Abstract
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.
Highlights
The viability of the populations of living organisms is strongly dependent on their fitness, referring to their ability to survive and reproduce in a specific environment [1]
We propose stochastic models which have been underutilized in demographic studies, as they could provide important information on the functionality of T. granarium
The estimated demographic parameters showed considerable variation across the different temperature regimes used in this study. This was evident based upon the inspection of the 95% confidence intervals (Table 1) which were used for hypothesis testing
Summary
The viability of the populations of living organisms is strongly dependent on their fitness, referring to their ability to survive and reproduce in a specific environment [1]. Survival and reproduction are critical aspects of population dynamics, regulating their growth rate and allowing for several temporal fluctuations [2,3,4]. To this end, ecologists are often interested in understanding the patterns of these biological features in order to describe and predict populations’ performance [5,6,7]. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript
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