SPATIAL AND TEMPORAL COMPUTER ANALYSIS OF INSECTS AND WEATHER: GRASSHOPPERS AND RAINFALL IN ALBERTA
AbstractNew technology allows the rapid mapping of point or polygon variables, the correlation of maps, and the use of maps as variables in computer models. An illustration is the use of map correlation to investigate how changes in abundance of adult grasshoppers relate to rainfall in Alberta: maps of monthly rainfall, monthly hours of sunlight and annual grasshopper counts (8391 survey records) from a 5-year period were contoured and correlated. The methods of smoothing are described. Correlograms of Moran's I over distance show spatial autocorrelation of grasshopper abundance on a geographic scale. The grasshopper counts were autocorrelated to 20–30 km on most maps, and the relationship of correlograms to contour mapping is discussed. Quotient maps were produced: each population–abundance map was divided by the map from the previous year, and the results were correlated with monthly rainfall maps. There was significant association between areas of increase and levels of rainfall. Population tended to decline in areas of above-average rainfall. A simple model enabled a forecast of grasshopper distribution from the previous year's grasshopper population, monthly rainfall maps, and sunlight hours during the previous August.