Two cryptic species of Bemisia tabaci (Gennadius) (Hemiptera: Aleyrodidae), B and Q whiteflies, have been invading many parts of the world. In Japan, Q whiteflies are displacing the predominant B whiteflies. To elucidate the mechanism of whitefly displacement, we compared the reproductive capacities of these species at different temperatures on three host plants and investigated negative interactions in the mixed cohort of mated females of both species. We measured their development times and emergence rates at six temperatures ranging from 20 to 35 °C on tomato, cucumber, and sweet pepper. In addition, we measured their life spans and the number of eggs at 20 and 30 °C on tomato and cucumber. On sweet pepper, B whiteflies mostly did not develop and died as first instar, but Q whiteflies completed their development. On tomato and cucumber, the development times, emergence rates, and life spans of B and Q whiteflies at all experimental temperatures did not differ significantly. B whiteflies had a higher intrinsic rate of population increase (rm) and net reproductive rate (R0) than Q whiteflies at 30 °C on these plants. In a mixed cohort of mated females, Q whiteflies had longer development times than B whiteflies. Furthermore, Q whiteflies had a lower proportion of emerged adults (25.4%) and higher progeny sex ratio (i.e., percentage sons) in the mixed cohort (52.8%) than in the single cohort (36.8%). The reduction in female Q progeny suggests that the interaction between B and Q whiteflies negatively affects only Q whiteflies, resulting in a lower Q population in the presence of B whiteflies. This reduction does not explain the recent displacement of B whiteflies by Q whiteflies in Japan.
The typical short generation length of insects makes their population dynamics highly sensitive not only to mean annual temperatures but also to their intra-annual variations. To consider the combined effect of both thermal factors under global warming, we propose a modeling framework that links general circulation models (GCMs) with a stochastic weather generator and population dynamics models to predict species population responses to inter- and intra-annual temperature changes. This framework was utilized to explore future changes in populations of Bemisia tabaci, an invasive insect pest-species that affects multiple agricultural systems in the Mediterranean region. We considered three locations representing different pest status and climatic conditions: Montpellier (France), Seville (Spain), and Beit-Jamal (Israel). We produced ensembles of local daily temperature realizations representing current and future (mid-21st century) climatic conditions under two emission scenarios for the three locations. Our simulations predicted a significant increase in the average number of annual generations and in population size, and a significant lengthening of the growing season in all three locations. A negative effect was found only in Seville for the summer season, where future temperatures lead to a reduction in population size. High variability in population size was observed between years with similar annual mean temperatures, suggesting a strong effect of intra-annual temperature variation. Critical periods were from late spring to late summer in Montpellier and from late winter to early summer in Seville and Beit-Jamal. Although our analysis suggested that earlier seasonal activity does not necessarily lead to increased populations load unless an additional generation is produced, it is highly likely that the insect will become a significant pest of open-fields at Mediterranean latitudes above 40° during the next 50 years. Our simulations also implied that current predictions based on mean temperature anomalies are relatively conservative and it is better to apply stochastic tools to resolve complex responses to climate change while taking natural variability into account. In summary, we propose a modeling framework capable of determining distinct intra-annual temperature patterns leading to large or small population sizes, for pest risk assessment and management planning of both natural and agricultural ecosystems.
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