Here we present the first in a series of articles about the ecology of immature stages of anophelines in the Brazilian Yanomami area. We propose a new larval habitat classification and a new larval sampling methodology. We also report some preliminary results illustrating the applicability of the methodology based on data collected in the Brazilian Amazon rainforest in a longitudinal study of two remote Yanomami communities, Parafuri and Toototobi. In these areas, we mapped and classified 112 natural breeding habitats located in low-order river systems based on their association with river flood pulses, seasonality and exposure to sun. Our classification rendered seven types of larval habitats: lakes associated with the river, which are subdivided into oxbow lakes and nonoxbow lakes, flooded areas associated with the river, flooded areas not associated with the river, rainfall pools, small forest streams, medium forest streams and rivers. The methodology for larval sampling was based on the accurate quantification of the effective breeding area, taking into account the area of the perimeter and subtypes of microenvironments present per larval habitat type using a laser range finder and a small portable inflatable boat. The new classification and new sampling methodology proposed herein may be useful in vector control programs.
Here we present the first in a series of articles about the ecology of immature stages of anophelines in the Brazilian Yanomami area. We propose a new larval habitat classification and a new larval sampling methodology. We also report some preliminary results illustrating the applicability of the methodology based on data collected in the Brazilian Amazon rainforest in a longitudinal study of two remote Yanomami communities, Parafuri and Toototobi. In these areas, we mapped and classified 112 natural breeding habitats located in low-order river systems based on their association with river flood pulses, seasonality and exposure to sun. Our classification rendered seven types of larval habitats: lakes associated with the river, which are subdivided into oxbow lakes and nonoxbow lakes, flooded areas associated with the river, flooded areas not associated with the river, rainfall pools, small forest streams, medium forest streams and rivers. The methodology for larval sampling was based on the accurate quantification of the effective breeding area, taking into account the area of the perimeter and subtypes of microenvironments present per larval habitat type using a laser range finder and a small portable inflatable boat. The new classification and new sampling methodology proposed herein may be useful in vector control programs.
Nearly all malaria cases in Brazil are reported from the Amazon Region (99.8%), where
malaria remains a public health problem (Oliveira-Ferreira
et al. 2010). Between 2001-2013, an average of 392,600 malaria cases per year was
recorded in Brazil. Although there was a decreasing trend in the number of malaria cases
nationwide, from half a million annual cases during the 1990s to 130 thousand malaria cases
currently, highly focal hotspots of malaria transmission persist, especially for
Plasmodium vivax (de Pina-Costa et al.
2014). In 2011, approximately 10.6% of all malaria cases in the Amazon Region
were registered in indigenous areas, with higher incidences in certain states, such as
Amazonas (AM), where 49% of the cases were reported in indigenous villages (MS/ SVS 2013). Despite this critical malaria burden in
indigenous areas of the Amazon Region, few studies have reported in detail how malaria
transmission is sustained in these remote areas or the ecology of anopheline larvae in such
settings.In Brazil, Anopheles darlingi, Anopheles albitarsis s.l.
and Anopheles aquasalis are considered the main malaria vectors in
different areas of the Amazon Region. Anopheles nuneztovari s.l. and
Anopheles triannulatus s.l. also play a role in malaria transmission as
secondary or occasional vectors in some areas (Deane et al.
1948, 1986, Rosa-Freitas et al. 1998, Pimenta et al.
2015). Studies of anophelines in undisturbed and remote indigenous areas of the
Amazon rainforest are difficult to perform due to their location and restricted access to
these areas, which require the use of light aircrafts, boats and/or many walking hours to
reach them. This is the case of the Yanomami areas studied herein. The Yanomami are a
numerous, semi-isolated indigenous group living in the northern part of the Brazilian
Amazon and southern Venezuela (Pithan et al.
1991).For the ecological study of anopheline larvae, it is crucial to correctly identify and
classify the main breeding sites in the area and thus to monitor their dynamics over
time.Lakes along the floodplains of Amazonian white-water rivers, known
asvárzeas, have been classified by Junk
et al. (2012) into four types: scroll lakes (i.e., elongated lakes that are
narrow and mostly covered by aquatic macrophytes), oxbow lakes (OX) (originating from
abandoned river meanders with a horseshoe shape), depression lakes (located in floodplain
depressions) and upland ria-lakes (i.e., dendritic lakes formed in drowned valleys of
tributary rivers). OX may be connected in various degrees to the river and this connection
greatly influences the seasonal water quality and volume as well as the macrophyte and
invertebrate fauna composition (Mormul et al. 2013).
According to the Strahler (1957) stream order
classification, rivers are categorised based on a hierarchy of tributaries. The flood
pulse, defined as the pulsing events of a river discharge, has been proposed as the
principal driving force of biota dynamics in river-floodplain systems (Junk et al. 1989). Therefore, in the Amazonian rivers
and their tributaries, characteristics such as river order level and relation with flood
pulsing, river width and watercourse sinuosity will determine the abundance and
characteristics of the natural breeding habitats, the distribution of anopheline species
and their densities, and will thus influence local malaria patterns of transmission.In general, studies of anopheline larvae present difficulties related to the great
diversity of larval habitats used by anopheline females, some of which are difficult to
access (Rejmankova et al. 2013). Larval habitats of
the major African malaria vectors within the Anopheles gambiaespecies
complex, for example, are typically small, sunlit, temporary and with turbid waters. These
larval habitats are typically created as a result of human or animal activities and they
may be difficult to locate, especially during the wet season (Mutuku et al. 2006). However, within the Amazon Basin, some breeding
habitats may be relatively large (Deane et al. 1948)
and may present microhabitats. These large breeding habitats require specific tools to
cover all potential breeding microhabitats within their water body in order to avoid biased
sampling results.In this paper, we propose a comprehensive classification of larval habitats and present a
new methodology to investigate the natural breeding habitats of anopheline larvae in areas
of low-order rivers in the Brazilian Amazon. We also included some preliminary results
regarding the application of a new larval field methodology.
MATERIALS AND METHODS
Study area - We conducted a longitudinal study from January 2013-July
2014 in two remote Yanomami areas of Brazil, the communities of Parafuri (3º17’1.68”N
63º51’2.16”W, 440 m) and Toototobi (1º45’54.72”N 63º37’7.68”W, 128 m), which are located
in western state of Roraima (RR) and northern AM, respectively (Fig. 1). Parafuri and Toototobi are communities composed of six
and seven villages, respectively, and each village may comprise one big, circular,
central open hut (called a shabono) or by smaller and separated huts.
We selected four villages to study in each community based on malaria incidence and for
logistical reasons. In Parafuri and Toototobi, systematic ground surveys were conducted
at two-month intervals for 19 months; during each survey we performed anopheline
collections for 15 consecutive days. The Yanomami are the major indigenous ethnic group
living semi-isolated in an area of 192,000 km2, spanning the northern
Brazilian Amazon and adjacent areas of the southern of Venezuela (Fig. 1) (Pithan et al.
1991). The Parafuri and Toototobi communities occupy different ecological
areas, with diverse geomorphologic, hydrologic and larval habitat dynamics and with
different malaria vector species compositions and abundances. Parafuri is located in a
submontane tropical rainforest ecoregion. The submontane ecoregion of RR is located
exclusively inside the Yanomami reserve at 350-650 m in altitude, while Toototobi, which
is located 170 km south of Parafuri, lies in a lowland tropical rainforest ecoregion of
Amazon with a maximum of 150 m in altitude (Rosa-Freitas
et al. 2007).
Fig. 1
: Brazil, the states of Roraima and Amazonas, the Yanomami indigenous
communities, Parafuri and Toototobi.
Classification of anopheline breeding habitats - During fieldwork, we
observed that there were many different types of breeding habitats for which there
existed no classification that would fulfil our needs. Therefore, we classified the
breeding habitats where we collected anopheline larvae based on three main environmental
variables: seasonality (permanent or temporary), sun exposure (shadowed, partially or
fully exposed to the sun) and association with low-order river flood pulses (larval
habitats associated with large fluctuations in water river levels). All breeding
habitats were georeferenced. During the dry season, ponds in small and medium sized
forest streams of Toototobi were mapped and terrain data were acquired with a hand-held
global positioning system (GPS) (GPSMAP 78 s, Garmin®, USA). We also mapped
most forest streams in Toototobi, typically starting at the nearest point from each
Yanomami hut, following the watercourse in both the upstream and downstream directions
up to 1 km distance from the hut.Methodology of sampling of anopheline larvae in natural breeding habitats in the
Brazilian Amazon - In the two Yanomami communities, Parafuri and Toototobi,
systematic mosquito collections were conducted in each of the eight villages (4 in
Toototobi and 4 in Parafuri) and individuals were asked to note the location of known
water bodies within a 1 km range of the village. An initial sketch was made of the
location of each water body with respect to the village. Afterwards, all of the water
bodies were located with the help of a Yanomami guide and mapped by GPS; almost all
breeding habitats were surveyed and anopheline larvae were sampled.We carried out a pilot study in September 2012 in both Yanomami areas with the following
objectives: (i) to map all breeding habitats, (ii) to establish a local sampling
strategy according to time constraints for each village, (iii) to test the new sampling
larvae methodology for sampling larvae and refine possible pitfalls on-site and (iv) to
obtain a preliminary idea of the composition of anopheline fauna around the eight
Yanomami villages.We observed that only some microhabitats inside the breeding habitat were suitable for
anopheline immature stages to thrive and calculated the effective breeding area (EBA).
The EBA was defined as the area in m2 of a given breeding habitat that is
suitable for the occurrence of immature stages of Neotropical anophelines. One EBA unit
equals 1 m2. To calculate the EBA and sample the different breeding habitats,
we used a laser measurement tool (Laser Rangefinder Scout DX 1000 ARC,
Bushnell®, USA) and a small inflatable boat (Atlantic 200,
Nautika®, Brazil). The laser tool was able to accurately measure distances
under dense canopy and under low light conditions. One limitation of this technique is
that the laser tool cannot measure distances ≤ 5 m. Therefore, such short distances
needed to be visually estimated, which may lead to some measurement inaccuracies. Thus,
the EBA measurement technique may be less suitable for anopheline species that prefer to
thrive in very small water bodies.In the case of aquatic habitats with difficult access, where a part of the perimeter
could not be tracked and measured either on foot or by boat, we used a trigonometric
approach to calculate the total EBA of the perimeter (pEBA) (Fig. 2). pEBA of a larval habitat is the sum of all 1
m2 along its shoreline. Basically, two distances on each extreme of the
segment were calculated and we subsequently estimated the angle between both
measurements with a half circle protractor marked in degrees.
Fig. 2
: effective breeding area measurement. Schematic approach of how was
calculated difficult-to-walk-through breeding perimeter areas using a laser
measurement tool. D is calculated from the measurement of A + B and angle α1,
while E is calculated from B + C and angle α2.
The final distance of the unknown segment was calculated using equation 1.In the case of circular-shaped breeding habitats, after measuring the diameter with the
laser tool, we calculated the total perimeter EBA using equation 2.For large OX, we standardised accurate measurements by first measuring the perimeter
only on the external side of the lake (typically the more accessible side, either by
foot or by boat) and the width followed by an estimation of the internal perimeter of
the water body. We used EBA measurement mainly due to time constraints and accessibility
issues. EBA measurement was considered the most appropriate approach to calculate the
total perimeter of a determined oxbow lake on the field within our timetable. Each oxbow
lake was calculated following the same parameters in each survey. Equation 3 estimates
the internal perimeters of OX.where B = total internal perimeter, B1 = linear segments of internal
perimeter, B2 = curved segment of internal perimeter, C1 = linear
segment of external perimeter, C2 = curved segment of external perimeter and
A = width of the oxbow lake (Fig. 3).
Fig. 3
: schematic representation of the linear and curved segments of an oxbow
lake used to calculate the total perimeter effective breeding area.
If an oxbow lake presented a markedly irregular form, we applied the above approach but
fragmented the external perimeter into fewer subunits, each consisting of two linear and
one curved segments. Finally, for those OX that were nearly circular in shape, we
simplified the previous equation considering that C1 = 0, resulting in
equation 4.For breeding habitats where it was impossible to determine the EBA accurately, such as
the massive flooded areas not associated with the river (FANAR) during the peak of the
rainy season, we arbitrarily assigned a value of 500 m2 EBA to allow for
comparisons between areas and seasons. In the case of small forest streams (SFS) and
medium forest streams (MFS), microhabitats suitable for anopheline larvae are not
uniformly distributed along the water courses. In order to consider these types of water
bodies in the total EBA (tEBA) quantification per village, we also arbitrarily allocated
500 m2 EBA to those SFS and MFS that presented a substantial part of its
course within a 1 km radius of the Yanomami village hut. For those forest streams that
were shorter or situated distant from the village hut, we allocated 250 m2
EBA each. During the dry season, forest stream pools were accurately quantified if, when
summed, they comprised less than 500 m2 EBA, otherwise a maximum of 500
m2 of EBA was also assigned.Once the total pEBA was calculated per breeding site, we added 0%, 10%, 25% or 50% of
additional EBA in respect to the pEBA depending on whether we found no (0%), low (10%),
medium (25%) or high (50%) abundance of additional EBA other than the pEBA along the
water body margins. These additional EBA subtypes could be patches of floating debris,
clusters of submersed and emergent macrophytes or small terrain “islands” inside the
water body that could create additional “internal” perimeter-like EBA in addition to
those of the global perimeter of the water body shoreline. Adjusting for the additional
EBA, we obtained the tEBA for each larval habitat. In the case of lakes associated with
the river (LAR) where different subtypes of EBA were present, we quantified the EBA for
each of the EBA subtypes. During our pilot study in September 2012, we detected high
aggregation patterns of immature anopheline stages; some breeding sites were classified
as positive if the majority of its tEBA was sampled. Therefore, we established a rule to
try to sample the 50% of EBA for water bodies up to 200 m2 tEBA. From the
calculated tEBA, we determined the total number of dips. For example, if a larval
habitat computed 110 m2 of tEBA, we equally distributed 55 sampling points
along the breeding site. For breeding sites larger than 200 EBA units in m2
and for those whose size did not allow measurement, we established a maximum of 100
sampling points to cover as many possible different subtypes of EBA and water body
surfaces. If different subtypes of EBA were present, we uniformly distributed sampling
points in the different microhabitats (for example: 60 dippings in each EBA subtype).
For sampling, we used a 350 mL, 13 cm diameter dipper (BioQuip, USA) and two dippings
were conducted per EBA unit/m2/sampling point. The total number of larvae per
stage for each dip was recorded and all immature stages were kept in small plastic
tubes. The larvaes were later transferred to tubes with 80% ethanol for morphological
identification in the laboratory. Sampling based on tEBA was preferred to capturing by
units of time since there was different accessibility among breeding habitats, which
improved collection efficiency. The relative abundance of culicines and the total number
of predatory macroinvertebrates were recorded, along with different environmental
variables such as association with the river flood pulses, distance to the village huts,
degree of sunlight exposure, presence of macrophytes and filamentous algae, water
turbidity and movement. The following physicochemical variables were also evaluated: pH
and temperature (pH meter AK95, AKSO®, Brazil), salinity, total dissolved
salts and conductivity (conductivity meter AK50, AKSO®) and dissolved oxygen
(dissolved oxygen meter AK84, AKSO®). We estimated the degree of sun exposure
using three categories: shadowed (0-25%), partially sun-exposed (25-50% and 50-75%) and
sun-exposed (75-100%) breeding habitats. In other words, sun-exposed breeding habitats
had between 75% and 100% of their tEBA exposed to the sun during sunlight hours.
Shadowed breeding sites were typically under dense canopy and almost no sunlight reached
their water surface during the day. During each survey, all breeding habitats were
photographed and identified with a unique code and EBA subtypes that could be present
were highlighted.We conducted exploratory samplings in all of the three low-order rivers, including the
Toototobi River in the Toototobi area and the Inajá and Parima Rivers in the mountainous
area of Parafuri. River samplings were conducted up to 1 km down and upstream from each
Yanomami village in Parafuri and Toototobi. We looked for typical river anopheline
microhabitats such as riverbed sunlight pools, slow-flowing edges of the river with
emergent, submersed vegetation or filamentous algae and microdams. Microdams are
considered primary oviposition sites along rivers and have been defined as points of
natural blocking of the river/stream current typically by a fallen stump or bamboo
clumps with dense root systems that impede water flow and favour the accumulation of
floating debris, allowing anopheline larvae to thrive (Manguin et al. 1996, Barros et al.
2011, Rejmankova et al. 2013). For small
and MFS, we conducted our sampling in the areas in which we were most likely to find
anopheline immature stages, such as slow-flowing margins with emergent vegetation,
clusters of floating debris and other microhabitats of filamentous algae and submersed
macrophytes in those few spots in the dense forest where sunlight had access to the
water body surface.
RESULTS
Classification of anopheline natural breeding habitats in low-order rivers of
the Brazilian Amazon - Breeding habitats were categorised into seven types:
LAR, which are subdivided in OX and non-OX (NOX), flooded areas associated with the
river (FAAR), flooded areas not associated with the river (FANAR), rainfall pools (RP),
SFS, MFS and rivers (RIV) (Fig. 4).
Fig. 4
: classification of the different anophelines breeding habitats and their
association with low-order rivers found in the Yanomami area, Brazilian Amazon.
FAAR: flooded areas associated with the river; FANAR: flooded areas not
associated with the river; LAR: lakes associated with the river; MFS: medium
forest streams; NOX: nonoxbow lakes; OX: oxbow lakes; RIV: rivers; RP: rainfall
pools; SFS: small forest streams.
A detailed description of the classified breeding habitats follows:LAR - All anopheline breeding habitats located in the river floodplain
were directly associated with river levels fluctuations. This is because breeding
habitats get flooded when rivers overflow their banks; when flooding water recedes,
stagnant water remains in these habitats (Drago et al.
2008). LAR may undergo variable isolation phases during rainy and dry seasons,
which fluctuate in time between each flood pulse event. During the isolation phase,
other sources of water, such as smaller forest streams draining into the lake,
groundwater and rainfall, may maintain the lake. However, evaporation forces tend to
diminish the lake water volume (Lesack & Melack
1995). According to the shape, geomorphologic origin and abundance, LAR can be
further separated into OX and NOX lakes.OX - OX are LAR formed by old river paths and may have a U-shaped form.
U-shaped LAR were formed from the isolation of a river meander through erosion and
sedimentation forces along the river edges (Esteves
1998). OX sizes vary considerably depending on the old river path that was
isolated from the active river canal. The 17 OX sampled during January 2013-July 2014
were permanent even during the driest months of the year and were mostly partial or well
exposed to the sun. Two LANDSAT images illustrate different segments of the Parima River
that cross the Parafuri Yanomami area. Makabey village is located along a segment of the
river that is more meandering and thus presented a considerable number of OX, while
Xaruna village is located upstream along a river segment that did not present any
U-shaped LAR near the village (Fig. 5).
Fig. 5
: Makabey and Xaruna villages along the Parima River in Parafuri community
Yanomami indigenous area, Brazilian Amazon [LANDSAT images (MCTI 2011)].
Location of oxbow 1 and 2 of Makabey village where anopheline larvae were
detected. Oxbow 1 corresponds to a U-shaped lake associated with the river that
is fully connected to a small tributary of the Parima River, while oxbow 2 was
an old Parima River path well disconnected from the actual river course and
with very high abundance of emergent and submersed macrophytes. Only extreme
flood pulses from Parima River will feed the oxbow 2. Oxbow 3 was not sampled,
as it was located more than 1 km from the Yanomami huts. Within 1 km radius of
Xaruna no oxbow lake was found since the Parima River is less
meandering.
NOX lakes - NOX lakes are non-U-shaped LAR permanent aquatic habitats
and are typically partially or well exposed to the sun. NOX were generally smaller than
OX. We classified small bodies of water ≤ 200 m2 as NOX based on water
permanence and the association with river fluctuations. NOX lakes are not derived from
the old river path and thus lack a clear U-shaped form. NOX lakes may be more important
in regions of larger rivers where typical U-shaped LARs are less commonly found (Junk 2005). LAR are likely to play a major role in
the local malaria transmission patterns, as LAR are important breeding habitats for some
of the main Amazonian malaria vectors.FAAR - FAAR are temporary breeding habitats where the main source of
water comes from the river flood pulses. FAAR may have highly variable sizes and
different levels of exposure to the sun. River flooding occurs frequently during the
rainy season, though a few unpredictable flood pulses that lead to short floodplain
inundations may also occur during the dry season months in low-order river systems
(Junk et al. 2011). FAAR are a common type of
breeding habitat found in Parafuri and Toototobi and because of their variable sun
exposure characteristics, FAAR seasonally amplify a wide range of different anopheline
species. As in the case of LAR, the place where the river feeds each of the identified
FAAR was identified. As FAAR remain dry for many months, we did not find submersed
macrophytes in these water bodies, but in cases where there was plentiful sun exposure,
filamentous algae proliferated.FANAR - FANAR are typically shadowed water bodies that are far and
disconnected from the rivers. The origin of FANAR is related to increased rainfall
during the wettest months of the year. FANAR sizes varied from vast areas in the peak of
the rainy season to mostly dried spots during the driest months of the year. Most FANAR
in the Yanomami area were seasonal and did not present submersed macrophytes or
filamentous algae. Anopheline species that prefer fully shadowed breeding habitats are
expected to predominate in FANAR.RP - RP are temporary breeding habitats occurring in shallow,
well-defined and typically small depressions in the forest soil that depend on rainfall
to be filled. RP presented some similarities with FANAR as they are not associated with
river flood pulses and are typically shadowed. However, RP are more ephemeral breeding
sites than FANAR. In the Yanomami area RP were found to be located inside the preserved
forest. RP exposed to the sun were also found after deforestation due to crop growing
near the Yanomami huts. Like FANAR, anopheline species that prefer shadowed breeding
habitats are expected to prevail in RP.SFS - SFS are forest stream breeding habitats of ≤ 5 m of width that
are typically shadowed. They are present in drained forested areas near the closest
river or a bigger forest stream. Many SFS interconnect with other types of breeding
habitats. For example, a distant FANAR may be connected through an SFS to an FAAR that
receives water directly from the river flood pulses. Most SFS dry out towards the middle
of the dry season. SFS tend to gradually change into ponds earlier during the dry
season, potentially increasing anopheline densities of certain species during this
period.MFS - MFS are forest stream breeding habitats of 5-10 m in width that
are almost always shadowed. They are present in drained forested areas near the closest
river. In the submontane rainforest area of Parafuri, most forest streams, independent
of their size, had a current flow, even during the driest months of the year. MFS form
ponds more frequently through the mid-end of the dry season. Depending on the water flow
and the amount of ponds formed by MFS, different anopheline species will be
favoured.RIV - All rivers located in the Yanomami study area can be classified
as low-order rivers (Junk et al. 2011). We
further subdivided low-order rivers into small (5-15 m width), medium (15-100 m width)
and large rivers (≥ 100 m width). Sizes and widths of LAR, especially for the OX, follow
RIV sizes. Characteristics of large Amazon rivers differ from smaller rivers, which
affects the dynamics of potential associated natural breeding sites for
Anopheles. We present an example of each type of breeding site
surveyed in Fig. 6.
Fig. 6
: natural anopheline breeding habitats in the Brazilian Amazon. A: U-shaped
lakes associated with the river (LAR) or oxbow lake. ManyAnopheles
darlingi larvae were collected from submersed macrophytes-effective
breeding area (EBA) using the small inflatable boat, a spot otherwise
inaccessible on foot near Komomassipe village, Parafuri; B: non-U-shaped LAR
with circular shape. As many oxbow lakes, they are permanent and well exposed
to the sun; C: flooded area associated with the river, shallow and temporal
breeding habitat. In this case, well exposed to the sun and with abundant
additional emergent vegetation-EBA. This breeding site would correspond to the
type that we would increase by 25% the EBA of the perimeter to obtain the total
EBA. Anopheles mattogrossensis, Anopheles triannulatus s.s.
and Anopheles oswaldoi s.l. were retrieved in high numbers
from this site; D: flooded area not associated with the river, fully shadowed
breeding site. A potential larval habitat for An. oswaldoi
s.l., Anopheles intermedius/Anopheles guarao-like
and Anopheles costai-like, Apiahik village, Toototobi; E:
rainfall pools, very ephemeral larval habitat, these ones were exposed to sun
after forest clearance for crop cultivation and yielded many An.
darlingi larvae, Komomassipe area; F, G: example of small (< 5 m
wide) and medium (5-10 m wide) forest streams, respectively; H, I: medium-sized
Inaja River in the hilly Parafuri area and Toototobi River, respectively. No
Anopheles larvae were retrieved from these low-order
rivers.
Anopheline natural breeding habitat classification in the Yanomami area studied
- During the 19 month longitudinal study in the Brazilian Yanomami area, 112
breeding sites were located, classified and sampled whenever water was present. The
number of each breeding habitat type encountered in the two communities was compiled in
the Table. We sampled 30 FANAR (26.8% of the
total larval habitats), constituting the most abundant type of water body. The second
most abundant larval habitat was LAR and we included in our study 27 of this type, which
represented 24.1% of all larval habitats surveyed. Among the studied LAR, 17 LAR (63% of
all LAR) were LAR-OX and 10 (37%) were LAR-NOX. The submontane area of Parafuri
presented more LAR of both types (17 out of 27) than the lowland rainforest region of
Toototobi (10 out of 27), with a remarkably higher number of NOX lakes (8 out of 10).
However, in the Toototobi area, we encountered approximately double the amount of
seasonal flooded areas than in Parafuri; both were associated with river flood pulses
(FAAR - 11 out of 16) and were not associated with river fluctuations (FANAR - 20 out of
30). MFS prevalence was similar in both areas, but SFS were more predominant in Parafuri
(11 out of 16), draining the numerous hills of the region to the closest river. The less
common breeding site type was the ephemeral RP, which were only encountered on one
occasion in Toototobi and twice in Parafuri.
TABLE
Breeding habitats types and their main characteristics in the Yanomami
Indian Reserve, Brazilian Amazon Region
Breeding
habitat type
Associated to flood
pulse
Permanent
Sun exposure
Submerse
macrophytes
Emergent
vegetation
Filamentous
algae
Current water
LAR-OX (n = 17)
3
3
0-3
0-3
2
0-3
0
LAR-NOX (n = 10)
3
3
0-3
0-3
2
0-3
0
FAAR (n = 16)
3
0
0-3
0
2
0-3
0
FANAR (n = 30)
0
0-1
0-1
0
0-1
0
0
RP (n = 3)
0
0
0-1
0
0-1
0-1
0
SFS (n = 16)
1
0-1
0-1
0-1
1
0-1
2
MFS (n = 15)
1
0-1
0-1
0-1
1
0-1
1
RIV (n = 5)
3
3
2
0
1
0
3
larval habitat characteristics were described as absent (0), low (1), medium
(2) and high (3) [total number of breeding habitats in Parafuri and
Toototobi (n)]. FAAR: flooded areas associated with the river; FANAR:
flooded areas not associated with the river; LAR-NOX: lakes associated with
the river-non-oxbow lakes; LAR-OX: LAR-OX-oxbow lakes; MFS: medium forest
streams; RIV: rivers; RP: rainfall pools; SFS: small forest streams.
larval habitat characteristics were described as absent (0), low (1), medium
(2) and high (3) [total number of breeding habitats in Parafuri and
Toototobi (n)]. FAAR: flooded areas associated with the river; FANAR:
flooded areas not associated with the river; LAR-NOX: lakes associated with
the river-non-oxbow lakes; LAR-OX: LAR-OX-oxbow lakes; MFS: medium forest
streams; RIV: rivers; RP: rainfall pools; SFS: small forest streams.Larval habitat characteristics - Some larval habitats showed variable
characteristics. A summary of the main features for the breeding habitats is presented
in the Table. We considered the association with
river flood pulses, seasonality and sun exposure as the three key variables to classify
the larval habitats with a frequency scale of 0 (absent), 1 (low), 2 (medium) and 3
(high). For example, sun exposure classified as 0-3 for OX means that we encountered
some LAR-OX that were fully shadowed while others were well exposed to the sun. When
looking at water permanence in breeding habitats, all LAR were always classified as
permanent (3). FAAR and RP always dried up for some months of the year (0) and some
breeding habitats such as FANAR, MFS and SFS presented variability in this
characteristic (0-1). For instance, of the 30 FANAR included in the study, only four
(13.3%) had water in all the surveys and were considered permanent inland water bodies.
Finally, the two types of LAR and all FAAR (3) were mainly formed because of the
influence of river flood pulses, whereas FANAR and RP originated from rainfall waters
(0). Forest streams, SFS and MFS experienced a variable influx of water from the river
at high river water levels (1).Anopheline larvae collections, preliminary data - We collected 6,295
anopheline immature stages, including species such as An.
darlingi,Anopheles oswaldoi s.l., An. triannulatus
s.s., Anopheles mattogrossensis, Anophe-les
intermedius/Anopheles guarao-like and Anopheles
costai-like. Anopheline larvae were more abundant in certain breeding habitats,
as we retrieved 3,777 anophelines in LAR (of which 3,342 were obtained from U-shaped
LAR), representing 60% of all larvae captured. Therefore, LAR and especially OX
constituted a major breeding habitat for some of the anopheline species collected. For
example, 1,356 (96.93%) An. darlingi and 133 (92.46%) An.
triannulatus s.s. were collected in LAR.Larvae sampling methodology for anopheline natural breeding habitats in the
Brazilian Amazon - The use of a small, portable and light inflatable boat
allowed us to conduct a stratified sampling covering most EBA subtypes of every LAR
surveyed. The reduced size of the boat allowed us great flexibility to navigate the very
shallow waters (as shallow as 25 cm in depth) and reach almost every corner of interest
inside of a LAR. The pEBA encountered in the lake margins were sampled either on foot or
by boat. Apart from enhanced accessibility, this device conferred excellent tested
safety against life-threatening hazards that may inhabit LAR, such as the Amazonian
electric eel (Electrophorus electricus). Plastic boats confer excellent
isolation from their electrical shocks. Sampling EBA distant from the LAR shoreline
without properly using this device is not recommended. When a LAR was sampled for the
first time when lake levels were very low or when water was semi-turbid or turbid,
careful navigation was performed and internal navigation routes for each LAR and
condition were traced. These approaches allowed us to reach most EBA subtypes within the
lake and minimise boat punctures by submersed sticks. Two people, each in one boat, can
collect simultaneously from the same LAR, increasing the security of the team. The use
of regular metal boats or traditional indigenous wood canoes may be impractical in most
LAR, especially those that are not fully and continuously connected to the river. Using
this method, we saved time and the need for substantial human resources to move a heavy
regular boat across the jungle, which in most cases would make larvae sampling
impossible.Heterogeneity of EBA availability at a microscale level - The tEBA per
breeding site type in each of the eight Yanomami villages included in the study is
reported in Fig. 7. The data shown is from
September 2013 fieldwork for Toototobi and from July 2013 for Parafuri, which
corresponds approximately to the transitional period of the wet-to-dry season for both
areas. During this period, larval habitat sizes tend to have already stabilised and most
seasonal larval habitats contain water. Therefore, flooded forest areas of some larval
habitats associated with the river and vast FANAR areas that are impossible to quantify
during the rainy season were not encountered. We showed EBA data for Parafuri from
previous field work because Parafuri anticipated the beginning of the dry season
compared to Toototobi. Indeed, some aquatic sites of Parafuri during the collection of
September 2013 were already dry and others presented a significantly retracted maximum
EBA (especially for FANAR larval habitat type).
Fig. 7
: effective breeding area (EBA) per larval habitat type in each of the
Yanomami villages surveyed in September and July 2013 for Toototobi and
Parafuri communities, respectively. FAAR: flooded areas associated with the
river; FANAR: flooded areas not associated with the river; MFS: medium forest
streams; NOX: nonoxbow lakes; OX: oxbow lakes; RP: rainfall pools; SFS: small
forest streams.
A marked heterogeneity of EBA availability for anopheline proliferation was encountered
between both Yanomami areas and even within very close Yanomami huts of the same region.
For example, while U-shaped LAREBA was relatively abundant in communities such as
Apiahik and Mahaxipoha, both in Toototobi, and Komomassipe, Warareu and Makabey located
in Parafuri, U-shaped LAREBA was not present in Xaruna (Parafuri) and Koiopi
(Toototobi). However, within 1 km of the dwellings, these last two communities presented
EBA available from larval habitats such as forest streams and FANAR. This variability on
EBA-type occurrence will greatly influence the anopheline repertory that will
predominate in the proximities of certain Yanomami communities. For example,
forest-loving mosquitoes such as An. oswaldoi s.l., An.
intermedius/An. guarao-like and An. costai-like were
predominant in Xaruna and Koiopi.
DISCUSSION
Malaria epidemiology in relatively undisturbed areas of the Amazon Region may vary
considerably between regions, depending on if they are located in areas of low or
higher-order rivers and the nature of breeding sites associated to the river floodplain
system. This will determine to a great extent which Neotropical malaria vectors will
occur and at what densities. All rivers in our study area were low-order rivers, which
are subject to short, polymodal and generally unpredictable flood pulses. These flood
pulses may also occur during the drier months of the year, overflowing again the larval
habitats associated with rivers during this period. This type of wetland dynamic is
associated with low-order rivers between first-fifth stream order and depends to a great
extent on the intensity of local rainstorms (Junk et al.
2011). Large Amazonian rivers and their floodplains are influenced by
long-lasting, monomodal and predictable flood pulses (Junk et al. 2014). This flood pulse pattern is encountered along the Amazon
River and its major tributaries (rivers of more than 5th stream order) (Junk et al. 2011).There have been various classifications of larval habitats that have been used for many
mosquito species (Silver 2008). Few comprehensive
attempts to classify breeding sites of Neotropical anophelines have been proposed. In
one proposal, larval habitats for Anopheles albimanus were classified
in 16 clusters or habitat types and were strictly defined according to dominant
botanical and limnological characteristics. The authors also ranked these 16 habitat
types based on larval densities (Rejmankova et al.
1992). In their review, Sinka et al.
(2010) provided a list of studies that reported the occurrence of the main
Neotropical malaria vectors in some of the most commonly defined larval habitats. They
were classified as large and small water bodies and as either natural or man-made.
Lagoons, lakes, marshes, bogs and slow flowing rivers were considered the main large
natural breeding sites, while small streams, seepage springs, pools, wells and dips in
the ground were found as the most common small natural breeding sites for Neotropical
anophelines. LAR would include some previously reported permanent water bodies such as
lagoons and lakes.In our study, we introduced the concept of LAR for malaria ecology, which combines the
two types of larval habitats (OX and NOX lakes) that may have the most influence on
malaria transmission in unaltered areas of the Amazon Basin, such as many of the
indigenous areas located within low-order river systems. OX are the most frequent type
of lake in the Brazilian territory, especially in the Pantanal wetlands and Amazon
Basin, where a flat landscape and numerous meandering rivers favours the formation of
many of these lakes (Esteves 1998). More
meandering rivers tend to form more OX and thus areas with these characteristics may be
more prone to become breeding habitats for An. darlingi, leading to
malaria transmission landscapes. Different levels of hydrological connectivity
propitiate colonisation by different species of macrophytes, different composition and
water heaviness (Junk 2005), thus converting some
LAR to a suitable breeding place for certain species of Anopheles. In
addition, anopheline-washing episodes will be more frequent in fully connected LAR than
in those that are more disconnected.In a study carried out in the Solomon Islands, Belkin
(1954) introduced the term “effective breeding surface” or “effective breeding
site” to define those areas within a larval habitat suitable for anopheline breeding.
Areas of open and deep standing water and water habitats with open flowing water were
considered not effective breeding surfaces. In a posterior study, the “effective
breeding area” in an irrigated pastureland was stratified into different
microenvironments and, according to their contribution to the total breeding area, a
proportional number of dips from each microenvironment were taken (Silver 2008). We used the term EBA to define those water surface
areas that were productive for the different anopheline species encountered in our study
areas. We refined the use of this concept by accurately quantifying the EBA of the
different larval habitats with the use of a fine-scale precision and easy-to-use laser
rangefinder.With our classification, we propose a comprehensive nomenclature that attempts to
simplify different denominations of natural breeding sites for low-order river systems
of the Amazon. The main characteristics that we used for our classification were
association to river flood pulses, seasonality and degree of sun exposure. We found that
these were the best parameters to help us explain the occurrence of density hotspots of
certain anopheline species and to characterise how they are dispersed during the dry and
wet seasons (J Sánchez-Ribas et al., unpublished observations). Immature stage habitats
were also previously classified, including water permanence (permanent, semi-permanent
and temporary) and sun exposure (sunlight, partial shade and complete shade) as some of
the main classification criteria (Almirón & Brewer
1996). In a larval survey in West Virginia, 15 larval types were described and
mainly classified by their exposure to the sun. Habitats within the sunlit category had
water surface and thus had immature mosquito stages exposed to sunlight during most
daylight hours. Larval habitats located inside forests protected from direct sunlight
were classified as shaded (Joy & Clay
2002).Manguin et al. (1996) reported the use of an
inflatable raft to sample microdams along the margins of the Sibun River in Belize. In
our study area, the use of a smaller inflatable device was key to thoroughly sample the
main breeding habitats of An. darlingi in our study area, the LAR.
Otherwise, important anopheline microhabitats a few meters from the lake shoreline, such
as submersed macrophytes EBA and floating debris exposed to the sun, would not have been
accessible by foot, resulting in potential information bias regarding anopheline
occurrence, larval habitat preferences and population densities.The flight range of different anopheline species may vary, although it has been
considered that the maximum distance that anophelines may flight is up to 2 km. However,
it is believed that most of the flights occur at shorter distances in the 0-2 km
distance range (Service 1997). According to
previous reports in the literature for the flight range of Neotropical malaria vectors,
we determined to collect sample from larval habitats in a range of 1 km from the
Yanomami huts. This distance was considered epidemiologically relevant with a potential
influence on the intra, peri and immediate extra-domiciliary transmission environments
of each village. However, few studies have reported consistent data on dispersal
dynamics of Neotropical anophelines. In a mark-release-recapture experiment, Charlwood and Alecrim (1989) reported most recaptures
to be up to 1 km away, although a couple of An. darlingi were
recaptured 7.2 km away from the release point. It was also noted that other Amazonian
vectors such as Anopheles strodei, An. triannulatus or
An. oswaldoimay have a more limited flight range. Achee et al. (2005) also performed a
mark-release-recapture study in which they confirmed that the recapture rate for
An. darlingi was greatest at 0 m (29%; 124/428) and decreased by
11.6% (37/318) and 5.8% (21/361) at the 400 m and 800 m recapture sites,
respectively.Disease transmission and vector ecology studies have consistently used tools such as
remote sensing (RS) and Geographic Information Systems, greatly facilitating the ability
to analyse relationships of vectors and diseases over time and space (Rejmankova et al. 2013). However, within the quite
homogeneous landscape of undisturbed areas of the Amazon rainforest, RS may be
particularly difficult to perform in areas associated with low-order river systems. For
example, high-resolution satellite imagery (i.e., IKONOS images) does not exist for most
of the Brazilian Yanomami area and many small FAAR and LAR, and all habitats that are
under the dense canopy may be undetected on the freely available satellite images
(LANDSAT images) and thus it is impossible to precisely locate and measure EBA and
habitat size fluctuations. On-site accurate measurement of water bodies with this new
field laser measurement approach may be the only feasible way to quantify the EBA
dynamics of the different larval habitats in these remote areas of the Amazon.Concluding remarks - We have proposed an easy-to-use and accurate
methodology for quantifying the EBA dynamics of the main larval habitats of some key
malaria vectors of the Brazilian Amazon. We believe that our classification of natural
larval habitats and the new larval sampling methodology will contribute to the
understanding of the influence of breeding habitat types on anopheline species-specific
production and malaria transmission seasonality in low-order river systems of the
Amazon. OX had enormous epidemiological relevance in our study areas, as important
Amazon vectors such as An. darlingi, An. triannulatus
s.s. and An. oswaldoi s.l. thrived in abundance within
their domains. We recognise that this larvae methodology is especially suitable for some
Neotropical malaria vectors, as they may breed in considerable large, spatially fixed
and size variable breeding habitats. However, we also foresee applicability of the
larvae methodology to accurately determine the EBA dynamics for larval habitats of other
dominant malaria vectors that exploit relatively large and size-variable aquatic
habitats. The larvae sampling methodology may also assist in the planning of effective
control measures directed at the immature mosquito stages by precisely quantifying the
tEBA (and EBA subtypes) that must be targeted during time-limited larval source
management activities. Finally, with the reviewed larval habitat nomenclature, we
attempted to simplify and standardise the classification of natural breeding sites in
low-order river systems of the Amazon Basin.
Authors: Maria Goreti Rosa-Freitas; Pantelis Tsouris; A Townsend Peterson; Nildimar Alves Honório; Fábio Saito Monteiro de Barros; Ducinéia Barros de Aguiar; Helen da Costa Gurgel; Mércia Eliane de Arruda; Simão Dias Vasconcelos; José Francisco Luitgards-Moura Journal: Mem Inst Oswaldo Cruz Date: 2007-06 Impact factor: 2.743
Authors: M G Rosa-Freitas; R Lourenço-de-Oliveira; C J de Carvalho-Pinto; C Flores-Mendoza; T F Silva-do-Nascimento Journal: Mem Inst Oswaldo Cruz Date: 1998 Sep-Oct Impact factor: 2.743
Authors: Nicole L Achee; John P Grieco; Richard G Andre; Eliska Rejmankova; Donald R Roberts Journal: J Am Mosq Control Assoc Date: 2005-12 Impact factor: 0.917
Authors: Francis M Mutuku; M Nabie Bayoh; John E Gimnig; John M Vulule; Luna Kamau; Edward D Walker; Ephantus Kabiru; William A Hawley Journal: Am J Trop Med Hyg Date: 2006-01 Impact factor: 2.345
Authors: Paulo F P Pimenta; Alessandra S Orfano; Ana C Bahia; Ana P M Duarte; Claudia M Ríos-Velásquez; Fabrício F Melo; Felipe A C Pessoa; Giselle A Oliveira; Keillen M M Campos; Luis Martínez Villegas; Nilton Barnabé Rodrigues; Rafael Nacif-Pimenta; Rejane C Simões; Wuelton M Monteiro; Rogerio Amino; Yara M Traub-Cseko; José B P Lima; Maria G V Barbosa; Marcus V G Lacerda Journal: Mem Inst Oswaldo Cruz Date: 2015-02-13 Impact factor: 2.743
Authors: Thibault Catry; Zhichao Li; Emmanuel Roux; Vincent Herbreteau; Helen Gurgel; Morgan Mangeas; Frédérique Seyler; Nadine Dessay Journal: Int J Environ Res Public Health Date: 2018-03-07 Impact factor: 3.390
Authors: Teresa Fernandes Silva-do-Nascimento; Jordi Sánchez-Ribas; Tatiane M P Oliveira; Brian Patrick Bourke; Joseli Oliveira-Ferreira; Maria Goreti Rosa-Freitas; Ricardo Lourenço-de-Oliveira; Mariana Marinho-E-Silva; Maycon Sebastião Alberto Santos Neves; Jan E Conn; Maria Anice Mureb Sallum Journal: Genes (Basel) Date: 2021-12-16 Impact factor: 4.096