Regional abundance of a planthopper pest: the effect of host patch area and configuration

Abstract

The effect of host patch area and configuration on the abundance of dispersing individuals of Delphacodes kuscheli Fennah (Homoptera: Delphacidae), the vector of Río Cuarto disease in maize, was investigated in the main maize production area of Argentina. Actively dispersing D. kuscheli individuals were collected from 15 sampling sites during the spring seasons of 1999 and 2000, using sticky traps placed at 6 m above ground level. Host patches were detected and quantified using Landsat 5 TM images for the periods studied. The spatial pattern analysis program FRAGSTATS was used to estimate the total class area, largest patch index, mean proximity index, and patch cohesion index for patches of winter pastures (the main insect host during winter) as observed from the satellite images. Landsat 5 TM estimations showed local variability in the proportion of winter pastures, with patches bigger during 1999 than during 2000, but these patches represented only a very small part of the total landscape. Proximity between host patches was also variable between sites and higher values of cohesion occurred during the first sampling season. The relationship between host area and D. kuscheli mean abundance was adjusted to an exponential (R2= 77.5%) model. Host patch dominance, host patch isolation, and host patch connectivity all showed a positive relationship with D. kuscheli mean abundance, adjusting significantly to linear models (R2= 92%, R2= 90%, and R2= 22%, respectively). Outbreaks of Río Cuarto disease in the main maize production area of Argentina are related to high vector populations. The results indicate that the abundance of D. kuscheli depends on factors related to the abundance and configuration of its host patches.

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

“…This means that the abundance of L. striatellus is driven by the surrounding landscape, especially in a small and segmented agricultural landscape. It is consistent with the recent report by Grilli [30] who concluded that the proximity of other host patches had an effect on the abundance of the dispersive fraction of the population of D. Kuscheli in Argentina's central plain.…”

“…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.…”

Impact of 9 years of Bt-maize cultivation on the distribution of maize viruses

“…Such positive effects may have contributed to the emergence and maintenance of MRDV since high planthopper populations have been found to increase the incidence of fijivirus (Grilli and Bruno 2007).…”

Consequences of ecological connectivity: the coastal ecosystem mosaic

“…Connectivity is apparent at scales from the centimetre-scale movement of rotifers to food patches (Ignoffo et al 2005) to longdistance bird migration (Alerstam et al 2007). From a conceptual point of view, connectivity is crucial in a broad spectrum of contexts from conservation (Jones et al 2007) and pest and disease vector management (Grilli & Bruno 2007) to gene flow (Boulet et al 2007), the generation of species diversity (Genner et al 2007), the regulation of competitive advantage (Hagen et al 2007) and metapopultion dynamics (Hanski 1998).…”