Mosquito (Diptera: Culicidae) Species Composition in Ovitraps From a Mesoamerican Tropical Montane Cloud Forest

Abstract

Knowledge about mosquito species diversity at tropical montane cloud forests (TMCFs) in Mesoamerica is scarce. Here, we present data on mosquito species richness from samples biweekly collected, from January to December 2017, in ovitraps installed in a TMCF patch at Vázquez de Coronado County, Costa Rica. Ovitraps were placed at 2.25, 1.50 and 0.75 m at 16 sampling points. During the study period we measured relative humidity and air temperature at each sampling point, and water temperature, volume and pH in each ovitrap. We collected a total of 431 mosquito larvae belonging to five taxonomic units, one identified to the genus level and four to the species level. The most common mosquito species was Culex bihaicolus Dyar & Nuñez Tovar (Diptera: Culicidae), which accounted for nearly 80% (n = 344) of the collected mosquitoes. Culex nigripalpus Theobald (Diptera: Culicidae) was the only medically important species we found and it was collected both in the dry (January to March) and rainy season (April to December). Over 95% (n = 411) of the mosquitoes were collected during the rainy season and 60% (n = 257) at 0.75 m. Among the environmental variables that we measured, only water volume and pH were significantly (P < 0.05) different between the dry and rainy season, the former increasing and the later decreasing during the rainy season. These results suggest that rainfall plays a major role regulating the phenology of the sampled mosquito species and highlight the need to screen for pathogens in Cx. nigripalpus at the study area.

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Sampling, Distribution, Dispersal
Mosquito (Diptera: Culicidae) Species Composition
in Ovitraps From a Mesoamerican Tropical Montane
CloudForest
Luis MarioRomero,1 Luis GuillermoChaverri,2 and Luis FernandoChaves3,4,5,
1Centro de Investigación en Enfermedades Tropicales, Universidad de Costa Rica, San Pedro de Montes de Oca, San José, Costa
Rica, 2Departamento de Ciencias Naturales, Escuela de Enseñanza de las Ciencias, Universidad Estadal a Distancia, San Pedro
de Montes de Oca, San José, Costa Rica, 3Instituto Costarricense de Investigación y Enseñanza en Nutrición y Salud (INCIENSA),
Apartado Postal 4-2250, Tres Ríos, Cartago, Costa Rica, 4Programa de Investigación en Enfermedades Tropicales (PIET), Escuela de
Medicina Veterinaria, Universidad Nacional, Heredia, Costa Rica, and 5Corresponding author, e-mail: lfchavs@gmail.com
Subject Editor: JonathanDay
Received 3 June 2018; Editorial decision 20 August 2018
Abstract
Knowledge about mosquito species diversity at tropical montane cloud forests (TMCFs) in Mesoamerica is scarce.
Here, we present data on mosquito species richness from samples biweekly collected, from January to December
2017, in ovitraps installed in a TMCF patch at Vázquez de Coronado County, Costa Rica. Ovitraps were placed at 2.25,
1.50 and 0.75 m at 16 sampling points. During the study period we measured relative humidity and air temperature
at each sampling point, and water temperature, volume and pH in each ovitrap. We collected a total of 431 mosquito
larvae belonging to five taxonomic units, one identified to the genus level and four to the species level. The most
common mosquito species was Culex bihaicolus Dyar & Nuñez Tovar(Diptera: Culicidae), which accounted for
nearly 80% (n = 344) of the collected mosquitoes. Culex nigripalpus Theobald (Diptera: Culicidae) was the only
medically important species we found and it was collected both in the dry (January to March) and rainy season
(April to December). Over 95% (n=411) of the mosquitoes were collected during the rainy season and 60% (n=257)
at 0.75 m.Among the environmental variables that we measured, only water volume and pH were significantly
(P<0.05) different between the dry and rainy season, the former increasing and the later decreasing during the rainy
season. These results suggest that rainfall plays a major role regulating the phenology of the sampled mosquito
species and highlight the need to screen for pathogens in Cx. nigripalpus at the study area.
Key words: Culicidae, Costa Rica, container mosquito, longitudinal data
Mosquito diversity surveys are important for disease control because
they reveal the entomological risk posed by the presence of domi-
nant vector species, i.e., those species competent and able to ef-
ciently transmit pathogens that affect human health (Turell etal.
2001, Turell et al. 2005). Furthermore, when mosquito diversity
surveys are longitudinal they also allow to describe the phenology of
mosquito species with and without medical importance (Toma and
Miyagi 1981, Reisen etal. 1999, Hoshi etal. 2014b), and to evalu-
ate associations between mosquito diversity and infection (Chaves
etal. 2011).
From an ecological perspective, understanding mosquito diversity
is necessary to generalize principles about insect diversity and factors
shaping it (Foley etal. 2007), and to also generate landmark obser-
vations that could be useful to evaluate impacts of climate change
on medically important taxa (Chaves 2016, Chaves and Añez 2016,
Chaves 2017a). For example, Costa Rica is a global biodiversity
hotspot (Mittermeier etal. 1998, Myers et al. 2000), and this pat-
tern of overwhelming diversity also extends to mosquitoes (Foley
etal. 2007). In Costa Rica, longitudinal studies on mosquito species
diversity have been unusual, and most data comes from short-term
surveys (Heinemann and Belkin 1977, Burkett‐Cadena et al. 2013,
Chaverri etal. 2018). Despite its small geographical area Costa Rica
has a great richness of natural ecosystems which in part explains
its huge diversity of living taxa (Kappelle 2016), but some highland
ecosystems have been poorly studied, e.g., tropical montane cloud
forests (Myers etal. 2000), hereafter referred asTMCFs.
In general, mosquito diversity studies in Costa Rica have been
biased toward the lowlands (Heinemann and Belkin 1977, Gilbert
et al. 2008, Burkett‐Cadena et al. 2013, Chaverri et al. 2018), an
area that historically has faced epidemics of mosquito-borne dis-
eases, including arboviruses, such as dengue (Calderón-Arguedas
etal. 2015, Soto-Garita etal. 2016) and Yellow fever (Romero and
Journal of Medical Entomology, XX(X), 2018, 1–10
doi: 10.1093/jme/tjy170
Research
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Trejos 1954), and parasites, e.g., Plasmodium spp. Machiafava &
Celli, the causative agent of malaria (Núñez 1926, Kumm and Ruiz
1939, Kumm etal. 1940, Warren etal. 1975, Sáenz etal. 2012) and
Wuchereria bancrofti (Cobbold), the worm causing lymphatic la-
riasis (Weinstock etal. 1977, Paniagua etal. 1983). The Costa Rican
lowlands also comprise the areas where the invasion by the Asian
tiger mosquito, Aedes albopictus (Skuse), was rst documented
(Marín etal. 2009) and its ecology (Calderón Arguedas etal. 2012)
and phylogeography (Futami etal. 2015) have been studied in more
detail. Costa Rica’s lowland areas have year-round high tempera-
tures and high relative humidity (Herrera 2016), which are opti-
mal conditions for mosquito movement and vector-borne disease
transmission (Silver 2008). Nevertheless, Costa Rica is crossed by
mountains (Vargas 2006), and high-altitude ecosystems are known
to harbor a diverse array of mosquito species (Eisen et al. 2008),
but the ecology of montane mosquito species has been poorly stud-
ied, with a few exceptions (Barker etal. 2009, Lozano-Fuentes etal.
2012a,b), and even fewer mosquito studies in TMCFs (Parker etal.
2012, Abella-Medrano etal. 2015).
TMCFs are high altitude (over 1,650 m above the sea) eco-
systems characterized by a high proportion of endemic species
(Bruijnzeel etal. 2010), and are among the ecosystems more affected
by global warming and expected to disappear if global temperatures
continue to increase (Ponce-Reyes et al. 2012). From the perspec-
tive of mosquitoes an interesting aspect of tropical cloud forests is
the high abundance of epiphytes (Foster 2001), among which the
Bromeliaceae are known to serve as natural habitat for many mos-
quito species (Müller etal. 2008, Marques etal. 2012, Parker etal.
2012, Müller et al. 2014, Alencar et al. 2016, Inácio et al. 2017).
Ovitrap sampling is a cheap and simple way to collect diverse mos-
quito species (Moriya 1974, Toma and Miyagi 1981, Zea Iriarte
etal. 1991, Ritchie etal. 2003). Ovitraps have shown encouraging
results when used for mosquito diversity studies in tropical rainfor-
ests of Mesoamerica (Chaverri etal. 2018) and South America (Silva
et al. 2018). Since no outbreaks of mosquito-borne diseases have
been reported at high elevations in Costa Rica, an open question
is whether species with known vectorial competence and capacity
are present in natural areas expected to undergo major ecological
transformations as product of climate change. Thus, given the lack
of knowledge about mosquitoes from TMCFs, here we present
results from a season-long study looking at mosquito species rich-
ness and their phenology in ovitraps biweekly sampled, from
January to December 2017, at a TMCF patch in the central valley
of CostaRica.
Methods
StudySite
Our study was done at Finca San Francisco de Asis (FSFA),
an 8.5-hectare secondary growth TMCF plot centered at (10°
1′31.01″N, 83°56′27.34″W) with a mean altitude of 1,760 m.FSFA
is located in Montserrat, Vázquez de Coronado County, San José
Province, Costa Rica (Fig. 1). This area has been populated since
pre-hispanic times, and by the time Spaniards arrived to the area
the kingdom of Toyopán was a highly developed Huetar culture
(Rodríguez Argüello 2010). Nevertheless, with the arrival of Spanish
explorer Juan de Cavallón y Arboleda in 1561, who subjugated the
major native kingdoms in the central valley of Costa Rica, and then
by Juan Vázquez de Coronado who furtherly imposed Spanish rule
in Costa Rica, the development of this area waned until 1834, when
the area started to be colonized as part of the historic and economic
development of Costa Rica as an independent nation (Rodríguez
Argüello 2010). Until 1910 land transformation was minimal, and
associated with subsistence agriculture, but with the separation of
the historic Toyopán area, from San José county, as the ‘Vázquez
de Coronado’ county, the historic Toyopán area was extensively
deforested for both the exploitation of wood as a commodity and
the transformation of forests into ranchland for livestock, mainly
for dairy cattle ranches (Rodríguez Argüello 2010). For example,
between 1910 and 1914 over 6,000 of the 22,000 hectares of the
Vázquez de Coronado county were deforested to become farmland
(Rodríguez Argüello 2010). As of 2000, around 73% of the county
22,000 hectares are covered by primary and secondary forests, and
there is little pressure for further deforestation (Bonilla-Carrion
and Rosero-Bixby 2004). Interspersed with the dairy cattle ranches
remain several patches of TMCF the original landcover of this area,
Fig.1. Study area Map. The left map shows the location of the oviposition traps at the study site and on the right is the location of Finca San Francisco de Asis
in Costa Rica, where San José is shown as reference. The base maps are courtesy of Google Earth.
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one of these patches is FSFA which is covered by a secondary for-
est that grew from the primary forest growing at the margin of
Quebrada Juncos, a stream that ows across FSFA and is tributary
to Rio Sucio, a major river in the central valley of Costa Rica. FSFA
is near to ‘Parque Nacional Braulio Carrillo’ one of the largest natu-
ral Areas in Costa Rica (475.8 km2), comprising several ecosystems
and ranging from 30 to 2,906 m, including TMCFs similar to FSFA
(Meza and Bonilla 1990).
Mosquito Sampling
For mosquito sampling we set ovitraps at 16 points along a longi-
tudinal transect (Fig.1). The selected points were mainly composed
of bamboo clumps and ovitraps were set at heights of 0.75, 1.5,
and 2.0 m, thus totaling 48 ovitraps. Each ovitrap (Chaves etal.
2015) was made from 333 ml recycled soda cans, which were
painted, both in the inside and the outside, with black paint (2X
Double Coverage, Harris, Vernon Hills, IL). Traps were set on 23
December 2016, when all traps were lled with 250ml of tap water,
and the data presented here correspond to the biweekly collections
from 30 December 2016 to 30 December 2017. Specically, each
14 d we checked every individual ovitrap, repeating the following
procedure: 1)Contents from each ovitrap were emptied on a trans-
parent tray 150×220×45mm (Mujirushi Ryōhin Co. LTD. Tokyo,
Japan) and we carefully searched for mosquito larvae and pupae;
2)Large larvae, third and fourth instar, were collected in vials with
70% ethanol (LABQUIMAR, San José, Costa Rica), although we
considered collecting pupae, we did not nd any during the studied
period; 3) Contents from the tray were returned into the ovitrap;
4)The tray was thoroughly rinsed with a pressurized water sprinkler
before starting the cycle with the next ovitrap. This last step was
made to prevent the accidental transfer of eggs and rst instar larvae
between ovitraps (Chaves and Moji 2018). The collected larvae were
then mounted on slides using PVA (Bioquip, Rancho Dominguez,
CA) and then identied using a light microscope and the taxonomic
key for mosquitoes of Costa Rica by Darsie (1993). Vouchers of all
collected taxa were deposited at the Museo Nacional de Costa Rica.
EnvironmentalData
During each sampling session we collected water temperature data
using a bafx3435 infrared thermometer (BAFX Products, Franksville,
WI), pH with a 35423-10 EcoTestr pH 2 pH meter (Oakton
Instruments, Vernon Hills, IL) and measured the water volume of
each ovitrap with a graduated cup (OXO, New York, NY). We also
measured relative humidity and air temperature using a Kestrel 3000
weather sensor (Kestrel Meters, Minneapolis, MN). All measure-
ments were taken during the study period, with the exception of pH,
whose systematic measurements started on 11 February 2017. Since
these data only spanned one season we also retrieved rainfall data
from NOAA CPC Morphing Technique (‘CMORPH’) database and
temperature data from the NOAA Global Historical Climatology
Network version 2 and the Climate Anomaly Monitoring System
(GHCN_CAMS 2m model). We accessed the data using the KNMI
explorer available at http://climexp.knmi.nl/start.cgi. The spatial res-
olution of these two databases is 0.5° for temperature and 0.25° for
rainfall. Data were extracted from the cell containing the studysite.
Figure 2 shows the seasonal rainfall (Fig. 2A) and tempera-
ture (Fig.2B) prole based on monthly observation from January
1998 to December 2017. During, the study period rainfall followed
a normal pattern, with a dry season from January to April, and a
rainy season for the rest of the year, reaching a rainfall peak in July
(Fig.2A). Meanwhile temperatures were abnormally high during the
dry season and November and December, reaching a historic peak
in February (Fig.2B).
Statistical Analysis
We estimated the mean and standard deviation (Zar 1998) of mos-
quito persistence, i.e., how often were larvae present at the ovit-
raps (Chaves 2017b), per season (dry and rainy), for all ovitraps
and for ovitraps placed at the different studied heights. We also
estimated the mean and standard deviation of each of the locally
measured environmental variables (ovitrap water temperature, pH
and volume) per season. We compared the mean of mosquito per-
sistence and environmental variables, during the dry (January to
April, i.e., biweeks 1 to 9)and rainy season (May to December,
i.e., biweeks 10 to 26), using a Welch’s t test. We chose this test as
it corrects for differences in the variance between the two groups
compared (Zar 1998). To perform a time series analysis we input-
ted missing ovitrap water temperature and pH data points using
the locally weighted smoothing (LOESS) method (Cleveland and
Devlin 1988). Briey, a LOESS regression on the collected time
series allows to intepolate the missing data points (Faraway 2006).
We estimated cross-correlation functions (Shumway and Stoffer
Fig.2. Seasonal climatic profiles of Vázquez de Coronado County (A) rainfall and (B) temperature. The monthly boxplots show the distribution of the observations
between January 1998 and December 2017, and the boxes show the second and third quantiles of the data, while the bar indicates the median of the data. The
dashed line corresponds to observations for 2017.
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2011) between the time series of environmental variables and the
persistence and total abundance of all collected mosquitoes (Hoshi
etal. 2014a, Hoshi etal. 2017). We also estimated spatial persis-
tence, i.e., how often we were able to collect mosquito larvae by
trap height and by sampling location (Chaves 2017b). Finally, we
studied the spatial association patterns between the season-long
averages of the environmental variables and the season-long cumu-
lative abundance and spatial persistence patterns of all collected
mosquitoes.
Results
We collected a total 431 mosquito larvae, which belonged to ve
taxonomic units, including four taxa identied to the species level
and a homogenous taxon identied to the genus level (Table 1).
Figure3 shows time series of the collected data. Figure3A shows
mosquito abundance through time, where it is clear that over the
studied period mosquitoes were more abundant at 0.75 m, followed
by samples collected at 1.50 m and less abundant at 2.25 m.Indeed
over 60% (n = 257) of the mosquitoes were collected at 0.75 m
(Table1). Over 95% (n=411) of the mosquitoes were collected dur-
ing the rainy season (Table1), biweeks 10 to 26 in Fig.3A. Asimilar
seasonal pattern was observed for mosquito persistence (Fig. 3B)
where the maximum persistence observed at any given sampling ses-
sion was 50% at 0.75 m during biweek 16 (Fig. 3B). In general,
mosquito persistence was signicantly (P<0.05) smaller during the
dry season, biweeks 1 to 9 in Fig.3B, than during the rainy season,
across all ovitraps, and also at the three heights where ovitraps were
placed (Table2). Relative humidity (Fig.3C) was consistently high
during the study period, with similar values during the dry and rainy
seasons (Table2). Air temperature was slightly higher than in the
ovitraps (Fig.3D) during the study period and temperature increased
with ovitrap height. Although temperature increased its mean value
during the rainy season, the difference was not statistically sig-
nicant (P > 0.05) when compared with the dry season (Table2).
Also, due to a malfunction, during intense rain, of the water tem-
perature thermometer on biweeks 12 and 14, values for those time
periods were inputted (Fig. 3D). Ovitrap water volume (Fig. 3E),
decreased when temperature reached peak values (Fig. 3D), and
traps had more water during the rainy than the dry season (Table2).
Additionally, ovitrap water volume slightly increased as trap height
decreased (Fig.3D and Table2). Ovitrap water pH (Fig.3F) became
more acidic during the rainy than the dry season (Table2) and more
extreme pH uctuations were observed as trap height increased
(Fig.3F). Due to a decalibration of our pH meter during biweek 9
we inputted values for that biweek (Fig.3F). We want to highlight
that differences in the df for the comparisons between dry and rainy
(Table2) arose from the correction for variance heterogeneity of the
Welch’s t test but also because we did not include any inputted obser-
vation, but the collected rawdata.
The collected species included Cx. bihaicolus, which was the
most abundant (Table1) and was present through all the rainy sea-
son, from biweeks 10 to 25 (Fig.4A). This species was followed by
Cx. nigripalpus, which appeared during the dry, at biweek 6, and
rainy season, at biweek 14 (Fig.4B). The third most abundant spe-
cies Aedes spinossus Berlin which appeared after biweek 16 (Fig.4C)
followed by Culex erethyzonpher Galindo & Blanton, which also
appeared during the rainy season after biweek 16 (Fig.4D). Finally,
the least abundant taxon we identied was a homogeneous group of
larvae belonging to the genus Wyeomyia sp. Lynch, which appeared
on the 13th biweek (Fig. 4E). Regarding the species distribution
across ovitrap height, it is worth highlighting Cx. erethyzonpher was
the species more abundant, in proportion to its total abundance, at
2.25 m, while the Wyeomyia sp. was the most abundant, in propor-
tion to its total abundance, at 1.5 m and the rest of the species were
mainly found at 0.75 m (Table1).
Air temperature and relative humidity, in general, were not signif-
icantly associated with neither mosquito abundance nor persistence,
and signicant associations (P<0.05) occurred for relatively long
lags, of 6 biweeks or more (Table3). By contrast, ovitrap water tem-
perature was positively and signicantly (P<0.05) associated with
mosquito abundance, with short time delays, in general between
1 and 2 biweeks (the exception being abundance at 2.25 m, were
the signicant lag was 7 biweeks). The association pattern between
mosquito abundance and temperature was positive in all cases, indi-
cating that an increasing ovitrap water temperature was followed
by increases in mosquito abundance and persistence at the FSFA,
with the exception of ovitraps at 1.50 m (Table3). An increase in
water volume, was correlated, with a lag of around 3 biweeks with
mosquito persistence in ovitraps at 2.25 m and 0.75 m (Table3).
Meanwhile a more basic pH around, with a lag between 5 and 8
biweeks, was positively and signicantly associated (P<0.05) with
an increase in mosquito persistence and abundance at all heights but
0.75 m (Table3). For further reference the cross-correlation func-
tions, CCFs, between mosquito abundance and persistence, with the
environmental variables used to generate Table3 are presented in
Supp. Fig.1.
Spatial patterns of association between mosquito abundance
and persistence showed, in general, no clear association with any of
the environmental variables we studied (Fig. 5). More specically,
in Fig. 5A, we show unique symbols for each sampling location in
our study transect. These symbols were used in subsequent panels
to individually identify each sampling location and tones were used
(Fig. 5B) to identify the height of each ovitrap. We then plotted
cumulative mosquito abundance as function of the different environ-
mental variables: relative humidity (Fig.5B), temperature (Fig.5C),
Table1. Mosquito species abundance by ovitrap height at Finca San Francisco de Asis, Vázquez de Coronado County, Costa Rica during
2017
Season Dry season Rainy season
Ovitrap height (m) 2.25 1.50 0.75 2.25 1.50 0.75
Culex (Carrollia) bihaicolus Dyar & Nuñez Tovar 0 0 0 63 100 181
Culex (Culex) nigripalpus Theobald 0 0 20 0 0 39
Aedes (Howardina) spinosus Berlin 0 0 0 0 1 15
Culex (Micraedes) erethyzonpher Galindo & Blanton 0 0 0 4 1 1
Wyeomyia sp. Theobald 0 0 0 0 5 1
Total 0 0 20 67 107 237
The dry season spanned January–April and the rainy season was from May to December.
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ovitrap water volume (Fig.5D) and ovitrap water pH (Fig.5E), and
did not nd any clear pattern of association. We also plotted mos-
quito spatial persistence as function of relative humidity (Fig.5F),
temperature (Fig.5G), ovitrap water volume (Fig.5H) and ovitrap
water pH (Fig. 5I), and a similar pattern to the one observed for
abundance was observed, without any clear pattern of association
between mosquito persistence and the environmental variables.
Discussion
A key nding of this study was the occurrence of Cx. nigripalpus at
the study site, a dominant vector species in the transmission of sev-
eral arboviruses in the New World, including St. Louis Encephalitis
virus (Edman and Taylor 1968, Day and Edman 1988, Day et al.
1990, Day and Curtis 1994, Day and Curtis 1999), Eastern Equine
Encephalitis virus (Day etal. 2015) and West Nile virus in North
America (Rutledge et al. 2003, Vitek et al. 2008), Venezuelan
Equine Encephalitis virus (Mendez etal. 2001), and Eastern Equine
Encephalitis virus (Downs etal. 1959) in South America. Cx. nigri-
palpus is also known to transmit pathogens of wildlife veterinary
importance, e.g., Plasmodium hermani Telford & Forrester the etio-
logic agent of Wild Turkey malaria (Forrester etal. 1980). Thus, the
nding of Cx. nigripalpus at the study site calls for a more detailed
monitoring of this mosquito species and its potential to transmit
pathogens, especially as temperatures warm up rendering possible
pathogen development and transmission by Cx. nigripalpus (Dohm
etal. 2002) in the study area, where current low temperatures likely
limit pathogen development and transmission in mosquito vector
species (Carrington etal. 2013a,b, Chaves 2017a).
From an ecological perspective our data showed that species
richness sampled with ovitraps at the studied TMCF patch was
relatively low, with only ve taxonomic units collected, especially
Fig.3. Time series of collected data (A) Mosquito abundance, (B) Mosquito persistence, (C) Ralative humidity, (D) Temperature, (E) Ovitrap water volume, and
(F) Ovitrap water pH. The inset legend of panel Agives codes for data from ovitraps set at different heights, and dashed lines indicate variables that were not
measured at the ovitraps (‘Air’). For ovitrap water temperature and pH we needed to impute a few observations that are indicated by points (see inset legend
of panel D).
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when compared with results from ovitraps employed in lowland
areas (Chaverri etal. 2018) and other mosquito studies using dif-
ferent traps and sampling methods also in the lowlands (Calderón
Arguedas et al. 2012, Burkett‐Cadena et al. 2013), but similar to
what has been observed for mosquitoes in diverse phytotelmata
from TCMF (Seifert 1980, Seifert and Barrera 1981). This result
might also reect the impacts of the landscape matrix where FSAS
is located, as a TMCF patch surrounded by dairy cattle ranchs, a
matrix that has been associated with overall low species richness and
diversity in the tropics (Perfecto and Vandermeer 2008).
The colonization of traps at different heights by different mos-
quito species might reect their natural habitat preferences. For
example, Cx. nigripalpus was only found at 75cm, and it is common
for this species to colonize natural and articial water containers
placed near ground level (Hribar etal. 2004, Hribar 2007) as we
observed during the study period. Meanwhile, Cx. erethyzonpher,
which in proportion to its total abundance was the mosquito species
most common at 2.25 m, is known for having a preference for arbo-
real epiphytes, as opposed to ground epiphytes (Galindo and Blanton
1954). By contrast, all the other species we were able to identify are
known to be associated with larval habitats at wider height ranges.
For example, Cx. bihaicolus has been frequently found at low-height
phytotelmata, including Heliconia spp., which are common at FSFA,
and aspects of its ecology in Heliconia spp. bracts have been studied
in a TMCF of Venezuela (Seifert 1980, Seifert and Barrera 1981). In
addition, Cx. bihaicolus is also known to colonize treeholes at higher
heights (Galindo etal. 1955), bamboo stumps, leaf axils of brome-
liads and fallen palm fronds (Valencia 1973). It is also common
that Wyeomyia spp. are associated with Heliconia spp. of TMCFs,
as revealed in the few mosquito studies from TCMFs in the New
World (Seifert 1980, Seifert and Barrera 1981, Abella-Medrano etal.
2015), and when checking Heliconia spp. near our ovitraps we only
found Wyeomyia spp., including larvae similar to the homogeneous
taxon we found in the ovitrap and at least two more taxa, which
we were unable to identify given the lack of taxonomic keys for this
group of Sabethini mosquitoes, whose classication and phylogeny
remains largely unresolved (Motta et al. 2012). Ae. spinosus was
Table2. Mosquito larvae persistence and environmental parameters by ovitrap height and season at Finca San Francisco de Asis, Vázquez
de Coronado County, Costa Rica during 2017
Parameter Height (m) Dry season Rainy season tdf P-value
Mosquito persistence (%) Average 0.231±0.069 15.196±9.310 −6.593 16.334 <5×10−6*
2.25 0.000±0.000 10.662±9.047 −4.859 16 <2×10−4*
1.50 0.000±0.000 16.911±11.851 −5.884 16 <2×10−5*
0.75 0.694±2.0833 18.015±12.862 −5.419 17.539 <4×10−5*
Relative humidity (%) Average 92.56±7.04 95.37±4.300 −1.483 11.253 0.1655
Air temperature (°C) Average 18.035±2.975 18.851±1.097 −0.794 9.169 0.4471
Water temperature (°C) Average 15.339±2.647 17.357±1.208 −2.148 10.172 0.0568
2.25 15.481±2.666 17.502±1.279 −2.122 10.403 0.0587
1.50 15.337±2.663 17. 372±1.258 −2.144 10.329 0.0567
0.75 15.197±2.617 17.197±1.093 −2.174 9,820 0.0553
Water volume (ml) Average 276.30±13.05 289.25±10.39 −2.577 13.507 <0.0224*
2.25 273.785±14.570 287.846±11.715 −2.499 13.615 <0.0259*
1.50 276.088±16.113 287.953±11.984 −1.943 12.822 0.0743
0.75 279.016±12.313 291.942±12.303 −2.548 16.426 <0.0212*
Water pH Average 6.681±0.177 6.133±0.337 4.826 13.331 <0.0003*
2.25 6.708±0.213 6.265±0.525 2.783 17.276 <0.012*
1.50 6.583±0.128 6.014±0.284 6.347 15.704 <1×10−5*
0.75 6.753±0.203 6.118±0.381 4.899 13.117 <2×10−4*
All parameters are presented as mean ± SD. t indicates the Welch’s t statistic comparing the dry and rainy seasons mean values, df, the degrees of freedom and
P-value the signicance of the test. The dry season was from January to April and the rainy season was from May to December. In ‘Height (m)’ average indicates
the mean from ovitraps at the three heights.*P < 0.05.
Fig. 4. Biweekly mosquito abundance (A) Culex bihaicolus, (B) Culex
nigripalpus, (C) Aedes spinosus, (D) Culex erethyzonpher, and (E) Wyeomyia
sp. Each bar indicates the abundance for the biweek ending on the date
presented in the x-axis.
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Table3. Association sign and lags of weather variables significantly correlated with mosquito abundance and persistence at Finca San
Francisco de Asis, Vázquez de Coronado County, Costa Rica during 2017
Parameter Height (M) Relative humidity Air temperature Water temperature Water volume Water pH
Abundance Average N.S. N.S. +(2) N.S. +(5) and +(7)
2.25 −(7) N.S. +(7) N.S. +(5)
1.50 N.S. +(6) N.S. N.S. +(5), +(6) and +(7)
0.75 N.S. N.S. +(2) N.S. N.S.
Persistence Average N.S. N.S. +(1) and +(2) N.S. +(5) and +(7)
2.25 N.S. N.S. +(1) +(3) −(2) and +(5)
1.50 N.S. N.S. N.S. N.S. +(6), +(7) and +(8)
0.75 N.S. N.S. N.S. +(2) and +(3) N.S.
Columns indicate weather variables. N.S.stands for not signicant, + for a positive association, − for a negative association and the number inside parenthesis
() indicates the lag, in biweeks, of the association. In ‘Height (m)’ average indicates the time series that averages data from ovitraps at the three heights.
Fig.5. Spatial data (A) Ovitrap locations with unique identification symbols for each trap. Total mosquito abundance, during the study period, by trap height
as function of (B) relative humidity, (C) ovitrap water temperature, (D) ovitrap water volume, and (E) ovitrap water pH. Mosquito persistence, during the study
period, by trap height as function of (F) relative humidity, (G) ovitrap water temperature, (H) ovitrap water volume, and (I) ovitrap water pH. In panels (B) to (I)
data from different ovitrap heights are codedas presented in the inset legend of panel (B).
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8
also predominant at 75cm, and was the only other species we found
when incidentally sampling phytotelmata near the ovitraps. Ae. spi-
nosus was present in the leaf axils of a common Araceae at the study
site, and more generally, Ae. spinosus is known to be associated with
epiphytic bromeliads at altitudes above 1,200 m above the sea level
in Panamá and Costa Rica (Berlin 1969). Ae. spinosus also belongs
to the subgenus Howardina, a taxon where little is known about its
medical importance, without any circumstantial evidence, at least
to the best of our knowledge, supporting a role in pathogen trans-
mission (Berlin 1969), other that infections with Plasmodium spp.
malaria parasites in the thorax of Aedes quadrivittatus (Coquillet)
(Abella-Medrano etal. 2018).
The phenology of the mosquito taxa we collected suggests that
rainfall likely plays a major role regulating mosquito populations
at our study site given that all species, with the exception of Cx.
nigripalpus, were only collected during the rainy season. Also the
nding of Cx. nigripalpus during the dry season occurred after an
unusual rain event, a phenomenon observed for this mosquito in
North America (Day and Edman 1988, Day and Curtis 1989, Day
et al. 1990, Day and Curtis 1999), which further highlights the
importance of rainfall for the phenology of mosquitoes sampled
with ovitraps at the study site. As shown by our analysis, the per-
sistence and abundance of mosquitoes in the ovitraps above 75cm
was favored by high temperatures, and mosquito persistence was
favored by water accumulation in the ovitraps, something that might
reect the importance of oviposition site availability for the species
we collected, as observed for several mosquito species (Day etal.
1990, Takagi etal. 1995, Edman etal. 1998, Harrington etal. 2008,
Chaves and Kitron 2011, Nguyen et al. 2012). We also found that
across a trend of decreasing pH, mosquitoes were more likely to
be abundant and persistent when the pH was more basic, and with
a long delay, suggesting that the mosquito species we collected are
selective with their oviposition (Mangel 1987, Mangel and Heimpel
1998, Spencer etal. 2002).
Finally, our results highlight the need to better study mosquito
fauna at TMCFs as these ecosystems are likely to undergo signicant
changes in response to global warming (Foster 2001). It is impor-
tant to assess mosquito diversity using several sampling tools (Hoshi
et al. 2014b) to better assess mosquito diversity in the TMCF of
FSFA, and to assess patterns of interannual mosquito abundance
and persistence variability modulated by phenomena like El Niño
Southern Oscillation (Chaves et al. 2014), unusual weather pat-
terns (Chaves etal. 2014) and long-term landscape transformation
(Chaves 2016). In that sense, this study provides baseline data for a
reproducible long-term evaluation of changes in mosquito species
richness and diversity at TMCFs. The presence of Cx. nigripalpus
(Day and Curtis 1994) at the study site highlights the need for arbo-
virus transmission surveillance, especially as temperatures keep rais-
ing, enabling the transmission of mosquito-borne pathogens at the
study site and the whole Vázquez de Coronado county. Our results
also encourage the use of samples like ours for the development of
DNA barcode libraries, especially thinking in the large proportion of
damaged specimens, up to 30% of the collected samples (Morrison
etal. 2008, Torres etal. 2017), that cannot be identied to the spe-
cies level in epidemiological studies sampling adult mosquitoes to
isolate and quantify pathogen infection in tropical settings.
SupplementaryData
Supplementary data are available at Journal of Medical Entomology
online.
Acknowledgments
We thank Francisco Romero and Cecilia Vega for granting access to ‘Finca
San Francisco de Asis’. Laura Ríos occasionally helped with the mosquito col-
lections and Aryana Zardkoohi provided feedback on this manuscript. This
study was partially funded by Sumitomo Foundation grant 153107 to L.F.C.
ReferencesCited
Abella-Medrano, C. A., S.Ibáñez-Bernal, I.MacGregor-Fors, and D.Santiago-
Alarcon. 2015. Spatiotemporal variation of mosquito diversity (Diptera:
Culicidae) at places with different land-use types within a neotropical
montane cloud forest matrix. Parasit. Vectors. 8: 487.
Abella-Medrano, C. A., S.Ibáñez-Bernal, P.Carbó-Ramírez, and D.Santiago-
Alarcon. 2018. Blood-meal preferences and avian malaria detection in
mosquitoes (Diptera: Culicidae) captured at different land use types within
a neotropical montane cloud forest matrix. Parasitol. Int. 67: 313–320.
Alencar, J., C. F.Mello, L. S.Barbosa, H. R.Gil-Santana, D.d. E. A.Maia,
C. B.Marcondes, and J.d.O. S.S.Silva. 2016. Diversity of yellow fever
mosquito vectors in the Atlantic Forest of Rio de Janeiro, Brazil. Rev. Soc.
Bras. Med. Trop. 49: 351–356.
Barker, C. M., B. G.Bolling, W. C.Black, IV, C. G.Moore, and L.Eisen. 2009.
Mosquitoes and West Nile virus along a river corridor from prairie to
montane habitats in eastern Colorado. J. Vector Ecol. 34: 276–293.
Berlin, O. G.W. 1969. Mosquito studies (Diptera, Culicidae) XII a revision
of the neotropical subgenus Howardina of Aedes. Contrib. Am. Entomol.
Inst. (Ann Arbor) 4: 1–190.
Bonilla-Carrion, R., and L.Rosero-Bixby. 2004. Presión demográca sobre
los bosques y áreas protegidas, Costa Rica 2000, pp. 575–594. In L.
Rosero-Bixby (ed.), Costa Rica a la luz del censo del 2000. Centro
Centroamericano de Población, San José, Costa Rica.
Bruijnzeel, L., M.Kappelle, M.Mulligan, and F.Scatena. 2010. Tropical mon-
tane cloud forests: state of knowledge and sustainability perspectives in a
changing world. Tropical montane cloud forests. Science for Conservation
and Management, Cambridge University Press, Cambridge, UK.
Burkett-Cadena, N., S. P.Graham, and L. A.Giovanetto. 2013. Resting envi-
ronments of some Costa Rican mosquitoes. J. Vector Ecol. 38: 12–19.
Calderón Arguedas, O., A. Troyo, A. Avendaño, and M. Gutiérrez. 2012.
Aedes albopictus (Skuse) en la región Huetar Atlántica de Costa Rica.
Revista Costarricense de Salud Pública 21: 76–80.
Calderón-Arguedas, O., A. Troyo, R. D. Moreira-Soto, R. Marín, and
L.Taylor. 2015. Dengue viruses in Aedes albopictus Skuse from a pineap-
ple plantation in Costa Rica. J. Vector Ecol. 40: 184–186.
Carrington, L. B., M. V. Armijos, L. Lambrechts, and T. W.Scott. 2013a.
Fluctuations at a low mean temperature accelerate dengue virus transmis-
sion by Aedes aegypti. Plos Neglect. Trop. Dis. 7: 8.
Carrington, L. B., S. N.Seifert, M. V.Armijos, L.Lambrechts, and T. W.Scott.
2013b. Reduction of Aedes aegypti vector competence for dengue virus
under large temperature uctuations. Am. J.Trop. Med. Hyg. 88: 689–697.
Chaverri, L. G., C.Dillenbeck, D.Lewis, C. Rivera, L. M.Romero, and L.
F. Chaves. 2018. Mosquito species (Diptera: Culicidae) diversity from
ovitraps in a Mesoamerican tropical rainforest. J. Med. Entomol. 55:
646–653.
Chaves, L. F. 2016. Globally invasive, withdrawing at home: Aedes albop-
ictus and Aedes japonicus facing the rise of Aedes avopictus. Int.
J.Biometeorol. 60: 1727–1738.
Chaves, L. F. 2017a. Climate change and the biology of insect vectors of human
pathogens, pp. 126–147. In S.Johnson and H. Jones (eds.), Invertebrates
and global climate change. Wiley, Chichester, United Kingdom.
Chaves, L. F. 2017b. Mosquito species (Diptera: Culicidae) persistence and
synchrony across an urban altitudinal gradient. J. Med. Entomol. 54:
329–339.
Chaves, L. F., and N.Añez. 2016. Nestedness patterns of sand y (Diptera:
Psychodidae) species in a neotropical semi-arid environment. Acta Trop.
153: 7–13.
Chaves, L. F., and U. D.Kitron. 2011. Weather variability impacts on oviposi-
tion dynamics of the southern house mosquito at intermediate time scales.
Bull. Entomol. Res. 101: 633–641.
Journal of Medical Entomology, 2018, Vol. XX, No. XX
Copyedited by: OUP
Downloaded from https://academic.oup.com/jme/advance-article-abstract/doi/10.1093/jme/tjy170/5114623 by ESA Member Access, Luis Chaves on 04 October 2018

9
Chaves, L. F., and K.Moji. 2018. Density dependence, landscape, and weather
impacts on aquatic Aedes japonicus japonicus (Diptera: Culicidae) abun-
dance along an urban altitudinal gradient. J. Med. Entomol. 55: 329–341.
Chaves, L. F., G. L.Hamer, E. D.Walker, W. M.Brown, M. O.Ruiz, and U.
D.Kitron. 2011. Climatic variability and landscape heterogeneity impact
urban mosquito diversity and vector abundance and infection. Ecosphere
2: art70.
Chaves, L. F., J. E.Calzada, A.Valderrama, and A.Saldaña. 2014. Cutaneous
leishmaniasis and sand y uctuations are associated with El Niño in
Panamá. Plos Negl. Trop. Dis. 8: e3210.
Chaves, L. F., N. Imanishi, and T. Hoshi. 2015. Population dynamics of
Armigeres subalbatus (Diptera: Culicidae) across a temperate altitudinal
gradient. Bull. Entomol. Res. 105: 589–597.
Cleveland, W. S., and S. J.Devlin. 1988. Locally weighted regression: an
approach to regression analysis by local tting. J. Am. Stat. Assoc. 83:
596–610.
Darsie Jr, R. F. 1993. Keys to the mosquitoes of Costa Rica (Diptera:
Culicidae). International Center for Disease Control, University of South
Carolina, Columbia, SC.
Day, J. F., and G. A. Curtis. 1989. Inuence of rainfall on Culex nigripal-
pus (Diptera: Culicidae) blood feeding behavior in Indian river County,
Florida. Ann. Entomol. Soc. Am. 82: 32–37.
Day, J. F., and G. A.Curtis. 1994. When it rains they soar - and that makes
Culex nigripalpus a dangerous mosquito. Am Entomologist 40: 162–167.
Day, J. F., and G. A.Curtis. 1999. Blood feeding and oviposition by Culex
nigripalpus (Diptera: Culicidae) before, during, and after a widespread
St. Louis encephalitis virus epidemic in Florida. J. Med. Entomol. 36:
176–181.
Day, J. F., and J. D.Edman. 1988. Host Location, blood-feeding, and oviposoi-
tion behavior of Culex nigripalpus (Diptera: Culicidae): their inuence on
St. Louis encephalitis virus transmission in southern Florida, pp. 1–8. In
T. W.Scott and J. Grumstrup-Scott (eds.), Proceedings of a Symposium:
The Role of vector-host interactions in disease tranmission. Entomological
Society of America, Washington, DC.
Day, J. F., G. A.Curtis, and J. D.Edman. 1990. Rainfall-directed oviposition
behavior of Culex nigripalpus (Diptera: Culicidae) and its inuence on St.
Louis encephalitis virus transmission in Indian River County, Florida. J.
Med. Entomol. 27: 43–50.
Day, J. F., W. J.Tabachnick, and C. T.Smartt. 2015. Factors that inuence the
transmission of West Nile Virus in Florida. J. Med. Entomol. 52: 743–754.
Dohm, D. J., M. L.O’Guinn, and M. J.Turell. 2002. Effect of environmental
temperature on the ability of Culex pipiens (Diptera: Culicidae) to trans-
mit West Nile virus. J. Med. Entomol. 39: 221–225.
Downs, W. G., T. H.Aitken, and L.Spence. 1959. Eastern equine encephalitis
virus isolated from Culex nigripalpus in Trinidad. Science. 130: 1471.
Edman, J. D., and D. J.Taylor. 1968. Culex nigripalpus: seasonal shift in the
bird-mammal feeding ratio in a mosquito vector of human encephalitis.
Science. 161: 67–68.
Edman, J. D., T. W.Scott, A.Costero, A. C.Morrison, L. C.Harrington, and
G. G.Clark. 1998. Aedes aegypti (Diptera: Culicidae) movement inu-
enced by availability of oviposition sites. J. Med. Entomol. 35: 578–583.
Eisen, L., B. G. Bolling, C. D. Blair, B. J. Beaty, and C. G.Moore. 2008.
Mosquito species richness, composition, and abundance along habitat-
climate-elevation gradients in the northern Colorado Front Range. J. Med.
Entomol. 45: 800–811.
Faraway, J. J. 2006. Extending the linear model with R: generalized linear,
mixed effects and nonparametric regression models. CRC Press, Boca
Raton, FL.
Foley, D. H., L. M.Rueda, and R. C. Wilkerson. 2007. Insight into global
mosquito biogeography from country species records. J. Med. Entomol.
44: 554–567.
Forrester, D. J., J. K.Nayar, and G. W.Foster. 1980. Culex nigripalpus: a nat-
ural vector of wild turkey malaria (Plasmodium hermani) in Florida. J.
Wildl. Dis. 16: 391–394.
Foster, P. 2001. The potential negative impacts of global climate change on
tropical montane cloud forests. Earth-Sci. Rev. 55: 73–106.
Futami, K., A.Valderrama, M.Baldi, N.Minakawa, R.Marín Rodríguez, and
L. F.Chaves. 2015. New and common haplotypes shape genetic diversity
in Asian tiger mosquito populations from Costa Rica and Panamá. J. Econ.
Entomol. 108: 761–768.
Galindo, P., and F. S.Blanton. 1954. Nine new species of neotropical Culex,
eight from Panama and one from Honduras (Diptera, Culicidae). Ann.
Entomol. Soc. Am. 47: 231–247.
Galindo, P., S. J. Carpenter, and H. Trapido. 1955. A contribution to the
ecology and biology of tree hole breeding mosquitoes of Panama. Ann.
Entomol. Soc. Am. 48: 158–164.
Gilbert, B., D. S.Srivastava, and K. R.Kirby. 2008. Niche partitioning at mul-
tiple scales facilitates coexistence among mosquito larvae. Oikos 117:
944–950.
Harrington, L. C., A.Ponlawat, J. D.Edman, T. W.Scott, and F.Vermeylen.
2008. Inuence of container size, location, and time of day on oviposition
patterns of the dengue vector, Aedes aegypti, in Thailand. Vector Borne
Zoonotic Dis. 8: 415–423.
Heinemann, S., and J. N. Belkin. 1977. Collection records of the project
“Mosquitoes of Middle America” 7. Costa Rica (CR). Mosq. Syst. 9:
237–287.
Herrera, W. 2016. Climate of Costa Rica, pp. 19–29. In M. Kappelle (ed.),
Costa Rican ecosystems. University of Chicago Press, Chicago, IL.
Hoshi, T., Y.Higa, and L. F.Chaves. 2014a. Uranotaenia novobscura ryukyu-
ana (Diptera: Culicidae) population dynamics are denso-dependent and
autonomous from weather uctuations. Ann. Entomol. Soc. Am. 107:
136–142.
Hoshi, T., N.Imanishi, Y.Higa, and L. F.Chaves. 2014b. Mosquito biodi-
versity patterns around urban environments in South-central Okinawa
Island, Japan. J. Am. Mosq. Control Assoc. 30: 260–267.
Hoshi, T., N.Imanishi, K.Moji, and L. F.Chaves. 2017. Density dependence
in a seasonal time series of the bamboo mosquito, Tripteroides bambusa
(Diptera: Culicidae). The Canadian Entomologist 149: 338–344.
Hribar, L. J. 2007. Larval habitats of potential mosquito vectors of West Nile
virus in the Florida Keys. J. Water Health 5: 97–100.
Hribar, L. J., J. J.Vlach, D. J.DeMay, S. S.James, J. S.Fahey, and E. M.Fussell.
2004. Mosquito larvae (Culicidae) and other Diptera associated with con-
tainers, storm drains, and sewage treatment plants in the Florida Keys,
Monroe County, Florida. Fla. Entomol. 87: 199–203.
Inácio, C. L. S., J. H. T.da Silva, R. C. D. M. Freire, R. A. Gama, C.
B.Marcondes, and M. D.F. F. D. M.Ximenes. 2017. Checklist of mos-
quito species (Diptera: Culicidae) in the Rio Grande do Norte State,
Brazil—contribution of entomological surveillance. J. Med. Entomol. 54:
763–773.
Kappelle, M. 2016. Costa Rica’s ecosystems: setting the stage, pp. 3–18. In
M. Kappelle (ed.), Costa Rican ecosystems. University of Chicago Press,
Chicago, IL.
Kumm, H. W., and S. H.Ruiz. 1939. A malaria survey of the Republic of Costa
Rica, Central America. Am. J.Trop. Med. Hyg. 19 (s1): 425–445.
Kumm, H. W., W. H.W.Komp, and H.Ruiz. 1940. The mosquitoes of Costa
Rica. Am. J.Trop. Med. Hyg. 1: 385–422.
Lozano-Fuentes, S., C. Welsh-Rodriguez, M. H.Hayden, B.Tapia-Santos,
C.Ochoa-Martinez, K. C.Kobylinski, C. K.Uejio, E.Zielinski-Gutierrez,
L. D.Monache, A. J.Monaghan, etal. 2012a. Aedes (Ochlerotatus) epac-
tius along an elevation and climate gradient in Veracruz and Puebla States,
México. J. Med. Entomol. 49: 1244–1253.
Lozano-Fuentes, S., M. H.Hayden, C.Welsh-Rodriguez, C.Ochoa-Martinez,
B.Tapia-Santos, K. C.Kobylinski, C. K.Uejio, E.Zielinski-Gutierrez, L.
D.Monache, A. J.Monaghan, etal. 2012b. The dengue virus mosquito
vector Aedes aegypti at high elevation in Mexico. Am. J.Trop. Med. Hyg.
87: 902–909.
Mangel, M. 1987. Oviposition site selection and clutch size in insects. J. Math.
Biol. 25: 1–22.
Mangel, M., and G. E.Heimpel. 1998. Reproductive senescence and dynamic
oviposition behaviour in insects. Evol. Ecol. 12: 871–879.
Marín, R., M. del Carmen Marquetti, Y. Álvarez, J. M. Gutiérrez, and
R.González. 2009. Especies de mosquitos (Diptera: Culicidae) y sus sitios
de cría en la región Huetar Atlántica, Costa Rica. Revista Biomédica 20:
15–23.
Marques, T. C., B. P. Bourke, G. Z. Laporta, and M. A. Sallum. 2012.
Mosquito (Diptera: Culicidae) assemblages associated with Nidularium
Journal of Medical Entomology, 2018, Vol. XX, No. XX
Copyedited by: OUP
Downloaded from https://academic.oup.com/jme/advance-article-abstract/doi/10.1093/jme/tjy170/5114623 by ESA Member Access, Luis Chaves on 04 October 2018

10
and Vriesea bromeliads in Serra do March, Atlantic Forest, Brazil. Parasit.
Vectors. 5: 41.
Mendez, W., J. Liria, J. C.Navarro, C. Z.Garcia, J. E.Freier, R.Salas, S.
C.Weaver, and R.Barrera. 2001. Spatial dispersion of adult mosquitoes
(Diptera: Culicidae) in a sylvatic focus of Venezuelan Equine Encephalitis
virus. J. Med. Entomol. 38: 813–821.
Meza, T., and H.Bonilla. 1990. Areas naturales protegidas de Costa Rica, Ed.
Tecnológica de Costa Rica, Cartago, Costa Rica.
Mittermeier, R. A., N.Myers, J. B.Thomsen, G. A.Da Fonseca, and S.Olivieri.
1998. Biodiversity hotspots and major tropical wilderness areas:
approaches to setting conservation priorities. Conserv. Biol. 12: 516–520.
Moriya, K. 1974. Seasonal trends of eld population of mosquitoes with
ovitrap in Kanagawa prefecture: 1) Comparison of the populations of
four residental areas in Kamakura City in 1971. Jpn. J.Sanit. Zool. 25:
237–244.
Morrison, A. C., B. M.Forshey, D.Notyce, H.Astete, V.Lopez, C.Rocha,
R.Carrion, C.Carey, D.Eza, J. M.Montgomery, etal. 2008. Venezuelan
equine encephalitis virus in Iquitos, Peru: urban transmission of a sylvatic
strain. Plos Negl. Trop. Dis. 2: e349.
Motta, M. A., R.Lourenço-de-Oliveira, and M. A.M.Sallum. 2012. Phylogeny
of genus Wyeomyia (Diptera: Culicidae) inferred from morphological and
allozyme data. The Canadian Entomologist 139: 591–627.
Müller, G. A., E. F. Kuwabara, J. E.Duque, M. A.Navarro-Silva, and C.
B.Marcondes. 2008. New records of mosquito species (Diptera: Culicidae)
for Santa Catarina and Paraná (Brazil). Biota Neotropica 8.
Müller, G. A., M. J.Marchi, and C. B.Marcondes. 2014. Mosquito imma-
tures in bamboo internodes in eastern Santa Catarina State, South Brazil
(Diptera: Culicidae). Biotemas 27: 151–154.
Myers, N., R. A. Mittermeier, C. G. Mittermeier, G. A.da Fonseca, and
J. Kent. 2000. Biodiversity hotspots for conservation priorities. Nature
403: 853–858.
Nguyen, A. T., A. J.Williams-Newkirk, U. D.Kitron, and L. F.Chaves. 2012.
Seasonal weather, nutrients, and conspecic presence impacts on the
southern house mosquito oviposition dynamics in combined sewage over-
ows. J. Med. Entomol. 49: 1328–1338.
Núñez, S. 1926. The occurrence and non-occurrence of certain diseases in
Costa Rica1. Am. J.Trop. Med. Hyg. 6 (s1): 347–356.
Paniagua, F., J. L. Garcés, C. Granados, A. Zúñiga, M. Ramírez, and
L.Jimenez. 1983. Prevalence of bancroftian lariasis in the city of Puerto
Limón and the province of Limón, Costa Rica. Am. J.Trop. Med. Hyg.
32: 1294–1297.
Parker, D. M., T. J.Zavortink, T. J.Billo, U.Valdez, and J. S.Edwards. 2012.
Mosquitoes and other arthropod macro fauna associated with tank bro-
meliads in a Peruvian cloud forest. J. Am. Mosq. Control Assoc. 28: 45–46.
Perfecto, I., and J.Vandermeer. 2008. Biodiversity conservation in tropical
agroecosystems - a new conservation paradigm. Ann. N. Y. Acad. Sci.
1134: 173–200.
Ponce-Reyes, R., V.-H. Reynoso-Rosales, J. E. Watson, J. VanDerWal, R.
A.Fuller, R. L.Pressey, and H. P.Possingham. 2012. Vulnerability of cloud
forest reserves in Mexico to climate change. Nat. Clim. Change 2: 448.
Reisen, W. K., K. Boyce, R. C. Cummings, O. Delgado, A. Gutierrez, R.
P.Meyer, and T. W.Scott. 1999. Comparative effectiveness of three adult
mosquito sampling methods in habitats representative of four different
biomes of California. J. Am. Mosq. Control Assoc. 15: 24–31.
Ritchie, S. A., S.Long, A.Hart, C. E.Webb, and R. C.Russell. 2003. An adul-
ticidal sticky ovitrap for sampling container-breeding mosquitoes. J. Am.
Mosq. Control Assoc. 19: 235–242.
Rodríguez Argüello, P. K. 2010. Historia del cantón Vázquez de Coronado.
Editorial Izcandé, San José, Costa Rica.
Romero, A., and A.Trejos. 1954. Clinica y laboratorio de la ebre amarilla en
Costa Rica. Revista de Biología Tropical 2: 113–168.
Rutledge, C. R., J. F.Day, C. C.Lord, L. M.Stark, and W. J.Tabachnick. 2003.
West Nile virus infection rates in Culex nigripalpus (Diptera: Culicidae)
do not reect transmission rates in Florida. J. Med. Entomol. 40: 253–258.
Sáenz, R., R. A.Bissell, and F.Paniagua. 2012. Post-disaster malaria in Costa
Rica. Prehosp. Disaster Med. 10: 154–160.
Seifert, R. P. 1980. Mosquito Fauna of Heliconia aurea. J. Anim. Ecol. 49:
687–697.
Seifert, R. P., and R. Barrera. 1981. Cohort studies on mosquito (Diptera:
Culicidae) larvae living in the water‐lled oral bracts of Heliconia aurea
(Zingiberales: Musaceae). Ecol. Entomol. 6: 191–197.
Shumway, R. H., and D. S.Stoffer. 2011. Time series analysis and its applica-
tions, 3rd ed. Springer, New York, NY.
Silva, S. O.F., C.Ferreira de Mello, R.Figueiró, D.de Aguiar Maia, and
J.Alencar. 2018. Distribution of the mosquito communities (Diptera:
Culicidae) in oviposition traps introduced into the Atlantic Forest in
the State of Rio de Janeiro, Brazil. Vector Borne Zoonotic Dis. 18:
214–221.
Silver, J. B. 2008. Mosquito ecology: eld sampling methods, 3rd ed. Springer,
New York, NY.
Soto-Garita, C., T.Somogyi, A.Vicente-Santos, and E.Corrales-Aguilar. 2016.
Molecular characterization of two major dengue outbreaks in Costa Rica.
Am. J.Trop. Med. Hyg. 95: 201–205.
Spencer, M., L.Blaustein, and J. E.Cohen. 2002. Oviposition habitat selection
by mosquitoes (Culiseta longiareolata) and consequences for population
size. Ecology 83: 669–679.
Takagi, M., Y. Tsuda, and Y.Wada. 1995. Movement and oviposition of
released Aedes albopictus (Diptera: Culicidae) in Nagasaki, Japan. Jpn.
J.Sanit. Zool. 46: 131–138.
Toma, T., and I.Miyagi. 1981. Notes on the mosquitoes collected at forest
areas in the northern part of Okinawajima, Ryukyu Islands, Japan. Jpn.
J.Sanit. Zool. 32: 271–279.
Torres, R., R. Samudio, J. P.Carrera, J.Young, R. Márquez, L. Hurtado,
S.Weaver, L. F.Chaves, R.Tesh, and L.Cáceres. 2017. Enzootic mosquito
vector species at equine encephalitis transmission foci in the República de
Panamá. PLoS One 12: e0185491.
Turell, M. J., M. R.Sardelis, D. J.Dohm, and M. L.O’Guinn. 2001. Potential
North American vectors of West Nile virus. Ann. N. Y. Acad. Sci. 951:
317–324.
Turell, M. J., M. L.O’Guinn, J. W.Jones, M. R.Sardelis, D. J.Dohm, D.
M.Watts, R.Fernandez, A.Travassos da Rosa, H.Guzman, R.Tesh,
et al. 2005. Isolation of viruses from mosquitoes (Diptera: Culicidae)
collected in the Amazon Basin region of Peru. J. Med. Entomol. 42:
891–898.
Valencia, J. D. 1973. Mosquito studies (Diptera, Culicidae) XXI. Arevision of
the subgenus Carrollia of Culex. Contrib Am Entomol Inst (Ann Arbor)
9: 1–138.
Vargas, G. 2006. Geografía de Costa Rica. EUNED, San Pedro de Montes de
Oca, Costa Rica.
Vitek, C. J., S. L.Richards, C. N.Mores, J. F.Day, and C. C.Lord. 2008.
Arbovirus transmission by Culex nigripalpus in Florida, 2005. J. Med.
Entomol. 45: 483–493.
Warren, M., W. E.Collins, G. M.Jeffery, and J. C.Skinner. 1975. The seroepi-
demiology of malaria in Middle America. II. Studies on the Pacic coast of
Costa Rica. Am. J.Trop. Med. Hyg. 24: 749–754.
Weinstock, H., F. Paniagua, J. L. Garcés, A. Zúñiga, C. Granados, and
E.Hernández. 1977. Bancroftian lariasis in Puerto Limón, Costa Rica.
Am. J.Trop. Med. Hyg. 26: 1148–1152.
Zar, J. H. 1998. Biostatistical analysis. Prentice Hall, San Francisco, CA.
Zea Iriarte, W. L., Y.Tsuda, Y.Wada, and M.Takagi. 1991. Distribution of
mosquitoes on a hill of Nagasaki city, with emphasis to the distance from
human dwellings. Trop. Med. 33: 55–60.
Journal of Medical Entomology, 2018, Vol. XX, No. XX
Copyedited by: OUP
Downloaded from https://academic.oup.com/jme/advance-article-abstract/doi/10.1093/jme/tjy170/5114623 by ESA Member Access, Luis Chaves on 04 October 2018