The spatio-temporal pattern of Delphacodes kuscheli (Homoptera: Delphacidae) abundance in central Argentina

Abstract

Delphacodes kuscheli Fennah is the vector of maize rough dwarf virus, that affects maize production in central Argentina. The spatial and temporal abundance pattern of the insect vector was studied from October 1992 to November 1994, within endemic and non-endemic areas of the crop disease. Insect density was estimated every 7-15 days during spring and summer (maize season) or monthly during autumn and winter from high (6 m) and low (1.5 m) sticky traps placed at eight sampling stations along a 300 km transect. Each year, D. kuscheli density increased from October, peaked in December, to decrease afterwards and disappear in May. Density was lower in the nonendemic area and higher in the endemic one. The average absolute difference of density between sampling station pairs increased with the distance between the sampling stations (R 2 =0.85), and the correlation of density changes decreased with the distance between the sampling stations (R 2 =0.78), suggesting that the population dynamics were affected more by local than by regional factors. There was a significant correlation (with a 36 days lag) between the normalized difference vegetation index (NDVI) (calculated from 15 days maximum value composites images of NOAA-11 meteorological satellites) and D. kuscheli abundance. Based on this regression model, and using the time series of the satellite derived NDVI values, maps of the distribution and abundance of D. kuscheli within the study area for the spring and summer of 1992 were produced.

Estimating habitat suitability for potential hantavirus reservoirs in north-western Patagonia using satellite imagery: Searching for the best predictive tools

“…As demonstrated by Rogers and Randolph (1993), Randolph and Rogers (1997), Gorla (2002), and Rogers et al (2002) the spatial distribution of animal species is associated with variability in primary productivity. In addition, other researchers investigated the efficiency of meteorological satellite images by using a vegetation index time series to develop a surveillance system of plagues that depend on microhabitat vegetation cover (Gleiser et al 1997;Grilli and Gorla 1997). Birney et al (1976) suggested that, during Microtis outbreaks, only those areas that offer sufficient vegetation cover are suited as "source" habitat, where individuals can remain and reproduce.…”

The Effect of Landscape Composition on the Abundance of Laodelphax striatellus Fallén in Fragmented Agricultural Landscapes

“…In comparison with our study, previous studies were mostly conducted at larger spatial scales [4,27], because their research subjects had stronger flying or moving capabilities than L. striatellus. Even though the research subject belongs to the same family of Delphacidae (Delphacodes kuscheli) like our study, the spatial scale at the agricultural landscape had over 2000 m for a radius buffer [19,[28][29][30][31]. Our result showed that for L. striatellus, its host habitat's composition in the study region was extremely segmented and heterogeneous.…”

“…The maximal radius was set at 200 m to avoid artificially large correlations due to overlapping buffers [27]. Landscape composition and configuration can affect planthopper dynamics independently and interactively [19,[28][29][30][31], the measures of landscape composition and configuration would be calculated in this study.…”

NOAA/AVHRR satellite detection of Siberian silkmoth outbreaks in eastern Siberia

“…More sophisticated processing techniques were used to obtain high correlation of Thematic Mapper derived green leaf fraction and Satellite detection of Siberian silkmoth outbreaks 5545 budworm populations (Radeloff et al 1999). Smaller scale satellite data from National Oceanic and Atmospheric Administration (NOAA) Advanced Very High Resolution Radiometer (AVHRR) have been used successfully by Gilli and Gorla (1997) to monitor insect activity in crops. In addition, an initial investigation of NOAA/AVHRR (1.1 km) data for monitoring large-scale pest outbreaks was described in the Russian literature by Kharuk et al (1998).…”