期刊
THEORETICAL ECOLOGY
卷 9, 期 3, 页码 365-380出版社
SPRINGER HEIDELBERG
DOI: 10.1007/s12080-016-0295-y
关键词
Aquaculture; Dispersal; Ecosystem service; Phase locking; Population dynamics; Synchrony
类别
资金
- Natural Sciences and Engineering Research Council of Canada
- Bill Shostak Wildlife Award and Fisher Scientific Schoalrship
- Canada Research Chair and Killam Fellowship
- Sloan Fellowship in Ocean Science
- Killam Postdoctoral Fellowship
The dynamics of coupled populations have mostly been studied in the context of metapopulation viability with application to, for example, species at risk. However, when considering pests and pathogens, eradication, not persistence, is often the end goal. Humans may intervene to control nuisance populations, resulting in reciprocal interactions between the human and natural systems that can lead to unexpected dynamics. The incidence of these human-natural couplings has been increasing, hastening the need to better understand the emergent properties of such systems in order to predict and manage outbreaks of pests and pathogens. For example, the success of the growing aquaculture industry depends on our ability to manage pathogens and maintain a healthy environment for farmed and wild fish. We developed a model for the dynamics of connected populations subject to control, motivated by sea louse parasites that can disperse among salmon farms. The model includes exponential population growth with a forced decline when populations reach a threshold, representing control interventions. Coupling two populations with equal growth rates resulted in phase locking or synchrony in their dynamics. Populations with different growth rates had different periods of oscillation, leading to quasiperiodic dynamics when coupled. Adding small amounts of stochasticity destabilized quasiperiodic cycles to chaos, while stochasticity was damped for periodic or stable dynamics. Our analysis suggests that strict treatment thresholds, although well intended, can complicate parasite dynamics and hinder control efforts. Synchronizing populations via coordinated management among farms leads to more effective control that is required less frequently. Our model is simple and generally applicable to other systems where dispersal affects the management of pests and pathogens.
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