How reliable are light traps in estimating biting rates of adult Anopheles gambiae s.l. (Diptera: Culicidae) in the presence of treated bed nets?

The sampling efficiency of light trap catches relative to human bait catches in estimating biting rates of the mosquito Anopheles gambiae Giles was investigated in two types of community in southern Sierra Leone: (i) where most of the inhabitants slept under treated bed nets; and (ii) where most of the inhabitants slept without bed nets. The number of female A. gambiae mosquitoes caught in these communities by light trap was strongly correlated (r > or = 0.72) with those from corresponding human biting catches performed either on the same or adjacent nights. It was found that the relative sampling efficiency of light traps varied slightly but significantly with mosquito abundance in villages with treated bed nets, but not in those without them. Nevertheless, the relationship between relative sampling efficiency and mosquito abundance did not differ significantly between the two types of village. Overall, there was insufficient evidence to show that the presence of treated nets altered the relative efficiency of light traps and any bias was only slight, and unlikely to be of any practical importance. Hence, it was concluded that light traps can be used as a surrogate for human bait catches in estimating biting rates of A. gambiae mosquitoes in the two communities.     

A standardized sampling method to estimate mosquito richness and abundance for research and public health surveillance programmes

Programmes involving mosquito research and surveillance are normally focused on the study of aquatic larval stages, but sampling methods are varied and not systematized, which hinders the comparative analysis of ecological data. A standardized method for assessing the richness and abundance of mosquito larval populations of value for the analysis of mosquito diversity is presented. Based on the study of all the aquatic sites in a one hectare sample area with a proportional number of dips according to the size of the aquatic habitat, comparative data can be obtained on species richness and relative abundance of species found between pairs of sites or in the same area at different times. This technique provides information on the total mosquito fauna at each site, helps recognize species of medical importance and estimates the abundance of each species; parameters that are not estimated by the current entomological indexes used in surveillance programmes. The quality of the inventory is obtained by estimation of the efficiency effort. Procedures for calculating alpha, beta and gamma diversity are presented. The technique was validated in a natural and an urban zone at La Mancha, Veracruz, Mexico, over two years of sampling made during different climatic seasons.     

Estimating abundance from detection–nondetection data for randomly distributed or aggregated elusive populations

Estimating abundance is important in many ecological studies in order to understand the spatial and temporal dynamics of a population, which can assist in management and conservation. However, direct estimates of abundance can be difficult and expensive to obtain, particularly for wide-ranging, rare or elusive species. An alternative – estimating from detection-nondetection data – is a challenging but alluring concept to ecologists since the cost and effort of a study can be greatly reduced. This paper describes a method for estimating the abundance of randomly distributed or aggregated populations by using binary data where the probability of detection is less than one. The performances of the models were evaluated by computer simulations comprising 1620 cases. The results show that the accuracy of the abundance estimates increases as the sampling rate, efficiency of survey method, and the number of repeated surveys increase, whereas the accuracy declines as individuals become more aggregated. For a randomly distributed population, using a sampling rate of 0.05 in a survey method with a detection probability of 0.5, and repeating surveys three times provides sufficient accuracy of abundance. For an aggregated population, to achieve reasonably accurate abundance estimates the sampling rate should be doubled and each cell should be repeatedly surveyed on 4 to 6 occasions.     

Raised houses reduce mosquito bites

BACKGROUND: In many parts of continental Africa house construction does not appear to impede entry of malaria vectors and, given their generally late biting cycle, the great majority of transmission takes place indoors. In contrast, many houses in S?o Tomé, 140 km off the coast of Gabon, are raised on stilts and built of wooden planks. Building on stilts is a time-honoured, but largely untested, way of avoiding mosquito bites. Exposure may also be affected by mosquito activity times and age composition of host-seeking females. A study was therefore undertaken on the island of S?o Tomé to determine if exposure to Anopheles gambiae, the only vector on the island, varied with house construction or time of the night. METHODS: A series of all-night landing collections were undertaken out of doors at ground level, inside houses at ground level, on the verandas of, and inside houses built on stilts. The gonotrophic age of an unselected sample of insects from the first three hours of landing collection (18:00-21:00) was determined by dissection. In addition, 1,149 miniature light-trap collections were obtained from 125 houses in the study area. Numbers collected were related to house construction. RESULTS: Biting of An. gambiae took place primarily outside at ground level. Less than one third of biting occurred inside houses. Houses built on stilts had half the number of An. gambiae in them compared to those built at ground level. Conversely houses with an eaves gap had more An. gambiae in them than houses without such a gap. Gonotrophic age did not affect house entry rates in An. gambiae. House construction affected Culex quinquefasciatus less than An. gambiae. Mean density per house, derived from a series of 1,490 randomly assigned light-trap collections, was over-dispersed with 18% of houses having 70% of the vectors. CONCLUSION: House construction plays an important role in determining exposure to malaria vectors in S?o Tomé. Neighbours can have very different exposure levels. Recommendations for improvement in control are given.     

Monitoring temporal trends in spatially structured populations: how should sampling effort be allocated between space and time?

Estimating temporal trends in spatially structured populations has a critical role to play in understanding regional changes in biological populations and developing management strategies. Designing effective monitoring programmes to estimate these trends requires important decisions to be made about how to allocate sampling effort among spatial replicates (i.e. number of sites) and temporal replicates (i.e. how often to survey) to minimise uncertainty in trend estimates. In particular, the optimal mix of spatial and temporal replicates is likely to depend upon the spatial and temporal correlations in population dynamics. Although there has been considerable interest in the ecological literature on understanding spatial and temporal correlations in species’ population dynamics, little attention has been paid to its consequences for monitoring design. We address this issue using model‐based survey design to identify the optimal allocation of sampling effort among spatial and temporal replicates for estimating population trends under different levels of spatial and temporal correlation. Based on linear trends, we show that how we should allocate sampling effort among spatial and temporal replicates depends crucially on the spatial and temporal correlations in population dynamics, environmental variation, observation error and the spatial variation in temporal trends. When spatial correlation is low and temporal correlation is high, the best option is likely to be to sample many sites infrequently, particularly when observation error and/or spatial variation in temporal trends are high. When spatial correlation is high and temporal correlation is low, the best option is likely to be to sample few sites frequently, particularly when observation error and/or spatial variation in temporal trends are low. When abundances are spatially independent, it is always preferable to maximise spatial replication. This provides important insights into how spatio‐temporal monitoring programmes should be designed to estimate temporal trends in spatially structured populations.     

Towards an optimal sampling strategy for Alexandrium catenella (Dinophyceae) benthic resting cysts

The study proposes methodological developments to optimize sampling strategy of resting cysts of Alexandrium catenella to estimate their abundance with a predefined error. This work also aims to provide information on spatial distribution of resting cysts in sediments. The distribution mode of A. catenella resting cysts related to the abundance variability was studied through sediment cores sampling on four different spatial scales and using Ludox CLX gradient density method. The quantification method underestimates by a factor of 2 the resting cysts abundance in one gram of sediment. Application of Taylor's power law allowed us to define a compromise between sampling effort and abundance estimation error. In the case of A. catenella resting cysts from Thau lagoon, the optimal sampling strategy consists of sampling 10 stations on a surface of 2 km² for a given coefficient of variability (C) of 15%, sampling 3 sediment cores at each station (C = 30%) and counting only one replicate by core (C = 18%). Results related to the application of Taylor's power law are closely dependent on resting cyst density and aggregation in a given sediment. In our area, A. catenella resting cysts are mainly observed in the upper 3 cm of sediment. Horizontally, their heterogeneity is lower on 10 cm² surface and tends to stabilize itself beyond a surface of 10 m². Each author has to carry out this pre-sampling effort for his own resting cysts-forming species, in his own area, in order to increase accuracy of resting cyst mapping.     

A longitudinal entomologic survey on the transmission of malaria in Ouagadougou (Burkina Faso)

A longitudinal entomological malaria survey was carried out in five zones of the town of Ouagadougou, Burkina Faso, and in three neighbouring villages. The main vector is Anopheles gambiae s.l. with An. funestus having a role in some localities during the dry season. Pyrethrum spray catches were carried out once or twice per month to determine variations in vector density. Inoculation rates were estimated from the number of blood-fed vectors per man and from the sporozoite rates. Larval sampling was routinely carried out all over the urban area in order to map the larval breeding sites. Widely different degrees of malaria transmission were documented in the urban area mainly related to the spatial and temporal distribution of An. gambiae larval breeding sites. Higher inoculation rates, depending both on higher vector densities and sporozoite rates, were documented in the villages.     

A statistical theory for sampling species abundances

The pattern of species abundances is central to ecology. But direct measurements of species abundances at ecologically relevant scales are typically unfeasible. This limitation has motivated a long-standing interest in the relationship between the abundance distribution in a large, regional community and the distribution observed in a small sample from the community. Here, we develop a statistical sampling theory to describe how observed patterns of species abundances are influenced by the spatial distributions of populations. For a wide range of regional-scale abundance distributions we derive exact expressions for the sampled abundance distributions, as a function of sample size and the degree of conspecific spatial aggregation. We show that if populations are randomly distributed in space then the sampled and regional-scale species-abundance distribution typically have the same functional form: sampling can be expressed by a simple scaling relationship. In the case of aggregated spatial distributions, however, the shape of a sampled species-abundance distribution diverges from the regional-scale distribution. Conspecific aggregation results in sampled distributions that are skewed towards both rare and common species. We discuss our findings in light of recent results from neutral community theory, and in the context of estimating biodiversity.     

Anopheles gambiae genome: perspectives for malaria control

Malaria, a disease that infects 300 million people throughout the world and kills more than a million people, mostly children in sub-Saharan Africa, involves three organisms. The human host where the disease is seen, the protozoan Plasmodium parasite and the mosquito. The parasite is transmitted to humans only by the mosquito vector, which in sub-Saharan regions is generally Anopheles gambiae. Malaria along with AIDS and tuberculosis are killing large numbers of people and crippling the economies of the affected African countries. Though an enormous effort has been made during the past twenty years to develop vaccines to block malaria in humans, the incidence of the disease is increasing in Africa. The reasons for this development include a breakdown in mosquito control related to increased insecticide resistance, as well as increased parasite resistance to antimalarial drugs. It is clear that new methods of Anopheles mosquito control are needed to ameliorate the medical and economic situation in sub-Saharan Africa. As a step toward new malaria control methods, the international Plasmodium falciparum and Anopheles gambiae consortia have carried out the full genome sequencing of the most deadly malaria parasite and the most efficient vector. These, combined with the human genome sequence, provide the genomic infrastructure for a better understanding of the complex interactions within the malaria triad. This essay discusses possible strategies as to how the Anopheles genome can contribute to malaria control.     

Determining the spatial autocorrelation of dengue vector populations: influences of mosquito sampling method,covariables, and vector control

We investigated spatial autocorrelation of female Aedes aegypti L. mosquito abundance from BG‐Sentinel trap and sticky ovitrap collections in Cairns, north Queensland, Australia. BG‐Sentinel trap collections in 2010 show a significant spatial autocorrelation across the study site and over a smaller spatial extent, while sticky ovitrap collections only indicate a non‐significant, weak spatial autocorrelation. The BG‐Sentinel trap collections were suitable for spatial interpolation using ordinary kriging and cokriging techniques. The uses of Premise Condition Index and potential breeding container data have helped improve our prediction of vector abundance. Semiovariograms and prediction maps indicate that the spatial autocorrelation of mosquito abundance determined by BG‐Sentinel traps extends farther compared to sticky ovitrap collections. Based on our data, fewer BG‐Sentinel traps are required to represent vector abundance at a series of houses compared to sticky ovitraps. A lack of spatial structure was observed following vector control treatment in the area. This finding has implications for the design and costs of dengue vector surveillance programs.     

Temporal aggregation bias and inference of causal regulatory networks.

Time course experiments with microarrays have begun to provide a glimpse into the dynamic behavior of gene expression. In a typical experiment, scientists use microarrays to measure the abundance of mRNA at discrete time points after the onset of a stimulus. Recently, there has been much work on using these data to infer causal regulatory networks that model how genes influence each other. However, microarray studies typically have slow sampling rates that can lead to temporal aggregation of the signal. That is, each successive sampling point represents the sum of all signal changes since the previous sample. In this paper, we show that temporal aggregation can bias algorithms for causal inference and lead them to discover spurious relations that would not be found if the signal were sampled at a much faster rate. We discuss the implications of temporal aggregation on inference, the problems it creates, and potential directions for solutions.     

The Temporal Spectrum of Adult Mosquito Population Fluctuations: Conceptual and Modeling Implications

An improved understanding of mosquito population dynamics under natural environmental forcing requires adequate field observations spanning the full range of temporal scales over which mosquito abundance fluctuates in natural conditions. Here we analyze a 9-year daily time series of uninterrupted observations of adult mosquito abundance for multiple mosquito species in North Carolina to identify characteristic scales of temporal variability, the processes generating them, and the representativeness of observations at different sampling resolutions. We focus in particular on Aedes vexans and Culiseta melanura and, using a combination of spectral analysis and modeling, we find significant population fluctuations with characteristic periodicity between 2 days and several years. Population dynamical modelling suggests that the observed fast fluctuations scales (2 days-weeks) are importantly affected by a varying mosquito activity in response to rapid changes in meteorological conditions, a process neglected in most representations of mosquito population dynamics. We further suggest that the range of time scales over which adult mosquito population variability takes place can be divided into three main parts. At small time scales (indicatively 2 days-1 month) observed population fluctuations are mainly driven by behavioral responses to rapid changes in weather conditions. At intermediate scales (1 to several month) environmentally-forced fluctuations in generation times, mortality rates, and density dependence determine the population characteristic response times. At longer scales (annual to multi-annual) mosquito populations follow seasonal and inter-annual environmental changes. We conclude that observations of adult mosquito populations should be based on a sub-weekly sampling frequency and that predictive models of mosquito abundance must include behavioral dynamics to separate the effects of a varying mosquito activity from actual changes in the abundance of the underlying population.     

A spatial model of bird abundance as adjusted for detection probability

Modeling the spatial distribution of animals can be complicated by spatial and temporal effects (i.e. spatial autocorrelation and trends in abundance over time) and other factors such as imperfect detection probabilities and observation-related nuisance variables. Recent advances in modeling have demonstrated various approaches that handle most of these factors but which require a degree of sampling effort (e.g. replication) not available to many field studies. We present a two-step approach that addresses these challenges to spatially model species abundance. Habitat, spatial and temporal variables were handled with a Bayesian approach which facilitated modeling hierarchically structured data. Predicted abundance was subsequently adjusted to account for imperfect detection and the area effectively sampled for each species. We provide examples of our modeling approach for two endemic Hawaiian nectarivorous honeycreepers: 'i'iwi Vestiaria coccinea and 'apapane Himatione sanguinea .     

Mosquito net barriers for sample collection of zoophilic Culicidae

Mosquito net fences 2.30-2.50 m high placed around cowsheds at their night resting sites have been successfully utilized to obtain large samples of malaria vectors of the Anopheles gambiae complex and of other mosquito species. Collections of blood-fed mosquitoes were carried out during the night by inspecting regularly the net side facing the animal enclosure. This sampling procedure has important advantages over alternative procedures based on direct collection on animal or on the use of animal-baited traps.     

Estimating similarity of communities: a parametric approach to spatio‐temporal analysis of species diversity

Several stochastic models with environmental noise generate spatio‐temporal Gaussian fields of log densities for the species in a community. Combinations of such models for many species often lead to lognormal species abundance distributions. In spatio‐temporal analysis it is often realistic to assume that the same species are expected to occur at different times and/or locations because extinctions are rare events. Spatial and temporal β‐diversity can then be analyzed by studying pairs of communities at different times or locations defined by a bivariate lognormal species abundance model in which a single correlation occurs. This correlation, which is a measure of similarity between two communities, can be estimated from samples even if the sampling intensities vary and are unknown, using the bivariate Poisson lognormal distribution. The estimators are approximately unbiased, although each specific correlation may be rather uncertain when the sampling effort is low with only a small fraction of the species represented in the samples. An important characteristic of this community correlation is that it relates to the classical Jaccard‐ or the Sørensen‐indices of similarity based on the number of species present or absent in two communities. However, these indices calculated from samples of species in a community do not necessarily reflect similarity of the communities because the observed number of species depends strongly on the sampling intensities. Thus, we propose that our community correlation should be considered as an alternative to these indices when comparing similarity of communities. We illustrate the application of the correlation method by computing the similarity between temperate bird communities.     

Use of classical bird census transects as spatial replicates for hierarchical modeling of an avian community

New monitoring programs are often designed with some form of temporal replication to deal with imperfect detection by means of occupancy models. However, classical bird census data from earlier times often lack temporal replication, precluding detection‐corrected inferences about occupancy. Historical data have a key role in many ecological studies intended to document range shifts, and so need to be made comparable with present‐day data by accounting for detection probability. We analyze a classical bird census conducted in the region of Murcia (SE Spain) in 1991 and 1992 and propose a solution to estimating detection probability for such historical data when used in a community occupancy model: the spatial replication of subplots nested within larger plots allows estimation of detection probability. In our study, the basic sample units were 1‐km transects, which were considered spatial replicates in two aggregation schemes. We fit two Bayesian multispecies occupancy models, one for each aggregation scheme, and evaluated the linear and quadratic effect of forest cover and temperature, and a linear effect of precipitation on species occupancy probabilities. Using spatial rather than temporal replicates allowed us to obtain individual species occupancy probabilities and species richness accounting for imperfect detection. Species‐specific occupancy and community size decreased with increasing annual mean temperature. Both aggregation schemes yielded estimates of occupancy and detectability that were highly correlated for each species, so in the design of future surveys ecological reasons and cost‐effective sampling designs should be considered to select the most suitable aggregation scheme. In conclusion, the use of spatial replication may often allow historical survey data to be applied formally hierarchical occupancy models and be compared with modern‐day data of the species community to analyze global change process.     

Composition of human skin microbiota affects attractiveness to malaria mosquitoes

The African malaria mosquito Anopheles gambiae sensu stricto continues to play an important role in malaria transmission, which is aggravated by its high degree of anthropophily, making it among the foremost vectors of this disease. In the current study we set out to unravel the strong association between this mosquito species and human beings, as it is determined by odorant cues derived from the human skin. Microbial communities on the skin play key roles in the production of human body odour. We demonstrate that the composition of the skin microbiota affects the degree of attractiveness of human beings to this mosquito species. Bacterial plate counts and 16S rRNA sequencing revealed that individuals that are highly attractive to An. gambiae s.s. have a significantly higher abundance, but lower diversity of bacteria on their skin than individuals that are poorly attractive. Bacterial genera that are correlated with the relative degree of attractiveness to mosquitoes were identified. The discovery of the connection between skin microbial populations and attractiveness to mosquitoes may lead to the development of new mosquito attractants and personalized methods for protection against vectors of malaria and other infectious diseases.     

Anopheles nili as the main vector of human malaria in villages of southern Cameroon

In villages near Sanaga river, in the forest zone of south Cameroon, Anopheles nili Theobald is the main species of mosquito regularly found biting man inside houses. Its densities are related to the flow level of the river. It is also the main malaria vector in terms of intensity and seasonal duration of transmission. The yearly malaria inoculation rate due to An. nili alone is 104 infective bites/man, varying between 3 infective bites/man in October and 20 in March. Anopheles gambiae Giles is a less important vector in the area but reached its peak in the dry season, when the Sanaga river is at its lowest level. These observations underline the influence of local ecology on malaria transmission and the need for entomological studies in each situation.     

Environmental factors associated with the distribution of Anopheles arabiensis and Culex quinquefasciatus in a rice agro-ecosystem in Mwea, Kenya

Studies were conducted between May and June, 2006 to investigate the environmental factors affecting the distribution of An. arabiensis Patton and Culex quinquefasciatus Say in Mwea, Kenya. The sampling unit comprised all non-paddy aquatic habitats and ten randomly selected paddies and canals located within a 200 m radius from the periphery of the study site. Thirteen physico-chemical variables were recorded for each sampling site in each sampling occasion and a sample of mosquito larvae and other aquatic invertebrates collected. The non-paddy aquatic habitats identified included pools and marshes. Morphological identification of 1,974 mosquito larvae yielded four species dominated by Cx. quinquefasciatus (73.2%) and An. arabiensis (25.0%). Pools were associated with significantly higher Cx. quinquefasciatus larval abundance and less diversity of other aquatic invertebrates compared with other habitat types. In contrast, the abundance of An. arabiensis did not differ significantly among habitat types. Culex quinquefasciatus habitats had higher water conductivity and exhibited a higher abundance of other aquatic invertebrates than An. arabiensis habitats. Chi-square analysis indicated that the two species were more likely to coexist in the same habitats than would be expected by chance alone. Anopheles arabiensis larvae were positively associated with dissolved oxygen and adults of family Haliplidae and negatively associated with emergent vegetation and Heptageniidae larvae. Culex quinquefasciatus larvae were positively associated with dissolved oxygen, total dissolved solids, Chironomidae larvae, and Microvelidae adults and negatively associated with emergent vegetation. These findings suggest that both biotic and abiotic factors play a significant role in niche partitioning among Cx. quinquefasciatus and An. arabiensis, a factor that should be considered when designing an integrated vector control program.