Impact of larval diet on fitness outcomes of Aedes aegypti mosquitoes infected with wAlbB and wMelM

Impact of larval diet on fitness outcomes of Aedes aegypti mosquitoes infected with wAlbB and wMelM | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Impact of larval diet on fitness outcomes of Aedes aegypti mosquitoes infected with wAlbB and wMelM Mohd Farihan Md Yatim, Perran Stott-Ross, Xinyue Gu, Ary Anthony Hoffmann This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6459379/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 24 Sep, 2025 Read the published version in Parasites & Vectors → Version 1 posted 10 You are reading this latest preprint version Abstract Background Releases of Aedes aegypti infected with Wolbachia are being used to effectively control diseases related to arboviruses in some settings. A well-balanced larval diet is essential for producing Wolbachia- infected mosquitoes with optimal fitness for release. Methods In this study, four diets with varying protein-to-carbohydrate ratios were tested with three Aedes aegypti lines (carrying the w AlbB, w MelM infections or uninfected) to identify optimal diets for larval rearing based on diet allocations ranging from 0.4 to 3.2 mg/larva/day. The diets were selected based on a review of existing literature and are characterized by progressively increasing protein and decreasing carbohydrate content: Diet 1(Pd) was based on plant-based protein (low protein, high carbohydrate), Diet 2 (Kd) was based on animal-based protein (moderate protein, high carbohydrate), Diet 3 (Fd)- involved Hikari fish food (high protein and moderate carbohydrate), and Diet 4 (IAEA) followed a widely used very high protein and low carbohydrate diet developed by the International Atomic Energy Agency (IAEA). The optimal concentration for each diet was determined using a fitness index that incorporated pupation success, fecundity, hatch proportion, and development time. Results The optimal dietary allocations for Diets 1 to 4 were 1.6, 1.2, 1.2, and 0.8 mg per larva per day, respectively, regardless of Wolbachia status. There was a consistent significant positive relationship between female wing length and fecundity in w AlbB (r 2 = 0.881), w MelM (r 2 = 0.329), and uninfected (r 2 = 0.886) mosquitoes. Diet 3 (Fd) reduced a fitness cost commonly associated with the w AlbB line compared to the uninfected line when provided at the optimal concentration. The w MelM line showed a persistently low fecundity regardless of diet and concentration. Conclusions These findings highlight the importance of an appropriate larval diet and dietary allocations in optimizing mosquito fitness for Wolbachia -based vector control programs. Further research into dietary composition, gut microbial interactions, and Wolbachia associations could refine larval nutrition strategies, enhancing the effectiveness of mass-rearing for release programs. Wolbachia wMelM wAlbB larval diet optimum concentrations fitness traits dengue control Aedes aegypti Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Background Wolbachia releases are being undertaken for the control of arboviruses across the world [ 1 , 2 , 3 , 4 ]. Two general approaches have been identified. (a) The release of Wolbachia -infected adult males that can lead to suppression of the mosquito population through cytoplasmic incompatibility (CI), which results in non-viable offspring when infected males mate with uninfected females [ 5 , 6 ]. (b) The release of both male and female Wolbachia -infected mosquitoes with the aim of replacing the wild mosquito population with mosquitoes carrying a Wolbachia strain [ 7 , 8 , 9 ]. These novel techniques have demonstrated success in limiting disease transmission [ 4 , 10 , 11 ] compared to conventional insecticide spraying which carries significant environmental and economic costs. Both Wolbachia -based strategies rely on the large-scale production of mosquitoes that can either compete with wild-type males for mating (suppression strategy) or establish a self-sustaining Wolbachia -infected population (replacement strategy) through release of females that can compete with wild females for breeding sites and transmit the Wolbachia infection, as well as having competitive males that induce cytoplasmic incompatibility. In the context of mosquito mass rearing programs for vector-borne disease intervention, producing highly competitive Aedes aegypti mosquitoes that can compete with wild mosquitoes is essential. An effective larval diet is important to achieve this objective. Various diets have been tested for Ae. aegypti larval growth and the most often used diets are the IAEA diet (developed by the International Atomic Energy Agency) and diets incorporating commercial fish food such as TetraMin [ 12 , 13 ]. Commonly used as a standard reference in many studies, the IAEA diet consists of 50% tuna powder, 35% liver powder, and 15% Brewer's yeast [ 14 ]. A balanced protein and carbohydrate larval diet ratio can lead to the production of larger wings in Ae. aegypti mosquitoes [ 15 ] whereas microorganisms and algae diets resulted in reduced adult survival, suggesting poor nutrition [ 16 ]. In contrast, diets based on various animal-based sources (porcine, beef liver, fish food, and beef liver–shrimp powder combinations) yield better development and survival [ 17 ]. However, these diets have been tested at relatively low feeding rates (average 0.41 mg per larva per day), whereas feeding rates for rearing Aedes mosquitoes at a medium-scale have been as high as 0.84 mg per larva per day [ 18 ]. In another study, the largest wings in Ae. aegypti infected with w Mel and w MelPop strain were observed using the Tetramin fish food diet at 1 mg per larva per day [ 19 ]. Several studies have found that the microbiome in the mosquito gut is essential for digestion, immune function, and shaping mosquito fitness [ 20 , 21 , 22 , 23 ]. In one study examining microbiome density in mosquitoes, high larval food allocation (up to 2 mg per larva per day) was shown to increase gut microbiome density, which remained at a high level even after eclosion and blood feeding [ 24 ]. This raises the question whether certain microbiome or gut bacterial density could play a role to improve mosquito fitness. Generally, most of the nutritional studies were conducted on uninfected Ae. aegypti lines. However, a study in Drosophila showed that Wolbachia can increase fertility in response to dietary changes [ 25 ]. There is a macronutrient balance that moderates the functional link between Drosophila and Wolbachia , hence affecting reproductive success [ 26 ]. Additionally, under nutritional stress, Wolbachia may supply nutrients to the host, indicating a possible compensating function of Wolbachia when meal quality is poor [ 27 ]. Turning to Ae . aegypti , diets based on animal sources showed no negative impacts on Wolbachia density, development time or survival of w AlbB-infected Ae. aegypti [ 28 ]. However, blood meal quality—including artificial or nutrient-modified meals—was found to influence Wolbachia -infected mosquito performance [ 29 ], and starvation modulated Wolbachia fitness effects [ 30 ]. These results taken together highlight the need of taking dietary environment and infection status into consideration while assessing mosquito fitness characteristics. To address these issues, this study evaluates the effects of different larval diets on Wolbachia -infected ( w AlbB and w MelM-strains described in [ 31 ] and [ 32 ]) and uninfected mosquitoes by examining a range of protein and carbohydrate compositions, including both plant- and animal-based protein sources. The study examines how both diet composition and concentration affect key fitness traits, including development time, survival, wing length, fecundity, and egg hatchability across Wolbachia- infected and uninfected Ae. aegypti mosquitoes. Potential trade-offs between fitness traits are also explored, along with the influence of Wolbachia infection status on dietary responses. By evaluating these key life traits, we explored whether optimum diets and concentrations could help mitigate the fitness costs associated with Wolbachia infection in Ae. aegypti mosquitoes. Methods Ethical statement Blood feeding on adult human volunteers was approved by the University of Melbourne Human Ethics committee (project ID 28583). Informed consent was obtained from all subjects. A single volunteer for blood feeding was used across all experiments to ensure consistency in blood meals. Mosquito maintenance The Ae. aegypti mosquito lines used in this study were either infected with the w MelM or w AlbB strains of Wolbachia or uninfected. All lines had a Cairns, Australia, genetic background and were maintained in the laboratory for at least 60 generations. The w MelM line is a variant of w Mel, derived from a field-collected Drosophila melanogaster , and exhibits greater heat tolerance than w Mel [31]. The w AlbB line was derived from a trans-infection [33] developed by [32] involving the transfer of the infection to Ae. aegypti with a Cairns, Australia mitochondrial haplotype. To ensure a consistent nuclear background, females from all three lines were backcrossed to males from a different uninfected line derived from Cairns for four generations prior to the experiment. Mosquito colonies were maintained under a 12-hour light/12-hour dark cycle at 26°C. Larval Diets The composition of the diets is outlined in Table 1. These diets were selected to represent a range of protein and carbohydrate compositions. Diet 1 or Plant-based diet (Pd) contains 58% carbohydrate (C) and 17% protein (P), representing a high carbohydrate/low protein diet [34]; Diet 2 or Khan Diet (Kd) contains 52% (C) and 23% (P), representing a high carbohydrate/moderate protein diet [34, 35]; Diet 3 or Hikari fish food (Fd) diet contains 24% (C) and 36% (P), representing a moderate carbohydrate / high protein diet; Diet 4 or the IAEA [14] diet contains 2% (C) and 72% (P), representing a low carbohydrate/very high protein diet. The complete macronutrient content of all diets is shown in Table 2. Table 1. Ingredients list for all four diets (10g / diet) Diet 1 (Pd) Diet 2 (Kd) Diet 3 (Fd) Diet 4 (IAEA) Bean (2g) Bean (1.2g) Hikari Fish Food (10g) Brewer’s Yeast (1.5g) Chickpea (2g) Chickpea (1.8g) Ingredients : Fish meal, wheat germ meal, soybean meal, wheat flour, whole crushed silkworm pupae, dried seaweed meal, dried bakery product, brewers dried yeast, fish oil, krill meal, spirulina, garlic, DL-methionine, astaxanthin, choline chloride, vitamin E supplement, L-ascorbyl-2-polyphosphate (stabilized vitamin C), inositol, d-calcium pantothenate, riboflavin, vitamin A supplement, thiamine mononitrate, pyridoxine hydrochloride, niacin, folic acid, vitamin D3 supplement, biotin, disodium phosphate, ferrous sulfate, magnesium sulfate, zinc sulfate, manganese sulfate, copper sulfate, calcium iodate. Liver Powder (3.5g) Mung Bean (2g) Corn (1.8g) Tuna Powder (5g) Mushroom (2g) Liver Powder (2.2g) Rice (2g) Rice (1.8g) Wheat (1.2g) 10g 10g 10g 10g Table 2. Macronutrients content in all diets (per 10g) Macronutrients Diet 1 (Pd) Diet 2 (Kd) Diet 3 (Fd) Diet 4 (IAEA) Carbohydrate 5.758 g (57.58%) 5.151g (51.51%) 2.42g (24.20%) 0.16g (1.6%) Protein 1.698 g (16.98%) 2.348 g (23.48%) 3.6g (36.00%) 7.17 g (71.70%) Fat 0.3 g (3.00%) 0.520 g (5.20%) 0.9 g (9.00%) 1.115g (11.15%) Ingredient preparation Commercially available wheat flour ( White Wings Premium Plain Flour ; White Wings, Australia), rice flour ( Erawan Brand ; Cho Heng Rice Vermicelli Factory Co. Ltd., Thailand), corn flour ( Sunflower Corn Flour ; Singapore), chickpea flour ( McKenzie's Australian Chick Pea Flour ; McKenzie's Foods, Australia), mung bean flour ( Xinliang Mung Bean Starch , China), beef liver powder ( Barbell Organic Beef Liver ; Barbell Foods, Australia), Brewer’s yeast ( Macro Wholefoods Market ; Woolworths, Australia) and Hikari fish food ( Hikari Tropical Sinking Wafers; Kyorin Food Industries, Japan) were used. Fresh mushrooms ( Agaricus bisporus ) and tuna in water ( Ocean Rise®; ALDI Stores, Australia) were chopped into small pieces, dried at 50°C for six hours, and ground into powder. All flours and powders were sifted through a fine strainer, and a 2% solution was prepared by mixing 10 g of each diet with 500 mL of reverse osmosis (RO) water. Larval development time and survival Eggs from each mosquito line were hatched in reverse osmosis (RO) water with a small amount of Brewer’s yeast. After 12 hours, 50 first-instar larvae were transferred into plastic containers filled with 500 mL of RO water and assigned to diet treatments at concentrations of 0.4, 0.8, 1.2, 1.6, and 3.2 mg/larva/day. Note that we use the term “concentration” and “allocation” interchangeably in the paper because a higher allocation is expected to result in a higher concentration of food. Each concentration/diet/line combination was tested as six replicates (300 larvae in total per treatment). Across the three mosquito lines, 4,500 larvae were assessed per diet, resulting in a total sample size of 18,000 larvae for all four diets. Given the large sample size and impacts on development time, diet treatments had to be tested in separate experiments even though they were set up within a few days of each other. Larval development time, defined as the duration from egg hatching to pupation, was recorded twice daily (morning and evening) starting from the onset of pupation. Pupae were counted, sexed, and transferred to designated containers within rearing cages according to their respective lines and concentrations. This process was consistently applied across all diet treatments. Survival was defined as the proportion of first-instar larvae that successfully pupated and calculated as the number of pupae divided by the initial number of first-instar larvae. Wing length measurement Fifteen two- to four-day-old adult males and females from each concentration and line were selected and preserved in 100% ethanol for wing length measurement. Wings were dissected using forceps under a stereomicroscope. Measurements were taken using a Nikon SMZ1500 microscope equipped with a camera and IS Capture software. Wing length was determined as the distance from the alular notch to the radius 3 vein. Fecundity and egg hatch All concentration/line combinations for a diet were blood fed on the same day; however, due to differences in larval development time across diet concentrations, the age of females at the time of blood feeding varied between 4- and 7-days post-emergence. After blood feeding, twenty fully engorged females were transferred to small plastic containers lined with sandpaper ( Norton Master Painters P80 ; Saint-Gobain Abrasives Pty. Ltd., Thomastown, Victoria, Australia) and partially filled with RO water to facilitate oviposition. Eggs were collected by removing the sandpaper after four days. Females that did not lay eggs within this period remained in the containers until day 7 to account for potential late oviposition. Collected eggs were stored for three days before hatching trials. On the third day, RO water and a small amount of Brewer’s yeast ( Macro Wholefoods Market ; Woolworths, Australia) were added to the container to stimulate hatching. After 24 hours, fecundity was measured as the total number of eggs per female, while hatch proportion was calculated as the total number of hatched eggs divided by the total number of eggs laid. Statistical analysis A two-way ANOVA followed by Tukey’s-b post-hoc tests was performed to evaluate fitness traits across mosquito lines and diet concentrations. Partial eta squared values (η²) were computed to reflect effect sizes. As each diet was tested separately, analyses did not involve a direct comparison across diets. Hatch proportion and survival data were logit-transformed [36] while other measures were not transformed. Pearson correlation analysis was conducted to assess the relationship between female wing length and fecundity. The optimal allocation/concentration for each diet was determined by computing life table scores by multiplying the averages of fecundity, hatch proportion, and pupation success (survival) proportion, and then dividing by the development time [37]. All statistical analyses were performed using IBM SPSS Statistics version 29. Graphs were generated using RStudio (version 2024.12.0, Build 467), and further graphical edits were performed in Inkscape (version 1.4). Results Development time Two-way ANOVA showed a significant effect of lines and concentration on mosquito development time across all diets (Figure 1A-D, Table 3-6; all p < 0.015). Higher allocations consistently resulted in shorter development times, indicating a strong dose-dependent relationship (Figure 1A-D, Table 3-6; all p < 0.001). Significant interaction effects between mosquito lines and concentration were observed only in Diet 4 (IAEA) (Table 6; p < 0.001), suggesting variability in how mosquito lines responded to changes in food concentration in this particular diet. Pupation success (Survival) In the ANOVAs concentration significantly influenced the proportion of larvae surviving to the pupal stage across all diets (Figure 1E-H, Table 3-6; all p < 0.001). Mosquito line effects were not significant for any diet, indicating no overall consistent differences among the lines. Interaction effects between mosquito lines and concentration were not significant for Diets 1 (Pd), 2 (Kd) and 3 (Fd), suggesting the effect of concentration on survival was consistent across lines for these diets. While concentration consistently influenced survival across all diets, only Diet 4 (IAEA) showed a marginal interaction (Table 6; p = 0.050, η² = 0.180). Table 3. Two-way ANOVA results for development time, survival proportion, wing length, fecundity and hatch proportion for Diet 1 (Pd). Dependent Variable Source Type III Sum of Squares df Mean Square F p value Partial Eta Squared (η²) Development Time Lines 4.330 2 2.165 8.807 <0.001 0.190 Concentration 166.491 4 41.623 169.324 <0.001 0.900 Lines * Concentration 2.013 8 0.252 1.023 0.426 0.098 Error 18.436 75 0.246 Survival Proportion (logit transformed) Lines 4.314 2 2.157 2.355 0.102 0.059 Concentration 42.305 4 10.576 11.548 <0.001 0.381 Lines * Concentration 5.507 8 0.688 0.752 0.646 0.074 Error 68.688 75 0.916 Wing Length (Male) Lines 0.057 2 0.028 3.316 0.038 0.031 Concentration 1.968 4 0.492 57.246 <0.001 0.522 Lines * Concentration 0.125 8 0.016 1.816 0.076 0.065 Error 1.805 210 0.009 Wing Length (Female) Lines 0.048 2 0.024 2.456 0.088 0.023 Concentration 4.430 4 1.108 112.250 <0.001 0.681 Lines * Concentration 0.338 8 0.042 4.280 <0.001 0.140 Error 2.072 210 0.010 Fecundity Lines 21707.625 2 10853.813 42.537 <0.001 0.252 Concentration 11657.967 4 2914.492 11.422 <0.001 0.153 Lines * Concentration 3764.767 8 470.596 1.844 0.069 0.055 Error 64555.772 253 255.161 Hatch Proportion (Logit Transformed) Lines 60.832 2 30.416 35.754 <0.001 0.229 Concentration 10.643 4 2.661 3.128 0.016 0.049 Lines * Concentration 33.710 8 4.214 4.953 <0.001 0.141 Error 205.020 242 0.851 Table 4. Two-way ANOVA Results for Development Time, Survival Proportion, Wing Length, Fecundity and Hatch Proportion for Diet 2 (Kd). Dependent Variable Source Type III Sum of Squares df Mean Square F p value Partial Eta Squared (η²) Development Time Lines 0.502 2 0.251 4.472 0.015 0.107 Concentration 41.145 4 10.286 183.407 <0.001 0.907 Lines * Concentration 0.444 8 0.056 0.991 0.450 0.096 Error 4.206 75 0.056 Survival Proportion (logit transformed) Lines 2.741 2 1.371 1.761 0.179 0.045 Concentration 46.522 4 11.631 14.946 <0.001 0.444 Lines * Concentration 4.477 8 0.560 0.719 0.674 0.071 Error 58.365 75 0.778 Wing Length (Male) Lines 0.044 2 0.022 3.399 0.035 0.031 Concentration 0.954 4 0.239 36.736 <0.001 0.412 Lines * Concentration 0.179 8 0.022 3.445 <0.001 0.116 Error 1.364 210 0.006 Wing Length (Female) Lines 0.662 2 0.331 24.983 <0.001 0.192 Concentration 2.650 4 0.662 49.965 <0.001 0.488 Lines * Concentration 0.574 8 0.072 5.410 <0.001 0.171 Error 2.784 210 0.013 Fecundity Lines 55470.826 2 27735.413 72.775 <0.001 0.361 Concentration 45541.502 4 11385.375 29.874 <0.001 0.317 Lines * Concentration 17649.577 8 2206.197 5.789 <0.001 0.152 Error 98327.376 258 381.114 Hatch Proportion (Logit Transformed) Lines 26.900 2 13.450 19.732 <0.001 0.137 Concentration 16.824 4 4.206 6.171 <0.001 0.090 Lines * Concentration 23.201 8 2.900 4.255 <0.001 0.120 Error 169.725 249 0.682 Table 5. Two-way ANOVA Results for Development Time, Survival Proportion, Wing Length, Fecundity and Hatch Proportion for Diet 3 (Fd). Dependent Variable Source Type III Sum of Squares df Mean Square F p value Partial Eta Squared (η²) Development Time Lines 1.186 2 0.593 56.680 <0.001 0.602 Concentration 10.678 4 2.670 255.265 <0.001 0.932 Lines * Concentration 0.091 8 0.011 1.082 0.385 0.103 Error 0.784 75 0.010 Survival Proportion (logit transformed) Lines 4.636 2 2.318 1.510 0.228 0.039 Concentration 44.983 4 11.246 7.325 <0.001 0.281 Lines * Concentration 9.142 8 1.143 0.744 0.652 0.074 Error 115.142 75 1.535 Wing Length (Male) Lines 0.006 2 0.003 0.781 0.459 0.007 Concentration 0.836 4 0.209 50.278 <0.001 0.489 Lines * Concentration 0.101 8 0.013 3.047 0.003 0.104 Error 0.873 210 0.004 Wing Length (Female) Lines 0.027 2 0.013 1.365 0.258 0.013 Concentration 3.073 4 0.768 78.412 <0.001 0.599 Lines * Concentration 0.145 8 0.018 1.849 0.070 0.066 Error 2.058 210 0.01 Fecundity Lines 113003.450 2 56501.725 106.631 <0.001 0.445 Concentration 16478.966 4 4119.741 7.775 <0.001 0.105 Lines * Concentration 5341.724 8 667.715 1.260 0.265 0.037 Error 140948.285 266 529.881 Hatch Proportion (Logit Transformed) Lines 99.245 2 49.623 58.941 <0.001 0.314 Concentration 6.533 4 1.633 1.940 0.104 0.029 Lines * Concentration 14.165 8 1.771 2.103 0.036 0.061 Error 216.370 257 0.842 Table 6. Two-way ANOVA Results for Development Time, Survival Proportion, Wing Length, Fecundity and Hatch Proportion for Diet 4 (IAEA). Dependent Variable Source Type III Sum of Squares df Mean Square F p value Partial Eta Squared (η²) Development Time Lines 1.554 2 .777 41.808 <0.001 0.527 Concentration 6.216 4 1.554 83.615 <0.001 0.817 Lines * Concentration .750 8 0.094 5.042 <0.001 0.350 Error 1.394 75 0.019 Survival Proportion (logit transformed) Lines 0.914 2 0.457 1.724 0.185 0.044 Concentration 16.819 4 4.205 15.869 <0.001 0.458 Lines * Concentration 4.370 8 0.546 2.061 0.050 0.180 Error 19.873 75 0.265 Wing Length (Male) Lines 0.087 2 0.043 10.644 <0.001 0.092 Concentration 0.044 4 0.011 2.725 0.030 0.049 Lines * Concentration 0.40 8 0.005 1.232 0.282 0.045 Error 0.854 210 0.004 Wing Length (Female) Lines 0.294 2 0.147 14.105 <0.001 0.118 Concentration 0.144 4 0.036 3.462 0.009 0.062 Lines * Concentration 0.159 8 0.020 1.909 0.060 0.068 Error 2.190 210 0.010 Fecundity Lines 44185.373 2 22092.686 44.991 <0.001 0.254 Concentration 5902.170 4 1475.542 3.005 0.019 0.044 Lines * Concentration 4526.728 8 565.841 1.152 0.329 0.034 Error 129637.431 264 491.051 Hatch Proportion (Logit Transformed) Lines 90.030 2 45.015 63.734 <0.001 0.328 Concentration 4.178 4 1.044 1.479 0.209 0.022 Lines * Concentration 7.617 8 0.952 1.348 0.220 0.040 Error 184.343 261 0.706 Male wing length Two-way ANOVAs showed that concentration significantly influenced male wing length in all diets (Figure 2A-D, Table 3-6; all p ≤ 0.030). Mosquito line significantly affected male wing length in Diets 1 (Pd), 2 (Kd), and 4 (IAEA) (p ≤ 0.038), but not in Diet 3 (Fd) (p = 0.459). Significant interaction effects between mosquito line and concentration were observed in Diets 2 (Kd) (Table 4; p < 0.001) and 3 (Fd) (Table 5; p = 0.003), indicating that the impact of concentration varied by mosquito line for these diets. Increasing food concentrations significantly enhanced male wing length, with the strongest effects observed for Diets 1 (Pd) to 3 (Fd) (Table 3-5; all p < 0.001). For Diet 4 (IAEA), the relationship was weaker but still statistically significant (p = 0.030). Differences between mosquito lines were generally smaller, varying by diet and concentration, and indicating no consistent pattern of line superiority across all diets. Female wing length In two-way ANOVAs, food concentration significantly influenced female wing length across all diets (Figure 2E-H, Table 3-6; all p ≤ 0.009). Mosquito line had a significant effect on female wing length only in Diets 2 (Kd) and 4 (IAEA) (Figure 2F and 2H, Table 4 and 6; both p < 0.001). Additionally, significant interaction effects between mosquito line and concentration were found in Diets 1 (Pd) and 2 (Kd) (Figure 2E and 2F, Table 3-4; both p < 0.001), suggesting that the effect of food concentration on wing length varied by mosquito line in these diets. Fecundity The ANOVAs indicated significant effects of mosquito lines and concentration on fecundity across all diets (Figure 3A-D, Table 3-6, p ≤ 0.0019). Significant interactions between mosquito lines and concentration were observed only in Diet 2 (Kd) (Table4; p < 0.001), reflecting an effect of concentration on fecundity among mosquito lines in this diet. The uninfected line typically exhibiting higher fecundity compared to the w MelM and w AlbB lines (Figure 3A-D). Specifically, w MelM consistently had the lowest fecundity, significantly differing from both uninfected and w AlbB lines across all diets. Hatch proportion The ANOVAs indicated significant differences in hatch proportion among mosquito lines across all diets (Figure 3E-H, Table 3-6, Diet 1–4, all p < 0.001). Concentration significantly influenced hatch proportion only in Diets 1 (Pd) and 2 (Figure 3E and 3F, Table 3 and 4; p ≤ 0.016), but not in Diets 3 (Fd) and 4 (IAEA) (Figure 3G and 3H, Table 5 and 6; p ≥ 0.104). Interaction effects between mosquito line and concentration were significant in Diets 1, 2, 3, but not in Diet 4 (IAEA) (Table 6; p ≥ 0.220). Relationship between female wing length and fecundity For female mosquitoes, a strong positive correlation was observed between wing length and fecundity (Figure 4) in both the uninfected (r 2 = 0.881) and w AlbB (r 2 = 0.886) lines when combining data across diets, indicating that larger females consistently produced more eggs. The relationship was mostly linear except at higher fecundities, and the data suggest that wing length is a reliable predictor of fecundity in these two lines. In w MelM, there was a weaker association (r 2 = 0.329). The reasons for this were unclear, since the fecundity and wing length values for this line covered a similar range than the other lines. Optimal concentration The Fitness Index used in this study was developed based on mosquito fitness traits, following the method described in [37]. The optimal concentration was 1.6 mg/larva/day for Diet 1 (Pd), and 1.2 mg/larva/day for Diet 2 (Kd) and Diet 3 (Fd). For Diet 4 (IAEA) the optimum concentration was 0.8 mg/larva/day, indicating that diet composition and concentrations influence mosquito fitness. Almost all mosquito lines reached their maximum Fitness Index at identical concentrations within each diet, suggesting that the quantity of food at a specific composition is more influential in determining fitness than features unique to each line. The similar patterns across lines may indicate a common nutrient absorption that optimizes performance for each dietary type. Discussion Diet allocation always had big impact on almost all fitness traits as shown in Table 3-6 and Figure 1-3. Fitness traits tended to increase at intermediate concentrations before decreasing again at high concentrations of larval food. Effects of lines ( w MelM, w AlbB or uninfected) were also detected, with uninfected larvae tending to perform better in fecundity and egg hatching, as shown in Figure 3. The overall impact of line was less evident compared to diet concentrations; however, in the w MelM line, reduced fecundity consistently occurred across all diets. This reduction was suspected to be due to the blood- meal-related rather than the larval diet factor. The low fecundity in w Mel was also reported in another study [38]. However, in Diet 2 (Kd) at 1.2 mg/larva/day concentration, high fecundity and hatch proportion in the w MelM line at this concentration were detected. This variation could be due to uncontrolled variability in the experiment, which may have led to a lower Wolbachia density and therefore reduced symbiont-induced reproductive suppression. Further analysis of the Wolbachia screening data in the w MelM line across food allocations will help us to further test this hypothesis. In high-carbohydrate diets, the protein composition of the larval diet strongly influenced mosquito fitness traits. Increased protein content significantly improved developmental outcomes, supporting previous findings on the critical role of dietary protein in larval growth, development rate, and adult size in Aedes aegypti and related species [39, 40, 41]. Under a plant-based, low-protein diet, the proportion of pupation success remained relatively high despite delayed development, indicating that while energy availability can sustain survival, it is insufficient for optimal growth. In other work, replacing mushroom powder with animal-based liver powder markedly enhanced fitness traits and reduced development time [34]. When comparing a balanced diet (Diet 3 (Fd)) with a very high-protein, low-carbohydrate diet (Diet 4 (IAEA)), the fastest larval development was observed under Diet 4 (IAEA) across all Ae. aegypti lines. This is consistent with earlier findings showing that elevated dietary protein levels enhance developmental speed [42, 43]. However, this rapid development was accompanied by reduced female wing length, suggesting an environmentally based trade-off between development speed and adult fitness. A more balanced protein–carbohydrate ratio larval diet (LRD) produced larger females in uninfected Ae. aegypti compared to a high-protein, low-carbohydrate diet [42]. In contrast, male wing length showed similar trends across both Diet 3 (Fd) and Diet 4 (IAEA), with minimal variation between diets or lines. This suggests a potential physiological constraint on male body size, whereby males may reach a species-specific upper limit regardless of nutritional conditions. This observation aligns with previous findings showing that female size was more responsive to dietary variation, while male size remained relatively stable across nutritional conditions [15]. Bigger females are a good indicator of higher fecundity, as larger individuals have a better ability to hold a greater volume of blood and possess higher energy reserves for egg production[44]. A diet with a balanced carbohydrate and protein content tends to result in higher lipid reserves at the adult stage, compared to a high-protein, low-carbohydrate diet, which can lead to reduced size and lower energy storage despite faster development [45]. Diet 3 (Fd) and Diet 4 (IAEA) consistently yielded higher fitness index scores in Aedes aegypti than the carbohydrate-rich, low-protein diet. Among the diets tested, Diet 3 (Fd), supported the highest composite life table scores across in w AlbB and uninfected line at optimal concentration for maximizing development, survival, and reproductive output. These results are consistent with the possibility that improved larval nutrition could mitigate Wolbachia -associated fitness costs [7, 46] particularly for w AlbB-infected mosquitoes, which in this study performed nearly as well as the uninfected line at optimum concentration. The narrowing gap in life table scores between w AlbB and uninfected mosquitoes suggests that nutritional quality can buffer fitness costs and improve competitiveness. In contrast, in w MelM, reduced fecundity was observed despite adequate wing length, suggesting that other contributing factors beyond larval nutrition. This is consistent with predictions from metabolic modelling studies indicating that Wolbachia strains such as w Mel may rely on host-derived lipids and amino acids for growth, potentially influencing pathways relevant to reproduction. [47]. Blood source may also be a factor, since a previous study on w MelM using Diet 3 (Fd) but with a different human volunteer did not identify any costs to fertility [31]. Conclusions In this study, we found that diet composition and allocation play a significant role in determining key life traits of mosquitoes. A well-balanced protein and carbohydrate content produces mosquitoes with higher fitness compared to diets with lower protein content. The uninfected mosquito line showed the highest overall fitness across all diets compared to the w MelM and w AlbB lines. However, with a balanced diet and at an optimum concentration, the w AlbB line seems to mitigate the fitness cost of Wolbachia infection. In contrast, the w MelM line showed lower fecundity across all diets, probably due to factors other than the larval diet. Overall, almost all mosquito lines achieved maximum fitness scores at the same concentration. The different responses among mosquito lines also suggest that gut microbiota could play an important role in mediating nutrient utilization and overall fitness. Further microbiome profiling using 16S rRNA gene sequencing could improve our understanding of these interactions. This, in turn, could enhance Wolbachia release strategies to control arboviral infections. Such approaches would greatly benefit the consistency, scalability, and success of mass-release programs aiming to suppress or replace disease-transmitting mosquito populations. Declarations Ethics approval and consent to participate Blood feeding on adult human volunteers was approved by the University of Melbourne Human Ethics committee (project ID 28583). Informed consent was obtained from all subjects. Consent for publication NA Availability of data and materials The datasets analysed during the current study are available on Figshare at: https://doi.org/10.26188/28785869. Competing interests The authors declare that they have no competing interests. Funding This work was supported by the Wellcome Trust [grant numbers 226166, 108508, and 202888] Authors' contributions MF, PR, XG and AH designed the study. MF performed the experiments and collected experimental data. MF, PR, XG and AH interpreted the results and wrote the manuscript. All authors read and approved the final manuscript. Acknowledgements We thank Nancy Endersby-Harshman, Lawrence G. Harshman and Alex Gill for their assistance with laboratory assistance and technical support during this study. References Nazni WA, Hoffmann AA, NoorAfizah A, Cheong YL, Mancini MV, Golding N, et al. Establishment of Wolbachia strain w AlbB in Malaysian populations of Aedes aegypti for dengue control. Current Biology. 2019;29:4241-8. Velez ID, Uribe A, Barajas J, Uribe S, Angel S, Suaza-Vasco JD, et al. Large-scale releases and establishment of w Mel Wolbachia in Aedes aegypti mosquitoes throughout the Cities of Bello, Medellín and Itagüí, Colombia. PLOS Neglected Tropical Diseases. 2023;17:e0011642. Tantowijoyo W, Andari B, Arguni E, Budiwati N, Nurhayati I, Fitriana I, et al. Stable establishment of w Mel Wolbachia in Aedes aegypti populations in Yogyakarta, Indonesia. PLOS Neglected Tropical Diseases. 2020;14:e0008157. Hoffmann AA, Ahmad NW, Keong WM, Ling CY, Ahmad NA, Golding N, et al. Introduction of Aedes aegypti mosquitoes carrying w AlbB Wolbachia sharply decreases dengue incidence in disease hotspots. Iscience. 2024; doi: https://doi.org/10.1016/j.isci.2024.108942. Zheng X, Zhang D, Li Y, Yang C, Wu Y, Liang X, et al. Incompatible and sterile insect techniques combined eliminate mosquitoes. Nature Biotechnology. 2019;572:56-61. Lim JT, Bansal S, Chong CS, Dickens B, Ng Y, Deng L, et al. Efficacy of Wolbachia -mediated sterility to reduce the incidence of dengue: a synthetic control study in Singapore. The Lancet Microbe. 2024; 5:e422. Hoffmann AA, Montgomery B, Popovici J, Iturbe-Ormaetxe I, Johnson P, Muzzi F, et al. Successful establishment of Wolbachia in Aedes populations to suppress dengue transmission. Nature. 2011;476:454-7. Pinto SB, Riback TI, Sylvestre G, Costa G, Peixoto J, Dias FB, et al. Effectiveness of Wolbachia -infected mosquito deployments in reducing the incidence of dengue and other Aedes -borne diseases in Niterói, Brazil: A quasi-experimental study. PLOS Neglected Tropical Diseases. 2021;15:e0009556. Ross PA, Elfekih S, Collier S, Klein MJ, Lee SS, Dunn M, et al. Developing Wolbachia -based disease interventions for an extreme environment. PLOS Pathogens. 2023;19:e1011117. Utarini A, Indriani C, Ahmad RA, Tantowijoyo W, Arguni E, Ansari MR, et al. Efficacy of Wolbachia -infected mosquito deployments for the control of dengue. New England Journal of Medicine. 2021;384:2177-86. Ryan PA, Turley AP, Wilson G, Hurst TP, Retzki K, Brown-Kenyon J, et al. Establishment of w Mel Wolbachia in Aedes aegypti mosquitoes and reduction of local dengue transmission in Cairns and surrounding locations in northern Queensland, Australia. Gates Open Research. 2019;3. Benedict MQ, Hunt CM, Vella MG, Gonzalez KM, Dotson EM, Collins CM. Pragmatic selection of larval mosquito diets for insectary rearing of Anopheles gambiae and Aedes aegypti . PLOS One. 2020;15:e0221838. Haghighat-Khah RE, Harvey-Samuel T, Basu S, StJohn O, Scaife S, Verkuijl S, et al. Engineered action at a distance: Blood-meal-inducible paralysis in Aedes aegypti . PLOS Neglected Tropical Diseases. 2019;13:e0007579. IAEA: Guidelines For Routine Colony Maintenance of Aedes Mosquito Species Version 1.0.https://www.iaea.org/sites/default/files/21/06/nafa-ipc-manual-guidelines-for-routine-colony-maintenance-of-aedes-mosquito-species-v1.0.pdf (2017). Van Schoor T, Kelly ET, Tam N, Attardo GM. Impacts of dietary nutritional composition on larval development and adult body composition in the yellow fever mosquito ( Aedes aegypti ). Insects. 2020;11:535. Souza RS, Virginio F, Riback TIS, Suesdek L, Barufi JB, Genta FA. Microorganism-based larval diets affect mosquito development, size and nutritional reserves in the yellow fever mosquito Aedes aegypti (Diptera: Culicidae). Frontiers in Physiology. 2019;10:152. Contreras-Perera Y, Flores-Pech JP, Pérez-Carillo S, Puerta-Guardo H, Geded-Moreno E, Correa-Morales F, et al. Different larval diets for Aedes aegypti (Diptera: Culicidae) under laboratory conditions: in preparation for a mass-rearing system. Biologia. 2023;78:3387-99. Zhang D, Zhang M, Wu Y, Gilles JR, Yamada H, Wu Z, et al. Establishment of a medium-scale mosquito facility: optimization of the larval mass-rearing unit for Aedes albopictus (Diptera: Culicidae). Parasites & Vectors. 2017;10:1-9. Kho EA, Hugo LE, Lu G, Smith DD, Kay BHy. Effects of larval nutrition on Wolbachia -based dengue virus interference in Aedes aegypti (Diptera: Culicidae). Journal of Medical Entomology. 2016;53:894-901. Coon KL, Vogel KJ, Brown MR, Strand MR. Mosquitoes rely on their gut microbiota for development. Molecular Ecology. 2014;23:2727-39. Coon KL, Brown MR, Strand MR. Gut bacteria differentially affect egg production in the anautogenous mosquito Aedes aegypti and facultatively autogenous mosquito Aedes atropalpus (Diptera: Culicidae). Parasites & Vectors. 2016;9. Cansado-Utrilla C, Zhao SY, McCall PJ, Coon KL, Hughes GL. The microbiome and mosquito vectorial capacity: rich potential for discovery and translation. Microbiome. 2021;9:111. Correa MA, Matusovsky B, Brackney DE, Steven B. Generation of axenic Aedes aegypti demonstrate live bacteria are not required for mosquito development. Nature Communications. 2018;9:4464. MacLeod HJ, Dimopoulos G, Short SM. Larval diet abundance influences size and composition of the midgut microbiota of Aedes aegypti mosquitoes. Frontiers in Microbiology. 2021;12:645362. Deconninck G, Larges J, Henri H, Beaugeard L, Foray V, Pincebourde S. Wolbachia improves the performance of an invasive fly after a diet shift. Journal of Pest Science. 2024;97:2087-99. Ponton F, Wilson K, Holmes A, Raubenheimer D, Robinson KL, Simpson SJ. Macronutrients mediate the functional relationship between Drosophila and Wolbachia . Proceedings of the Royal Society B: Biological Sciences. 2015;282:20142029. Brownlie JC, Cass BN, Riegler M, Witsenburg JJ, Iturbe-Ormaetxe I, McGraw EA, et al. Evidence for metabolic provisioning by a common invertebrate endosymbiont, Wolbachia pipientis , during periods of nutritional stress. PLOS Pathogens. 2009;5:e1000368. Caragata EP, Rancès E, O’Neill SL, McGraw EA. Competition for amino acids between Wolbachia and the mosquito host, Aedes aegypti . Microbial Ecology. 2014;67:205-18. Dutra HLC, Rodrigues SL, Mansur SB, de Oliveira SP, Caragata EP, Moreira LA. Development and physiological effects of an artificial diet for Wolbachia -infected Aedes aegypti . Scientific Reports. 2017; doi: https://doi.org/10.1038/s41598-017-16045-6. Ross PA, Endersby NM, Hoffmann AA. Costs of three Wolbachia infections on the survival of Aedes aegypti larvae under starvation conditions. PLOS Neglected Tropical Diseases. 2016;10:e0004320. Gu X, Ross PA, Rodriguez‐Andres J, Robinson KL, Yang Q, Lau MJ, et al. A w Mel Wolbachia variant in Aedes aegypti from field‐collected Drosophila melanogaster with increased phenotypic stability under heat stress. Environmental Microbiology. 2022;24:2119-35. Ross PA, Gu X, Robinson KL, Yang Q, Cottingham E, Zhang Y, et al. A w AlbB Wolbachia transinfection displays stable phenotypic effects across divergent Aedes aegypti mosquito backgrounds. Applied Environmental Microbiology. 2021;87:e01264. Xi Z, Khoo CC, Dobson SL. Wolbachia establishment and invasion in an Aedes aegypti laboratory population. Science. 2005;310:326-8. Salim M, Kamran M, Khan I, Saljoqi AUR, Ahmad S, Almutairi MH, et al. Effect of larval diets on the life table parameters of dengue mosquito, Aedes aegypti (L.)(Diptera: Culicidae) using age-stage two sex life table theory. Scientific Reports. 2023;13:11969. Sasmita HI, Tu W-C, Bong L-J, Neoh K-B. Effects of larval diets and temperature regimes on life history traits, energy reserves and temperature tolerance of male Aedes aegypti (Diptera: Culicidae): optimizing rearing techniques for the sterile insect programmes. Parasites & Vectors. 2019;12:1-16. Warton DI, Hui FK. The arcsine is asinine: the analysis of proportions in ecology. Ecology. 2011;92:3-10. Livdahl TP, Sugihara G. Non-linear interactions of populations and the importance of estimating per capita rates of change. The Journal of Animal Ecology. 1984;53:573-80. Maciel-de-Freitas R, Sauer FG, Kliemke K, Garcia GA, Pavan MG, David MR, et al. Wolbachia strains w Mel and w AlbB differentially affect Aedes aegypti traits related to fecundity. Microbiology Spectrum. 2024;12:e00128. Briegel H. Metabolic relationship between female body size, reserves, and fecundity of Aedes aegypti . Journal of Insect Physiology. 1990;36:165-72. Telang A, Li Y, Noriega FG, Brown MR. Effects of larval nutrition on the endocrinology of mosquito egg development. Journal of Experimental Biology. 2006;209:645-55. Clements AN. The biology of mosquitoes: development, nutrition and reproduction. vol. 1. London: Chapman Hall; 1992. Bond J, Ramírez-Osorio A, Marina C, Fernández-Salas I, Liedo P, Dor A, et al. Efficiency of two larval diets for mass-rearing of the mosquito Aedes aegypti . PLOS One. 2017;12:e0187420. Bimbilé Somda NS, Dabiré KR, Maiga H, Yamada H, Mamai W, Gnankiné O, et al. Cost-effective larval diet mixtures for mass rearing of Anopheles arabiensis Patton (Diptera: Culicidae). Parasites & Vectors. 2017;10:1-12. Yan J, Kibech R, Stone CM. Differential effects of larval and adult nutrition on female survival, fecundity, and size of the yellow fever mosquito, Aedes aegypti . Frontiers in Zoology. 2021;18:1-9. Arrese EL, Soulages JL. Insect fat body: energy, metabolism, and regulation. Annual Review of Entomology. 2010;55:207-25. Ross PA, Axford JK, Richardson KM, Endersby-Harshman NM, Hoffmann AA. Maintaining Aedes aegypti mosquitoes infected with Wolbachia . JoVE. 2017; 126:e56124. Jiménez NE, Gerdtzen ZP, Olivera-Nappa Á, Salgado JC, Conca C. A systems biology approach for studying Wolbachia metabolism reveals points of interaction with its host in the context of arboviral infection. PLOS Neglected Tropical Diseases. 2019;13:e0007678. Additional Declarations No competing interests reported. Supplementary Files Graphicalabstract.pdf Mean development time (A–D) and proportion of pupation success (survival) (E–H) of across four larval diets (Diet 1–Diet 4) with varying protein-to-carbohydrate ratios and concentrations (0.4 to 3.2 mg/larva/day). Data are presented for three mosquito lines: uninfected (blue), MelM (orange), and AlbB (green). Error bars represent 95% bootstrapped confidence intervals (CI). Cite Share Download PDF Status: Published Journal Publication published 24 Sep, 2025 Read the published version in Parasites & Vectors → Version 1 posted Editorial decision: Revision requested 20 May, 2025 Reviews received at journal 20 May, 2025 Reviews received at journal 14 May, 2025 Reviewers agreed at journal 29 Apr, 2025 Reviewers agreed at journal 28 Apr, 2025 Reviewers agreed at journal 28 Apr, 2025 Reviewers invited by journal 28 Apr, 2025 Editor assigned by journal 22 Apr, 2025 Submission checks completed at journal 22 Apr, 2025 First submitted to journal 16 Apr, 2025 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-6459379","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":449735042,"identity":"d6ee0c5c-fb62-4e21-8908-2483c727a8fc","order_by":0,"name":"Mohd Farihan Md Yatim","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAABLElEQVRIie3QsUrDQBjA8U8iyXKS9QsVfAIhEAiR9k1cUgJxuWQJlA6hBIRMYjZx6ENYhMytB5kKXSO6uDhlKBREQYKXkoDVU1eH+0OOyx0/jjsAmex/ZvIPQW+mpF2aAzhuu/UDcRGMRNkSbAn+Rfg4/0TgN3J8xXJ8e3VOrdWqwGr8OAEMFnflGEPQznOEmH0l9oM/Mi5cDPLSU43p8hkBQ5fRJUZAihFCISDURrIlito7SBkn1GRBisME+RaoQmK8c3KbMU7qjtScHFWc1ELSa065AY+TpCNJcwqxcS8V3SXqH/oYXJeedTItmJGSymS0wEglfuQML8++E292Xw0mQZYtnsoqZrquUWtD40Goa2xWrl/6gnfex51fdWfiCgCAshYuy2QymazrA3SIbG75ce3OAAAAAElFTkSuQmCC","orcid":"","institution":"The University of Melbourne","correspondingAuthor":true,"prefix":"","firstName":"Mohd","middleName":"Farihan Md","lastName":"Ya","suffix":"Md"},{"id":449735043,"identity":"babccfe3-341d-4491-b933-578437304cde","order_by":1,"name":"Perran Stott-Ross","email":"","orcid":"","institution":"The University of Melbourne","correspondingAuthor":false,"prefix":"","firstName":"Perran","middleName":"","lastName":"Stott-Ross","suffix":""},{"id":449735044,"identity":"ca12a9ac-7209-4663-b608-4166d9afaf13","order_by":2,"name":"Xinyue Gu","email":"","orcid":"","institution":"The University of Melbourne","correspondingAuthor":false,"prefix":"","firstName":"Xinyue","middleName":"","lastName":"Gu","suffix":""},{"id":449735045,"identity":"c4a16882-65ec-4419-8a7d-f73248a1d76b","order_by":3,"name":"Ary Anthony Hoffmann","email":"","orcid":"","institution":"The University of Melbourne","correspondingAuthor":false,"prefix":"","firstName":"Ary","middleName":"Anthony","lastName":"Hoffmann","suffix":""}],"badges":[],"createdAt":"2025-04-16 04:23:15","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-6459379/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6459379/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1186/s13071-025-06978-7","type":"published","date":"2025-09-24T15:57:22+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":81820155,"identity":"d4155192-c2cc-420a-9de1-1b0f7630e0a2","added_by":"auto","created_at":"2025-05-02 11:07:49","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":3355245,"visible":true,"origin":"","legend":"\u003cp\u003eMean development time (A–D) and proportion of pupation success (survival) (E–H) of \u003cem\u003eAedes aegypti\u003c/em\u003e across four larval diets (Diet 1–Diet 4) with varying protein-to-carbohydrate ratios and concentrations (0.4 to 3.2 mg/larva/day). Data are presented for three mosquito lines: uninfected (blue), \u003cem\u003ew\u003c/em\u003eMelM (orange), and \u003cem\u003ew\u003c/em\u003eAlbB (green). Error bars represent 95% bootstrapped confidence intervals (CI).\u003c/p\u003e","description":"","filename":"Figure1.png","url":"https://assets-eu.researchsquare.com/files/rs-6459379/v1/e79eb4e1a79b0153cd6529f8.png"},{"id":81820152,"identity":"a33b5d4e-0860-4c40-9971-13338f943d2a","added_by":"auto","created_at":"2025-05-02 11:07:49","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":3326908,"visible":true,"origin":"","legend":"\u003cp\u003eMean of male (A–D) and female (E–H) wing lengths of \u003cem\u003eAedes aegypti\u003c/em\u003e reared on four larval diets (Diet 1–Diet 4) across five concentrations (0.4 to 3.2 mg/larva/day). Results are shown for uninfected (blue), \u003cem\u003ew\u003c/em\u003eMelM (orange), and \u003cem\u003ew\u003c/em\u003eAlbB (green) lines. Error bars represent 95% bootstrapped confidence intervals (CI).\u003c/p\u003e","description":"","filename":"Figure2.png","url":"https://assets-eu.researchsquare.com/files/rs-6459379/v1/de7b3f0a7a31573d6f6472fd.png"},{"id":81820156,"identity":"2691d35c-3bc5-400a-a4ba-060aabd7081a","added_by":"auto","created_at":"2025-05-02 11:07:49","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":3938409,"visible":true,"origin":"","legend":"\u003cp\u003eMean fecundity (A–D) and hatch proportion (E–H) of \u003cem\u003eAedes aegypti\u003c/em\u003e females reared on four larval diets (Diet 1–Diet 4) across five concentrations (0.4 to 3.2 mg/larva/day). Data are shown for uninfected (blue), \u003cem\u003ew\u003c/em\u003eMelM (orange), and \u003cem\u003ew\u003c/em\u003eAlbB (green) mosquito lines. Error bars represent 95% bootstrapped confidence intervals (CI).\u003c/p\u003e","description":"","filename":"Figure3.png","url":"https://assets-eu.researchsquare.com/files/rs-6459379/v1/4d6277d6e6aa4b9add100c2c.png"},{"id":81820154,"identity":"0e048189-d729-41ae-acc7-9e577af0c2d5","added_by":"auto","created_at":"2025-05-02 11:07:49","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":2322585,"visible":true,"origin":"","legend":"\u003cp\u003eRelationship between mean female wing length and mean fecundity in uninfected (A), \u003cem\u003ew\u003c/em\u003eMelM (B), and \u003cem\u003ew\u003c/em\u003eAlbB (C) \u003cem\u003eAedes aegypti\u003c/em\u003e lines across all diets and concentrations/ allocations. Each point represents the mean values per diet treatment across all allocations; colours indicate the corresponding diet.\u003c/p\u003e","description":"","filename":"Figure4.png","url":"https://assets-eu.researchsquare.com/files/rs-6459379/v1/b7fd4bc1db389b8a6df85049.png"},{"id":81820157,"identity":"9deaa629-87c5-40d2-9416-d61590c8e85e","added_by":"auto","created_at":"2025-05-02 11:07:49","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":2715929,"visible":true,"origin":"","legend":"\u003cp\u003eFitness index (life table score) across different diet concentrations for uninfected, \u003cem\u003ew\u003c/em\u003eMelM, and \u003cem\u003ew\u003c/em\u003eAlbB \u003cem\u003eAedes aegypti\u003c/em\u003e lines reared on four larval diets (A–D). The Fitness Index was calculated using life table parameters, following the method proposed by [37]. Each plot shows the performance of the three mosquito lines across five concentrations (0.4 to 3.2 mg/larva/day), with the vertical dashed line indicating the concentration yielding the highest fitness index (optimal concentration).\u003c/p\u003e","description":"","filename":"Figure5.png","url":"https://assets-eu.researchsquare.com/files/rs-6459379/v1/b39f458d5b200eb9a0eeea19.png"},{"id":81820151,"identity":"aa72d91a-ed21-4af4-87e9-1bdc02d902fe","added_by":"auto","created_at":"2025-05-02 11:07:49","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":88676,"visible":true,"origin":"","legend":"Mean development time (A\u0026ndash;D) and proportion of pupation success (survival) (E\u0026ndash;H) of across four larval diets (Diet 1\u0026ndash;Diet 4) with varying protein-to-carbohydrate ratios and concentrations (0.4 to 3.2 mg/larva/day). Data are presented for three mosquito lines: uninfected (blue), MelM (orange), and AlbB (green). Error bars represent 95% bootstrapped confidence intervals (CI).","description":"","filename":"Graphicalabstract.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6459379/v1/d09c892a7dcf3a83bada27f5.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Impact of larval diet on fitness outcomes of Aedes aegypti mosquitoes infected with wAlbB and wMelM","fulltext":[{"header":"Background","content":"\u003cp\u003e \u003cem\u003eWolbachia\u003c/em\u003e releases are being undertaken for the control of arboviruses across the world [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e, \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. Two general approaches have been identified. (a) The release of \u003cem\u003eWolbachia\u003c/em\u003e-infected adult males that can lead to suppression of the mosquito population through cytoplasmic incompatibility (CI), which results in non-viable offspring when infected males mate with uninfected females [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e, \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. (b) The release of both male and female \u003cem\u003eWolbachia\u003c/em\u003e-infected mosquitoes with the aim of replacing the wild mosquito population with mosquitoes carrying a \u003cem\u003eWolbachia\u003c/em\u003e strain [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. These novel techniques have demonstrated success in limiting disease transmission [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e] compared to conventional insecticide spraying which carries significant environmental and economic costs. Both \u003cem\u003eWolbachia\u003c/em\u003e-based strategies rely on the large-scale production of mosquitoes that can either compete with wild-type males for mating (suppression strategy) or establish a self-sustaining \u003cem\u003eWolbachia\u003c/em\u003e-infected population (replacement strategy) through release of females that can compete with wild females for breeding sites and transmit the \u003cem\u003eWolbachia\u003c/em\u003e infection, as well as having competitive males that induce cytoplasmic incompatibility.\u003c/p\u003e \u003cp\u003eIn the context of mosquito mass rearing programs for vector-borne disease intervention, producing highly competitive \u003cem\u003eAedes aegypti\u003c/em\u003e mosquitoes that can compete with wild mosquitoes is essential. An effective larval diet is important to achieve this objective. Various diets have been tested for \u003cem\u003eAe. aegypti\u003c/em\u003e larval growth and the most often used diets are the IAEA diet (developed by the International Atomic Energy Agency) and diets incorporating commercial fish food such as TetraMin [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e, \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. Commonly used as a standard reference in many studies, the IAEA diet consists of 50% tuna powder, 35% liver powder, and 15% Brewer's yeast [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eA balanced protein and carbohydrate larval diet ratio can lead to the production of larger wings in \u003cem\u003eAe. aegypti\u003c/em\u003e mosquitoes [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e] whereas microorganisms and algae diets resulted in reduced adult survival, suggesting poor nutrition [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. In contrast, diets based on various animal-based sources (porcine, beef liver, fish food, and beef liver\u0026ndash;shrimp powder combinations) yield better development and survival [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]. However, these diets have been tested at relatively low feeding rates (average 0.41 mg per larva per day), whereas feeding rates for rearing \u003cem\u003eAedes\u003c/em\u003e mosquitoes at a medium-scale have been as high as 0.84 mg per larva per day [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]. In another study, the largest wings in \u003cem\u003eAe. aegypti\u003c/em\u003e infected with \u003cem\u003ew\u003c/em\u003eMel and \u003cem\u003ew\u003c/em\u003eMelPop strain were observed using the Tetramin fish food diet at 1 mg per larva per day [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eSeveral studies have found that the microbiome in the mosquito gut is essential for digestion, immune function, and shaping mosquito fitness [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e, \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e, \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e, \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]. In one study examining microbiome density in mosquitoes, high larval food allocation (up to 2 mg per larva per day) was shown to increase gut microbiome density, which remained at a high level even after eclosion and blood feeding [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]. This raises the question whether certain microbiome or gut bacterial density could play a role to improve mosquito fitness.\u003c/p\u003e \u003cp\u003eGenerally, most of the nutritional studies were conducted on uninfected Ae. \u003cem\u003eaegypti\u003c/em\u003e lines. However, a study in \u003cem\u003eDrosophila\u003c/em\u003e showed that \u003cem\u003eWolbachia\u003c/em\u003e can increase fertility in response to dietary changes [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]. There is a macronutrient balance that moderates the functional link between Drosophila and \u003cem\u003eWolbachia\u003c/em\u003e, hence affecting reproductive success [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]. Additionally, under nutritional stress, \u003cem\u003eWolbachia\u003c/em\u003e may supply nutrients to the host, indicating a possible compensating function of \u003cem\u003eWolbachia\u003c/em\u003e when meal quality is poor [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e]. Turning to \u003cem\u003eAe\u003c/em\u003e. \u003cem\u003eaegypti\u003c/em\u003e, diets based on animal sources showed no negative impacts on Wolbachia density, development time or survival of \u003cem\u003ew\u003c/em\u003eAlbB-infected Ae. \u003cem\u003eaegypti\u003c/em\u003e [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]. However, blood meal quality\u0026mdash;including artificial or nutrient-modified meals\u0026mdash;was found to influence \u003cem\u003eWolbachia\u003c/em\u003e-infected mosquito performance [\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e], and starvation modulated \u003cem\u003eWolbachia\u003c/em\u003e fitness effects [\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e]. These results taken together highlight the need of taking dietary environment and infection status into consideration while assessing mosquito fitness characteristics.\u003c/p\u003e \u003cp\u003eTo address these issues, this study evaluates the effects of different larval diets on \u003cem\u003eWolbachia\u003c/em\u003e-infected (\u003cem\u003ew\u003c/em\u003eAlbB and \u003cem\u003ew\u003c/em\u003eMelM-strains described in [\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e] and [\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e]) and uninfected mosquitoes by examining a range of protein and carbohydrate compositions, including both plant- and animal-based protein sources. The study examines how both diet composition and concentration affect key fitness traits, including development time, survival, wing length, fecundity, and egg hatchability across \u003cem\u003eWolbachia-\u003c/em\u003einfected and uninfected \u003cem\u003eAe. aegypti\u003c/em\u003e mosquitoes. Potential trade-offs between fitness traits are also explored, along with the influence of \u003cem\u003eWolbachia\u003c/em\u003e infection status on dietary responses. By evaluating these key life traits, we explored whether optimum diets and concentrations could help mitigate the fitness costs associated with \u003cem\u003eWolbachia\u003c/em\u003e infection in \u003cem\u003eAe. aegypti\u003c/em\u003e mosquitoes.\u003c/p\u003e"},{"header":"Methods","content":"\u003cp\u003e\u003cu\u003eEthical statement\u003c/u\u003e\u003c/p\u003e\n\u003cp\u003eBlood feeding on adult human volunteers was approved by the University of Melbourne Human Ethics committee (project ID 28583). Informed consent was obtained from all subjects.\u0026nbsp;\u003cbr\u003e\u0026nbsp;A single volunteer for blood feeding was used across all experiments to ensure consistency in blood meals.\u003c/p\u003e\n\u003cp\u003e\u003cu\u003eMosquito maintenance\u003c/u\u003e\u003c/p\u003e\n\u003cp\u003eThe \u003cem\u003eAe. aegypti\u003c/em\u003e mosquito lines used in this study were either infected with the \u003cem\u003ew\u003c/em\u003eMelM or \u003cem\u003ew\u003c/em\u003eAlbB strains of \u003cem\u003eWolbachia\u0026nbsp;\u003c/em\u003eor uninfected. All lines had a Cairns, Australia, genetic background and were maintained in the laboratory for at least 60 generations. The \u003cem\u003ew\u003c/em\u003eMelM line is a variant of \u003cem\u003ew\u003c/em\u003eMel, derived from a field-collected \u003cem\u003eDrosophila melanogaster\u003c/em\u003e, and exhibits greater heat tolerance than \u003cem\u003ew\u003c/em\u003eMel [31]. The \u003cem\u003ew\u003c/em\u003eAlbB line was derived from a trans-infection [33] developed by [32] involving the transfer of the infection to \u003cem\u003eAe. aegypti\u0026nbsp;\u003c/em\u003ewith a Cairns, Australia mitochondrial haplotype. To ensure a consistent nuclear background, females from all three lines were backcrossed to males from a different uninfected line derived from Cairns for four generations prior to the experiment. Mosquito colonies were maintained under a 12-hour light/12-hour dark cycle at 26°C.\u003c/p\u003e\n\u003cp\u003e\u003cu\u003eLarval Diets\u003c/u\u003e\u003c/p\u003e\n\u003cp\u003eThe composition of the diets is outlined in Table 1. These diets were selected to represent a range of protein and carbohydrate compositions. Diet 1 or Plant-based diet (Pd) contains 58% carbohydrate (C) and 17% protein (P), representing a high carbohydrate/low protein diet [34]; Diet 2 or Khan Diet (Kd) contains 52% (C) and 23% (P), representing a high carbohydrate/moderate protein diet [34, 35]; Diet 3 or Hikari fish food (Fd) diet contains 24% (C) and 36% (P), representing a moderate carbohydrate / high protein diet; Diet 4 or the IAEA [14] diet contains 2% (C) and 72% (P), representing a low carbohydrate/very high protein diet. The complete macronutrient content of all diets is shown in Table 2.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eTable 1. Ingredients list for all four diets (10g / diet)\u0026nbsp;\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eDiet 1 (Pd)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eDiet 2 (Kd)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eDiet 3 (Fd)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eDiet 4 (IAEA)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eBean (2g)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eBean (1.2g)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eHikari Fish Food (10g)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eBrewer’s Yeast (1.5g)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eChickpea (2g)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eChickpea (1.8g)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"5\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eIngredients\u003c/strong\u003e: Fish meal, wheat germ meal, soybean meal, wheat flour, whole crushed silkworm pupae, dried seaweed meal, dried bakery product, brewers dried yeast, fish oil, krill meal, spirulina, garlic, DL-methionine, astaxanthin, choline chloride, vitamin E supplement, L-ascorbyl-2-polyphosphate (stabilized vitamin C), inositol, d-calcium pantothenate, riboflavin, vitamin A supplement, thiamine mononitrate, pyridoxine hydrochloride, niacin, folic acid, vitamin D3 supplement, biotin, disodium phosphate, ferrous sulfate, magnesium sulfate, zinc sulfate, manganese sulfate, copper sulfate, calcium iodate.\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eLiver Powder (3.5g)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eMung Bean (2g)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eCorn (1.8g)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eTuna Powder (5g)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eMushroom (2g)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eLiver Powder (2.2g)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eRice (2g)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eRice (1.8g)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eWheat (1.2g)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e10g\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e10g\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e10g\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e10g\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eTable 2. Macronutrients content in all diets (per 10g)\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eMacronutrients\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eDiet 1 (Pd)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eDiet 2 (Kd)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eDiet 3 (Fd)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eDiet 4 (IAEA)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eCarbohydrate\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e5.758 g\u003c/p\u003e\n \u003cp\u003e(57.58%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e5.151g\u003c/p\u003e\n \u003cp\u003e(51.51%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e2.42g\u003c/p\u003e\n \u003cp\u003e(24.20%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.16g\u003c/p\u003e\n \u003cp\u003e(1.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eProtein\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1.698 g\u003c/p\u003e\n \u003cp\u003e(16.98%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e2.348 g\u003c/p\u003e\n \u003cp\u003e(23.48%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e3.6g\u003c/p\u003e\n \u003cp\u003e(36.00%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e7.17 g\u003c/p\u003e\n \u003cp\u003e(71.70%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eFat\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.3 g\u003c/p\u003e\n \u003cp\u003e(3.00%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.520 g\u003c/p\u003e\n \u003cp\u003e(5.20%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.9 g\u003c/p\u003e\n \u003cp\u003e(9.00%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1.115g\u003c/p\u003e\n \u003cp\u003e(11.15%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cu\u003eIngredient preparation\u003c/u\u003e\u003c/p\u003e\n\u003cp\u003eCommercially available wheat flour (\u003cem\u003eWhite Wings Premium Plain Flour\u003c/em\u003e; White Wings, Australia), rice flour (\u003cem\u003eErawan Brand\u003c/em\u003e; Cho Heng Rice Vermicelli Factory Co. Ltd., Thailand), corn flour (\u003cem\u003eSunflower Corn Flour\u003c/em\u003e; Singapore), chickpea flour (\u003cem\u003eMcKenzie's Australian Chick Pea Flour\u003c/em\u003e; McKenzie's Foods, Australia), mung bean flour (\u003cem\u003eXinliang Mung Bean Starch\u003c/em\u003e, China), beef liver powder (\u003cem\u003eBarbell Organic Beef Liver\u003c/em\u003e; Barbell Foods, Australia), Brewer’s yeast (\u003cem\u003eMacro Wholefoods Market\u003c/em\u003e; Woolworths, Australia) and Hikari fish food (\u003cem\u003eHikari Tropical Sinking Wafers;\u0026nbsp;\u003c/em\u003eKyorin Food Industries, Japan) \u0026nbsp;were used. Fresh mushrooms (\u003cem\u003eAgaricus bisporus\u003c/em\u003e) and tuna in water (\u003cem\u003eOcean Rise®;\u003c/em\u003e ALDI Stores, Australia) were chopped into small pieces, dried at 50°C for six hours, and ground into powder. All flours and powders were sifted through a fine strainer, and a 2% solution was prepared by mixing 10 g of each diet with 500 mL of reverse osmosis (RO) water.\u003c/p\u003e\n\u003cp\u003e\u003cu\u003eLarval development time and survival\u003c/u\u003e\u003c/p\u003e\n\u003cp\u003eEggs from each mosquito line were hatched in reverse osmosis (RO) water with a small amount of Brewer’s yeast. After 12 hours, 50 first-instar larvae were transferred into plastic containers filled with 500 mL of RO water and assigned to diet treatments at concentrations of 0.4, 0.8, 1.2, 1.6, and 3.2 mg/larva/day. Note that we use the term “concentration” and “allocation” interchangeably in the paper because a higher allocation is expected to result in a higher concentration of food. Each concentration/diet/line combination was tested as six replicates (300 larvae in total per treatment). Across the three mosquito lines, 4,500 larvae were assessed per diet, resulting in a total sample size of 18,000 larvae for all four diets. Given the large sample size and impacts on development time, diet treatments had to be tested in separate experiments even though they were set up within a few days of each other.\u003c/p\u003e\n\u003cp\u003eLarval development time, defined as the duration from egg hatching to pupation, was recorded twice daily (morning and evening) starting from the onset of pupation. Pupae were counted, sexed, and transferred to designated containers within rearing cages according to their respective lines and concentrations. This process was consistently applied across all diet treatments.\u003c/p\u003e\n\u003cp\u003eSurvival was defined as the proportion of first-instar larvae that successfully pupated and calculated as the number of pupae divided by the initial number of first-instar larvae.\u003c/p\u003e\n\u003cp\u003e\u003cu\u003eWing length measurement\u0026nbsp;\u003c/u\u003e\u003c/p\u003e\n\u003cp\u003eFifteen two- to four-day-old adult males and females from each concentration and line were selected and preserved in 100% ethanol for wing length measurement. Wings were dissected using forceps under a stereomicroscope. Measurements were taken using a Nikon SMZ1500 microscope equipped with a camera and IS Capture software. Wing length was determined as the distance from the alular notch to the radius 3 vein.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cu\u003eFecundity and egg hatch\u0026nbsp;\u003c/u\u003e\u003c/p\u003e\n\u003cp\u003eAll concentration/line combinations for a diet were blood fed on the same day; however, due to differences in larval development time across diet concentrations, the age of females at the time of blood feeding varied between 4- and 7-days post-emergence. After blood feeding, twenty fully engorged females were transferred to small plastic containers lined with sandpaper (\u003cem\u003eNorton Master Painters P80\u003c/em\u003e; Saint-Gobain Abrasives Pty. Ltd., Thomastown, Victoria, Australia) and partially filled with RO water to facilitate oviposition.\u003c/p\u003e\n\u003cp\u003eEggs were collected by removing the sandpaper after four days. Females that did not lay eggs within this period remained in the containers until day 7 to account for potential late oviposition. Collected eggs were stored for three days before hatching trials. On the third day, RO water and a small amount of Brewer’s yeast (\u003cem\u003eMacro Wholefoods Market\u003c/em\u003e; Woolworths, Australia) were added to the container to stimulate hatching. After 24 hours, fecundity was measured as the total number of eggs per female, while hatch proportion was calculated as the total number of hatched eggs divided by the total number of eggs laid.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cu\u003eStatistical analysis\u003c/u\u003e\u003c/p\u003e\n\u003cp\u003eA two-way ANOVA followed by Tukey’s-b post-hoc tests was performed to evaluate fitness traits across mosquito lines and diet concentrations. Partial eta squared values (η²) were computed to reflect effect sizes. As each diet was tested separately, analyses did not involve a direct comparison across diets. Hatch proportion and survival data were logit-transformed [36] while other measures were not transformed. Pearson correlation analysis was conducted to assess the relationship between female wing length and fecundity.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe optimal allocation/concentration for each diet was determined by computing life table scores by multiplying the averages of fecundity, hatch proportion, and pupation success (survival) proportion, and then dividing by the development time [37]. All statistical analyses were performed using IBM SPSS Statistics version 29. Graphs were generated using RStudio (version 2024.12.0, Build 467), and further graphical edits were performed in Inkscape (version 1.4).\u003c/p\u003e"},{"header":"Results ","content":"\u003cp\u003e\u003cu\u003eDevelopment time\u003c/u\u003e\u003c/p\u003e\n\u003cp\u003eTwo-way ANOVA showed a significant effect of lines and concentration on mosquito development time across all diets (Figure 1A-D, Table 3-6; all p \u0026lt; 0.015). Higher allocations consistently resulted in shorter development times, indicating a strong dose-dependent relationship (Figure 1A-D, Table 3-6; all p \u0026lt; 0.001). Significant interaction effects between mosquito lines and concentration were observed only in Diet 4 (IAEA) (Table 6; p \u0026lt; 0.001), suggesting variability in how mosquito lines responded to changes in food concentration in this particular diet.\u003c/p\u003e\n\u003cp\u003e\u003cu\u003ePupation success (Survival)\u003c/u\u003e\u003c/p\u003e\n\u003cp\u003eIn the ANOVAs concentration significantly influenced the proportion of larvae surviving to the pupal stage across all diets (Figure 1E-H, Table 3-6; all p \u0026lt; 0.001). Mosquito line effects were not significant for any diet, indicating no overall consistent differences among the lines. Interaction effects between mosquito lines and concentration were not significant for Diets 1 (Pd), 2 (Kd) and 3 (Fd), suggesting the effect of concentration on survival was consistent across lines for these diets. While concentration consistently influenced survival across all diets, only Diet 4 (IAEA) showed a marginal interaction (Table 6; p = 0.050, \u0026eta;\u0026sup2; = 0.180).\u003c/p\u003e\n\u003cp\u003eTable 3. Two-way ANOVA results for development time, survival proportion, wing length, fecundity and hatch proportion for Diet 1 (Pd).\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eDependent Variable\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eSource\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eType III Sum of Squares\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003edf\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eMean Square\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cem\u003eF\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cem\u003ep\u003c/em\u003e value\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003ePartial Eta Squared (\u0026eta;\u0026sup2;)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"4\" valign=\"top\"\u003e\n \u003cp\u003eDevelopment Time\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eLines\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e4.330\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e2.165\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e8.807\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.190\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eConcentration\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e166.491\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e41.623\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e169.324\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.900\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eLines * Concentration\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e2.013\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.252\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1.023\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.426\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.098\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eError\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e18.436\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e75\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.246\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"4\" valign=\"top\"\u003e\n \u003cp\u003eSurvival Proportion (logit transformed)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eLines\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e4.314\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e2.157\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e2.355\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.102\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.059\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eConcentration\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e42.305\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e10.576\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e11.548\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.381\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eLines * Concentration\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e5.507\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.688\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.752\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.646\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.074\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eError\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e68.688\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e75\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.916\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"4\" valign=\"top\"\u003e\n \u003cp\u003eWing Length (Male)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eLines\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.057\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.028\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e3.316\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.038\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.031\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eConcentration\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1.968\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.492\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e57.246\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.522\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eLines * Concentration\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.125\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.016\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1.816\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.076\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.065\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eError\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1.805\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e210\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.009\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"4\" valign=\"top\"\u003e\n \u003cp\u003eWing Length (Female)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eLines\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.048\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.024\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e2.456\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.088\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.023\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eConcentration\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e4.430\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1.108\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e112.250\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.681\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eLines * Concentration\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.338\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.042\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e4.280\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.140\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eError\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e2.072\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e210\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.010\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"4\" valign=\"top\"\u003e\n \u003cp\u003eFecundity\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eLines\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e21707.625\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e10853.813\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e42.537\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.252\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eConcentration\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e11657.967\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e2914.492\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e11.422\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.153\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eLines * Concentration\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e3764.767\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e470.596\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1.844\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.069\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.055\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eError\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e64555.772\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e253\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e255.161\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"4\" valign=\"top\"\u003e\n \u003cp\u003eHatch Proportion (Logit Transformed)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eLines\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e60.832\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e30.416\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e35.754\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.229\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eConcentration\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e10.643\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e2.661\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e3.128\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.016\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.049\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eLines * Concentration\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e33.710\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e4.214\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e4.953\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.141\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eError\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e205.020\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e242\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.851\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eTable 4. Two-way ANOVA Results for Development Time, Survival Proportion, Wing Length, Fecundity and Hatch Proportion for Diet 2 (Kd).\u0026nbsp;\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eDependent Variable\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eSource\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eType III Sum of Squares\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003edf\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eMean Square\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cem\u003eF\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cem\u003ep\u003c/em\u003e value\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003ePartial Eta Squared (\u0026eta;\u0026sup2;)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"4\" valign=\"top\"\u003e\n \u003cp\u003eDevelopment Time\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eLines\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.502\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.251\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e4.472\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.015\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.107\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eConcentration\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e41.145\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e10.286\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e183.407\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.907\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eLines * Concentration\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.444\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.056\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.991\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.450\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.096\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eError\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e4.206\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e75\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.056\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"4\" valign=\"top\"\u003e\n \u003cp\u003eSurvival Proportion (logit transformed)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eLines\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e2.741\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1.371\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1.761\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.179\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.045\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eConcentration\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e46.522\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e11.631\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e14.946\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.444\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eLines * Concentration\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e4.477\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.560\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.719\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.674\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.071\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eError\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e58.365\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e75\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.778\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"4\" valign=\"top\"\u003e\n \u003cp\u003eWing Length (Male)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eLines\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.044\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.022\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e3.399\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.035\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.031\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eConcentration\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.954\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.239\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e36.736\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.412\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eLines * Concentration\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.179\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.022\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e3.445\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.116\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eError\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1.364\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e210\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.006\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"4\" valign=\"top\"\u003e\n \u003cp\u003eWing Length (Female)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eLines\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.662\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.331\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e24.983\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.192\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eConcentration\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e2.650\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.662\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e49.965\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.488\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eLines * Concentration\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.574\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.072\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e5.410\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.171\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eError\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e2.784\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e210\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.013\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"4\" valign=\"top\"\u003e\n \u003cp\u003eFecundity\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eLines\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e55470.826\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e27735.413\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e72.775\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.361\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eConcentration\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e45541.502\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e11385.375\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e29.874\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.317\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eLines * Concentration\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e17649.577\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e2206.197\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e5.789\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.152\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eError\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e98327.376\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e258\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e381.114\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"4\" valign=\"top\"\u003e\n \u003cp\u003eHatch Proportion (Logit Transformed)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eLines\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e26.900\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e13.450\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e19.732\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.137\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eConcentration\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e16.824\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e4.206\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e6.171\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.090\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eLines * Concentration\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e23.201\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e2.900\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e4.255\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.120\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eError\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e169.725\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e249\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.682\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eTable 5. Two-way ANOVA Results for Development Time, Survival Proportion, Wing Length, Fecundity and Hatch Proportion for Diet 3 (Fd).\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eDependent Variable\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eSource\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eType III Sum of Squares\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003edf\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eMean Square\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cem\u003eF\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cem\u003ep\u003c/em\u003e value\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003ePartial Eta Squared (\u0026eta;\u0026sup2;)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"4\" valign=\"top\"\u003e\n \u003cp\u003eDevelopment Time\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eLines\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1.186\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.593\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e56.680\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.602\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eConcentration\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e10.678\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e2.670\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e255.265\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.932\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eLines * Concentration\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.091\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.011\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1.082\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.385\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.103\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eError\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.784\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e75\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.010\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"4\" valign=\"top\"\u003e\n \u003cp\u003eSurvival Proportion (logit transformed)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eLines\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e4.636\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e2.318\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1.510\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.228\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.039\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eConcentration\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e44.983\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e11.246\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e7.325\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.281\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eLines * Concentration\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e9.142\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1.143\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.744\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.652\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.074\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eError\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e115.142\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e75\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1.535\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"4\" valign=\"top\"\u003e\n \u003cp\u003eWing Length (Male)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eLines\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.006\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.003\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.781\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.459\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.007\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eConcentration\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.836\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.209\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e50.278\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.489\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eLines * Concentration\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.101\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.013\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e3.047\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.003\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.104\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eError\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.873\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e210\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.004\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"4\" valign=\"top\"\u003e\n \u003cp\u003eWing Length (Female)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eLines\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.027\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.013\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1.365\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.258\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.013\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eConcentration\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e3.073\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.768\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e78.412\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.599\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eLines * Concentration\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.145\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.018\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1.849\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.070\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.066\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eError\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e2.058\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e210\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"4\" valign=\"top\"\u003e\n \u003cp\u003eFecundity\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eLines\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e113003.450\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e56501.725\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e106.631\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.445\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eConcentration\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e16478.966\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e4119.741\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e7.775\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.105\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eLines * Concentration\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e5341.724\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e667.715\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1.260\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.265\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.037\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eError\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e140948.285\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e266\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e529.881\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"4\" valign=\"top\"\u003e\n \u003cp\u003eHatch Proportion (Logit Transformed)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eLines\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e99.245\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e49.623\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e58.941\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.314\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eConcentration\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e6.533\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1.633\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1.940\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.104\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.029\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eLines * Concentration\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e14.165\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1.771\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e2.103\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.036\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.061\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eError\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e216.370\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e257\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.842\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eTable 6. Two-way ANOVA Results for Development Time, Survival Proportion, Wing Length, Fecundity and Hatch Proportion for Diet 4 (IAEA).\u0026nbsp;\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eDependent Variable\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eSource\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eType III Sum of Squares\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003edf\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eMean Square\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cem\u003eF\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cem\u003ep\u003c/em\u003e value\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003ePartial Eta Squared (\u0026eta;\u0026sup2;)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"4\" valign=\"top\"\u003e\n \u003cp\u003eDevelopment Time\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eLines\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1.554\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e.777\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e41.808\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.527\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eConcentration\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e6.216\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1.554\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e83.615\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.817\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eLines * Concentration\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e.750\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.094\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e5.042\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.350\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eError\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1.394\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e75\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.019\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"4\" valign=\"top\"\u003e\n \u003cp\u003eSurvival Proportion (logit transformed)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eLines\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.914\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.457\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1.724\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.185\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.044\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eConcentration\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e16.819\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e4.205\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e15.869\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.458\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eLines * Concentration\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e4.370\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.546\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e2.061\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.050\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.180\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eError\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e19.873\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e75\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.265\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"4\" valign=\"top\"\u003e\n \u003cp\u003eWing Length (Male)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eLines\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.087\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.043\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e10.644\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.092\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eConcentration\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.044\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.011\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e2.725\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.030\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.049\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eLines * Concentration\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.40\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.005\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1.232\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.282\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.045\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eError\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.854\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e210\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.004\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"4\" valign=\"top\"\u003e\n \u003cp\u003eWing Length (Female)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eLines\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.294\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.147\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e14.105\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.118\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eConcentration\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.144\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.036\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e3.462\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.009\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.062\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eLines * Concentration\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.159\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.020\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1.909\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.060\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.068\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eError\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e2.190\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e210\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.010\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"4\" valign=\"top\"\u003e\n \u003cp\u003eFecundity\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eLines\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e44185.373\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e22092.686\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e44.991\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.254\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eConcentration\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e5902.170\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1475.542\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e3.005\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.019\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.044\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eLines * Concentration\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e4526.728\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e565.841\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1.152\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.329\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.034\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eError\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e129637.431\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e264\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e491.051\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"4\" valign=\"top\"\u003e\n \u003cp\u003eHatch Proportion (Logit Transformed)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eLines\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e90.030\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e45.015\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e63.734\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.328\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eConcentration\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e4.178\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1.044\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1.479\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.209\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.022\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eLines * Concentration\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e7.617\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.952\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1.348\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.220\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.040\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eError\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e184.343\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e261\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.706\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cu\u003eMale wing length\u003c/u\u003e\u003c/p\u003e\n\u003cp\u003eTwo-way ANOVAs showed that concentration significantly influenced male wing length in all diets (Figure 2A-D, Table 3-6; all p \u0026le; 0.030). Mosquito line significantly affected male wing length in Diets 1 (Pd), 2 (Kd), and 4 (IAEA) (p \u0026le; 0.038), but not in Diet 3 (Fd) (p = 0.459). Significant interaction effects between mosquito line and concentration were observed in Diets 2 (Kd) (Table 4; p \u0026lt; 0.001) and 3 (Fd) (Table 5; p = 0.003), indicating that the impact of concentration varied by mosquito line for these diets.\u003c/p\u003e\n\u003cp\u003eIncreasing food concentrations significantly enhanced male wing length, with the strongest effects observed for Diets 1 (Pd) to 3 (Fd) (Table 3-5; all p \u0026lt; 0.001). For Diet 4 (IAEA), the relationship was weaker but still statistically significant (p = 0.030). Differences between mosquito lines were generally smaller, varying by diet and concentration, and indicating no consistent pattern of line superiority across all diets.\u003c/p\u003e\n\u003cp\u003e\u003cu\u003eFemale wing length\u0026nbsp;\u003c/u\u003e\u003c/p\u003e\n\u003cp\u003eIn two-way ANOVAs, food concentration significantly influenced female wing length across all diets (Figure 2E-H, Table 3-6; all p \u0026le; 0.009). Mosquito line had a significant effect on female wing length only in Diets 2 (Kd) and 4 (IAEA) (Figure 2F and 2H, Table 4 and 6; both p \u0026lt; 0.001). Additionally, significant interaction effects between mosquito line and concentration were found in Diets 1 (Pd) and 2 (Kd) (Figure 2E and 2F, Table 3-4; both p \u0026lt; 0.001), suggesting that the effect of food concentration on wing length varied by mosquito line in these diets.\u003c/p\u003e\n\u003cp\u003e\u003cu\u003eFecundity\u003c/u\u003e\u003c/p\u003e\n\u003cp\u003eThe ANOVAs indicated significant effects of mosquito lines and concentration on fecundity across all diets (Figure 3A-D, Table 3-6, p \u0026le; 0.0019). Significant interactions between mosquito lines and concentration were observed only in Diet 2 (Kd) (Table4; p \u0026lt; 0.001), reflecting an effect of concentration on fecundity among mosquito lines in this diet.\u003c/p\u003e\n\u003cp\u003eThe uninfected line typically exhibiting higher fecundity compared to the \u003cem\u003ew\u003c/em\u003eMelM and \u003cem\u003ew\u003c/em\u003eAlbB lines (Figure 3A-D). Specifically, \u003cem\u003ew\u003c/em\u003eMelM consistently had the lowest fecundity, significantly differing from both uninfected and \u003cem\u003ew\u003c/em\u003eAlbB lines across all diets.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cu\u003eHatch proportion\u0026nbsp;\u003c/u\u003e\u003c/p\u003e\n\u003cp\u003eThe ANOVAs indicated significant differences in hatch proportion among mosquito lines across all diets (Figure 3E-H, Table 3-6, Diet 1\u0026ndash;4, all p \u0026lt; 0.001). Concentration significantly influenced hatch proportion only in Diets 1 (Pd) and 2 (Figure 3E and 3F, Table 3 and 4; p \u0026le; 0.016), but not in Diets 3 (Fd) and 4 (IAEA) (Figure 3G and 3H, Table 5 and 6; p \u0026ge; 0.104). Interaction effects between mosquito line and concentration were significant in Diets 1, 2, 3, but not in Diet 4 (IAEA) (Table 6; p \u0026ge; 0.220).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cu\u003eRelationship between female wing length and fecundity\u003c/u\u003e\u003c/p\u003e\n\u003cp\u003eFor female mosquitoes, a strong positive correlation was observed between wing length and fecundity (Figure 4) in both the uninfected (r\u003csup\u003e2\u003c/sup\u003e = 0.881) and \u003cem\u003ew\u003c/em\u003eAlbB (r\u003csup\u003e2\u003c/sup\u003e = 0.886) lines when combining data across diets, indicating that larger females consistently produced more eggs. The relationship was mostly linear except at higher fecundities, and the data suggest that wing length is a reliable predictor of fecundity in these two lines. In \u003cem\u003ew\u003c/em\u003eMelM, there was a weaker association (r\u003csup\u003e2\u003c/sup\u003e = 0.329). The reasons for this were unclear, since the fecundity and wing length values for this line covered a similar range than the other lines.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cu\u003eOptimal concentration\u003c/u\u003e\u003c/p\u003e\n\u003cp\u003eThe Fitness Index used in this study was developed based on mosquito fitness traits, following the method described in [37]. The optimal concentration was 1.6 mg/larva/day for Diet 1 (Pd), and 1.2 mg/larva/day for Diet 2 (Kd) and Diet 3 (Fd). For Diet 4 (IAEA) the optimum concentration was 0.8 mg/larva/day, indicating that diet composition and concentrations influence mosquito fitness. Almost all mosquito lines reached their maximum Fitness Index at identical concentrations within each diet, suggesting that the quantity of food at a specific composition is more influential in determining fitness than features unique to each line. The similar patterns across lines may indicate a common nutrient absorption that optimizes performance for each dietary type.\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eDiet allocation always had big impact on almost all fitness traits as shown in Table 3-6 and Figure 1-3. Fitness traits tended to increase at intermediate concentrations before decreasing again at high concentrations of larval food. Effects of lines (\u003cem\u003ew\u003c/em\u003eMelM, \u003cem\u003ew\u003c/em\u003eAlbB or uninfected) were also detected, with uninfected larvae tending to perform better in fecundity and egg hatching, as shown in Figure 3.\u003c/p\u003e\n\u003cp\u003eThe overall impact of line was less evident compared to diet concentrations; however, in the \u003cem\u003ew\u003c/em\u003eMelM line, reduced fecundity consistently occurred across all diets. This reduction was suspected to be due to the blood- meal-related rather than the larval diet factor. The low fecundity in \u003cem\u003ew\u003c/em\u003eMel was also reported in another study [38]. However, in Diet 2 (Kd) at 1.2 mg/larva/day concentration, high fecundity and hatch proportion in the \u003cem\u003ew\u003c/em\u003eMelM line at this concentration were detected. This variation could be due to uncontrolled variability in the experiment, which may have led to a lower \u003cem\u003eWolbachia\u0026nbsp;\u003c/em\u003edensity and therefore reduced symbiont-induced reproductive suppression. Further analysis of the \u003cem\u003eWolbachia\u003c/em\u003e screening data in the \u003cem\u003ew\u003c/em\u003eMelM line across food allocations will help us to further test this hypothesis.\u003c/p\u003e\n\u003cp\u003eIn high-carbohydrate diets, the protein composition of the larval diet strongly influenced mosquito fitness traits. Increased protein content significantly improved developmental outcomes, supporting previous findings on the critical role of dietary protein in larval growth, development rate, and adult size in \u003cem\u003eAedes aegypti\u003c/em\u003e and related species [39, 40, 41]. \u0026nbsp;Under a plant-based, low-protein diet, the proportion of pupation success remained relatively high despite delayed development, indicating that while energy availability can sustain survival, it is insufficient for optimal growth. In other work, replacing mushroom powder with animal-based liver powder markedly enhanced fitness traits and reduced development time [34].\u003c/p\u003e\n\u003cp\u003eWhen comparing a balanced diet (Diet 3 (Fd)) with a very high-protein, low-carbohydrate diet (Diet 4 (IAEA)), the fastest larval development was observed under Diet 4 (IAEA) across all \u003cem\u003eAe. aegypti\u003c/em\u003e lines. This is consistent with earlier findings showing that elevated dietary protein levels enhance developmental speed [42, 43]. However, this rapid development was accompanied by reduced female wing length, suggesting an environmentally based trade-off between development speed and adult fitness. A more balanced protein–carbohydrate ratio larval diet (LRD) produced larger females in uninfected \u003cem\u003eAe. aegypti\u003c/em\u003e compared to a high-protein, low-carbohydrate diet [42]. In contrast, male wing length showed similar trends across both Diet 3 (Fd) and Diet 4 (IAEA), with minimal variation between diets or lines. This suggests a potential physiological constraint on male body size, whereby males may reach a species-specific upper limit regardless of nutritional conditions. This observation aligns with previous findings showing that female size was more responsive to dietary variation, while male size remained relatively stable across nutritional conditions [15].\u003c/p\u003e\n\u003cp\u003eBigger females are a good indicator of higher fecundity, as larger individuals have a better ability to hold a greater volume of blood and possess higher energy reserves for egg production[44]. A diet with a balanced carbohydrate and protein content tends to result in higher lipid reserves at the adult stage, compared to a high-protein, low-carbohydrate diet, which can lead to reduced size and lower energy storage despite faster development [45].\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eDiet 3 (Fd) and Diet 4 (IAEA) consistently yielded higher fitness index scores in \u003cem\u003eAedes aegypti\u003c/em\u003e than the carbohydrate-rich, low-protein diet. Among the diets tested, Diet 3 (Fd), supported the highest composite life table scores across in \u003cem\u003ew\u003c/em\u003eAlbB and uninfected line at optimal concentration for maximizing development, survival, and reproductive output. These results are consistent with the possibility that improved larval nutrition could mitigate \u003cem\u003eWolbachia\u003c/em\u003e-associated fitness costs [7, 46] particularly for \u003cem\u003ew\u003c/em\u003eAlbB-infected mosquitoes, which in this study performed nearly as well as the uninfected line at optimum concentration. The narrowing gap in life table scores between \u003cem\u003ew\u003c/em\u003eAlbB and uninfected mosquitoes suggests that nutritional quality can buffer fitness costs and improve competitiveness. In contrast, in \u003cem\u003ew\u003c/em\u003eMelM, reduced fecundity was observed despite adequate wing length, suggesting that other contributing factors beyond larval nutrition. This is consistent with predictions from metabolic modelling studies indicating that \u003cem\u003eWolbachia\u003c/em\u003e strains such as \u003cem\u003ew\u003c/em\u003eMel may rely on host-derived lipids and amino acids for growth, potentially influencing pathways relevant to reproduction. \u0026nbsp;[47]. Blood source may also be a factor, since a previous study on \u003cem\u003ew\u003c/em\u003eMelM using Diet 3 (Fd) but with a different human volunteer did not identify any costs to fertility [31].\u0026nbsp;\u003c/p\u003e"},{"header":"Conclusions","content":"\u003cp\u003eIn this study, we found that diet composition and allocation play a significant role in determining key life traits of mosquitoes. A well-balanced protein and carbohydrate content produces mosquitoes with higher fitness compared to diets with lower protein content. The uninfected mosquito line showed the highest overall fitness across all diets compared to the \u003cem\u003ew\u003c/em\u003eMelM and \u003cem\u003ew\u003c/em\u003eAlbB lines. However, with a balanced diet and at an optimum concentration, the \u003cem\u003ew\u003c/em\u003eAlbB line seems to mitigate the fitness cost of \u003cem\u003eWolbachia\u003c/em\u003e infection. In contrast, the \u003cem\u003ew\u003c/em\u003eMelM line showed lower fecundity across all diets, probably due to factors other than the larval diet. Overall, almost all mosquito lines achieved maximum fitness scores at the same concentration. The different responses among mosquito lines also suggest that gut microbiota could play an important role in mediating nutrient utilization and overall fitness. Further microbiome profiling using 16S rRNA gene sequencing could improve our understanding of these interactions. This, in turn, could enhance \u003cem\u003eWolbachia\u003c/em\u003e release strategies to control arboviral infections. Such approaches would greatly benefit the consistency, scalability, and success of mass-release programs aiming to suppress or replace disease-transmitting mosquito populations.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cu\u003eEthics approval and consent to participate\u003c/u\u003e\u003c/p\u003e\n\u003cp\u003eBlood feeding on adult human volunteers was approved by the University of Melbourne Human Ethics committee (project ID 28583). Informed consent was obtained from all subjects.\u003c/p\u003e\n\u003cp\u003e\u003cu\u003eConsent for publication\u003c/u\u003e\u003c/p\u003e\n\u003cp\u003eNA\u003c/p\u003e\n\u003cp\u003e\u003cu\u003eAvailability of data and materials\u003c/u\u003e\u003c/p\u003e\n\u003cp\u003eThe datasets analysed during the current study are available on Figshare at: https://doi.org/10.26188/28785869.\u003c/p\u003e\n\u003cp\u003e\u003cu\u003eCompeting interests\u003c/u\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that they have no competing interests.\u003c/p\u003e\n\u003cp\u003e\u003cu\u003eFunding\u0026nbsp;\u003c/u\u003e\u003c/p\u003e\n\u003cp\u003eThis work was supported by the Wellcome Trust [grant numbers 226166, 108508, and 202888]\u003c/p\u003e\n\u003cp\u003e\u003cu\u003eAuthors\u0026apos; contributions\u003c/u\u003e\u003c/p\u003e\n\u003cp\u003eMF, PR, XG and AH designed the study. MF performed the experiments and collected experimental data. \u0026nbsp;MF, PR, XG and AH interpreted the results and wrote the manuscript. All authors read and approved the final manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cu\u003eAcknowledgements\u003c/u\u003e\u003c/p\u003e\n\u003cp\u003eWe thank Nancy Endersby-Harshman, Lawrence G. Harshman and Alex Gill for their assistance with laboratory assistance and technical support during this study.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eNazni WA, Hoffmann AA, NoorAfizah A, Cheong YL, Mancini MV, Golding N, et al. Establishment of \u003cem\u003eWolbachia\u003c/em\u003e strain \u003cem\u003ew\u003c/em\u003eAlbB in Malaysian populations of\u003cem\u003e Aedes aegypti \u003c/em\u003efor dengue control. Current Biology.\u003cem\u003e \u003c/em\u003e2019;29:4241-8.\u003c/li\u003e\n\u003cli\u003eVelez ID, Uribe A, Barajas J, Uribe S, Angel S, Suaza-Vasco JD, et al. Large-scale releases and establishment of \u003cem\u003ew\u003c/em\u003eMel \u003cem\u003eWolbachia\u003c/em\u003e in \u003cem\u003eAedes aegypti\u003c/em\u003e mosquitoes throughout the Cities of Bello, Medell\u0026iacute;n and Itag\u0026uuml;\u0026iacute;, Colombia. PLOS Neglected Tropical Diseases.\u003cem\u003e \u003c/em\u003e2023;17:e0011642.\u003c/li\u003e\n\u003cli\u003eTantowijoyo W, Andari B, Arguni E, Budiwati N, Nurhayati I, Fitriana I, et al. Stable establishment of \u003cem\u003ew\u003c/em\u003eMel \u003cem\u003eWolbachia\u003c/em\u003e in \u003cem\u003eAedes aegypti\u003c/em\u003e populations in Yogyakarta, Indonesia. PLOS Neglected Tropical Diseases.\u003cem\u003e \u003c/em\u003e2020;14:e0008157.\u003c/li\u003e\n\u003cli\u003eHoffmann AA, Ahmad NW, Keong WM, Ling CY, Ahmad NA, Golding N, et al. Introduction of \u003cem\u003eAedes aegypti\u003c/em\u003e mosquitoes carrying \u003cem\u003ew\u003c/em\u003eAlbB\u003cem\u003e Wolbachia\u003c/em\u003e sharply decreases dengue incidence in disease hotspots. Iscience.\u003cem\u003e \u003c/em\u003e2024; doi: https://doi.org/10.1016/j.isci.2024.108942.\u003c/li\u003e\n\u003cli\u003eZheng X, Zhang D, Li Y, Yang C, Wu Y, Liang X, et al. Incompatible and sterile insect techniques combined eliminate mosquitoes. Nature Biotechnology.\u003cem\u003e \u003c/em\u003e2019;572:56-61.\u003c/li\u003e\n\u003cli\u003eLim JT, Bansal S, Chong CS, Dickens B, Ng Y, Deng L, et al. Efficacy of \u003cem\u003eWolbachia\u003c/em\u003e-mediated sterility to reduce the incidence of dengue: a synthetic control study in Singapore. The Lancet Microbe.\u003cem\u003e \u003c/em\u003e2024; 5:e422.\u003c/li\u003e\n\u003cli\u003eHoffmann AA, Montgomery B, Popovici J, Iturbe-Ormaetxe I, Johnson P, Muzzi F, et al. Successful establishment of\u003cem\u003e Wolbachia\u003c/em\u003e in \u003cem\u003eAedes\u003c/em\u003e populations to suppress dengue transmission. Nature.\u003cem\u003e \u003c/em\u003e2011;476:454-7.\u003c/li\u003e\n\u003cli\u003ePinto SB, Riback TI, Sylvestre G, Costa G, Peixoto J, Dias FB, et al. Effectiveness of \u003cem\u003eWolbachia\u003c/em\u003e-infected mosquito deployments in reducing the incidence of dengue and other\u003cem\u003e Aedes\u003c/em\u003e-borne diseases in Niter\u0026oacute;i, Brazil: A quasi-experimental study. PLOS Neglected Tropical Diseases.\u003cem\u003e \u003c/em\u003e2021;15:e0009556.\u003c/li\u003e\n\u003cli\u003eRoss PA, Elfekih S, Collier S, Klein MJ, Lee SS, Dunn M, et al. Developing \u003cem\u003eWolbachia\u003c/em\u003e-based disease interventions for an extreme environment. PLOS Pathogens.\u003cem\u003e \u003c/em\u003e2023;19:e1011117.\u003c/li\u003e\n\u003cli\u003eUtarini A, Indriani C, Ahmad RA, Tantowijoyo W, Arguni E, Ansari MR, et al. Efficacy of \u003cem\u003eWolbachia\u003c/em\u003e-infected mosquito deployments for the control of dengue. New England Journal of Medicine.\u003cem\u003e \u003c/em\u003e2021;384:2177-86.\u003c/li\u003e\n\u003cli\u003eRyan PA, Turley AP, Wilson G, Hurst TP, Retzki K, Brown-Kenyon J, et al. Establishment of \u003cem\u003ew\u003c/em\u003eMel \u003cem\u003eWolbachia\u003c/em\u003e in \u003cem\u003eAedes aegypti\u003c/em\u003e mosquitoes and reduction of local dengue transmission in Cairns and surrounding locations in northern Queensland, Australia. Gates Open Research.\u003cem\u003e \u003c/em\u003e2019;3.\u003c/li\u003e\n\u003cli\u003eBenedict MQ, Hunt CM, Vella MG, Gonzalez KM, Dotson EM, Collins CM. Pragmatic selection of larval mosquito diets for insectary rearing of \u003cem\u003eAnopheles gambiae \u003c/em\u003eand \u003cem\u003eAedes aegypti\u003c/em\u003e. PLOS One.\u003cem\u003e \u003c/em\u003e2020;15:e0221838.\u003c/li\u003e\n\u003cli\u003eHaghighat-Khah RE, Harvey-Samuel T, Basu S, StJohn O, Scaife S, Verkuijl S, et al. Engineered action at a distance: Blood-meal-inducible paralysis in \u003cem\u003eAedes aegypti\u003c/em\u003e. PLOS Neglected Tropical Diseases.\u003cem\u003e \u003c/em\u003e2019;13:e0007579.\u003c/li\u003e\n\u003cli\u003eIAEA: Guidelines For Routine Colony Maintenance of \u003cem\u003eAedes \u003c/em\u003eMosquito Species Version 1.0.https://www.iaea.org/sites/default/files/21/06/nafa-ipc-manual-guidelines-for-routine-colony-maintenance-of-aedes-mosquito-species-v1.0.pdf (2017).\u003c/li\u003e\n\u003cli\u003eVan Schoor T, Kelly ET, Tam N, Attardo GM. Impacts of dietary nutritional composition on larval development and adult body composition in the yellow fever mosquito (\u003cem\u003eAedes aegypti\u003c/em\u003e). Insects.\u003cem\u003e \u003c/em\u003e2020;11:535.\u003c/li\u003e\n\u003cli\u003eSouza RS, Virginio F, Riback TIS, Suesdek L, Barufi JB, Genta FA. Microorganism-based larval diets affect mosquito development, size and nutritional reserves in the yellow fever mosquito \u003cem\u003eAedes aegypti \u003c/em\u003e(Diptera: Culicidae). Frontiers in Physiology.\u003cem\u003e \u003c/em\u003e2019;10:152.\u003c/li\u003e\n\u003cli\u003eContreras-Perera Y, Flores-Pech JP, P\u0026eacute;rez-Carillo S, Puerta-Guardo H, Geded-Moreno E, Correa-Morales F, et al. Different larval diets for \u003cem\u003eAedes aegypti \u003c/em\u003e(Diptera: Culicidae) under laboratory conditions: in preparation for a mass-rearing system. Biologia.\u003cem\u003e \u003c/em\u003e2023;78:3387-99.\u003c/li\u003e\n\u003cli\u003eZhang D, Zhang M, Wu Y, Gilles JR, Yamada H, Wu Z, et al. Establishment of a medium-scale mosquito facility: optimization of the larval mass-rearing unit for \u003cem\u003eAedes albopictus\u003c/em\u003e (Diptera: Culicidae). Parasites \u0026amp; Vectors.\u003cem\u003e \u003c/em\u003e2017;10:1-9.\u003c/li\u003e\n\u003cli\u003eKho EA, Hugo LE, Lu G, Smith DD, Kay BHy. Effects of larval nutrition on \u003cem\u003eWolbachia\u003c/em\u003e-based dengue virus interference in\u003cem\u003e Aedes aegypti\u003c/em\u003e (Diptera: Culicidae). Journal of Medical Entomology.\u003cem\u003e \u003c/em\u003e2016;53:894-901.\u003c/li\u003e\n\u003cli\u003eCoon KL, Vogel KJ, Brown MR, Strand MR. Mosquitoes rely on their gut microbiota for development. Molecular Ecology.\u003cem\u003e \u003c/em\u003e2014;23:2727-39.\u003c/li\u003e\n\u003cli\u003eCoon KL, Brown MR, Strand MR. Gut bacteria differentially affect egg production in the anautogenous mosquito \u003cem\u003eAedes aegypti\u003c/em\u003e and facultatively autogenous mosquito \u003cem\u003eAedes atropalpus\u003c/em\u003e (Diptera: Culicidae). Parasites \u0026amp; Vectors.\u003cem\u003e \u003c/em\u003e2016;9.\u003c/li\u003e\n\u003cli\u003eCansado-Utrilla C, Zhao SY, McCall PJ, Coon KL, Hughes GL. The microbiome and mosquito vectorial capacity: rich potential for discovery and translation. Microbiome.\u003cem\u003e \u003c/em\u003e2021;9:111.\u003c/li\u003e\n\u003cli\u003eCorrea MA, Matusovsky B, Brackney DE, Steven B. Generation of axenic \u003cem\u003eAedes aegypti\u003c/em\u003e demonstrate live bacteria are not required for mosquito development. Nature Communications.\u003cem\u003e \u003c/em\u003e2018;9:4464.\u003c/li\u003e\n\u003cli\u003eMacLeod HJ, Dimopoulos G, Short SM. Larval diet abundance influences size and composition of the midgut microbiota of \u003cem\u003eAedes aegypti\u003c/em\u003e mosquitoes. Frontiers in Microbiology.\u003cem\u003e \u003c/em\u003e2021;12:645362.\u003c/li\u003e\n\u003cli\u003eDeconninck G, Larges J, Henri H, Beaugeard L, Foray V, Pincebourde S. \u003cem\u003eWolbachia\u003c/em\u003e improves the performance of an invasive fly after a diet shift. Journal of Pest Science.\u003cem\u003e \u003c/em\u003e2024;97:2087-99.\u003c/li\u003e\n\u003cli\u003ePonton F, Wilson K, Holmes A, Raubenheimer D, Robinson KL, Simpson SJ. Macronutrients mediate the functional relationship between \u003cem\u003eDrosophila\u003c/em\u003e and \u003cem\u003eWolbachia\u003c/em\u003e. Proceedings of the Royal Society B: Biological Sciences.\u003cem\u003e \u003c/em\u003e2015;282:20142029.\u003c/li\u003e\n\u003cli\u003eBrownlie JC, Cass BN, Riegler M, Witsenburg JJ, Iturbe-Ormaetxe I, McGraw EA, et al. Evidence for metabolic provisioning by a common invertebrate endosymbiont, \u003cem\u003eWolbachia pipientis\u003c/em\u003e, during periods of nutritional stress. PLOS Pathogens.\u003cem\u003e \u003c/em\u003e2009;5:e1000368.\u003c/li\u003e\n\u003cli\u003eCaragata EP, Ranc\u0026egrave;s E, O\u0026rsquo;Neill SL, McGraw EA. Competition for amino acids between\u003cem\u003e Wolbachia\u003c/em\u003e and the mosquito host, \u003cem\u003eAedes aegypti\u003c/em\u003e. Microbial Ecology.\u003cem\u003e \u003c/em\u003e2014;67:205-18.\u003c/li\u003e\n\u003cli\u003eDutra HLC, Rodrigues SL, Mansur SB, de Oliveira SP, Caragata EP, Moreira LA. Development and physiological effects of an artificial diet for \u003cem\u003eWolbachia\u003c/em\u003e-infected \u003cem\u003eAedes aegypti\u003c/em\u003e. Scientific Reports.\u003cem\u003e \u003c/em\u003e2017; doi: https://doi.org/10.1038/s41598-017-16045-6.\u003c/li\u003e\n\u003cli\u003eRoss PA, Endersby NM, Hoffmann AA. Costs of three \u003cem\u003eWolbachia\u003c/em\u003e infections on the survival of \u003cem\u003eAedes aegypti\u003c/em\u003e larvae under starvation conditions. PLOS Neglected Tropical Diseases.\u003cem\u003e \u003c/em\u003e2016;10:e0004320.\u003c/li\u003e\n\u003cli\u003eGu X, Ross PA, Rodriguez‐Andres J, Robinson KL, Yang Q, Lau MJ, et al. A \u003cem\u003ew\u003c/em\u003eMel \u003cem\u003eWolbachia\u003c/em\u003e variant in \u003cem\u003eAedes aegypti\u003c/em\u003e from field‐collected \u003cem\u003eDrosophila melanogaster \u003c/em\u003ewith increased phenotypic stability under heat stress. Environmental Microbiology.\u003cem\u003e \u003c/em\u003e2022;24:2119-35.\u003c/li\u003e\n\u003cli\u003eRoss PA, Gu X, Robinson KL, Yang Q, Cottingham E, Zhang Y, et al. A \u003cem\u003ew\u003c/em\u003eAlbB \u003cem\u003eWolbachia\u003c/em\u003e transinfection displays stable phenotypic effects across divergent \u003cem\u003eAedes aegypti \u003c/em\u003emosquito backgrounds. Applied Environmental Microbiology.\u003cem\u003e \u003c/em\u003e2021;87:e01264.\u003c/li\u003e\n\u003cli\u003eXi Z, Khoo CC, Dobson SL. \u003cem\u003eWolbachia\u003c/em\u003e establishment and invasion in an \u003cem\u003eAedes aegypti \u003c/em\u003elaboratory population. Science.\u003cem\u003e \u003c/em\u003e2005;310:326-8.\u003c/li\u003e\n\u003cli\u003eSalim M, Kamran M, Khan I, Saljoqi AUR, Ahmad S, Almutairi MH, et al. Effect of larval diets on the life table parameters of dengue mosquito, \u003cem\u003eAedes aegypti \u003c/em\u003e(L.)(Diptera: Culicidae) using age-stage two sex life table theory. Scientific Reports.\u003cem\u003e \u003c/em\u003e2023;13:11969.\u003c/li\u003e\n\u003cli\u003eSasmita HI, Tu W-C, Bong L-J, Neoh K-B. Effects of larval diets and temperature regimes on life history traits, energy reserves and temperature tolerance of male \u003cem\u003eAedes aegypti\u003c/em\u003e (Diptera: Culicidae): optimizing rearing techniques for the sterile insect programmes. Parasites \u0026amp; Vectors.\u003cem\u003e \u003c/em\u003e2019;12:1-16.\u003c/li\u003e\n\u003cli\u003eWarton DI, Hui FK. The arcsine is asinine: the analysis of proportions in ecology. Ecology.\u003cem\u003e \u003c/em\u003e2011;92:3-10.\u003c/li\u003e\n\u003cli\u003eLivdahl TP, Sugihara G. Non-linear interactions of populations and the importance of estimating per capita rates of change. The Journal of Animal Ecology.\u003cem\u003e \u003c/em\u003e1984;53:573-80.\u003c/li\u003e\n\u003cli\u003eMaciel-de-Freitas R, Sauer FG, Kliemke K, Garcia GA, Pavan MG, David MR, et al. \u003cem\u003eWolbachia\u003c/em\u003e strains \u003cem\u003ew\u003c/em\u003eMel and \u003cem\u003ew\u003c/em\u003eAlbB differentially affect \u003cem\u003eAedes aegypti\u003c/em\u003e traits related to fecundity. Microbiology Spectrum.\u003cem\u003e \u003c/em\u003e2024;12:e00128.\u003c/li\u003e\n\u003cli\u003eBriegel H. Metabolic relationship between female body size, reserves, and fecundity of \u003cem\u003eAedes aegypti\u003c/em\u003e. Journal of Insect Physiology.\u003cem\u003e \u003c/em\u003e1990;36:165-72.\u003c/li\u003e\n\u003cli\u003eTelang A, Li Y, Noriega FG, Brown MR. Effects of larval nutrition on the endocrinology of mosquito egg development. Journal of Experimental Biology.\u003cem\u003e \u003c/em\u003e2006;209:645-55.\u003c/li\u003e\n\u003cli\u003eClements AN. The biology of mosquitoes: development, nutrition and reproduction. vol. 1. London: Chapman Hall; 1992.\u003c/li\u003e\n\u003cli\u003eBond J, Ram\u0026iacute;rez-Osorio A, Marina C, Fern\u0026aacute;ndez-Salas I, Liedo P, Dor A, et al. Efficiency of two larval diets for mass-rearing of the mosquito \u003cem\u003eAedes aegypti\u003c/em\u003e. PLOS One.\u003cem\u003e \u003c/em\u003e2017;12:e0187420.\u003c/li\u003e\n\u003cli\u003eBimbil\u0026eacute; Somda NS, Dabir\u0026eacute; KR, Maiga H, Yamada H, Mamai W, Gnankin\u0026eacute; O, et al. Cost-effective larval diet mixtures for mass rearing of \u003cem\u003eAnopheles arabiensis\u003c/em\u003e Patton (Diptera: Culicidae). Parasites \u0026amp; Vectors.\u003cem\u003e \u003c/em\u003e2017;10:1-12.\u003c/li\u003e\n\u003cli\u003eYan J, Kibech R, Stone CM. Differential effects of larval and adult nutrition on female survival, fecundity, and size of the yellow fever mosquito,\u003cem\u003e Aedes aegypti\u003c/em\u003e. Frontiers in Zoology.\u003cem\u003e \u003c/em\u003e2021;18:1-9.\u003c/li\u003e\n\u003cli\u003eArrese EL, Soulages JL. Insect fat body: energy, metabolism, and regulation. Annual Review of Entomology.\u003cem\u003e \u003c/em\u003e2010;55:207-25.\u003c/li\u003e\n\u003cli\u003eRoss PA, Axford JK, Richardson KM, Endersby-Harshman NM, Hoffmann AA. Maintaining \u003cem\u003eAedes aegypti \u003c/em\u003emosquitoes infected with \u003cem\u003eWolbachia\u003c/em\u003e. JoVE.\u003cem\u003e \u003c/em\u003e2017; 126:e56124.\u003c/li\u003e\n\u003cli\u003eJim\u0026eacute;nez NE, Gerdtzen ZP, Olivera-Nappa \u0026Aacute;, Salgado JC, Conca C. A systems biology approach for studying \u003cem\u003eWolbachia \u003c/em\u003emetabolism reveals points of interaction with its host in the context of arboviral infection. PLOS Neglected Tropical Diseases.\u003cem\u003e \u003c/em\u003e2019;13:e0007678.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":false,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"parasites-and-vectors","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"parv","sideBox":"Learn more about [Parasites \u0026 Vectors](http://parasitesandvectors.biomedcentral.com/)","snPcode":"13071","submissionUrl":"https://submission.nature.com/new-submission/13071/3","title":"Parasites \u0026 Vectors","twitterHandle":"@bugbittentweets","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Wolbachia, wMelM, wAlbB, larval diet, optimum concentrations, fitness traits, dengue control, Aedes aegypti","lastPublishedDoi":"10.21203/rs.3.rs-6459379/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6459379/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e \u003cp\u003eReleases of \u003cem\u003eAedes aegypti\u003c/em\u003e infected with \u003cem\u003eWolbachia\u003c/em\u003e are being used to effectively control diseases related to arboviruses in some settings. A well-balanced larval diet is essential for producing \u003cem\u003eWolbachia-\u003c/em\u003einfected mosquitoes with optimal fitness for release.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eIn this study, four diets with varying protein-to-carbohydrate ratios were tested with three \u003cem\u003eAedes aegypti\u003c/em\u003e lines (carrying the \u003cem\u003ew\u003c/em\u003eAlbB, \u003cem\u003ew\u003c/em\u003eMelM infections or uninfected) to identify optimal diets for larval rearing based on diet allocations ranging from 0.4 to 3.2 mg/larva/day. The diets were selected based on a review of existing literature and are characterized by progressively increasing protein and decreasing carbohydrate content: Diet 1(Pd) was based on plant-based protein (low protein, high carbohydrate), Diet 2 (Kd) was based on animal-based protein (moderate protein, high carbohydrate), Diet 3 (Fd)- involved Hikari fish food (high protein and moderate carbohydrate), and Diet 4 (IAEA) followed a widely used very high protein and low carbohydrate diet developed by the International Atomic Energy Agency (IAEA). The optimal concentration for each diet was determined using a fitness index that incorporated pupation success, fecundity, hatch proportion, and development time.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eThe optimal dietary allocations for Diets 1 to 4 were 1.6, 1.2, 1.2, and 0.8 mg per larva per day, respectively, regardless of \u003cem\u003eWolbachia\u003c/em\u003e status. There was a consistent significant positive relationship between female wing length and fecundity in \u003cem\u003ew\u003c/em\u003eAlbB (r\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;0.881), \u003cem\u003ew\u003c/em\u003eMelM (r\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;0.329), and uninfected (r\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;0.886) mosquitoes. Diet 3 (Fd) reduced a fitness cost commonly associated with the \u003cem\u003ew\u003c/em\u003eAlbB line compared to the uninfected line when provided at the optimal concentration. The \u003cem\u003ew\u003c/em\u003eMelM line showed a persistently low fecundity regardless of diet and concentration.\u003c/p\u003e\u003ch2\u003eConclusions\u003c/h2\u003e \u003cp\u003eThese findings highlight the importance of an appropriate larval diet and dietary allocations in optimizing mosquito fitness for \u003cem\u003eWolbachia\u003c/em\u003e-based vector control programs. Further research into dietary composition, gut microbial interactions, and \u003cem\u003eWolbachia\u003c/em\u003e associations could refine larval nutrition strategies, enhancing the effectiveness of mass-rearing for release programs.\u003c/p\u003e","manuscriptTitle":"Impact of larval diet on fitness outcomes of Aedes aegypti mosquitoes infected with wAlbB and wMelM","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-05-02 11:07:44","doi":"10.21203/rs.3.rs-6459379/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2025-05-20T17:33:19+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-05-20T15:07:51+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-05-14T22:14:39+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"329523640058973794543877602449020803851","date":"2025-04-29T13:46:07+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"272389614898103090642868676532988471232","date":"2025-04-28T14:36:45+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"275029939234888888005329298068184296194","date":"2025-04-28T14:05:09+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-04-28T09:44:15+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-04-22T18:14:39+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-04-22T15:02:59+00:00","index":"","fulltext":""},{"type":"submitted","content":"Parasites \u0026 Vectors","date":"2025-04-16T04:21:49+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"parasites-and-vectors","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"parv","sideBox":"Learn more about [Parasites \u0026 Vectors](http://parasitesandvectors.biomedcentral.com/)","snPcode":"13071","submissionUrl":"https://submission.nature.com/new-submission/13071/3","title":"Parasites \u0026 Vectors","twitterHandle":"@bugbittentweets","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"bf52e063-308e-4237-95ce-cca42d04e418","owner":[],"postedDate":"May 2nd, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2025-09-29T16:07:31+00:00","versionOfRecord":{"articleIdentity":"rs-6459379","link":"https://doi.org/10.1186/s13071-025-06978-7","journal":{"identity":"parasites-and-vectors","isVorOnly":false,"title":"Parasites \u0026 Vectors"},"publishedOn":"2025-09-24 15:57:22","publishedOnDateReadable":"September 24th, 2025"},"versionCreatedAt":"2025-05-02 11:07:44","video":"","vorDoi":"10.1186/s13071-025-06978-7","vorDoiUrl":"https://doi.org/10.1186/s13071-025-06978-7","workflowStages":[]},"version":"v1","identity":"rs-6459379","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6459379","identity":"rs-6459379","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}