| Literature DB >> 25295593 |
P Dilip Venugopal1, Peter L Coffey1, Galen P Dively1, William O Lamp1.
Abstract
The local dispersal of polyphagous, mobile insects within agricultural systems impacts pest management. In the mid-Atlantic region of the United States, stink bugs, especially the invasive Halyomorpha halys (Stål 1855), contribute to economic losses across a range of cropping systems. Here, we characterized the density of stink bugs along the field edges of field corn and soybean at different study sites. Specifically, we examined the influence of adjacent managed and natural habitats on the density of stink bugs in corn and soybean fields at different distances along transects from the field edge. We also quantified damage to corn grain, and to soybean pods and seeds, and measured yield in relation to the observed stink bug densities at different distances from field edge. Highest density of stink bugs was limited to the edge of both corn and soybean fields. Fields adjacent to wooded, crop and building habitats harbored higher densities of stink bugs than those adjacent to open habitats. Damage to corn kernels and to soybean pods and seeds increased with stink bug density in plots and was highest at the field edges. Stink bug density was also negatively associated with yield per plant in soybean. The spatial pattern of stink bugs in both corn and soybeans, with significant edge effects, suggests the use of pest management strategies for crop placement in the landscape, as well as spatially targeted pest suppression within fields.Entities:
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Year: 2014 PMID: 25295593 PMCID: PMC4190369 DOI: 10.1371/journal.pone.0109917
Source DB: PubMed Journal: PLoS One ISSN: 1932-6203 Impact factor: 3.240
Details on field corn and soybean field edges with different adjacent habitats sampled for stink bugs and the sampling occasions at each field in Maryland, USA during 2012–2013.
| Crop | Year | Site | Adjacent habitats (number of field edges) | Sampling dates (frequency) |
| Field Corn | 2012 | Beltsville | woods (4), buildings (3), crops (1), open (4) | 10 July–15 Aug (7–10 days) |
| Clarksville | woods (1), buildings (1), crops (3) | 10 July–15 Aug (7 days) | ||
| 2013 | Clarksville | woods (3), buildings (2), crops (3), open (1) | 18 July–22 Aug (7 days) | |
| Keedysville | woods (1), buildings (1), crops (1), open (2) | 16 July–20 Aug (7 days) | ||
| Overall | woods (9), buildings (7), crops (8), open (7) | 10 July–22 Aug (7–10 days) | ||
| Soybean | 2012 | Beltsville | woods (2), buildings (3), corn (1), open (2) | 23 Aug–20 Sept (7–10 days) |
| Keedysville | woods (2), buildings (1), corn (2), open (1) | 30 Aug–26 Sept (7–10 days) | ||
| 2013 | Beltsville | woods (1), buildings (1), corn (1), open (1) | 13 Aug–06 Sept (7 days) | |
| Clarksville | buildings (1), corn (1), open (1) | 16 Aug–12 Sept (5–7 days) | ||
| Keedysville | woods (2), buildings (1), corn (1), open (1) | 15 Aug–18 Sept (5–7 days) | ||
| Overall | woods (7), buildings (7), corn (6), open (6) | 13 Aug–26 Sept (5–10 days) |
Details on the field corn and soybean fields used for analyzing grain and seed damage in Maryland, USA during 2012–2013.
| Crop | Year | Site | Field ID | Variety | Planting Date | Density/acre |
| Field Corn | 2013 | Clarksville | Corn1 | P1319HR (113) | 2May13 | 26,000 |
| Corn2 | DKC61-21 (111) | 15May13 | 26,000 | |||
| Corn3 | P1319HR (113) | 2May13 | 26,000 | |||
| Corn4 | P1319HR (113) | 2May13 | 26,000 | |||
| Corn5 | DKC61-21 (111) | 16May13 | 26,000 | |||
| Corn6 | NK74R3000GT (114) | 16May13 | 26,000 | |||
| Keedysville | Corn7 | Doebler’s 633HXR (110) | 23Apr13 | 26,000 | ||
| Corn8 | Doebler’s 633HXR (110) | 23Apr13 | 26,000 | |||
| Soybean | 2012 | Beltsville | Soy1 | AG3030 (3.0) | 11May12 | 155,555 |
| Soy2 | AG3030 (3.0) | 11May12 | 155,555 | |||
| Keedysville | Soy3 | Doebler 3809RR (3.8) | 26May12 | 180,000 | ||
| Soy4 | Doebler 3809RR (3.8) | 4Jun12 | 180,000 | |||
| Soy5 | Doebler 3809RR (3.8) | 4Jun12 | 180,000 | |||
| 2013 | Soy6 | SCS9360RR (3.5) | 22May13 | 180,000 | ||
| Soy7 | Doebler 3809RR (3.8) | 27May13 | 180,000 |
For each of the corn and soybean varieties, the corn relative maturity in days and the soybean maturity groups respectively, have been provided in parenthesis.
Figure 1Mean stink bug density in field corn in relation to different adjacent habitats and distance from the field edge.
Estimates derived from Poisson-lognormal GLMMs are plotted for overall stink bug data pooled over all study sites (A), Keedysville (B), Clarksville (C) and Beltsville (D). Values presented here have been back transformed from their original link function estimated model coefficients. Multiple comparison of means with a bonferroni correction (α = 0.05) showed significant differences in: overall (A) - wooded habitats and buildings and, wooded and open habitats; Keedysville (B) – all adjacent habitats significantly different from each other; and Clarksville (C) - wooded habitats and buildings and, wooded and open habitats. For Beltsville (D), all multiple means comparisons were non-significant.
Figure 2Mean stink bug density in soybean field edges in relation to different adjacent habitats and distance from field edge.
Estimates derived from Poisson-lognormal GLMMs are plotted for overall stink bug data pooled over all study sites (A), Keedysville (B), Clarksville (C) and Beltsville (D). Values presented here have been back transformed from its original link function estimated model coefficients. Multiple comparison of means with a bonferroni correction (α = 0.05) showed significant differences in: overall (A) - wooded habitats and buildings, wooded and open habitats, buildings and corn habitats, buildings and open habitats; Keedysville (B) – wooded habitats and buildings, wooded and open habitats, buildings and corn habitats, buildings and open habitat; Clarksville (C) - buildings and open habitats, and corn and open habitats; Beltsville (D) – buildings and open habitats, buildings and wooded habitats, and wooded and corn habitats.
Statistical results of LMMs for analyzing the relationship between stink bug density and various soybean seed damage categories and yield.
| Response variable | Data Transformation | Intercept | Intercept SE | Estimate | SE | DF | Wald t | Pval | psuedo r2 |
| % normal seeds | None | 75.8 | 8.04 | −2.11 | 0.25 | 145 | 8.28 | <0.001 | 0.30 |
| % stink bug damaged seeds | Square Root | 3.41 | 0.5 | 0.07 | 0.01 | 145 | 4.58 | <0.001 | 0.12 |
| % purple damaged seeds | log | 1.39 | 0.14 | 0.09 | 0.01 | 145 | 9.99 | <0.001 | 0.44 |
| % moldy + shriveled + immature seeds | Square Root | 2.59 | 0.47 | 0.09 | 0.02 | 148 | 5.87 | <0.001 | 0.19 |
| % all damaged seeds | Square Root | 4.78 | 0.63 | 0.18 | 0.02 | 145 | 9.03 | <0.001 | 0.35 |
| Total Yield (grams/20 plants) | Square Root | 17.1 | 1.04 | −0.20 | 0.04 | 140 | 4.67 | <0.001 | 0.13 |
Figure 3Patterns of kernel damage in field corn (A), soybean yield (B), soybean seed damage by category (C), and soybean pod development (D) in relation to mean stink bug density at different distance from field edge.
The proportions of soybean seeds in each seed quality category (stink bug damaged, purple damaged, and normal seeds) and pod types (flat and full) are also provided. Mean stink bug abundance are denoted by the dashed lines which represent the second y axis.