Elucidating fitness components of the invasive dermestid beetle Trogoderma granarium combining deterministic and stochastic demography

• Published in: PloS one Vol. 14; no. 2; p. e0212182
• Main Authors: Papanikolaou, Nikos E., Kavallieratos, Nickolas G., Kondakis, Marios, Boukouvala, Maria C., Nika, Erifili P., Demiris, Nikos
• Format: Journal Article
• Language: English
• Published: United States Public Library of Science 14.02.2019; Public Library of Science (PLoS)
• Subjects: Animal Distribution; Animals; Backup software; Beetles; Biology and Life Sciences; Climate change; Coleoptera - physiology; Crop science; Demographics; Demography; Distribution; Earth Sciences; Ecology and Environmental Sciences; Entomology; Environmental aspects; Failure analysis; Female; Females; Fitness; Forecasts and trends; Growth rate; Insect populations; Insecticides; Insects; International trade; Introduced Species; Laboratories; Longevity; Mortality; Organisms; Population; Quarantine; Reproduction; Stochastic models; Stochastic Processes; Stochasticity; Stored products; Surveillance; Temperature; Trogoderma granarium; Zoology; Greece; Europe
• ISSN: 1932-6203; 1932-6203
• DOI: 10.1371/journal.pone.0212182

The invasive dermestid khapra beetle, Trogoderma granarium, is an important pest of stored products that is subject to strict phytosanitary measures. In this study, we conducted a demographic analysis of this species at 30, 35 and 40°C, combining deterministic and stochastic approaches. The net reproductive rate, the intrinsic rate of increase, the finite rate of increase and the doubling time did not differ significantly between 30 and 35°C, while at 40°C we detected negative values of the intrinsic rate of increase and the doubling time. The Briere model fit the data well with respect to the intrinsic rate of increase. Females of roughly 63, 42 and 21 days old reached their maximum reproductive potential at 30, 35 and 40°C, respectively. The stochastic models of this study allowed for checking model fit and the characterization of the most suitable distribution for each component of the process. We expect these results to have bearing on the management of T. granarium since they could be combined with models related to international trade and climatic change, alerting specialists towards early detection strategies against this species.