Influence of Spatial Processes on the Population Dynamics of Insect Pests
Principal Investigator: Ian Macrae
Project Description:
The population dynamics of many insect pests in Minnesota are related to spatial processes. Many pest insect species do not overwinter in Minnesota and their populations are re-established annually by immigrating individuals. The impact of these species is obviously related to the influence of national and regional weather events; very large scale spatial processes. For those species that do overwinter in the region, distance from overwintering sites to crops, distance between suitable hosts and relative abundance of alternate hosts, all moderate scale spatial processes, influence their impact on agricultural systems. Once established, a species' distribution within a field, a small scale spatial process, may well determine its impact on yield and the most appropriate management response. The evaluation of the spatial nature of insect pest populations can provide significant insight into management programs. Targeted application of insecticides, refinement of scouting and monitoring efforts and seasonal prediction of insect populations all can greatly benefit from detailed descriptions of the spatial nature of insect population dynamics. In the past 20 years, the tools necessary for these investigations have been developed to the point where such descriptions are attainable. Geospatial tools such as Geographic Information Systems (GIS) and Global Positioning Systems (GPS) and the ability to remotely sense population densities both facilitate the precise mapping of populations. These techniques are widely used in agriculture to apply agrochemicals to precise locations instead of broadly across entire fields (i.e. Site Specific Agriculture). This results in decreased chemical inputs into agroecosystems; lowering production costs, decreasing environmental impact and increasing safety for producers and consumers. Integrated Pest Management (IPM) is designed to decrease dependence on pesticides for control of insects, weeds, and plant pathogens while maximizing profitability. The incorporation of digital mapping and remote sensing into IPM is a natural progression. Mapping the regional and within-field spatial and temporal distributions of insect pests offers a number of benefits, e.g. specific targeting of pesticides and focusing scouting and monitoring efforts. In addition, the mapping of the origins of seasonal wind events can provide insight into the probability of an insect outbreak. This revision proposes three specific objectives which address insect management, population estimates and mapping at increasing scales, from within-field to regional population modeling. These are: adapting existing meteorologically-based predictive models for green peach aphid to cereal aphids in the Red River Valley and determine their within field distribution, assessing remote sensing as a mechanism to detect populations of soybean aphids and other insect pests, and assessing the ability of remotely sensed data, both aerial and within field obtained reflectance data, to differentiate between damage symptoms caused by Sugarbeet Root Maggot and soil characteristics.
Project Years: 2011-2016
Funding Source: State Agricultural Experiment Station