Analysis of the spatio-temporal distribution of Eurygaster integriceps (Hemiptera: Scutelleridae) by using spatial analysis by distance indices and geostatistics

Geostatistical Analysis of the Spatial Variation of Chrysolina aeruginosa Larvae at Different Stages in Desert Ecosystems

Chrysolina aeruginosa is a major pest of Artemisia ordosica, and knowledge of the spatial distribution pattern of its larvae in their natural habitat is crucial for the implementation of effective control measures. This study employed geostatistical methods to investigate the damage caused by larvae of different age groups and their spatial distribution pattern. The distribution of C. aeruginosa larvae, which cause damage to A. ordosica, differed significantly according to their age. Younger larvae were predominantly found in the middle and upper parts of the plant, whereas older larvae were mainly distributed in the middle and lower parts, with significant differences in distribution location. A generalized linear model analysis revealed that the height of the plant, and plant morphological characteristics such as height, crown width, and ground diameter were significantly correlated with the number of larvae present. Furthermore, the interaction of age with other variables had an impact on the number of larvae. Kriging interpolation showed that C. aeruginosa larvae were distributed in aggregated patches with strong spatial heterogeneity. The younger larvae were more abundant in the center of the sample site, while the older larvae tended to be distributed toward the edges. These findings provide valuable information for designing effective control programs.

Spatial Distribution of Hunting Billbugs (Coleoptera: Curculionidae) in Sod Farms

The hunting billbug, Sphenophorus venatus vestitus Chittenden (Coleoptera: Curculionidae), is an important turfgrass pest, especially in sod farms. S. venatus vestitus larvae feed on the stems and roots of turfgrass. Damaged turfgrass is loosely held together and poses a challenge for machine harvesting. Additionally, the normal growth of turfgrass is affected, especially after winter dormancy. Because S. venatus vestitus larvae are hidden inside the stems or under the soil, larval management is challenging. To improve sampling and management, the spatial distribution patterns of S. venatus vestitus larvae and adults were assessed at four sod farm sites with a history of S. venatus vestitus infestation in central Georgia (USA). The larvae were sampled by soil cores using a hole cutter, whereas adults were collected using pitfall traps for 7 d. The spatial distributions of larvae and adults was analyzed using SADIE and variograms. The SADIE and variogram analyses revealed a significant aggregation pattern for adults, whereas aggregated distributions were detected for larvae with variogram analyses. The average ranges of spatial dependence for larval and adult samples were 3.9 m and 5.4 m, respectively. Interpolated distribution maps were created to visually depict S. venatus vestitus infestation hotspots within the sod farms.

Characterization of the spatial distribution of alfalfa weevil, Hypera postica, and its natural enemies, using geospatial models

BACKGROUND

Understanding the spatio-temporal dynamics of prey and predator distributions can provide valuable insights into pest management strategies and conservation of natural enemies in agro-ecosystems. The alfalfa weevil, Hypera postica (Gyllenhal), is an economically important pest of alfalfa throughout the western United States. Coccinellids and nabids are among the most important natural enemies of this species, contributing to the biological control of H. postica in alfalfa fields. The spatio-temporal dynamics of H. postica and these two predator groups were investigated using 81 (= 9 × 9 grid) sample points in each of five alfalfa fields in north-central Montana. The data were analyzed using variogram and spatial analysis by distance indices (SADIE).

RESULTS

Variogram analysis revealed the spatial dependence (aggregation) of H. postica in 17 of 19 sampling times for larvae, and three of 12 sampling times for adults. Using SADIE, statistically significant aggregation distribution was evident in four of 19 sampling times for larvae, and five of 12 sampling times for adults of H. postica. Combined variogram and SADIE showed strong evidence of spatial aggregation of H. postica larval population (~95%) while a moderate level of aggregation in the adult population (~67%) of the sampling times analyzed. The average aggregation distances based on the range value of the variogram were 22.3 m and 14.7 m for larvae and adults, respectively. Based on variogram results, populations of natural enemies, coccinellids and Nabis spp. were found spatially aggregated in 57.9% and 5.6% of the sampling times, respectively. SADIE further supported the variogram results as coccinellid populations (52.6% of sampling times) were highly aggregated in contrast with the Nabis spp. populations (5.6% of sampling times) in alfalfa fields. There was no evidence of significant spatial synchrony between H. postica and its predators, coccinellids and Nabis spp.

CONCLUSION

Our study was able to determine the spatial and temporal distribution of H. postica and its two natural enemies (coccinellids and nabids) in irrigated alfalfa fields. The possible implications of these findings for integrated pest management (IPM) of alfalfa weevil populations are discussed.

Geostatistical Characterization of Cereal Leaf Beetle (Coleoptera: Chrysomelidae) Distributions in Wheat

A 3-yr study was conducted in wheat, Triticum aestivum L., in South Carolina to characterize the spatial distribution of Oulema melanopus (L.) adults, eggs, and larvae using semivariograms, which provides a measure of spatial dependence among sampling data. Moran's I coefficients for peak densities of each life stage indicated significant positive autocorrelation for seven (two for eggs, one for larvae, and four for adults) of the 16 datasets. Aggregation was detected in 13 of these 16 datasets when analyzed by semivariogram modeling, with spherical, Gaussian, and exponential models best fitting for eight, four, and one dataset, respectively, and with models for two datasets having only one parameter (nugget) significantly different from zero. The nugget-to-sill ratios ranged from 0.043 to 0.774, and indicated strong spatial dependence in six models (three for adults, two for eggs, and one for larvae), moderate spatial dependence in six models (three for adults and six for eggs), and weak spatial dependence in one model (adults). Range values varied from 39.1 m to 234.1 m, with an average of 120.1 ± 14.0 m. Average range values were 104.9, 135.2, and 161.2 m for adults, eggs, and larvae, respectively. Because the majority of semivariogram models in our study indicated aggregated distributions, spatial sampling will provide more information than nonspatial random sampling. Developing our understanding of spatial dependence of crop pests is needed to optimize sampling plans and can provide a basis for exploring site-specific management tactics.

Spatial Distribution and Coexisting Patterns of Adults and Nymphs of Tibraca limbativentris (Hemiptera: Pentatomidae) in Paddy Rice Fields

The rice stem stink bug, Tibraca limbativentris Stål (Hemiptera: Pentatomidae), is a primary insect pest of paddy rice in South America. Knowledge of its spatial distribution can support sampling plans needed for timely decisions about pest control. This study aimed to investigate the spatial distribution of adults and nymphs of T. limbativentris and determine the spatial coexistence of these stages of development. Fifteen paddy rice fields were scouted once each season to estimate insect densities. Scouting was performed on regular grids with sampling points separated by ∼50 m. Moran's I and semivariograms were used to determine spatial distribution patterns. Spatial coexistence of nymphs and adults was explored via spatial point process. Here, adults and nymphs had typically contrasting spatial distribution patterns within the same field; however, the frequency of aggregation was not different between these developmental stages. Adults and nymphs were aggregated in seven fields and randomly distributed in the other eight fields. Uniform distribution of adults or nymphs was not observed. The study-wide semivariogram ranges were ∼40 m for adults and ∼55 m for nymphs. Nymphs and adults spatially coexisted on 67% of the fields. Coexisting patterns were classified using one of the following processes: stage-independent, bidirectional attractive, unidirectional attractive, bidirectional inhibiting, or unidirectional inhibiting. The information presented herein can be important for developing sampling plans for decision-making, implementing tactics for site-specific management, and monitoring areas free of T. limbativentris.

Spatial distribution of reniform nematode in cotton as influenced by soil texture and crop rotations

Reniform nematode (RN) is an important pest in cotton production. Knowledge of the distribution patterns of RN is essential for selecting sampling strategies and for site-specific management. A 3-year study was conducted in two fields in South Carolina with the purpose of characterizing the distribution of RN using a fine-scale sampling scheme in plots representing different soil textures (field 1), and using a large-scale arbitrary sampling scheme (field 2). Horizontal distribution data showed an aggregated pattern of RN densities at planting and after harvest in both fields each year, with patches ranging from 8 to 12 m. However, a significant neighborhood structure was only detected when suitable hosts (cotton and soybean) were planted. Correlations between RN densities and percent sand and silt were detected, showing nematode densities peaked when sand content was around 60% and declined when sand content increased above 60 to 65%. When fewer samples were taken in the field with more uniform sand content, percentage of sand was a less reliable predictor of RN densities. Vertical sampling showed the highest numbers of RN were found at 15 to 30 cm deep after cotton, but were deeper after a nonhost crop. Understanding distribution patterns of RN within a field may improve the effectiveness of management practices.

Spatial distribution of grape root borer (Lepidoptera: Sesiidae) infestations in Virginia vineyards and implications for sampling

Grape root borer, Vitacea polistiformis (Harris) (Lepidoptera: Sesiidae) is a potentially destructive pest of grape vines, Vitis spp. in the eastern United States. After feeding on grape roots for ≍2 yr in Virginia, larvae pupate beneath the soil surface around the vine base. Adults emerge during July and August, leaving empty pupal exuviae on or protruding from the soil. Weekly collections of pupal exuviae from an ≍1-m-diameter weed-free zone around the base of a grid of sample vines in Virginia vineyards were conducted in July and August, 2008-2012, and their distribution was characterized using both nonspatial (dispersion) and spatial techniques. Taylor's power law showed a significant aggregation of pupal exuviae, based on data from 19 vineyard blocks. Combined use of geostatistical and Spatial Analysis by Distance IndicEs methods indicated evidence of an aggregated pupal exuviae distribution pattern in seven of the nine blocks used for those analyses. Grape root borer pupal exuviae exhibited spatial dependency within a mean distance of 8.8 m, based on the range values of best-fitted variograms. Interpolated and clustering index-based infestation distribution maps were developed to show the spatial pattern of the insect within the vineyard blocks. The temporal distribution of pupal exuviae showed that the majority of moths emerged during the 3-wk period spanning the third week of July and the first week of August. The spatial distribution of grape root borer pupal exuviae was used in combination with temporal moth emergence patterns to develop a quantitative and efficient sampling scheme to assess infestations.