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Many species interactions are dependent on environmental context, yet the benefits of obligate, mutualistic microbial symbioses to their hosts are typically assumed to be universal across environments. We directly tested this assumption, focusing on the symbiosis between the sap-feeding insect Megacopta cribraria and its primary bacterial symbiont Candidatus Ishikawaella capsulata. We assessed host development time, survival, and body size in the presence and absence of the symbiont on two alternative host plants and in the insects' new invasive range. We found that association with the symbiont was critical for host survival to adulthood when reared on either host plant, with few individuals surviving in the absence of symbiosis. Developmental differences between hosts with and without microbial symbionts, however, were mediated by the host plants on which the insects were reared. Our results support the hypothesis that benefits associated with this host-microbe interaction are environmentally contingent, though given that few individuals survive to adulthood without their symbionts, this may have minimal impact on ecological dynamics and current evolutionary trajectories of these partners. Open research badges This article has earned an Open Data Badge for making publicly available the digitally-shareable data necessary to reproduce the reported results. The data is available at https://doi.org/10.5061/dryad.kg4bc56.

Deep learning is a powerful approach for distinguishing classes of images, and there is a growing interest in applying these methods to delimit species, particularly in the identification of mosquito vectors. Visual identification of mosquito species is the foundation of mosquito-borne disease surveillance and management, but can be hindered by cryptic morphological variation in mosquito vector species complexes such as the malaria-transmitting Anopheles gambiae complex. We sought to apply Convolutional Neural Networks (CNNs) to images of mosquitoes as a proof-of-concept to determine the feasibility of automatic classification of mosquito sex, genus, species, and strains using whole-body, 2D images of mosquitoes. We introduce a library of 1, 709 images of adult mosquitoes collected from 16 colonies of mosquito vector species and strains originating from five geographic regions, with 4 cryptic species not readily distinguishable morphologically even by trained medical entomologists. We present a methodology for image processing, data augmentation, and training and validation of a CNN. Our best CNN configuration achieved high prediction accuracies of 96.96% for species identification and 98.48% for sex. Our results demonstrate that CNNs can delimit species with cryptic morphological variation, 2 strains of a single species, and specimens from a single colony stored using two different methods. We present visualizations of the CNN feature space and predictions for interpretation of our results, and we further discuss applications of our findings for future applications in malaria mosquito surveillance., Author summary Rapid and accurate identification of mosquitoes that transmit human pathogens is an essential part of mosquito-borne disease surveillance. Such identification can be difficult for mosquitoes that transmit malaria, as many are morphologically indistinguishable, including those in the Anopheles gambiae species complex. We photographed 1, 709 individual mosquitoes from 16 laboratory colonies housed at the Centers for Disease Control and Prevention to create a database of whole-body mosquito images. We present a methodology for image processing, data augmentation, and training and validation of a convolutional neural network (CNN). We applied this method to our mosquito image database, finding a 96.96% prediction accuracy for class identification and 98.48% for sex. Further, our best model accurately predicted images between 2 strains of a single species and between 2 storage methods of mosquitoes from the same colony. These results demonstrate that image classification with deep learning can be a useful method for malaria mosquito identification, even among species with cryptic morphological variation. We discuss the application of deep learning to mosquito identification in malaria mosquito surveillance.

Background Biological controls with predators of larval mosquito vectors have historically focused almost exclusively on insectivorous animals, with few studies examining predatory plants as potential larvacidal agents. In this study, we experimentally evaluate a generalist plant predator of North America, Utricularia macrorhiza, the common bladderwort, and evaluate its larvacidal efficiency for the mosquito vectors Aedes aegypti and Aedes albopictus in no-choice, laboratory experiments. We sought to determine first, whether U. macrorhiza is a competent predator of container-breeding mosquitoes, and secondly, its predation efficiency for early and late instar larvae of each mosquito species. Methods Newly hatched, first-instar Ae. albopictus and Ae. aegypti larvae were separately exposed in cohorts of 10 to field-collected U. macrorhiza cuttings. Data on development time and larval survival were collected on a daily basis to ascertain the effectiveness of U. macrorhiza as a larval predator. Survival models were used to assess differences in larval survival between cohorts that were exposed to U. macrorhiza and those that were not. A permutation analysis was used to investigate whether storing U. macrorhiza in laboratory conditions for extended periods of time (1 month vs 6 months) affected its predation efficiency. Results Our results indicated a 100% and 95% reduction of survival of Ae. aegypti and Ae. albopictus larvae, respectively, in the presence of U. macrorhiza relative to controls within five days, with peak larvacidal efficiency in plant cuttings from ponds collected in August. Utricularia macrorhiza cuttings, which were prey-deprived, and maintained in laboratory conditions for 6 months were more effective larval predators than cuttings, which were maintained prey-free for 1 month. Conclusions Due to the combination of high predation efficiency and the unique biological feature of facultative predation, we suggest that U. macrorhiza warrants further development as a method for larval mosquito control.

Meta-analysis of 33 studies of developmental timing of Culex pipiens s.l. Linnaeus demonstrates that development rate, or the rate of progression through immature life stadia, is primarily driven by temperature, whereas immature survival is driven by temperature, density, and variability in the environmental conditions. As expected, the linear relationship of temperature and development rate is positive for the larval period as well as development to adult emergence. However, the strength of this association varies significantly. Variation in development rate can be explained using additional environmental factors of intraspecific rearing density, sex, and study methodology. Heterogeneity in development rates even once temperature has been considered emphasizes the need for further research of multiple environmental factors and in changing environments. Immature survival is also significantly impacted by variability in environmental conditions. Development rates vary between subspecies of Cx. pipiens, but these population differences are no longer significant once an environmental factor of temperature is considered. Thus, variability in development rate of these insects appears to be primarily driven by response to certain environmental conditions rather than differences between populations. Broad patterns of phenotypic variation across latitude and 96 yr of empirical estimates were not significant once environmental rearing conditions had been considered.

Many environmental factors, biotic and abiotic interact to influence organismal development. Given the importance of Aedes aegypti as a vector of human pathogens including dengue and yellow fever, understanding the impact of environmental factors such as temperature, resource availability, and intraspecific competition during development is critical for population control purposes. Despite known associations between developmental traits and factors of diet and density, temperature has been considered the primary driver of development rate and survival. To determine the relative importance of these critical factors, wide gradients of conditions must be considered. We hypothesize that 1) diet and density, as well as temperature influence the variation in development rate and survival, 2) that these factors interact, and this interaction is also necessary to understand variation in developmental traits. Temperature, diet, density, and their two-way interactions are significant factors in explaining development rate variation of the larval stages of Ae. aegypti mosquitoes. These factors as well as two and three-way interactions are significantly associated with the development rate from hatch to emergence. Temperature, but not diet or density, significantly impacted juvenile mortality. Development time was heteroskedastic with the highest variation occurring at the extremes of diet and density conditions. All three factors significantly impacted survival curves of experimental larvae that died during development. Complex interactions may contribute to variation in development rate. To better predict variation in development rate and survival in Ae. aegypti, factors of resource availability and intraspecific density must be considered in addition, but never to the exclusion of temperature.

Background Oviposition-site choice is an essential component of the life history of all mosquito species. According to the oviposition-preference offspring-performance (P-P) hypothesis, if optimizing offspring performance and fitness ensures high overall reproductive fitness for a given species, the female should accurately assess details of the heterogeneous environment and lay her eggs preferentially in sites with conditions more suitable to offspring. Methods We empirically tested the P-P hypothesis using the mosquito species Aedes albopictus by artificially manipulating two habitat conditions: diet (measured as mg of food added to a container) and conspecific density (CD; number of pre-existing larvae of the same species). Immature development (larval mortality, development time to pupation and time to emergence) and fitness (measured as wing length) were monitored from first instar through adult emergence using a factorial experimental design over two ascending gradients of diet (2.0, 3.6, 7.2 and 20 mg food/300 ml water) and CD (0, 20, 40 and 80 larvae/300 ml water). Treatments that exerted the most contrasting values of larval performance were recreated in a second experiment consisting of single-female oviposition site selection assay. Results Development time decreased as food concentration increased, except from 7.2 mg to 20.0 mg (Two-Way CR ANOVA Post-Hoc test, P > 0.1). Development time decreased also as conspecific density increased from zero to 80 larvae (Two-Way CR ANOVA Post-Hoc test, P ). Combined, these results support the role of density-dependent competition for resources as a limiting factor for mosquito larval performance. Oviposition assays indicated that female mosquitoes select for larval habitats with conspecifics and that larval density was more important than diet in driving selection for oviposition sites. Conclusions This study supports predictions of the P-P hypothesis and provides a mechanistic understanding of the underlying factors driving mosquito oviposition site selection.

Background Development rates of Aedes aegypti are known to vary with respect to many abiotic and biotic factors including temperature, resource availability, and intraspecific competition. The relative importance of these factors and their interactions are not well established across populations. We performed meta-analysis on a dataset of development rate estimates from 49 studies. Results Meta-analytic results indicated that the environmental factor of temperature is sufficient to explain development rate variability in Ae. aegypti. While diet and density may greatly impact other developmental phenotypes, these results suggest that for development rate these factors should never be considered to the exclusion of temperature. The effect of temperature on development rate is not homogenous or constant. The sources of heterogeneity of the effect of temperature are difficult to analyze due to lack of consistent reporting of larval rearing methods. Conclusions Temperature is the most important ecological determinant of development rate in Ae. aegypti, but its effect is heterogeneous. Ignoring this heterogeneity is problematic for models of vector population and vector-borne disease transmission.