Peck Steven L
Biology Department, Brigham Young University, Provo, UT 84602, USA.
Acta Trop. 2014 Oct;138 Suppl:S22-5. doi: 10.1016/j.actatropica.2014.03.006. Epub 2014 Mar 25.
It is becoming clear that handling the inherent complexity found in ecological systems is an essential task for finding ways to control insect pests of tropical livestock such as tsetse flies, and old and new world screwworms. In particular, challenging multivalent management programs, such as Area Wide Integrated Pest Management (AW-IPM), face daunting problems of complexity at multiple spatial scales, ranging from landscape level processes to those of smaller scales such as the parasite loads of individual animals. Daunting temporal challenges also await resolution, such as matching management time frames to those found on ecological and even evolutionary temporal scales. How does one deal with representing processes with models that involve multiple spatial and temporal scales? Agent-based models (ABM), combined with geographic information systems (GIS), may allow for understanding, predicting and managing pest control efforts in livestock pests. This paper argues that by incorporating digital ecologies in our management efforts clearer and more informed decisions can be made. I also point out the power of these models in making better predictions in order to anticipate the range of outcomes possible or likely.
越来越明显的是,应对生态系统中固有的复杂性是找到控制热带家畜害虫(如采采蝇、新旧大陆嗜人瘤蝇)方法的一项基本任务。特别是,具有挑战性的多价管理计划,如区域综合虫害管理(AW-IPM),在多个空间尺度上面临着艰巨的复杂性问题,从景观层面的过程到较小尺度的过程,如个体动物的寄生虫负荷。同样等待解决的还有艰巨的时间挑战,比如使管理时间框架与生态甚至进化时间尺度上的时间框架相匹配。如何用涉及多个空间和时间尺度的模型来表示过程呢?基于主体的模型(ABM)与地理信息系统(GIS)相结合,可能有助于理解、预测和管理家畜害虫的防治工作。本文认为,通过将数字生态纳入我们的管理工作中,可以做出更清晰、更明智的决策。我还指出了这些模型在做出更好预测以预期可能或很可能出现的结果范围方面的作用。