Ecology

The experiment was conducted at Agricultural and Bio-Systems Engineering Department, Faculty of Agriculture Moshtohor, Benha University, Egypt (latitude 30° 21′ N and 31° 13′ E), during the period of May to July, 2019 season under the university guidelines and legislation. Basil seedlings were sown in the plastic cups (7 cm diameter and 7 cm height) filled with peat moss. The cups were irrigated daily using water with nutrient solution (Ca(NO3)2, 236 g L−1, KNO3, 101 g L−1, K2SO4, 115 g L−1, KH2PO4, 136 g L−1, MgSO4 246 g L−1 and chelates for trace elements into preacidified groundwater (from the following ppm concentration are achieved in this formulation: N = 210, P = 31, K = 234, Ca = 200, Mg = 48, S = 64, Fe = 14, Mn = 0.5, Zn = 0.05, Cu = 0.02, B = 0.5, Mo = 0.01)). Two weeks old basil seedlings were planted at 9.0 plant m−2 in the experimental tanks. These seedlings were planted according to the permission of Benha university rules and legislation.Culture systems descriptionFigure 1a,b show the experimental setup. It shows the system which consists of hydroponic system, aeroponic system, soilless substrate, solution system and pumps.Figure 1(a) The experimental setup. (b) Images of system.Full size imageThe hydroponic system (Deep Water Culture (DWC)) consists of three rectangular polyethylene tanks that used for basil plants culture. Dimensions of each tank are 80 cm long, 40 cm wide and 30 cm high. The slope of hydroponic tanks was 2% and stand 1 m high above the ground. The hydroponic tanks were covered with foam boards to support the plants. Each hydroponic tank provided with an air blower (Model NS 780—Flow Rate 850 L h−1—Head 1.5 m—Power 15 W, China) to increase dissolved oxygen concentrations. The solution was circulated by a pump (Model First QB60—Flow Rate 30 L min−1—Head 25 m—Power 0.5 hp, China) from the solution tank to the upper ends of the hydroponic tanks. Small tubes (16 mm) were used to provide tanks with solution in a closed system.Aeroponic system consists of three rectangular polyethylene tanks that used for basil plants culture. Dimensions of each tank are 80 cm long, 40 cm wide and 50 cm high. The aeroponic tanks were established 1 m above the ground. Each aeroponic tank was divided into two parts, the lower part was made from polyethylene and the upper part was made from wood. The aeroponic tanks were covered with foam boards to support the plants. Each aeroponic tank was provided with two fog nozzles (Model M3MNWT5M – Orifice 2 mm – Discharge 8 L h−1, India) located at the bottom of the tank sprayed nutrient solution into the tank in order to keep the roots wet. Small tubes (16 mm) were used to provide aeroponic tank with solution in a closed system.Soilless substrates consist are placed in three rows are 2 m long. Each row consists standard peat moss slabs (1.00 m × 0.20 m × 0.075 m). Basil plants were placed on row peat moss slabs with a drip irrigation system. There were three plants per slab giving a mean density of 9.0 plant m−2. Each plant was fed by a single drip.The circular polyethylene tank of the nutrient solution system 500 L capacity was used for collecting the drained solution by gravity from the ends of the three systems. The nutrient solutions were prepared manually once per ten days17,18 by dissolving appropriate amounts of Ca(NO3)2, 236 g L−1, KNO3, 101 g L−1, K2SO4, 115 g L−1, KH2PO4, 136 g L−1, MgSO4 246 g L−1 and chelates for trace elements into preacidified groundwater (from the following ppm concentration are achieved in this formulation: N = 210, P = 31, K = 234, Ca = 200, Mg = 48, S = 64, Fe = 14, Mn = 0.5, Zn = 0.05, Cu = 0.02, B = 0.5, Mo = 0.01). pH and Electrical Conductivity (EC) were further adjusted to 6.5–7.0 and 1.4–1.8 dS m−1, respectively, after salt addition. The average air ambient temperature was 25.97 ± 4.37 °C and the average water temperature was 24.03 ± 3.92 °C. The average relative humidity was 65.4% and the light intensity was 338.55 ± 40.06 W m−2.MeasurementsThree plants sample were taken during the vegetative and flowering stages (four and seven weeks after transplanting, respectively) for growth measurement and chemical analysis. Plant height, root length and the fresh and dry weight of leaves, stems and roots were determined. After measuring fresh mass, the plants were oven dried at 65 °C until constant weight was reached19. Total content of macro elements was evaluated after being digested20. Nitrogen was determined by Kjeldahl digestion methods21. Potassium, Calcium and magnesium were determined by Photofatometer (Model Jenway PFP7—Range 0—160 mmol L−1, USA) and phosphorus (P) was determined colorimetrically method22. The content of oil was determined in different organs: leaves, stems and inflorescences according to23.Water samples were taken, at inlet and outlet of the culture units for measuring nitrogen (N), phosphorus (P), potassium (K), calcium (Ca) and magnesium (Mg) were measured every week at 10 am during the experimental period.Total production costThe cost calculation based on the following parameters was also performed:Fixed costs (Fc)Depreciation costs (Dc)$$D_{c} = frac{{P_{d} – S_{r} }}{{L_{d} }}$$
(1)

where Dc is the depreciation cost, EGP (Egyptian pound) year−1. ($ = 15.63 EGP). Pd is the system price, EGP. Sr is the salvage rate (0.1Pd) EGP. Ld is the system life, year.Interest costs (In):$$I_{n} = frac{{P_{d} + S_{r} }}{2} times {text{i}}_{{text{n}}}$$
(2)

where In is the interest, EGP year−1. in is the interest as compounded annually, decimal (12%). Shelter, taxes and insurance costs (Si).Shelter, taxes and insurance costs were assumed to be 3% of the purchase price of the automatic feeder (Pm).Then:$${text{Fixed,cost }} = {text{ D}}_{{text{c}}} + {text{ I}}_{{text{n}}} + 0.03{text{ P}}_{{text{m}}} /{text{ hour, of, use ,per ,year}}$$
(3)
Variable (operating) costs (Vc)Repair and maintenance costs (Rm):$${text{R}}_{{text{m}}} = 100% ;{text{deprecation,cost/hour,of,use,per,year}}$$
(4)
Energy costs (E):$${text{E }} = {text{ EC }} times {text{ EP}}$$
(5)

where E is the energy costs, EGP h−1. EC is the electrical energy consumption, kWh. EP is the energy price, 0.57 EGP kW−1.Labor costs (La):$${text{L}}_{{text{a}}} = {text{ Salary, of, one, worker }} times {text{ No}}{text{. ,of, workers}}$$
(6)

where La is the Labor costs, EGP h−1. Salary of one worker = 10 EGP h−1. No. of workers = 1.Then:$${text{Variable,costs }} = {text{ Rm }} + {text{ E }} + {text{ La}}$$
(7)
Total costs (Tc)$${text{Total ,costs }} = {text{ Fixed ,costs }} + {text{ Variable ,costs}}$$
(8)

Table 1 shows the input parameters of calculate total production costs of basil plants grown in different soilless systems.Table 1 The input parameters of calculate total production costs of basil plants grown in different soilless systems.Full size tableNutrients consumption rateThe Nutrients consumption rate were calculated as the differences between the nutrients at inlet and outlet of culture units by the following formula24:$$C_{{Nc}} = frac{{Nc_{{in}} – Nc_{{out}} }}{{{text{Number, of ,plants}}}} times Q times {text{24}}$$
(9)

where CNc is the nutrients consumption rate, mg day−1 plant −1. Ncin is the nutrients at inlet of the hydroponic unit, mg L−1. Ncout is the nutrients at outlet of the hydroponic unit, mg L−1. Q is the discharge, L h−1.Model development of nutrient consumptionModel assumptions:

N, P, K, Ca and Mg are the nutrients used in study.

The plants are uniformity distributed in the solution, so they work as a uniform sink for water and minerals with space at any time.

The root systems are uniformly dispersed in the solution with uniform root length density at any time.

The whole root system uptake characteristics are uniform.

Water losses by evaporation are negligible.

The simplest nutrient consumption models relate the nutrient consumption to the concentration gradient using some sort of proportionality factor such as root permeability or conductivity25,26. The nutrient consumption was determined by using the following equation:$$NC = a_{{NC}} cdot Delta {text{C }}$$
(10)

where NC is the nutrient consumption, mg plant−1 day−1. ∆C is the concentration gradient, mg plant−1 day−1. aNC is the proportionality factor, dimensionless.A similar model of nutrient consumption takes into consideration the differing effects caused by variations in root growth stage. Assuming that growth follows a first order differential equation and assuming that the root growth is exponential27, then Eq. (11) can be derived. This equation is presented in similar form to Eq. (10) and use the following equation:$$NC = left( {frac{{left( {C_{{plant}} – {text{C}}_{{{text{plant0}}}} } right)}}{{A_{r} – A_{{r0}} }}} right) cdot left( {frac{{{text{ln}}left( {frac{{{text{A}}_{{text{r}}} }}{{{text{A}}_{{{text{r0}}}} }}} right)}}{{{text{t}} – {text{t}}_{0} }}} right){text{.A}}_{{text{r}}}$$
(11)

where Cplanto is the concentration of the nutrients in the plant at time t0, mg plant−1. Ar is the root surface area at time t, cm2 plant−1. Ar0 is the root surface area at time t0, cm2 plant−1.Root surface area was calculated from root length and mean root radius using the following equation:$$A_{r} = {text{2}}pi {text{r}}_{{text{0}}} {text{L}}_{{text{r}}}$$
(12)
The root length increment using the following equation28:$$Delta L_{r} = Delta DW_{{root}} {text{v }}$$
(13)

where ∆Lr is the root length increment, cm day−1. ∆DWroot is the daily amount of root dry mass increment, g day−1. v is the ratio of root length and mass of roots, cm g−1.The daily amount of dry weight of roots is calculated from the following equation29:$$Delta DW_{{root}} = left{ {begin{array}{*{20}l} {{text{5LAI}}} hfill & {{text{for,LAI}} le {{0}}{{.5}}} hfill \ {{{2}}{{.5}} + {{23}}{{.9}}left( {{text{LAI-0}}{{.5}}} right)} hfill & {{text{for,LAI}} > {{0}}{{.5}}} hfill \ end{array} } right.$$
(14)

where LAI is the leaf area index.Leaf area index was changed in the same proportions as root length density to maintain a constant ratio between roots and shoots. The leaf area index is calculated from the following equation30:$$LAI = frac{{LAI_{{max }} }}{{1 + K_{2} e^{{left( { – k_{1} t} right)}} }}$$
(15)

where LAImax is the maximum leaf area index. K2 and k1 are the coefficients of the growth functions.All computational procedures of the model were carried out using Excel spreadsheet. The computer program was devoted to mass balance for predicting the nutrients consumption. The differences between the predicted and measured values were evaluated using RMSE indicator (root means square error) which is calculated using the following equation:$$RMSE = sqrt {frac{{sum {left( {Predicted-Measured} right)^{2} } }}{n}}$$
(16)
The parameters used in the model that were obtained from the literature are listed in Table 2. Figure 2 shows flow chart of the model.Table 2 The parameters used in the model.Full size tableFigure 2Flow chart of nutrients consumption rate.Full size imageStatistical analysisThree replicates of each treatment were allocated in a Randomize Complete Block Design (RCBD) in the system. Data were analyzed one-way ANOVA (analysis of variance) using statistical package for social sciences (spss v21). Means were separated using New Duncan Multiple Range Test (DMRT). Data presented are mean ± standard division (SD) of four replicates. More

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A single long day induces the photoperiodic molecular responseFigure 1c shows results from the experiment 1, as evidenced from the qPCR measurement of mRNA expression of genes of known biological functions in the blood and hypothalamus. Clearly, the exposure to extended light period induced a molecular response by hour 18 of the first long day, as shown by change in mRNA levels of candidate genes in both central (hypothalamus) peripheral (blood) tissues of photosensitive buntings. Blood mRNA levels of peroxiredoxin 4 (prdx4) were significantly lower at hour 18 mimicking a long 18 h photoperiod than those at hour 10 mimicking a short 10 h photoperiod (p = 0.002, t = 5.18, n = 4/time point). Paradoxically, this indicated a reduced cellular response against oxidative stress in the otherwise photo stimulated birds on the first long day. We speculate that prdx4 expression pattern would be inversed (i.e. increased prdx4 mRNA levels) after several long days when birds show photoperiodically stimulated hyperphagia (increased food intake) and lipogenesis (fat accumulation). Intriguingly, however, blood mRNA levels of gpx1 (p = 0.399, t = 0.91, n = 4/time point) and sod1 (p = 0.845, t = 0.20, n = 4/time point) genes were not different between hours 10 and 18 (Student’s t-test, Fig. 1c(a–c)). Taken together differences in the expression pattern of these enzymes, we speculate differential activation of the enzymatic pathways that are probably involved in the oxidative cellular response when migratory birds are exposed to an acute change in their photoperiodic environment.On the other hand, blood il1β mRNA levels were significantly higher at hour 18 than the hour 10 (p = 0.041, t = 2.58, n = 4/time point; Student’s t-test, Fig. 1c(d)). It is consistent with the known role of il1β-encoded interleukin 1β, as a crucial mediator of the inflammation and a marker of the innate immune system22,23. Increased il1β mRNA expression on the first long day is consistent with the idea of parallel photoperiodic induction of multiple biological processes, including those associated with the innate immune response, body fattening and gonadal maturation in migratory songbirds28; however, the possibility that an upregulated interleukin was an indicative a stress response cannot be excluded at this time.Changes in hypothalamic gene expressions further confirm a rapid molecular response to the extended light period when it surpasses the threshold photoperiod, i.e. acts as the stimulatory long day. Reciprocal switching of genes involved in the thyroid hormone responsive pathway at hour 18 particularly evidences this. Hypothalamic mRNA levels of tshβ (p = 0.033, t = 2.75, n = 4/time point) and dio2 (p = 0.0004, t = 7.14, n = 4/time point) genes were higher, and that of dio3 gene expression was lower at hour 18 than the hour 10 (p = 0.036, t = 2.68, n = 4/time point). This is also in agreement with the rapid photoperiodic response found on the first long day in plasma LH secretion, and in hypothalamic expressions of Fos-immunoreactivity and thyroid hormone responsive genes in blackheaded buntings14,33 and other photoperiodic birds15,17,19,32,34,35,36,37,38. However, gnrh mRNA levels were not found significantly different between hours 10 and 18 of the first long day (p = 0.324, t = 1.07, n = 4/time point; Student’s t-test, Fig. 1c(e–h) indicating that hour 18 was probably too early a time for an upregulated gnrh expression on the first long day37,38,39.RNA-Seq reveals differences in time course of the photoperiodic responseTable S2 summarizes the primary statistics used for RNA-Seq results. Using only transcripts with non-zero abundance, we compared the time course of transcriptome-wide response in the hypothalamus both as the function of time (within photosensitive or photorefractory state) and LHS (photosensitive vs. photorefractory state; n = 2/time point/state except at hour 22 in photorefractory state which had n = 1 sample size). Further, to show a functional linkage of differentially expressed genes (DEGs), we performed STRING analysis that predicts the protein–protein interaction (see methods for details).Results on hypothalamic gene expressions suggest that buntings react to the acute photoperiodic change in photorefractory state almost as they do in the photosensitive state. However, the comparison of the overall RNASeq data from both states revealed LHS-dependent pattern in the time course of transcriptional response, with differences in the number and functions of DEGs and associated physiological pathways.Within state differences in time course of transcriptional responseWe examined the time course of response on the first long day, by comparing gene expressions at the hours 14, 18 and 22 of the extended light period that mimicked 14 h, 18 h and 22 h long photoperiods, respectively, with those at hour 10 that mimicked a 10 h short photoperiod.Photosensitive stateAt hour 14, we found 10 differentially expressed genes (DEGs) with 4 upregulated and 6 downregulated genes (Figs. 2a, 3a, Table S3). Of the 10 DEGs, atp6v1e1, atp6v1b2, uqcrc1 and pgam1 genes enriched the oxidative phosphorylation, metabolic pathways, phagosome and mTOR signalling pathways (Table 1). The oxidative phosphorylation and metabolic pathways were upregulated at hour 10, while the phagosome and mTOR signalling pathways were enriched by two genes that were opposite in the expression trend: atp6v1e1 was upregulated while atp6v1b2 was downregulated at hour 14. The STRING analysis showed a significant interaction of atp6v1e1 and atp6v1b2 encoded proteins (ATP6V1E1 and ATP6V1B2). These proteins are the components of vacuolar ATPase enzyme that mediates the acidification of eukaryotic intracellular organelles necessary for protein sorting and zymogen activation. Further, at hour 14, ttr gene that codes for transthyretin (a preferential T3 binder) and pomc gene that codes for the proopiomelanocortin receptor had significantly lower expressions. Whereas, low ttr gene expression, as in photostimulated redheaded buntings40, might indicate a reduced trafficking of thyroid hormones via ttr-encoded transthyretins in the photosensitive state, the low pomc gene expression might suggest the removal of inhibitory effects of the opioids (e.g. β-endorphin, a pomc-encoded proopiomelanocortin product) on hypothalamic GnRH and, in turn, pituitary LH secretion41,42.Figure 2Top panel: Volcano plots showing results of differential gene expression analysis (− log10 padj. vs. log2 fold change values) in the hypothalamus within the photosensitive (a–c) and photorefractory states (e–g). The comparison protocol is shown on the left. In each state, the comparisons were done with respect to the hour 10 value (akin to short day control). Venn diagram shows common and unique DEGs in photosensitive (d) and photorefractory states (h). Bottom panel: Volcano plots showing results of differential gene expression analysis (− log10 padj. vs. log2 fold change values) between the photosensitive and photorefractory states. The pairwise comparisons were made at all the four time points (hours 10 (i), 14 (j), 18 (k) and 22 (l)). Venn diagram shows common and unique DEGs between states at hours 10, 14, 18 and 22 (m). Genes in a volcano plot with log2 fold change  > 2 are marked by green colour, and those with log2 fold change  > 2 and p value (padj.)  More

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Ethics and vertebrate animalsThe field surveys and collections were conducted on accessible public areas or private residential areas with property owners’ permission. The study did not involve human participants, or endangered or protected species. Laboratory mice were used as a blood source for mosquitoes. All experimental protocols were approved by the Institutional Animal Care and Use Committee (IACUC) of the University of California, Irvine (UCI) (IACUC protocol number: AUP-19-165). All methods were carried out in accordance with relevant IACUC guidelines and regulations.Study sites and mosquito larval habitat surveillanceThe study was carried out in Orange County, California, USA. Orange County is a highly urbanized county with an estimated population density of approximately 1470 people/km2 according to U.S. Census Bureau, an average annual low/high temperature range of 13–25 °C, 65% relative humidity, and annual precipitation of about 350 mm according to U.S. Climate Data. Annual rainfall was 261 mm, 311 mm, 198 mm and 475 mm for 2016, 2017, 2018 and 2019, respectively. A major drought event occurred in December 2017 and February 2018 when the total rainfall in the 3-month period was 20.6% of the 30-year average. Both Ae. aegypti and Ae. albopictus were discovered in the county in 20158. Culex quinquefasciatus is the most abundant mosquito in the county and breeds readily in a variety of residential, commercial and USDS water sources, and is the primary vector of West Nile virus in southern California18.Larval mosquito surveillance in Orange County was conducted from 2016 to 2019 by the Orange County Mosquito and Vector Control District (OCMVCD) through its routine mosquito surveillance and treatment program, following the recommendations of the California Department of Public Health and the Mosquito and Vector Control Association of California19. Briefly, OCMVCD staff conducted routine inspection for aquatic habitats in randomly selected public areas, and performed door-to-door mosquito larval and adult sampling on residential or commercial premises upon the request of the residents or business owners while distributing public education materials for vector control and personal protection. Arial photography was used to examine the presence of abandoned swimming pools in residential areas. In addition to surface aquatic habitats, subsurface habitats (e.g., catch basins, underground drains, manhole chambers, and public utility vaults) were examined for larval abundance of all mosquito species. In 2019, OCMVCD completed 5,622 mosquito service requests, and conducted 11,813 inspection and treatments on routine sites using a variety of public health-approved adulticides and larvicides. A total of 38,099 underground drains and catch basins and 6925 km of flood channels were treated. In addition, a total of 17,783 km of gutters and 3562 neglected swimming pools were inspected and treated. The larval distribution data reported here were based on this extensive field sampling effort20.Larval sampling used standard mosquito dippers or pipettes, and specialized modifications of these to sample hard to reach areas. Mosquito larvae from each source were collected, transferred into a uniquely-numbered vial with isopropyl alcohol (70%), and submitted to the laboratory for identification; if present, live pupae were collected and held in site-specific labelled rearing chambers (BioQuip Products, Inc., Rancho Dominguez, CA) until emergence. Third and fourth instar mosquito larvae (1–100, depending on sample size) and emerged adults were identified to species using a stereo microscope (40–50x) and morphological features described in taxonomic keys21,22. Results were uploaded to OCMVCD’s data management system, along with collection date, GPS location, and habitat type for each sample site. For this study, larval habitats were classified into six types: small container, underground system, ornamental water features, marsh, pools/spas, and creek (Table S1). The container classification included flowerpots/vases, saucers, tires, bowls, boxes, buckets, dishes, tree holes, etc. Underground storm drain system referred to larval habitats such as catch basins, manhole chambers, underground drains, and public utility vaults that were below the ground. Water feature included flood control channels, ponds, fountains, birdbaths, street gutters and small reservoirs, etc. Marsh included both fresh and salt water marshes.Mosquito strains and water source for laboratory studiesWe examined the effect of USDS water on oviposition substrate preference and larval development in microcosms in an insectary with climate control (27 ± 1 °C, 70 ± 10% relative humidity, and 12 h light/12 h dark photoperiod) at UCI. To minimize potential bias on behavior and ecology from mosquito colonization, this study did not use previously established laboratory mosquito colonies. Instead, we used Ae. aegypti and Ae. albopictus adults reared from field-collected eggs using ovicups in residential areas of Orange and Los Angeles Counties, California, respectively. Culex quinquefasciatus were also reared from eggs of field-collected, blood-engorged adult mosquitoes using gravid traps in Orange County23.All experiments reported here used two types of habitat water: (1) USDS water collected from seven manhole chambers or catch basins (33°47′01.9″N, 117°53′19.0″W, Orange City, manhole; 33°52′25.0″N, 117°57′02.6″W, Fullerton City, manhole; 33°44′44.4″N, 118°06′24.2″W, Seal Beach City, manhole; 33°55′38.9″N, 117°56′51.4″W, La Habra City, manhole; 33°52′48.9″N, 117°55′21.4″W, Fullerton City, catch basin; 33°54′35.2″N, 117°56′02.5″W, Fullerton City, catch basin; 33°52′25.0″N, 117°57′02.6″W, Fullerton City, catch basin); and 2) flowerpot water from vases of three cemeteries in Orange County (33°50′29.0″N, 117°53′57.9″W; 33°46′21.5″N, 117°50′35.8″W; 33°46′12.3″N, 117°50′21.4″W). Water (including sediments) from each breeding source was collected with mosquito dippers and mixed together by habitat type into 18.9 L (five-gallon) Nalgene™ containers. The containers were transported to the laboratory in shaded ice containers, and stored overnight in a refrigerator at 4 °C. The experiments described below were conducted on the field-collected water for the two habitat types. We selected flowerpot water as the comparison substrate because flowerpot containers showed the highest larval positivity rate in the study area.Oviposition preference testTo examine whether USDS water attracts or repels egg laying by Ae. aegypti and Ae. albopictus mosquitoes, a two-choice oviposition preference test was conducted. Briefly, this experiment used two ovicups placed within a mosquito cage (1 × 0.5 × 0.5 m3), one ovicup with 200 ml USDS water and another with 200 ml flowerpot water. Adult mosquitoes were bloodfed on mice; fully engorged females 3-days post-bloodfeeding were used for oviposition preference tests. Ten gravid Ae. aegypti females were released into a cage and allowed to lay eggs for three days, and the number of eggs in each ovicup were counted. Five replicates were used. The same experiment was conducted for Ae. albopictus.To evaluate whether the presence of Cx. quinquefasciatus larvae has any impact on the egg laying behavior of invasive Aedes mosquitoes, the two-choice oviposition preference test described above was used. One ovicup contained 200 ml USDS water and ten first-instar Cx. quinquefasciatus larvae, while the second ovicup contained 200 ml USDS water only. Ten gravid Ae. aegypti or Ae. albopictus females were released into a cage and allowed to lay eggs for three days. Five replicates were used. We also conducted this experiment using flowerpot water with the same design and same number of replicates to determine whether the impact of Cx. quinquefasciatus larvae on Aedes mosquito egg laying behavior was similar across different water substrate types.Egg hatchingTo investigate the effects of different habitat water sources on egg hatching, 50 Ae. aegypti or Ae. albopictus eggs on separate filter papers were introduced into ovicups with 200 ml USDS water or flowerpot water. Deoxygenized distilled water that we routinely use in laboratory mosquito colony maintenance was used as a positive control. The experiment was conducted in an insectary with climate control (27 ± 1 °C). The number of larvae hatched were counted daily for six days continuously. Five replicates were used.Larval survivorshipA life table study was conducted on Ae. aegypti and Ae. albopictus larvae to determine the effect of USDS water and flowerpot water on larval development and survivorship. Twenty-five newly hatched Ae. aegypti or Ae. albopictus larvae were introduced into a microcosm that contained 200 ml USDS or field flowerpot water. The number of dead and surviving larvae was recorded daily until they pupated. Pupae were counted, and removed to different paper cups for emergence to adults. Four replicates were used for each type of habitat water per species. We included Cx. quinquefasciatus in the larval life table study for method validation purposes because the larvae of this species were known to successfully develop into pupae and adults in USDS water in southern California10.Larval survivorship experiments were conducted in two different seasons. The first was in the summer (August–September) 2019 when the density of invasive Aedes species peaked19, and also insecticide runoff from mosquito and residential/agricultural pest control applications were at the highest levels in southern California24. The second was in the winter (December) 2019 when there was little insecticide treatment for mosquito and pest control. This design enabled us to examine seasonality in larval survivorship and the impact of environmental insecticide runoff in USDS water. To determine whether USDS water’s nutritional deficiency plays a major role in limiting Aedes larval development, we repeated the larval survival experiment by adding 0.1 g Tetramin Tropical Flakes, the standard larval mosquito diet in insectaries, to the microcosms every 2 days. The number of dead and surviving larvae, pupae, and emergent adults was recorded daily.Data analysisAll aquatic habitats that were positive or negative for the larvae of Ae. aegypti, Ae. albopictus and Cx. quinquefasciatus (the predominant species), were mapped using ArcGIS 10.7.1. The proportion of aquatic habitats positive for Ae. aegypti and Cx. quinquefasciatus was calculated for each habitat type from 2016 to 2019. To examine variation in Aedes and Culex larval positivity rate among different groups of larval habitats within the USDS, larval positivity rates for Ae. aegypti and Cx. quinquefasciatus were calculated for underground water retention vaults, underground catch basins/manholes, and underground pipelines/tunnels. The Chi-square test was used to examine the statistical significance. Culex quinquefasciatus was analyzed because it was the most common species, whereas Ae. albopictus was not included in the analysis due to insufficient number of Ae. albopictus positive habitats. To determine whether USDS water attracted or repelled oviposition of invasive Aedes mosquitoes, a pairwise t test was used to compare egg number in USDS water ovicups to flowerpot water ovicups for each Aedes species. Similarly, a pairwise t-test was used to test the effect of Cx. quinquefasciatus larvae on Aedes mosquito oviposition choice.To examine the effect of water sources on egg hatching, the t-test was used to analyze the egg hatching rate. The analysis of larval life table study data focused on pupation rates and larval-to-pupal development times. The pupation rate was calculated as the proportion of first-instar larvae that molted into pupae. The effect of water sources and larval food supplementation on pupation rate was analyzed using non-parametric Wilcoxon test. The t-test was used to analyze the duration of larval-to-pupal development. Kaplan–Meier survival analysis was used to determine the effects of food supplementation and water source on larval development for each species, and the log-rank test was conducted to determine their statistical significance. All statistical analyses were performed using JMP software (JMP 14.2, SAS Institute Inc.). More

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