并不影响夜间选择的平均深度，但确实增加了种群的扩散。当代谢率降低，死亡率风险评估在一年而不是每天进行时，与观察结果最接近。该模型预测，在低食物条件下，人口应该会分布得更广。我们建议在预测磷虾行为和生命周期模式的未来状态依赖模型中包括密度依赖因素。
Net and acoustic studies of diel vertical migration (DVM) in krill often show a degree of dispersion around the mean population depth, which becomes greater during night-time. Trade-off models can predict optimum depths over diet cycles but rarely explain why there is vertical scatter and why aggregations disperse at certain times. We examined density-dependent factors as a potential explanation for these phenomena. A Genetic Algorithm model was developed that predicted DVM,in a krill population based on internal state (i.e. levels of energy reserves), risk of predation and location of conspecifics. The modelling approach was designed to be dynamic in that optimal policies could respond to changing circumstances through time. Parameterisation of the model was achieved through measurements made in the Clyde Sea Area on northern krill Meganyctiphanes norvegica and its environment. Light intensity at depth was used to assess the level of risk of visual predation. Food provision was a mixture of vertically stratified phytoplankton and vertically migrating copepods. A negative exponential function was used to simulate density dependence in the food returns at each depth. Sensitivity analyses involved alterations to the level of density dependence and the metabolic rate. DVM was predicted in all sensitivity analyses and each correlated positively with net catch and acoustic observations. Increased density dependence in feeding success did not affect the mean depths chosen at night but did increase the spread of the population. The closest fit to observations was achieved when the metabolic rate was lowered and risk of mortality rate was assessed over a yearly rather than daily period. The model predicted that the population should spread more under low food conditions. We recommend that density-dependent factors be included in future state-dependent models predicting krill behaviour and life-cycle patterns.