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Life Table Parameters of Three Mirid Bug (Adelphocoris) Species (Hemiptera: Miridae) under Contrasted Relative Humidity Regimes
The genus Adelphocoris (Hemiptera: Miridae) is a group of important insect pests of Bt cotton in China. The three dominant species are A. lineolatus, A. suturalis, and A. fasciaticollis, and these species have different population dynamics. The causal factors for the differences in population dynami...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2014
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4277414/ https://www.ncbi.nlm.nih.gov/pubmed/25541705 http://dx.doi.org/10.1371/journal.pone.0115878 |
Sumario: | The genus Adelphocoris (Hemiptera: Miridae) is a group of important insect pests of Bt cotton in China. The three dominant species are A. lineolatus, A. suturalis, and A. fasciaticollis, and these species have different population dynamics. The causal factors for the differences in population dynamics have not been determined; one hypothesis is that humidity may be important for the growth of Adelphocoris populations. In the laboratory, the demographic parameters of the three Adelphocoris species were compared when the mirid bugs were subjected to various levels of relative humidity (40, 50, 60, 70 and 80% RH). Middle to high levels of RH (60, 70 and 80%) were associated with higher egg and nymph survival rates and increased adult longevity and female fecundity. Lower humidity levels (40 and 50% RH) had negative effects on the survival of nymphs, adult longevity and fecundity. The intrinsic rate of increase (r(m)), the net reproductive rate (R(0)) and the finite rate of increase (λ) for each Adelphocoris species increased with increasing RH. Significant positive relationships were found between RH and the life table parameters, r(m), R(0) and λ for the three Adelphocoris species. These results will help to better understand the phenology of the three Adelphocoris species, and the information can be used in population growth models to optimize pest forecasting and management strategies for these key pests. |
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