https://orcid.org/0000-0001-9912-7746
Figures
Abstract
The spread of arboviruses like yellow fever, dengue, chikungunya, and Zika, transmitted by the invasive mosquito Aedes aegypti has led to the development of many strategies to suppress mosquito populations. Given the rapid development of resistance to common chemical larvicides and adulticides in some Ae. aegypti populations, as well as the ever-shrinking chemical options for mosquito control, there is a pressing need for new tools and deployment of those innovative tools as a component of integrative mosquito management programs. Prior to the adoption of any mosquito population intervention, be it conventional or innovative, understanding the baseline population is essential to evaluate the efficacy of the control measure. The Lee County Mosquito Control District in Florida has collected a three-year-long period of baseline entomological surveillance data collection for Ae. aegypti on Captiva and Sanibel Islands as foundational information prior to implementation of a new integrative mosquito management approach. We identified 18 mosquito species and described their population dynamics during the rainy and dry seasons. The two islands had no significant differences in species richness, diversity, dominance, or evenness overall. Yet, there were clear differences between the high rain season and low rain season in the Shannon diversity index, Simpson dominance index, and Pielou species evenness index within each site. Our data suggest that any innovative intervention should begin before mid to late April when the mosquito population is at its lowest and certainly before populations build up to their summer peak between June and September. These data also show the spatial distribution of Ae. aegypti is dynamic in space and time, identifying hotspots of mosquito abundance to focus on for future interventions. Overall, our study emphasizes the importance of entomological data collection to understand the population dynamics of Ae. aegypti mosquitoes, including the impact of environmental factors such as temperature and precipitation.
Citation: Morreale R, Stenhouse S, Carvalho DO, Hahn DA, Bourtzis K, Lloyd A, et al. (2024) Seasonal insights for integrative mosquito management from multi-year baseline entomological data on Aedes aegypti in Lee County, Florida. PLoS ONE 19(10): e0311407. https://doi.org/10.1371/journal.pone.0311407
Editor: James Colborn, Clinton Health Access Initiative, UNITED STATES OF AMERICA
Received: April 16, 2024; Accepted: September 18, 2024; Published: October 11, 2024
Copyright: © 2024 Morreale et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Data Availability: All relevant data are within the manuscript and its Supporting Information files.
Funding: DFH: CODRF; Centers for Disease Control - Florida Department of Health Hurricane Co-Agreement grant; www.cdc.gov; www.floridahealth.gov; No role in the study design, data collection and analysis, decision to publish, or preparation of the manuscript DAH: https:FLA-ENY-005943; National Institute of Food and Agriculture, United States Department of Agriculture, the Hatch project; https://www.nifa.usda.gov/grants/programs/capacity-grants/hatch-act-1887-multistate-research-fund; No role in the study design, data collection and analysis, decision to publish, or preparation of the manuscript DAH: Projects 25367 and 20220; Florida Department of Agriculture and Consumer Services; www. fdacs.gov; No role in the study design, data collection and analysis, decision to publish, or preparation of the manuscript DAH: CODRE; Centers for Disease Control - Florida Department of Health Hurricane Co-Agreement grant; www.cdc.gov; www.floridahealth.gov; No role in the study design, data collection and analysis, decision to publish, or preparation of the manuscript DAH: Mosquito Irradiation, Sterilization, and Quality Control Coordinated Research Project; Food and Agriculture Organization/International Atomic Energy Agency; https://www.fao.org/home/en; www.iaea.org; No role in the study design, data collection and analysis, decision to publish, or preparation of the manuscript.
Competing interests: The authors have declared that no competing interests exist.
1. Introduction
Arboviruses, such as yellow fever, dengue, chikungunya, and Zika, have burdened the public health system in many tropical and subtropical countries [1]. These diseases are transmitted by mosquitoes during blood feeding, in which the principal vector is the female of Aedes aegypti (L.) [2]. This species is invasive in tropical and sub-tropical locales world-wide and flourishes in urban environments, showing incredible resilience [2]. It can be found in a broad range of breeding sites and environments worldwide, needing only small amounts of standing water with low organic matter for development [2]. Suppressing mosquito populations can disrupt the disease cycle, reducing the infection risk. However, current methods of population suppression often center around the application of insecticides, which can have unintentional effects on non-target species and the environment as well as the selection of pesticide resistance [3–6]. Furthermore, most ultralow-volume spray treatments have low success in reaching this species’ cryptic breeding and resting sites. As a result, the impact of conventional chemical insecticides on Ae. aegypti control is low [7].
Alternative methods to chemical pesticides to suppress Ae. aegypti populations, thereby reducing the chances of disease transmission, are now under evaluation in several countries [8–10]. Autocidal techniques, where mosquitoes of the same species are used to kill other mosquitoes, are growing in their potential for effectively suppressing Ae. aegypti and Ae. albopictus populations in the wild and are also being explored for other essential vector species. An example of such a control tactic is the sterile insect technique (SIT), which is based on the release of large numbers of sterile male mosquitoes of the target species in the field to increase the chances of a wild female mating with an infertile male instead of mating with a (fertile) wild male. Consecutive releases of sterile males can increase the chances of sterile male mating and cause population collapse over the generations by transferring sterile sperm to wild females, thus introducing sterility to the target population [11]. SIT has been successfully deployed in the field to control populations of Ae. aegypti and Ae. albopictus [12–15]. Similarly, the incompatible insect technique (IIT) uses the bacteria Wolbachia to induce reproductive incompatibility between wild females and lab-reared males infected with a strain of Wolbachia not present in the wild females [9]. IIT is much like SIT in deployment and operations, except that Wolbachia-based cytoplasmic incompatibility is used to prevent wild female reproduction rather than the double-stranded DNA damage that induces sterility in SIT [9], and IIT has also successfully been used to suppress Ae. aegypti and Ae. albopictus in operational field trials [16–18]. Evaluation of the efficacy of autocidal techniques requires substantial baseline knowledge about the target wild mosquito populations [9, 19, 20]. This information includes the sizes and spatial distributions of wild populations so control efforts can release appropriate numbers of lab-reared mosquitoes to successfully impact the wild population and deploy those releases at sites within the intervention area with the greatest densities of wild mosquitoes. Similarly, all of these autocidal techniques work best if they begin when wild populations are at their lowest. For example, it is often recommended that SIT or IIT releases begin during the early spring before wild populations have grown substantially from their low overwintering densities so that population suppression can be enacted with fewer lab-reared mosquitoes released [11, 21]. Thus, precise estimates of seasonality in wild population abundances are needed to time the early releases of lab-reared mosquitoes in autocidal programs to achieve maximum potential suppression of wild mosquitoes in the field.
Overall, we believe that careful population monitoring is beneficial before applying any innovative intervention. For example, in the sterile insect technique (SIT), to achieve operational and large-scale production for field applications, SIT projects should begin as a pilot trial based on a phased conditional approach that starts with preintervention baseline data collection, small-scale field trials, preoperational, and operational phases [19]. Baseline data collection is essential for determining the mosquito population profile by deploying traps for different life stages (usually adults and eggs) in the target and control areas. The objective is to collect data to characterize the target mosquito species’ population profile and other species that may be attracted to the same traps. More broadly, autocidal techniques are species-specific and do not alter populations of non-target species present in the target area, making the collection of non-target species a critical component of successfully showing that the intervention affected only the target species without substantially affecting other co-occurring species [11]. Data on abiotic parameters, such as temperature and precipitation, that can influence the mosquito population profile, potentially predicting their peaks, spatial distribution, and size, should also be collected during baseline population monitoring [22–25]. Collection of baseline data for an extended period is crucial as it allows for comparisons among time points (i.e., years) and seasons, thus providing solid evidence for the validation of population suppression or elimination in the target area [11].
Regardless of the control method (conventional or innovative), there is a need for robust field data collection. The American Mosquito Control Association (AMCA) listed the main advantages of surveillance as 1) “requesting appropriate resources as part of a needs assessment; 2) determining changes in the geographic distribution and abundance of mosquito species; 3) evaluating control efforts by comparing pre-and post-surveillance data; 4) obtaining relative measurements of the vector populations over time and accumulating a historical database; 5) facilitating appropriate and timely decisions regarding interventions” [26]. The AMCA reinforces that entomological surveillance provides the opportunity to compare historical data to current data, helping mosquito control professionals make operational decisions and determine when action thresholds have been met, according to local and national regulations [26]. In addition, the European Mosquito Control Association (EMCA) emphasizes the importance of tracking invasive species capable of transmitting diseases and autochthonous species local to that area as a preventive initiative to avoid disseminating vector-borne diseases [27–29].
To enhance the management of the invasive, disease-vectoring mosquito Ae. aegypti, The Lee County Mosquito Control District (LCMCD) in Florida (USA) has completed a 3-year baseline entomological surveillance study on Captiva Island (intervention area) and Sanibel Island (non-intervention area). From mid-2017 until mid-2020 we collected mosquitoes from a network of 58 trapping sites, each with BG-Sentinel traps and ovitraps, spread across our focal areas on the two islands to describe the seasonal abundance, diversity, and distributions of Ae. aegypti and the allied mosquito community in our field sites over 3 years. These data will provide essential information for conventional chemical control applications and innovative control techniques for controlling Aedes aegypti that will ultimately improve LCMCD’s current integrative mosquito control program. While these data have many possible uses, LCMCD is especially focused on their application for an operational sterile insect technique (SIT) program evaluation targeting Ae. aegypti, and we interpret many of our observations through this lens.
2. Material and methods
2.1. Ethical considerations
The creation, existence, and activities of the Mosquito Control Districts in Florida are regulated under the 2018 Florida Statutes, title XXIX (Public Health), chapter 388 (Mosquito Control), in sections 171 and 181, which state the “Power to perform work” and the “Power to do all things necessary”, in which states “The respective districts of the state are hereby fully authorized to do and perform all things necessary to carry out the intent and purposes of this law”. With that said, there was no further authorization necessary to develop and apply mosquito trapping within the County.
2.2. Study area
Captiva Island was selected as the intervention area for the suppression of the Ae. aegypti. Areas of beaches and mangrove swamps were omitted because they are not breeding sites for this target species. Hence, the study area covered about 230 ha of the island’s 419.6 ha of total surface area. An area of 38 ha in the northwest part of Sanibel Island, connected to the southern part of Captiva Island by an automotive bridge, was selected for the non-intervention area as preliminary data indicated that it has similar environmental and presence of Ae. aegypti density conditions, allowing systematic and comprehensive monitoring.
2.3. Weather data
Temperature and precipitation data were obtained from the nearest available weather stations from the National Weather Service from the National Oceanic and Atmospheric Administration (NOAA) from mid-2017 until mid-2020. Because there were no closer weather stations collecting both parameters, the weather station that recorded precipitation was located in St. James City, Pine Island, FL (26.494623, -82.077372, around 12 km away), while temperature was recorded from a weather station in Fort Myers, FL (26.58495, -81.86146, around 34 km away). Precipitation data were divided between low and high rainy seasons; the high rainy season typically lasts from the second week of May until the second week of October, when precipitation events occur several times a week with regularity, and we consider the rest of the year the low rainy season when precipitation is sporadic.
2.4. Mosquito trapping
Surveillance began in June 2017, with 58 trapping stations distributed across both areas (Fig 1). These locations were selected based on previous trapping studies in which the presence of Ae. aegypti populations had been documented. Trap sites were selected based on the appropriate habitat and easy accessibility to the location, with a preference for areas that were unobtrusive to residents and were less likely to be interfered with. Surveillance points were placed approximately every 200 m throughout Captiva with a total of 48 points in this configuration, along with ten trapping stations on Sanibel. The three trapping stations covering the southernmost 1 km of Captiva were placed every 300 m.
Map of Captiva and northwest Sanibel Islands in Lee County (FL, USA) SIT intervention (orange) and non-intervention (outlined in red) areas, including GPS positioning of the trapping stations (represented with a triangle) deployed for the collection of baseline entomological data from mid-2017 to mid-2020.
2.4.1. Adult trapping.
Adult mosquitoes (Culicidae) were collected using BG-Sentinel 2 traps (BGS) baited with a BG-Lure in all 58 trapping stations. Trapping was conducted twice per week unless canceled due to extreme weather or LCMCD closure (i.e., during holidays), reducing collection events to once per week or omitting the trapping that week. Traps were placed in the field for approximately 24 hours. Collected samples were put into a cooler with dry ice to immediately knock down collected mosquitoes to better preserve specimens for identification. Mosquitoes were identified using dichotomous keys [30, 31]. Culex identified in the subgenus Melanoconion were not identified at the species level; instead, they were grouped as Cx. melanoconion for analyses. Very few individual mosquitoes were damaged enough by collection that they could not be identified to species when brought back to the laboratory. Specimens that could not be identified to species were not included in the analysis presented here, but it was overall less than ~0.038% of the total individuals sampled.
2.4.2. Egg trapping.
Eggs were collected weekly using ovitraps (OVT) unless during LCMCD closure or extreme weather events in which the OVTs were collected from the field in advance. The OVT consisted of a 473 ml black plastic cup stationed near each the BGSs. A hole was drilled approximately 2 cm from the top of the cup to allow excess water that may enter the cup due to rainfall to drain out. A trifold paper towel was replaced weekly into the cups as the oviposition medium. Any remaining water in the cup was fully drained before collection. Cups were then rinsed and replenished with approximately 200 ml of water. Oviposition papers were returned to the laboratory, where they were allowed to dry under insectary conditions. Once the egg papers dried, the numbers of Aedes eggs were quantified based on microscope examination.
2.5. Statistical analysis
Ecological parameters were calculated based on common indices for describing communities: the Margalef index for species richness, the Shannon index for diversity, and the Simpson index for dominance, all obtained using the package vegan for R [32]. Pielou’s species evenness index was calculated by E = H/ln S, where H is the Shannon diversity index, and S is the number of species; the value varies between 0 and 1, where 1 represents an utterly even distribution and 0 a completely clumped distribution. The Sørensen dissimilarity index was used between Captiva and Sanibel areas, defined as Qs = (2 × J)/(a + b), where J represents the number of species in common in both areas, while a + b indicates the total number of species found in each area. The relative abundance of mosquito species across the communities in each area was classified according to the description of Trojan (1992), in which satellite species correspond to less than 1% of the relative abundance (RA), sub-dominant species RA < 5%, and dominant species RA > 5%. Relative abundance was calculated based on the specimens of each species over the total captured throughout both areas [33]. The association index (Ai) was defined Ai = 2[c/(x + y) − 0.5], where c is the number of individuals of both species in samples where they occur together, while x or y is the total number of individuals of each species in all collected samples. The spatial distribution of each species in each area was obtained using the kernel density estimation from the software QGIS (version 3.22.10). All statistical analyses were performed using R and RStudio (libraries and versions available in supplementary material). The non-metric multidimensional scaling (NMDS) ordination process was performed in the package vegan for R [32], building a Bray-Curtis distance matrix and targeting a stress value around 0.2. The Permutational Multivariate Analysis of Variance Using Distance Matrices was implemented to test for differences between the two areas in either the low or high rainy season. The hotspot analysis begins by defining spatial neighbors using the dnearneigh function, which establishes spatial relationships based on a specified distance threshold. Subsequently, the nb2listw function is employed to convert the neighbor object into a spatial weights matrix, crucial for quantifying the strength of spatial connections. The localG function is then applied to compute local Moran’s I statistics, offering a localized perspective on spatial autocorrelation. This integrated approach, leveraging dnearneigh for neighbor specification and nb2listw for spatial weights, enhances the capability to discern fine-grained spatial patterns and identify local clusters or outliers within the dataset.
3. Results
3.1. Baseline entomological data on Captiva and Sanibel Islands
Using the 58 BGSs shown in Fig 1, adult mosquito collections operated from mid-June 2017 until mid-June 2020 resulting in the identification of seven Culicidae genera and 18 species between the proposed intervention area on Captiva Island and the non-intervention area on Sanibel Island. Through BGS collections over the course of three years, a total of 75 286 and 25 302 adult mosquitoes (both males and females) were collected on Captiva and Sanibel, respectively. On Captiva the most abundant species were Ae. aegypti with 53 090 individuals (70.5%), Culex quinquefasciatus with 15 239 individuals (20.2%), and Ae. taeniorhynchus with 2 838 individuals (3.77%). On Sanibel Ae. aegypti was also the most abundant species with 19 781 individuals (78.2%), followed by Ae. taeniorhynchus with 1 849 individuals (7.31%) and Cx. nigripalpus with 1 204 individuals (4.76%).
Table 1 shows the relative abundance (RA) of all species collected on Captiva and Sanibel. Overall, Ae. aegypti and Cx. quinquefasciatus were the most dominant species in the BGSs collections, with relative abundances of 72.4% and 16.2%, respectively. Ae. taeniorhynchus, Cx. nigripalpus, and Wyeomyia mitchelli were sub-dominant, with relative abundance values of 4.66%, 3.45%, and 1.72%, respectively. All other trap-collected species were classified as satellite species with relative abundance values below 0.7%, with Mansonia titillans, Psorophora ferox, and Aedes albopictus having the lowest values. Reinforcing the dominance of Ae. aegypti in these locations, most species showed low association with Ae. aegypti, generating association index values close to -1 (Table 1). The only exception was that Cx. quinquefasciatus had a low positive association index value of 0.134, showing the two species co-occurred in traps occasionally.
Using these data, a series of ecological indexes were calculated for Sanibel and Captiva Islands during the high and low-rain seasons as a reference for future interventions (Table 2). Throughout the study period, there was no difference between the sites on Sanibel and Captiva in the species richness index (3.86 and 3.49 for Sanibel and Captiva, respectively, t-test = 0.82, df = 12.74, p = 0.43). The Shannon diversity index was estimated at 0.98 and 0.93 for Sanibel and Captiva, respectively, with no statistical difference between the two sites detected across the three years (t-test = 0.56, df = 23.17, p = 0.58). The dominance index reached 0.46 and 0.48 for Sanibel and Captiva, respectively, but did not differ between the two areas (t-test = 0.43, df = 23.23, p = 0.66). Furthermore, the evenness ratio, which is the relative abundance of different species in the same area (defined as the species’ evenness), was similar between the two sites (0.47 and 0.48 for Sanibel and Captiva respectively, t = 0.28, df = 27.92, p = 0.781). Comparing the high and low-rainy seasons in both places, the similarity quotient indicated that the sites were similar irrespective of the season, 1.12 and 1.07 for the high and low-rain seasons, with an overall similarity quotient throughout the years equal to 1.11.
Although the mean number of species on Captiva trended towards being lower in the low-rain season compared to the high-rain season, 6.81 and 8.17 respectively, there was no statistically significant difference in the mean number of species trapped between the two seasons (t-test = -0.69, df = 92.4, p = 0.49). Fig 2 shows the species accumulation curve based on the number of samples and traps, where the cumulative number of species discovered (y-axis) is plotted against the cumulative number of individuals sampled (x-axis) according to the seasonality for Captiva and Sanibel. In both cases, the high-rain season has slightly faster species accumulation over time than the low-rain season, reaching a plateau. However, the Shannon diversity index was 0.85 and 1.0 for the high and low-rain seasons, respectively, showing that species diversity was actually slightly higher in the low-rain season than the high-rain season (t-test = 22.41, df = 91.41, p = 0.02). The Simpson dominance index was greater in the low-rain season than in the high-rain season (0.49 vs. 0.42 t-test = 4.4, df = 85.2, p = 3.18−5), demonstrating that Ae. aegypti was relatively more prevalent than any other species during the low-rain season than the high-rain season even if the absolute numbers of Ae. aegypti captured were substantially lower in the low-rain season. Similarly, the evenness of species across the areas sampled was greater in the low-rain season that during the high-rain season, Pielou index of 0.54 vs 0.42 (t-test = 3.6, f = 91.63, p = 4.2−4). In contrast, no statistically significant difference was observed concerning the Margalef index of richness between the low and the high-rain season, 1.40 and 1.46, respectively (t-test = 0.63, df = 17.65, p = 0.53).
Species accumulation curve for Captiva and Sanibel Islands during the low (orange) and high (blue) rainy season as sampling size or number of recaptures increases.
To compare species composition between the sites on Captiva and Sanibel we applied a non-metric multidimensional scaling (NMDS) ordination process separately in the high and low-rainy seasons (Fig 3A) and the same analysis was also used to partition the high vs. low rainy season within each site (Fig 3B). A Permutational Multivariate Analysis of Variance (PERMANOVA) using distance matrices was performed to test for effects of location, Captiva vs. Sanibel, and season, high vs. low-rain season. Reinforcing the above data showing little to no difference in species composition between Sanibel vs. Captiva, the multivariate species composition was detectably different between Sanibel vs. Captiva (p<0.001), but site only explained approximately 3.86% of the total variance in the multivariate species distance matrix among traps (Fig 3A). Perhaps more interesting was that there were substantial differences in the multivariate species composition between traps collected in the high vs. low-rainy season on both Sanibel and Captiva (p<0.001), with season explaining approximately 52.08% of the variance in the multivariate species composition among traps (Fig 3B). Despite the potential contradiction between the two indices (Shannon’s diversity and Simpson’s abundance), their high values presented spatial overlaps, in which some trapping stations had high values for diversity and dominance both on Captiva and Sanibel (S1 Fig). The contradictory intersection of the indexes may represent the overlap of several ecological niches that might be occupied by different species, contributing to those values of abundance and diversity in the trapping station area.
NMDS ordination from all mosquito species found during the low and high rainy seasons (A) in Captiva and Sanibel (B). The Bray-Curtis dissimilarity matrix was used to determine dissimilarities among mosquito community compositions as an arbitrary distance matrix—stress value = 0.05.
3.2. Aedes aegypti population dynamics
Climatic conditions were associated with predictable fluctuations in the numbers of Ae. aegypti adults collected in traps, with higher abundance during the high-rain season and lower abundance in the low-rain season across each of the three years (Fig 4A and 4B). Aedes aegypti trap captures were positively, correlated with weekly precipitation levels, albeit weakly (R2 = 0.23 with S = 8.0211, p < 0.05). There was a slightly higher positive correlation of Ae. aegypti abundance with weekly mean temperature (R2 = 0.54 with S = 4.9411, p < 0.05), as may be observed between panels in Fig 4. Aedes aegypti was dispersed throughout the intervention and non-intervention sites, with a significant decline during the low rainy season (GLM F = 129.9, df = 1, p < 0.05), resulting in 86.9% and 89.4% reduction of the adult population in Captiva and Sanibel, respectively, during the low-rain season. Egg collections from ovitraps had a similar pattern as adult captures (Fig 4C), in which Ae. aegypti egg density had clear seasonal fluctuations across all three years and a higher correlation with temperature (R2 = 0.35 with S = 8.3310, p < 0.05) compared with precipitation (R2 = 0.11 with S = 1.1311, p < 0.05).
Weather profile with the mean weekly temperature (black line) and weekly precipitation records (green bars with dark green denoting the high-rain season and light green denoting the low-rain season) (A), the total number of adult Ae. aegypti collected in BGSs each week (B), and the number of ovitraps containing Aedes eggs each week (C) from the study areas–Captiva and Sanibel with their respective weekly means. Hurricane Irma hit the area on September 10th, 2017 (grey dashed lines). Rare collection events of Ae. albopictus in Sanibel and Captiva are also noted by blue and orange dashed lines, respectively, representing one specimen collected by the BG-Sentinel trap in the weeks denoted. Aedes albopictus collections happened on Sanibel during the high-rain season while on Captiva, Ae. albopictus was found during the low-rain season.
Before this study, and as shown in LCMCD historical monitoring data, Ae. albopictus, a species very closely related to Ae. aegypti for arbovirus transmission, ecological niche, and blood meal host preference, had not been detected on Captiva and only rarely had been detected in routine surveillance on Sanibel Island. During the rigorous and consistent trapping of this study, however, Ae. albopictus was detected in the non-intervention area of Sanibel in week #30 in 2018 and a second time in week #26 in 2019. Aedes albopictus was also detected for the first time in Captiva in week #46 in 2018. In all three cases, a single individual was collected. No further Ae. albopictus collections were recorded in either area during the three-year-long study period. These highly sporadic Ae. albopictus collections could indicate separate introduction events without establishment, as we failed to consistently detect Ae. albopictus through subsequent sampling.
3.3. Describing the distribution of Ae. aegypti on Captiva and Sanibel
As a first pass towards identifying areas with greater Ae. aegypti density within our study areas, we used the kernel density extrapolation to estimate trap captures for Aedes aegypti, in Captiva and Sanibel during the high and low rain season to generate a heatmap for abundance by trap (Fig 5). Visual inspection of the heatmap suggested that there were potential hotspots of higher Ae. aegypti density, where we may target future interventions. Consistent with the analyses in the section above, visual inspection of the heatmaps separated by high vs. low-rain season in each year reinforces the point that Ae. aegypti populations are much lower in the low-rain season than in high-rain season. Beyond our first-pass visual inspections of the heat maps, we used the Local Moran’s I statistic to identify significant areas of spatial clustering according to trap position in the field, thereby quantitatively identifying hotspots (Fig 6 and S1 Table with the statistical data). Although which specific traps were parts of hotspot clusters differed between high vs. low-rain seasons within years and among years within the high vs. low-rain seasons, there was repeatable clustering of traps with high Ae. aegypti captures in the upper-middle region of Captiva in all years, that is a clear hotspot where control efforts should be targeted (Fig 6). Further, another hotspot was repeatable across the final two years of monitoring to the south of the persistent mid-island hotspot on Captiva that should also receive increased operational scrutiny in future work (Fig 6).
Visualization of the spatial distribution of adult Ae. aegypti collected in BG-Sentinel traps during the low and high-rain seasons from mid-2017 to mid-2020 using kernel density estimation interpolation.
Hotspots of adult Ae. aegypti identified by clustering of collections BG-Sentinel traps during the low and high-rain seasons from mid-2017 to mid-2020 identified by the Local Moran’s I method where traps that had repeatable significantly high captures are shown in blue and traps without repeatable high captures are shown in grey.
Taking advantage of the almost linear trap distribution from north to south on Captiva and Sanibel, we visualized the seasonal peaks of peaks of Ae. aegypti and Cx. quinquefasciatus by plotting the month in which trap capture was highest in relation to trap latitudinal distribution (Fig 7). Most of the peaks for Ae. aegypti were concentrated between July and September, with just one trap (T9), having a peak towards October. On the other hand, a wider seasonal distribution over the months was observed for Cx. quinquefasciatus, with at least three traps (T2, T9, and T21) with distinctly different seasonal peaks from the majority. Notably, the peak timing for both species in T9 peaked later than most of the other traps, suggesting the area in which this trap is located may be locally cooler during the hottest summer months. Interestingly, we also note that the peak month for Ae. aegypti was more synchronized among traps than the peak month for Cx. quinquefasciatus, which was more variable across traps.
Monthly primary peak describing the month with the highest collection peak of collection between mid-2017 to mid-2020, by trap position (latitude trap distribution) for Ae. aegypti (A) and Cx. quinquefasciatus (B).
4. Discussion
Detailed, multi-year entomological data collection constitutes a fundamental source of information to understand the population dynamics of target species before initiating any innovative control tactic, including our proposed SIT trial for Ae. aegypti. Because mosquito populations can fluctuate from season to season and year to year at the same location, a longer timeframe of background surveillance increases understanding about the stability of mosquito populations in a target area, thus facilitating better planning and implementation of control tactics. Furthermore, longer-term data collection allows practitioners to more clearly evaluate the extent to which declines in populations at a location are likely to be due to the implementation of a control tactic versus natural seasonal or year-to-year variation in baseline population densities [21]. The baseline entomological surveillance data recorded in this study from 2017–2020 provides us with a solid understanding of the unique dynamics of the Ae. aegypti populations found in Captiva and northwest Sanibel Islands, providing a base from which we can launch an operational SIT program for Captiva Island. Furthermore, the data gathered in this study provides the appropriate timing for SIT implementation, and a more precise understanding of the numbers of irradiated males needed for releases. We can now target effective release areas increasing the potential for success in implementing and evaluating the success of Ae. aegypti population suppression in a radiation-based SIT field trial [11, 15], such as those that have recently been successfully performed on Ae. aegypti in Cuba [44] and Thailand [34] as well as for Ae. albopictus in Greece [21] Spain [22], and Albania [23], among others. Because we also have spatially and temporally explicit long-term data on other mosquito species that co-occur with Ae. aegypti, we will be able to determine whether suppression of Ae. aegypti is correlated with increases in the populations of any of these other mosquito species in the community.
Environmental factors, such as temperature and precipitation, greatly influence Ae. aegypti populations and are often responsible for the seasonality and dynamics of this species. In some cases, human behaviors in response to these factors may impact mosquito populations indirectly, i.e. construction of water storage in areas with low precipitation [35–37]. On Captiva and Sanibel, both precipitation and temperature modulate the mosquito population in such a way that the population of Ae. aegypti practically disappears from both areas during the low-rain season and lower temperature, returning when the temperature and precipitation increase next season. This pattern was also seen in a study in Brazil from 2016 to 2018, in which the environmental conditions had a significant role in defining the population profile in the study site, thereby also influencing the epidemiological profile [38]. Extreme weather drastically affected the populations of Ae. aegypti when Hurricane Irma hit Captiva and Sanibel Island in September 2017. The year 2018 should be considered a “recovery” phase given the significance of the hurricane’s impact, as populations were lower over the year following the hurricane but had a resurgence in subsequent years. Natural disasters are of particular concern due to the increased availability of breeding sites, and can result in a newly emerged population that can facilitate pathogen transmission and cause the rise of vector-borne disease incidents [20, 39, 40].
Autocidal interventions, such as SIT, should ideally start when the target population is at its lowest density. The monthly primary peak analysis, shown in Fig 6, is a potent tool because it can reveal temporal peaks for each trap that are valuable indicators of where and when interventions should begin. This analysis also reinforces the link between population density and precipitation levels because the rainy season typically starts in May and the Ae. aegypti population starts growing, with population density then peaking between July to September (throughout the studied period). The importance of weather data in predicting Ae. aegypti population levels have been previously reported, as well as the high positive correlation between density levels with precipitation and temperature [41]. The data from this study suggest that future sterile male releases may be most successful if implemented before mid to late April before the high-rain season begins and well before the peak population density typically occurs. While weather data are an invaluable tool to understand fluctuations in the Ae. aegypti population, it should be noted that the existing egg bank is another complicating factor that will also contribute to population size, particularly early in the high-rain season. The presence of persistent egg banks in Ae. aegypti further necessitates continued surveillance once a population suppression intervention begins to indicate what adjustments may be needed in the number of sterile males released and the locations of those releases to achieve the best possible results for population suppression.
Documenting the spatial distribution of Ae. aegypti in the field can also reveal the dynamics of this species in space and time. Because Ae. aegypti flourishes in peridomestic habitats, the anthropogenic structure of a particular location may create new breeding sites or attract mosquitoes from other areas to specific hotspots that can be identified with BGS traps. The hotspots identified in this study will allow us to target interventions to areas where they can be most effective in suppressing wild Ae. aegypti populations. For example, continued high-density weekly trapping efforts during sterile male releases will allow us to adjust releases to compensate for shifts in wild Ae. aegypti population densities over the course of our planned SIT intervention, including compensating for changes in human use patterns that increase biting opportunities or changes to the environment, such as new construction or changes in vegetation that may alter the distribution of breeding sites [42–44].
Of course, an outstanding question for a species-specific suppression program is whether there will be impacts on other mosquitoes in the community. Removing a dominant, competitive mosquito like Ae. aegypti may not reduce biting pressure on residents and visitors to these vacation-spot islands if another anthropophilic species simply replaces Ae. aegypti by increasing their densities. For example, historically Ae. albopictus had not been detected on Captiva or Sanibel Islands, which is one of the reasons why these sites were selected for our upcoming Ae. aegypti SIT pilot trial. During our baseline study, three individual Ae. albopictus were trapped in 2018 and 2019; one in Captiva, the release site, and two in Sanibel, the control site. As reported by Lounibos and colleagues, who studied the population dynamics of Ae. aegypti and Ae. albopictus in several cities in peninsular Florida (USA) over a 20 year period (1994–2014), the two species tend to find equilibrium after waves of displacement [45]. Whether Ae. albopictus may become established in our field sites after SIT suppresses or eliminates the Ae. aegypti population on Captiva Island remains to be seen. However, there are contradictory reports about this in the literature [46, 47]. If population replacement of Ae. aegypti by Ae. albopictus does occur after a species-specific intervention, consistently monitoring Aedes mosquitoes in these areas would immediately trigger a response for species-specific control of Ae. albopictus, a species for which there are several species-specific control measures, including a complementary SIT package is already available and has been successfully used in field suppression [12–15, 48, 49].
5. Conclusion
Establishing a baseline data collection process is fundamental for planning innovative mosquito control applications and essential to implementation. Continuous trapping is critical to determining the population profile, along with abiotic parameters to predict its fluctuations and peaks as indicators for planning actions and interventions, for example in a phased conditional approach for implementing SIT. Keeping records for additional species beyond the target of the innovative control measure allows better characterization and comparative assessment of the study areas. Importantly, substantial pre-intervention knowledge of the whole mosquito community in a site can allow assessment of whether suppressing a target species with species-specific interventions lead to compensatory increases in the abundances other potentially concerning mosquito species. The authors believe that the data collected in this study from 2017–2020 has provided a fundamental understating of the Ae. aegypti population on Captiva and northwest Sanibel Island, providing the needed baseline data to properly evaluate the effectiveness of future innovative interventions, including a SIT program planned to be implemented on these islands.
Supporting information
S1 Fig. Heatmap.
Heatmap of mosquito distribution of diversity and dominance indexes during the high and low rainy seasons. Lat = latitude and Long = longitude.
https://doi.org/10.1371/journal.pone.0311407.s001
(TIF)
S1 Table. Data used for the analysis presented in this manuscript.
https://doi.org/10.1371/journal.pone.0311407.s002
(CSV)
Acknowledgments
We thank LCMCD technicians for their support in trapping, processing, and recording data.
References
- 1. Kraemer MU, Sinka ME, Duda KA, Mylne AQ, Shearer FM, Barker CM, et al. The global distribution of the arbovirus vectors Aedes aegypti and Ae. albopictus. eLife. 2015;4. pmid:26126267
- 2.
Christophers SR. Aëdes aegypti (L.) the yellow fever mosquito: its life history, bionomics and structure. Cambridge: Cambridge University Press; 1960.
- 3. Brattsten LB, Holyoke CW, Leeper JR, Raffa KF. Insecticide Resistance: Challenge to Pest Management and Basic Research. Science. 1986;231: 1255–1260. pmid:17839561
- 4. Coleman M, Hemingway J, Gleave KA, Wiebe A, Gething PW, Moyes CL. Developing global maps of insecticide resistance risk to improve vector control. Malar J. 2017;16: 86. pmid:28222727
- 5. Garcia G de A, David MR, Martins A de J, Maciel-de-Freitas R, Linss JGB, Araújo SC, et al. The impact of insecticide applications on the dynamics of resistance: The case of four Aedes aegypti populations from different Brazilian regions. Kittayapong P, editor. PLoS Negl Trop Dis. 2018;12: e0006227. pmid:29432488
- 6. Maciel-de-Freitas R, Avendanho FC, Santos R, Sylvestre G, Araújo SC, Lima JBP, et al. Undesirable Consequences of Insecticide Resistance following Aedes aegypti Control Activities Due to a Dengue Outbreak. Paul RE, editor. PLoS ONE. 2014;9: e92424. pmid:24676277
- 7. Achee NL, Gould F, Perkins TA, Reiner RC, Morrison AC, Ritchie SA, et al. A critical assessment of vector control for dengue prevention. Halstead SB, editor. PLoS Negl Trop Dis. 2015;9: e0003655. pmid:25951103
- 8. Achee NL, Grieco JP, Vatandoost H, Seixas G, Pinto J, Ching-NG L, et al. Alternative strategies for mosquito-borne arbovirus control. Kittayapong P, editor. PLoS Negl Trop Dis. 2019;13: e0006822. pmid:30605475
- 9. Bourtzis K, Lees RS, Hendrichs J, Vreysen MJB. More than one rabbit out of the hat: Radiation, transgenic and symbiont-based approaches for sustainable management of mosquito and tsetse fly populations. Acta Trop. 2016;157: 115–130. pmid:26774684
- 10. Maciel-de-Freitas R, Aguiar R, Bruno RV, Guimarães MC, Lourenço-de-Oliveira R, Sorgine MH, et al. Why do we need alternative tools to control mosquito-borne diseases in Latin America? Mem Inst Oswaldo Cruz. 2012;107: 828–829. pmid:22990977
- 11. Dyck VA, Hendrichs J, Robinson AS. Sterile insect technique: principles and practice in area-wide integrated pest management. Taylor & Francis; 2021.
- 12. Becker N, Langentepe-Kong SM, Tokatlian Rodriguez A, Oo TT, Reichle D, Lühken R, et al. Integrated control of Aedes albopictus in Southwest Germany supported by the Sterile Insect Technique. Parasit Vectors. 2022;15: 9. pmid:34983608
- 13. Bellini R, Medici A, Puggioli A, Balestrino F, Carrieri M. Pilot field trials with Aedes albopictus irradiated sterile males in Italian urban areas. J Med Entomol. 2013;50: 317–325. pmid:23540120
- 14. Balatsos G, Puggioli A, Karras V, Lytra I, Mastronikolos G, Carrieri M, et al. Reduction in egg fertility of Aedes albopictus mosquitoes in Greece following releases of imported sterile males. Insects. 2021;12: 110.
- 15. Gato R, Menéndez Z, Prieto E, Argilés R, Rodríguez M, Baldoquín W, et al. Sterile Insect Technique: Successful Suppression of an Aedes aegypti Field Population in Cuba. Insects. 2021;12: 469. pmid:34070177
- 16. Crawford JE, Clarke DW, Criswell V, Desnoyer M, Cornel D, Deegan B, et al. Efficient production of male Wolbachia-infected Aedes aegypti mosquitoes enables large-scale suppression of wild populations. Nat Biotechnol. 2020;38: 482–492. pmid:32265562
- 17. Mains JW, Kelly PH, Dobson KL, Petrie WD, Dobson SL. Localized control of Aedes aegypti (Diptera: Culicidae) in Miami, FL, via inundative releases of Wolbachia-infected male mosquitoes. J Med Entomol. 2019;56: 1296–1303. pmid:31008514
- 18. Zeng Q, She L, Yuan H, Luo Y, Wang R, Mao W, et al. A standalone incompatible insect technique enables mosquito suppression in the urban subtropics. Commun Biol. 2022;5: 1–13. pmid:36575240
- 19. Bouyer J, Yamada H, Pereira R, Bourtzis K, Vreysen MJB. Phased Conditional Approach for Mosquito Management Using Sterile Insect Technique. Trends Parasitol. 2020;36: 325–336. pmid:32035818
- 20. Connelly CR, Borchert J. Mosquito control emergency preparedness and response to natural disasters. J Am Mosq Control Assoc. 2020;36: 2–4. pmid:33575685
- 21. Bouyer J, Culbert NJ, Dicko AH, Pacheco MG, Virginio J, Pedrosa MC, et al. Field performance of sterile male mosquitoes released from an uncrewed aerial vehicle. Sci Robot. 2020;5: eaba6251. pmid:33022616
- 22. Padmanabha H, Correa F, Legros M, Nijhout HF, Lord C, Lounibos LP. An eco-physiological model of the impact of temperature on Aedes aegypti life history traits. J Insect Physiol. 2012;58: 1597–1608. pmid:23068992
- 23. Nasir S, Jabeen F, Abbas S, Nasir I, Debboun M. Effect of climatic conditions and water bodies on population dynamics of the dengue vector, Aedes aegypti (Diptera: Culicidae). J Arthropod-Borne Dis. 2017;11: 50. pmid:29026852
- 24. do Nascimento JF, Palioto-Pescim GF, Pescim RR, Suganuma MS, Zequi JAC, Golias HC. Influence of abiotic factors on the oviposition of Aedes (Stegomyia) aegypti (Diptera: Culicidae) in Northern Paraná, Brazil. Int J Trop Insect Sci. 2022; 1–6.
- 25. Custódio JM de O, Nogueira LMS, Souza DA, Fernandes MF, Oshiro ET, Oliveira EF de, et al. Abiotic factors and population dynamic of Aedes aegypti and Aedes albopictus in an endemic area of dengue in Brazil. Rev Inst Med Trop São Paulo. 2019;61.
- 26.
AMCA. Best Practices for Integrated Mosquito Management. American Mosquito Control Association Sacramento, CA, USA; 2021.
- 27. Balatsos G, Karras V, Puggioli A, Balestrino F, Bellini R, Papachristos DP, et al. Sterile Insect Technique (SIT) field trial targeting the suppression of Aedes albopictus in Greece. Parasite. 2024;31. Available: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10964849/
- 28.
Tur C, Almenar D, Benlloch-Navarro S, Argilés-Herrero R, Zacarés M, Dalmau V, et al. Sterile Insect Technique in an Integrated Vector Management Program against Tiger Mosquito Aedes albopictus in the Valencia Region (Spain): Operating Procedures and Quality Control Parameters. Insects. 2021;12: 272.
- 29. Velo E, Balestrino F, Kadriaj P, Carvalho DO, Dicko A, Bellini R, et al. A Mark-Release-Recapture study to estimate field performance of imported radio-sterilized male Aedes albopictus in Albania. Front Bioeng Biotechnol. 2022;10: 833698. pmid:36051578
- 30. Darsie RF, Morris CD. Keys to the adult females and fourth instar larvae of the mosquitoes of Florida (Diptera, Culicidae). Gainesville, FL: Florida Mosquito Control Association; 2003.
- 31. Darsie RF, Ward RA. Correction To: Identification And Geographical Distribution of the Mosquitoes of North America, North of Mexico. J Am Mosq Control Assoc. 2008;24: 108–109.
- 32. Oksanen J, Blanchet FG, Kindt R, Legendre P, Minchin PR, O’hara RB, et al. Package ‘vegan.’ Community Ecol Package Version. 2013;2: 1–295.
- 33. Trojan P. Analiza struktury fauny. Memorab Zool 47. 1992.
- 34. Kittayapong P, Ninphanomchai S, Limohpasmanee W, Chansang C, Chansang U, Mongkalangoon P. Combined sterile insect technique and incompatible insect technique: The first proof-of-concept to suppress Aedes aegypti vector populations in semi-rural settings in Thailand. PLoS Negl Trop Dis. 2019;13: e0007771. pmid:31658265
- 35. Benitez EM, Estallo EL, Grech MG, Frías-Céspedes M, Almirón WR, Robert MA, et al. Understanding the role of temporal variation of environmental variables in predicting Aedes aegypti oviposition activity in a temperate region of Argentina. Acta Trop. 2021;216: 105744. pmid:33189713
- 36. Santos IC da S, Braga C, de Souza WV, de Oliveira ALS, Regis LN. The influence of meteorological variables on the oviposition dynamics of Aedes aegypti (Diptera: Culicidae) in four environmentally distinct areas in northeast Brazil. Mem Inst Oswaldo Cruz. 2020;115: e200046. pmid:32667460
- 37. Rose NH, Sylla M, Badolo A, Lutomiah J, Ayala D, Aribodor OB, et al. Climate and Urbanization Drive Mosquito Preference for Humans. Curr Biol. 2020;30: 3570–3579.e6. pmid:32707056
- 38. Moura MCB de M, Oliveira JV, Pedreira RM, Tavares A de M, Souza TA, Lima KC, et al. Spatio‐temporal dynamics of Aedes aegypti and Aedes albopictus oviposition in an urban area of northeastern Brazil. Trop Med Int Health. 2020;25: 1510–1521. pmid:32959943
- 39. Connelly CR. Continuation of mosquito surveillance and control during public health emergencies and natural disasters. MMWR Morb Mortal Wkly Rep. 2020;69.
- 40. Nasci R. Vector-borne Disease Surveillance and Natural Disasters. Emerg Infect Dis. 1998;4: 333–334. pmid:9621210
- 41. Ibarra AMS, Ryan SJ, Beltrán E, Mejía R, Silva M, Muñoz Á. Dengue Vector Dynamics (Aedes aegypti) Influenced by Climate and Social Factors in Ecuador: Implications for Targeted Control. PLOS ONE. 2013;8: e78263. pmid:24324542
- 42. Wang Y, Yim SHL, Yang Y, Morin CW. The effect of urbanization and climate change on the mosquito population in the Pearl River Delta region of China. Int J Biometeorol. 2020;64: 501–512. pmid:31811391
- 43. Franklinos LH, Jones KE, Redding DW, Abubakar I. The effect of global change on mosquito-borne disease. Lancet Infect Dis. 2019;19: e302–e312. pmid:31227327
- 44. Wilke AB, Benelli G, Beier JC. Anthropogenic changes and associated impacts on vector-borne diseases. Trends Parasitol. 2021;37: 1027–1030. pmid:34686421
- 45. Lounibos LP, Bargielowski I, Carrasquilla MC, Nishimura N. Coexistence of Aedes aegypti and Aedes albopictus (Diptera: Culicidae) in Peninsular Florida Two Decades After Competitive Displacements. J Med Entomol. 2016;53: 1385–1390. pmid:27493253
- 46. Gorman K, Young J, Pineda L, Márquez R, Sosa N, Bernal D, et al. Short-term suppression of Aedes aegypti using genetic control does not facilitate Aedes albopictus. Pest Manag Sci. 2016;72: 618–628. pmid:26374668
- 47. Lloyd-Smith JO. Vacated niches, competitive release and the community ecology of pathogen eradication. Philos Trans R Soc B Biol Sci. 2013;368: 20120150. pmid:23798698
- 48. Zheng X, Zhang D, Li Y, Yang C, Wu Y, Liang X, et al. Incompatible and sterile insect techniques combined eliminate mosquitoes. Nature. 2019 [cited 26 Jul 2019]. pmid:31316207
- 49.
Bellini R, Calvitti M, Medici A, Carrieri M, Celli G, Maini S. Use of the Sterile Insect Technique Against Aedes albopictus in Italy: First Results of a Pilot Trial. In: Vreysen MJB, Robinson AS, Hendrichs J, editors. Area-Wide Control of Insect Pests. Springer Netherlands; 2007. pp. 505–515.