The Asian vinegar fly Drosophila suzukii (spotted wing Drosophila (SWD)) has emerged as a major invasive insect pest of small and stone fruits in both the Americas and Europe since the late 2000s. While research efforts have rapidly progressed in Asia, North America, and Europe over the past 5 years, important new insights may be gained in comparing and contrasting findings across the regions affected by SWD. In this review, we explore common themes in the invasion biology of SWD by examining (1) its biology and current pest status in endemic and recently invaded regions; (2) current efforts and future research needs for the development of predictive models for its geographic expansion; and (3) prospects for both natural and classical (=importation) biological control of SWD in invaded habitats, with emphasis on the role of hymenopteran parasitoids. We conclude that particularly fruitful areas of research should include fundamental studies of its overwintering, host-use, and dispersal capa- bilities; as well as applied studies of alternative, cost-ef- fective management techniques to complement insecticide use within the integrated pest management framework. Finally, we emphasize that outreach efforts are critical to effective SWD management by highlighting successful

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Invasion biology of spotted wing Drosophila (Drosophila suzukii): a global perspective and future priorities

Two novel and simple mathematical models of arthropod temperature-dependent development are proposed. These models are easy to use and have 3 (equation 1) and 4 (equation 2) ecologically meaningful parameters, respectively. Each parameter can be estimated using nonlinear regression. These models were used to compare developmental rates at constant temperatures for our own experiments on Lobesia botrana (Dennis & Schiffermuller) and for data from 6 insect species described (a total of 13 stages). In all cases, we obtained an accurate nonlinear description of the rate of development against temperature given by the adjusted R 2 ([Kvalseth, 1985][1]). The adjusted R 2 calculated extended from 0.86 to 0.99 and were identical for our equations 1 and 2. In all cases, equation 2 provided the lowest residual sums of squares. The models gave upper T L and lower T temperature threshold estimations, and the estimations obtained were better by using equation 1 rather equation 2. Confidence intervals for each parameter were given and a comparison between estimated and observed temperature thresholds were presented.

 [1]: #ref-11

A Novel Rate Model of Temperature-Dependent Development for Arthropods

The ecology of mosquito vectors and malaria parasites affect the incidence, seasonal transmission and geographical range of malaria. Most malaria models to date assume constant or linear responses of mosquito and parasite life-history traits to temperature, predicting optimal transmission at 31 °C. These models are at odds with field observations of transmission dating back nearly a century. We build a model with more realistic ecological assumptions about the thermal physiology of insects. Our model, which includes empirically derived nonlinear thermal responses, predicts optimal malaria transmission at 25 ° C( 6°C lower than previous models). Moreover, the model predicts that transmission decreases dramatically at temperatures > 28 °C, altering predictions about how climate change will affect malaria. A large data set on malaria transmission risk in Africa validates both the 25 °C optimum and the decline above 28 °C. Using these more accurate nonlinear thermal-response models will aid in understanding the effects of current and future temperature regimes on disease transmission.

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Optimal temperature for malaria transmission is dramatically lower than previously predicted.

The incubation period for malaria parasites within the mosquito is exquisitely temperature-sensitive, so that temperature is a major determinant of malaria risk. Epidemiological models are increasingly used to guide allocation of disease control resources and to assess the likely impact of climate change on global malaria burdens. Temperature-based malaria transmission is generally incorporated into these models using mean monthly temperatures, yet temperatures fluctuate throughout the diurnal cycle. Here we use a thermodynamic malaria development model to demonstrate that temperature fluctuation can substantially alter the incubation period of the parasite, and hence malaria transmission rates. We find that, in general, temperature fluctuation reduces the impact of increases in mean temperature. Diurnal temperature fluctuation around means >21°C slows parasite development compared with constant temperatures, whereas fluctuation around <21°C speeds development. Consequently, models which ignore diurnal variation overestimate malaria risk in warmer environments and underestimate risk in cooler environments. To illustrate the implications further, we explore the influence of diurnal temperature fluctuation on malaria transmission at a site in the Kenyan Highlands. Based on local meteorological data, we find that the annual epidemics of malaria at this site cannot be explained without invoking the influence of diurnal temperature fluctuation. Moreover, while temperature fluctuation reduces the relative influence of a subtle warming trend apparent over the last 20 years, it nonetheless makes the effects biologically more significant. Such effects of short-term temperature fluctuations have not previously been considered but are central to understanding current malaria transmission and the consequences of climate change.

https://www.pnas.org/content/pnas/106/33/13844.full.pdf

Understanding the link between malaria risk and climate.

Recent epidemics of Zika, dengue, and chikungunya have heightened the need to understand the seasonal and geographic range of transmission by Aedes aegypti and Ae. albopictus mosquitoes. We use mechanistic transmission models to derive predictions for how the probability and magnitude of transmission for Zika, chikungunya, and dengue change with mean temperature, and we show that these predictions are well matched by human case data. Across all three viruses, models and human case data both show that transmission occurs between 18-34°C with maximal transmission occurring in a range from 26-29°C. Controlling for population size and two socioeconomic factors, temperature-dependent transmission based on our mechanistic model is an important predictor of human transmission occurrence and incidence. Risk maps indicate that tropical and subtropical regions are suitable for extended seasonal or year-round transmission, but transmission in temperate areas is limited to at most three months per year even if vectors are present. Such brief transmission windows limit the likelihood of major epidemics following disease introduction in temperate zones.

/pdf/detecting-the-impact-of-temperature-on-transmission-of-zika-3g17u21e99.pdf

Detecting the impact of temperature on transmission of Zika, dengue, and chikungunya using mechanistic models.

Effects of temperature on egg, larval, and pupal developmental times of the grape berry moth, Lobesia botrana Dennis & Schiffermuller, were examined at several constant temperatures ranging from 8 to 34°C by 2°C increments, with a relative humidity of 65% and a photoperiod of 16:8 (L:D) h. Optimal temperatures for development ranged from 28 to 30°C. The lower and upper limits occurred between 8 and 12°C and between 32 and 34°C, respectively. The experimental conditions covering the complete temperature range for each stage allowed us to apply the data to 5 published equations describing the effect of constant temperatures on developmental rates of various insects. Criteria of choice from the literature were used to evaluate models and to select the most suitable equation for each developmental stage of L. botrana .

Jean-Francois Briere

Papers

A Novel Rate Model of Temperature-Dependent Development for Arthropods

Comparison of Temperature-Dependent Growth Models with the Development of Lobesia botrana (Lepidoptera: Tortricidae)