an exPloRatoRy analysis of seasonal and

intRaseasonal vaRiations of the main aiRboRne Pollen

tyPes in sunchales city, aRgentina

análisis exPloRatoRio de las vaRiaciones estacionales e

intRaestacionales de los PRinciPales tiPos Polínicos en la atmósfeRa

de la ciudad de sunchales, aRgentina

1,2

1

1,2

1

y Ana G. Ulke

Claudio F. Pérez * , Mauro Covi , María I. Gassmann

Resumen

Introducción y objetivos: El estudio de la variabilidad estacional e intraestacional de

la concentración de polen en el aire es de suma importancia para comprender las

relaciones con la vegetación emisora y los parámetros atmosféricos que modulan

el transporte de polen. Esta investigación tiene como objetivo estudiar estas

variabilidades en Sunchales, una ciudad ubicada en el centro-este de Argentina.

M&M: El monitoreo atmosférico se realizó con una trampa Burkard durante dos

temporadas en 2012 y 2013 en las afueras de la ciudad.

Resultados & Conclusiones: Los períodos de polinización de los tipos de polen

estudiados muestran un retraso en 2013 en comparación con el año anterior,

presuntamente relacionado con una mayor cantidad de unidades de calor

acumuladas en 2012. Sin embargo, la integral polínica para el período 2013 fue

1

. Departamento de Ciencias

de la Atmósfera y los Océanos,

Intendente Güiraldes 2160,

do

2

piso, Pabellón II, Ciudad

Universitaria, C1428 EHA Buenos

Aires, Argentina.

2

. Consejo Nacional de

Investigaciones Científicas y

Técnicas.

*

perez@at.fcen.uba.ar

1,4 veces mayor que 2012, hecho que no se explica por la precipitación acumulada

sino por la hora del día en que ocurren los hidrometeoros. Las concentraciones de

polen categorizadas en rangos muestran que los valores mayores coinciden con

la ubicación urbana de las fuentes arbóreas mientras que las herbáceas muestran

una asociación con un origen rural. En cuanto a la variabilidad intraestacional,

la mayor proporción de la varianza del polen en el aire se acumula en la escala

sinóptica (80 - 60%) con períodos entre 3 y 10 días. Durante 2012 predominaron

las ondas largas (> 5,5 días) mientras que en 2013 predominaron las ondas medias

Citar este artículo

PÉREZ, C. F., M. COVI, M. I.

GASSMANN & A. G. ULKE. 2021.

An exploratory analysis of seasonal

and intraseasonal variations of

the main airborne pollen types in

Sunchales city, Argentina. Bol. Soc.

Argent. Bot. 56: 269-287.

(3,9 - 5,5 días).

PalabRas clave

Análisis de Fourier, concentraciones de polen en el aire, inﬂuencia meteorológica,

Santa Fe, trampa Burkard.

DOI: https://doi.

org/10.31055/1851.2372.v56.

n3.31998

summaRy

Background and aims: The study of the seasonal and intra-seasonal variability

of the airborne pollen concentration is of paramount importance to understand

the relationships with the emitting vegetation and the atmospheric parameters

that modulate pollen transport. This research aims to study these variabilities in

Sunchales, a city located in the center-east of Argentina.

M&M:Atmospheric monitoring was carried out with a Burkard trap during two seasons

in 2012 and 2013 on the outskirts of the city.

Results & Conclusions: The pollination periods of the studied pollen types show

a delay in 2013 compared to the previous year, presumably related to a greater

amount of cumulative heat units in 2012. However, the integral pollen for the period

2013 was 1.4 times higher than 2012, a fact that is not explained by accumulated

precipitation but by the time of day when the hydrometeors occur. Binned pollen

concentrations show that the highest concentrations coincide with the urban

location of the tree sources while the herbaceous ones show an association with

a rural origin. Regarding the intra-seasonal variability, the highest proportion of the

airborne pollen variance accumulates on the synoptic-scale (80 - 60%) with periods

between 3 and 10 days. During 2012 long waves predominated (> 5.5 days) while

in 2013 medium waves prevailed (3.9 - 5.5 days).

Recibido: 23 Ene 2021

Aceptado: 22 Jun 2021

Key woRds

Publicado en línea: 2 Sep 2021

Publicado impreso: 30 Set 2021

Editor: Gonzalo Márquez

Airborne pollen concentrations, Burkard trap, Fourier analysis, meteorological

inﬂuence, Santa Fe province.

ISSN versión impresa 0373-580X

ISSN versión on-line 1851-2372

269

Bol. Soc. Argent. Bot. 56 (3) 2021

intRoduction

mateRials and methods

Forecasting airborne pollen concentrations Study area

is undeniable of high importance to biological,

Sunchalesisanagricultureandindustrialcitylocated

environmental, and ultimately medical practice in the core area of Argentine agricultural production.

(

Aznarte et al., 2007). The presence and amount According to the records of the National Institute

of airborne pollen depend on a wide range of Statistics and Censuses, its population is 21,304

of factors that can be grouped into physical, inhabitants. From the phytogeographic standpoint, the

concerning meteorology (wind, rain, air city of Sunchales is located in the Espinal province

humidity, and temperature) and biological, (Lewis & Collantes, 1973; Cabrera, 1976; Morello et

which depends on plant distribution, stand al. 2012), where the predominant natural physiognomy

maturity, phenological, physiological, and should resemble a xerophytic leguminous forest with

phytosanitary conditions among others. As there a stratum of grasses, interspersed with large Savanna

is no standardized modeling approach, many or Park areas. According to Oyarzábal et al. (2018),

authors tried to generate models of different the location corresponds to the Algarrobal unit:

nature (eg. Arizmendi et al., 1993; Hjelmroos, “Sclerophyll forest with Prosopis nigra and Prosopis

1

&

992; Kawashima & Takahashi, 1999; Levetin alba”. However, agricultural-livestock activity

Van de Water, 2003; Voukantsis et al., 2013; produced a signiﬁcant modiﬁcation of the landscape,

Fernández-Rodríguez et al., 2016; Damialis et where natural vegetation has been relegated to small

al., 2017 and many others), whose application patches in abandoned ﬁelds or along rural roads. As

has provided variable results. Pollen forecasting a result, the present physiognomy corresponds to

is a hard problem to be solved not only because a Savanna where the dominant woody species are:

of the chaotic nature of the airborne pollen Geoﬀroea decorticans (Gill. ex Hook. &Arn.) Burkart,

concentration intended as a time series of Vachellia caven (Molina) Seigler & Ebinger, and

infinite length (Bianchi et al., 1992), nor by the Parkinsonia aculeata L., accompanied by diﬀerent

high quantity of variables involved, but to the herbs and ruderal species. The most widespread

complexity of space and time scales in which these economic activity is agriculture, mostly dedicated to

variables operate on the system. Moreover, these dairy, where large plots are destined for feeding cattle

variables may have synergistic or antagonistic with extensive cultivation of Medicago sativa L. and

effects depending on the timing of their temporal grasses. In the urban area, the ﬂoristic composition

variability. Topography, as well as natural and includes numerous exotic tree species grown as

anthropogenic barriers, add new difficulties to be ornamentals along the streets, in public parks and in

solved. This has meant that the common answer private gardens. The most abundant species are Morus

to the challenge of forecasting airborne pollen sp., Broussonetia papyrifera (L.) Vent., Maclura

concentrations is to build pollen calendars, pomífera (Raf.) C.K. Schneid., Bauhinia variegata

however, more robust solutions require knowing L., Platanus × hispanica Mill. ex Münchh., Fraxinus

specific site-dependent interactions between excelsior L., Cupressus sempervirens L., and C.

biological and physical variables at different macrocarpa Hartw. ex Gord. Some other species like

time and space scales. A two-year survey of Populus deltoides W. Bartram ex Marshall, P. alba L.,

the atmospheric pollen content in the city of and P. nigra L. are planted as windbreaks in the city

Sunchales (Santa Fe, Argentina), allowed a first outskirts.

characterization of the aeroflora, determining

According to the updated Köppen-Geiger

the incidence and prevalence of the pollen classiﬁcation (Kottek et al., 2006), the climate is Cfa

content, and to estimate the allergenicity of the type: warm temperate with average annual temperature

pollen types present in the local air (Pérez et al., and precipitation of 18.5 °C and 928 mm respectively.

2

020a). In this paper, we address the preliminary July is the driest and coldest month (24 mm, 12 °C),

analysis of the relationship between airborne while the highest rainfall is recorded in March (147

pollen variability of the main pollen types, mm), and the maximum temperature in January (25.1

with meteorological parameters at seasonal and °C) (Argentine National Weather Service Climatology

intraseasonal timescales for the place.

for the period 1999-2000).

270

C. F. Pérez et. al. - Seasonal and intraseasonal pollen variations in Sunchales

Airborne pollen monitoring

specialized literature (Heusser, 1971; Markgraf

Atmospheric pollen monitoring was carried & D’Antoni, 1978; Pire et al., 1998, 2001).

out in two periods (01/08/2012 - 27/11/2012; Pollen data are expressed as a daily concentration

-3

0

9/08/2013 - 05/12/2013) from the Southern (pollen grains per cubic meter of air, gr m ).

Hemisphere late winter to late spring when the Data for the period 11/11/13 to 14/11/13 were

highest palynological richness is observed in lost due to pollen trap malfunctions. To maintain

most of the localities studied in Argentina (Pérez the continuity of the series, the missing data

et al., 2020b and references therein). The survey were linearly interpolated. Hourly and daily

was carried out with a Burkard trap located meteorological data (hourly, daily maximum and

approximately 3 km SW of the geographical minimum temperatures, hourly wind speed and

center of the city, at the National Weather Service direction, hourly pressure, present weather, and

station of the Sunchales airﬁeld (30° 57’ 24.5” daily precipitation) measured at Sunchales airﬁeld

S, 61° 31’ 59.2” W, 93, Fig. 1). The trap was station were provided by the National Weather

operated at a constant suction volume of air Service for 2012 and 2013.

3

-1

(

0.6 m h ), with the inlet at 1.3 m above the

The pollen integral in the 01/08/2012 -

-3

ground. The trap works with the volumetric - 27/11/2012 period reached 1830.3 gr m (13,178

isokinetic technique designed by Hirst (1952), grains), while on 09/08/2013 - 05/12/2013 it was

which is widely used in Europe and Asia for 1.4 times higher, with a total of 2564.3 gr m

-

3

aerobiological sampling and is described in detail (18,463 grains) (Pérez et al., 2020a). Up to 94

in numerous published papers (eg. Bianchi, 1992, pollen types were recognized in both records,

1

994; Latorre, 1999a; Pérez, 2000; Latorre & nevertheless, 74% (2012) and 72% (2013) of

Caccavari, 2010). The preparation of the sticky these pollen sums are represented by the most

surface and the assembly of the slides was carried abundant Urticaceae, Moraceae, Poaceae, and

out by standard techniques (Käpylä & Penttinen, Cupressaceae pollen types which also show the

1

981). Pollen counting was performed with an longest and continuous pollen records. These

optical microscope with a ﬁnal magniﬁcation of pollen types are allergenic species (Pérez et al.,

00x, analyzing the complete slide obtained for 2020a), therefore, they were selected for further

4

each day. Pollen types were recognized based on analysis in this paper (Appendix).

Fig. 1. Location of the sampling site and rotated coordinate system used for wind component decomposition

(see text).

271

Bol. Soc. Argent. Bot. 56 (3) 2021

bacKgRound

al. (1992) and Seeley et al. (1996) state that after a

dormancy period, the accumulation of heat above a

Pollen concentrations are reported as discrete temperature threshold is required to start the pollen

data series at regular time intervals of x seconds, shedding, therefore, heat units were calculated

minutes or hours. Therefore, the summarization with the single triangulation method (Zalom et al.,

of its properties using time-series methods are 1983) to analyze PPP-temperature relationships

appropriate. In this context, the variability of an for this timescale. The required lower threshold

observed pollen data set (S) could be viewed as temperature was set at 5.5°C according to the

contributions from natural processes occurring at recommendations of several authors for Urticaceae

diﬀerent timescales, or characteristic frequencies:

(Urtica dioica L.), Moraceae (Morus rubra L.,

M. microphylla L., Maclura pomifera (Raf.) C.K.

Schneid.), and Poaceae (Holcus lanatus L., Festuca

rubra L., Poa annua L.) (Bassett et al., 1977; Liem

S = S + S + S + S + ε

t

a

s

is

With S the change due to long-term trend, S , & Groot, 1980; Emberlin et al., 1994; Thompson

t

a

S , S , the interannual, seasonal, and intraseasonal et al., 2000; García - Mozo et al., 2009; Zhang et

s

is

variabilities and an error term. This approach al., 2015).

allows us to progressively remove the variability Intraseasonal variability (S ) was studied with

is

of diﬀerent timescales to analyze its relationship Fourier Analysis (Wilks, 2011) from the residuals

with presumed biological or meteorological driving obtained after removing the binomial ﬁlter from the

processes. The length of our record did not allow us original series of observed data (high pass ﬁltering).

to analyze the ﬁrst two terms, which require longer The new series contains k sub-seasonal timescales

data sets (several years).

intended as cycles throughout N observations

There are diﬀerent techniques to study S , being (frequency). These cycles could be represented

s

the most common to determine the main pollen- as having arisen from k series of sine and cosine

season or principal pollination period (PPP) with functions that being expressed in complex notation,

the onset and peak dates (García-Mozo et al.,

2

009). Most of the methods that calculate PPP,

require counting at least a whole year record since

the key dates are deﬁned as a percentage of pollen

accumulated from the annual pollen sum (Pathirane,

1

975; Lejoly-Gabriel, 1978; Nilsson & Persson, Where N is the total number of data in the series,

981; Frenguelli et al., 1991) while others detect t is the sampling interval, H is the complex Fourier

k

these dates upon reaching some pre-established coeﬃcient H = A + i B with A the real and B the

k

i[2πk/N]t

concentration thresholds (Mullenders et al., 1972; imaginary part of H , and e

= cos(2πt/N) + i

k

Mäkinen, 1977; Driessen et al., 1989, 1990; sin(2πt/N) with i = √-1 (Wilks, 2011).

Norris-Hill, 1998). The procedure employed in this

The Fourier transform X(k) which gives the

paper resembles that of Norris-Hill (1998) which frequency spectrum could be obtained as:

overcomes the annual pollen sum requirement

being more suitable to our data. A low pass ﬁltering

procedure was applied to reduce the high-frequency

variability, afterward selecting the onset of the

pollination period, as the date from which ﬁltered

As X(k) is computationally time-consuming, the

pollen concentration increases at least 5% for 5 most used tool to calculate the frequency spectrum

consecutive days. Low pass ﬁltering was performed is the Fast Fourier Transform (FFT). The data for

with a 17 weights binomial ﬁlter which, instead of this study were pre-treated as follows: The series

a moving average procedure, preserves the phase for both years were trimmed to 96 data points (7

of the oscillations and enhances the information of days were eliminated in 2012 and 8 days in 2013)

periods longer than 10.7 days.

and tapered with 10% data generated with a cosine

Temperature is considered the main driver of the function at both ends of the series. This technique

pollination period by many authors. Frenguelli et reduces distortions introduced by errors (aliasing)

272

C. F. Pérez et. al. - Seasonal and intraseasonal pollen variations in Sunchales

to the high frequencies. Pollen concentration series is obtained from applying empirical techniques

were tapered only when the pollen season was to detect the onset, peak, and end dates of the

truncated. For Fourier analysis the wind vector pollination season. The binomial ﬁltering showed

was decomposed into its NE-SW and SE-NW that 2012 and 2013 seasonal patterns are quite

components using a counterclockwise π/4 rotated similar with the only exception of Cupressaceae.

coordinate system (Fig. 1). NE and SE directions Seasonal patterns are multimodal as pollen types

were considered positive while SW and NW represent several genera and species which may

negative. The idea of this coordinate transformation show diﬀerent ﬂowering times (Fig. 2). Along with

arose from considering the shape of the wind rose the increase in concentration, there is a concomitant

that presented two axes of maximum variability delay of the 2013 pollination season, which seems

in the NW - SE and NE - SW directions (see Fig. to be greater in tree pollen types (Pérez et al. 2020a).

6

). In addition, the city is located to the NW of Moraceae and Urticaceae exhibit 3 and 4-day delays

the position of the pollen trap (Fig. 1). Thus, the respectively, while Poaceae scarcely registers a

transformation used maximizes the variability of 1-day delay. The onset of the Cupressaceae season

the wind rose and the urban-rural contrast of the could not be determined since pollen shedding

pollen sources.

started well before the beginning of the record.

Many kinds of research relate the seasonal

The calculated frequency spectra were smoothed

with a Parzen ﬁlter of 11 weights to prevent the pattern with diﬀerent meteorological variables,

misidentiﬁcation of peak frequencies due to noise. mainly temperature and precipitation (eg. Galán

Spectra were converted to periodograms where et al., 1995; Smith & Emberlin, 2006; Brighetti et

-1

period [days] = frequency .

al., 2014). Blooming species growing in the same

The choice of a ﬁlter with a cut-oﬀ period of 10.7 environment have a marked tendency to present the

days makes it possible to preserve the synoptic- same onset advance or delay, being the temperature

scale variability in the residuals. Although there the determinant factor (Marletto et al., 1992). Mean

is no agreement on the time span for this scale, daily temperature (Fig. 3), statistically have the

ranging from 0.5 days to 1 month (Eskridge et al., same rate of increase (α= 0.05) with 2012 slope =

-1

997; Gulev et al., 2002; Hogrefe et al., 2003), 0.083 ±0.008 Julian day and 2013 slope = 0.080

-1

1

we follow the criteria of Solman & Menéndez ±0.008 Julian day . Nevertheless, cumulative

2002) who consider the synoptic-scale variability heat units show greater diﬀerences between both

(

to be up to 10 days for the Southern Hemisphere. sampling periods (Fig. 4), which seem to explain

Particularly, in the Fourier spectra, the synoptic- the registered delay.

scale was analysed considering 3 equal frequency

The year 2012 was slightly warmer than in

bandwidths whose ranges expressed as periods are: 2013, shown by a higher minimum temperature

short waves (3.1 - 3.9 days), medium waves (3.9 - (Table 1), which agrees with the diﬀerences in

5

.5 days), and long waves (5.5 - 8.7 days).

pollen productivity registered between both years.

According to Cadman et al. (1994), temperature as

a controlling factor of the intensity of the pollination

season is higher during the summer, when trees

accumulate the major amount of resources available

for reproduction in the next spring. By the end of

Results and discussion

Seasonal characteristics of the pollination period

Comtois (1998, 2000) concludes that the seasonal the growing season, these resources are consumed

pattern of any pollen type should be a Normal by the pollen grains that start to form in the anthers

distribution function as it is the ideal statistical (Emberlin et al., 1990). Therefore, we suggest that

model following the aerobiological pathway of the higher temperature registered in 2012 drives

release, dispersal, and deposition phases described higher pollen concentrations in 2013. Besides,

by Edmonds (1979). Nevertheless, this can only be precipitation has diﬀerent eﬀects on the airborne

achieved when averaging a long time series of data. pollen record according to the scale of analysis

Short records like ours usually show quite large considered.

deviations from a Normal distribution function, so

It has been shown that the amount of

that the information referred to the seasonal scale inﬂorescences is related not only to temperature

273

Bol. Soc. Argent. Bot. 56 (3) 2021

Fig. 2. Airborne pollen series of selected pollen types for the periods 2012 and 2013. Lines show the

seasonal trends calculated with a 17-weights binomial ﬁlter. Arrows indicate the starting dates for the

principal pollen seasons.

Fig. 3. Daily mean temperatures and linear trends from August 1 to December 5.

274

C. F. Pérez et. al. - Seasonal and intraseasonal pollen variations in Sunchales

Fig. 4. Accumulated heat units from the winter solstice (Southern Hemisphere) to the end of the sampling

period (December 5) calculated with the single triangulation method (Zalom et al., 1983) and 5.5°C lower

threshold temperature. Inset shows the starting dates for the principal pollen seasons (blue arrows for

Moraceae, green arrows for Urticaceae and yellow arrows for Poaceae).

but to the quantity of rain fallen in the preceding result, airborne pollen concentration tends to

ﬂowering season (Stach et al., 2008). In this sense, decrease after rainstorms (Latorre, 1999b; Peternel

the high pollen integral recorded in 2013 could et al., 2004; Lo & Levetin, 2007; Jato et al.,

also be due to the high annual precipitation in 2012 2002). Cumulative precipitation within 2012 and

(Table 1). Nevertheless, although prevailing weather 2013 sampling periods are virtually equal which

before a flowering season plays an important does not presuppose to be of marked inﬂuence to

role, environmental factors alone cannot explain pollen concentrations (Table 1). However, mist

ﬂuctuations, and other biological factors such as and fog frequencies are markedly higher in 2012

masting should also be considered (Janzen, 1976; that could contribute to the lower amount of pollen

Kelly, 1994; Koenig & Knops, 2005). Some authors collected during the ﬁrst sampling period (Table

explain that this behavior responds to a resource 1). Moreover, the hourly distribution shows that

allocation strategy due to the modular structure of in 2013 the maximum frequency of mist and fog

trees (Isagi et al., 1997; Masaka et al., 2001; Ranta is within the time range in which pollen release

et al., 2005; Miyazaki, 2013).

occurs, but in the previous year, their distribution

On the other hand, airborne pollen becomes (as in the case of rain and drizzle) is more even,

condensation nuclei to the formation of cloud aﬀecting daylight hours when pollen is mainly

droplets (Huﬀman et al., 2013). Falling raindrops present in the air (Fig. 5). Although biological

also produce the washout of suspended particles aerosols are only a fraction of the condensation

which is largely recognised in the literature as nuclei present in the air, they are especially

an eﬃcient method of pollen removal from the important since they start condensation with low

atmosphere (McDonald, 1962, 1964; Gatz & levels of moisture saturation (Bauer et al., 2003).

Dingle, 1963; Scriven & Fisher, 1975). As a Besides, they also prevail in the lower atmosphere,

275

Bol. Soc. Argent. Bot. 56 (3) 2021

while in 2013 the most frequent wind came from E,

SW, S, and NE directions. The mean intensity was

Table 1. Average temperatures and accumulated

precipitation in 2012 and 2013 years. Percentage

frequency of hydrometeors was calculated from August 1

to December 5

-1

slightly higher in 2013 (4.3 m s ) compared to 2012

-1

3.8 m s ). Lower intensities were higher in 2012,

(

especially from E and S directions. High intensities

in 2012 were associated with NNE and E directions

while in 2013 are evenly distributed.

Year

Average maximum

temperature (°C)

2012

2013

26.4

Despite the low wind frequencies, and regardless

of the year, the highest Cupressaceae and Moraceae

concentrations come from WNW - N directions,

which points out the position of the city (see Figs.

Average minimum

temperature (°C)

13.1

19.8

2794

1

12.4

19.4

2337

0.8

Mean temperature (°C)

Annual precipitation (mm)

Fog frequency (%)

1

and 7). Poaceae shows the opposite pattern with

higher frequencies of peak concentration from

directions between S and ENE (Fig. 8). Morus

spp., Maclura pomifera (Raf.) C.K. Schneid.,

Broussonetia papyrifera (L.) Vent. along several

Cupressus species, are found in the parks and streets

of the city while Poaceae sources are more abundant

in the surrounding countryside (Pérez et al., 2020a).

A second Cupressaceae maximum is seen towards

W - SW due to a tiny Taxodium distichum (L.) Rich.

tree growing a few meters from the trap. Urticaceae

Mist frequency (%)

10.6

0.6

7.4

Rain frequency (%)

Drizzle frequency (%)

1

2.5

1.1

Cumulative precipitation

during the sampling

period (mm)

808

809

therefore fog presumably removes pollen more does not show a clear pattern (Fig. 8). During 2012

eﬃciently from the atmosphere than rainy events high pollen concentrations came from SW - W, and

(

Pérez et al., 2009).

N - ESE, while during 2013, they came from NW

NNW, and ENE - SSE directions which show a

greater impact of the change in wind direction than

-

Airborne pollen concentration and wind

The most notable characteristic of the wind in the case of tree species. Urtica and Parietaria

rose is the low wind frequency between WNW - are the two most frequently cited genera of the

NNE (Fig. 6), which is a regional climatic feature Urticaceae family in aerobiological literature and

conﬁrmed by other localities near the study site. both are present in the city of Sunchales (Pérez et

The most frequent directions were E and S in 2012, al., 2020a). The diﬀerences found in both sampling

Fig. 5. Daily frequency distributions of hydrometeors during 2012 and 2013 sampling periods.

276

C. F. Pérez et. al. - Seasonal and intraseasonal pollen variations in Sunchales

Fig. 6. Wind roses at Sunchales station for the 2012 and 2013 study periods.

Fig. 7. Airborne pollen concentration of Cupressaceae (upper row) and Moraceae (lower row) by wind direction.

277

Bol. Soc. Argent. Bot. 56 (3) 2021

Fig. 8. Airborne pollen concentration of Poaceae (upper row) and Urticaceae (lower row) by wind direction.

seasons could be due to changes in the spatial Intra seasonal scale results

distribution of these weeds. Results showed that

Despite the year, the highest wind speed (SE-

feasible tree pollen source inventory could be easily NW and NE-SW rotated components) percentage

achieved from vegetation censuses of the city. Other variances accumulate in the high-pass ﬁlter but

plants like weeds and grasses could be mapped by when the mean temperature and pressure are

remote sensing, although annual growth habits considered, it is found in the low-pass ﬁlter (Tables

and practices like regular lawn mowing constrain 2 and 3). This indicates that even analysing periods

the eﬀectiveness of this technique to model pollen less than one year, the most important temperature

sources (Skjøth et al., 2010).

and pressure changes respond to seasonal-scale

Not only direction and speed but persistence forcing, while the wind depends on shorter-time

as well should be included in these analyses as (synoptic) scale processes. The pollen variables

recommended by other authors, particularly when do not present a recognizable pattern over time

moderate to weak winds prevail throughout the year since they respond to both physical and biological

(Damialis et al., 2005). Nevertheless, the pursuit sources of variability. The synoptic-scale variability

of statistical relationships and interactions among includes 65 - 77 percentage variance of the high-

speed, direction, and persistence should require pass ﬁltered meteorological variables, while for

longer study periods than those analyzed in this pollen these percentages are 72 - 81% (2012) and

paper, especially aiming at forecast purposes.

60 - 79% (2013) (Tables 2 and 3).

278

C. F. Pérez et. al. - Seasonal and intraseasonal pollen variations in Sunchales

Table 2. Percentage variance decomposition of the weather and pollen variables measured in 2012.

Variance

decomposition

Range

(d)

Urticaceae Cupressaceae Poaceae Moraceae MP

93 96 40 37

MT

WS1

3

1.3

5.8

2 2

41 hPa 23 °C

Total variance

-3

2

-3

2

-3

2

-3

2

-1

2

-1

2

(gr m )

(m s ) (m s )

Low-pass ﬁltering

9

6 – 10.5

49.7

63

71.4

49.4

56

44

59

41

70

30

61

18

21

38

62

68

32

47

20

33

6.5

93.5

69

(LPF) %

High-pass

ﬁltering (HPF) %

Synoptic waves

1

0.5 - 2

50.3

80.1

37

75.5

24.5

40

28.6

72.4

27.6

21

50.6

81

8

.7 – 3.1

77

(

% of HPF)

Other waves

% of HPF)

< 3.1 and

> 8.7

19.9

19

23

31

(

Long synoptic

waves

Medium synoptic

waves

Short synoptic

waves

8

5

3

.7 – 5.5

.5 – 3.9

.9 – 3.1

44

38

18

52

63.4

20.4

16.2

49.3

20.5

30.2

40

46.5

32.5

31

20

17

References: MP= Mean pressure, MT= Mean Temperature, WS1= Wind speed (SE-NW) and WS2= WS (NE-SW).

The series of mean temperature, pressure and for the periods 6.9 and 7.4 days respectively

wind components (Table 2) show a predominance (Figs. 11A and 12B). Medium waves explain the

of long waves in 2012, with maximum density highest proportion of Poaceae variance (46.5%,

for the periods 6.9, 7.4, 6.9 (SE-NW) and 6.4 Table 2) with a peak for 4.6 days (Fig. 12A), while

(NE - SW) days respectively (Figs. 9A-B, 10A- Cupressaceae gathers 80% between medium and

B). Long waves predominate in Moraceae (52%) long waves with respective maximum densities for

and Urticaceae (44%) with maximum densities 4.6 and 7.4 day periods (Table 2 and Fig. 11A).

Table 3. Percentage variance decomposition of the weather and pollen variables measured in 2013.

Variance

decomposition

Range

(d)

Urticaceae Cupressaceae Poaceae Moraceae

53 236 117 250

MP

MT

WS1

WS2

1

2

7.5

2 2

47 hPa 44 °C

Total variance

-3

2

-3

2

-3

2

-3

2

-1

2

-1

2

(gr m )

(m s ) (m s )

Low-pass ﬁltering

9

6 – 10.5

55

51

72

64

62

80

20

68

32

43

42

15

11

7

(

LPF) %

High-pass ﬁltering

HPF) %

Synoptic waves

% of HPF)

Other waves

% of HPF)

1

0.5 - 2

45

49

28

36

59.9

40.1

28

38

89

93

(

8

.7 – 3.1

78.6

76.5

23.5

48.3

35.1

16.6

61.9

38.1

44.1

40.5

15.4

65.7

34.3

42.1

42.8

15.1

66.3

33.7

46.3

20

64.7

35.3

46.8

35.5

17.7

(

< 3.1 and

> 8.7

21.4

(

Long synoptic

waves

Medium synoptic

waves

Short synoptic

waves

8

5

3

.7 – 5.5

.5 – 3.9

.9 – 3.1

34.5

33.1

32.4

41

31

References: MP= Mean pressure, MT= Mean Temperature, WS1= Wind speed (SE-NW) and WS2= WS (NE-SW).

279

Bol. Soc. Argent. Bot. 56 (3) 2021

Fig. 9. Smoothed Fourier spectra for daily mean temperature (A, C) and daily mean pressure (B, D) for the

periods 2012 and 2013. Short waves: 3.1 - 3.9 days, Medium waves: 3.9 - 5.5 days, Long waves: 5.5 - 8.7 days.

Fig. 10. Smoothed Fourier spectra for daily wind speed for the periods 2012 and 2013. Left column (A, C)

represent the NW - SE component and right column (B, D) the NE - SW wind component. Short waves: 3.1

-

3.9 days, Medium waves: 3.9 - 5.5 days, Long waves: 5.5 - 8.7 days.

280

C. F. Pérez et. al. - Seasonal and intraseasonal pollen variations in Sunchales

Fig. 11. Smoothed Fourier spectra for daily airborne pollen concentration of arboreal species for the periods

2012 and 2013: Cupressaceae (A, C) and Moraceae (B, D). Short waves: 3.1 - 3.9 days, Medium waves:

3.9 - 5.5 days, Long waves: 5.5 - 8.7 days.

Fig. 12. Smoothed Fourier spectra for daily airborne pollen concentration of herbaceous species for the

periods 2012 and 2013: Poaceae (A, C) and Urticaceae (B, D). Short waves: 3.1 - 3.9 days, Medium waves:

3.9 - 5.5 days, Long waves: 5.5 - 8.7 days.

281

Bol. Soc. Argent. Bot. 56 (3) 2021

In 2013 the greatest meteorological variability pollen concentration favored by clear skies, high

was concentrated in the long bandwidths for NE- irradiance and light breezes, which occur with

SW wind, mean pressure and mean temperature anticyclonic conditions.

(

Table 3). The most frequent periods correspond

to 6.9 days for NE-SW wind component (Fig. ones, the increase/decrease in temperature triggers/

0D) and 9.6 days for pressure and temperature inhibits ﬂoral ripening and opening that occur in

Fig. 9C-D). Medium waves are also important more or less regular pulses. This is hardly seen in

Excluding short-wave variations like circadian

1

(

in temperature, pressure and the SE-NW wind phenological studies as they usually rely on weekly

component (Table 3). The most frequent periods are observations. Nevertheless, some authors discuss

4

.8, 5.1 and 4.6 days (Figs. 9C-D, 10C). Regarding the eﬀect of weather in ﬂoral phenology (Galán et

pollen, Cupressaceae presents 48% of its variability al., 1986; Latorre, 1997).

in long waves with peaks in periods of 6.4 and Our results show that, precisely located sources

.7 days (Table 3 and Fig. 11C) while Poaceae such as Moraceae (urban) or Cupressaceae

8

accumulates 84.6% in medium and long waves, (a tree located a few meters SW of the trap)

with peaks for 4.2 and 6 days respectively (Fig. show variabilities in the same bandwidth as the

1

2C). Moraceae presents the greatest contribution NE-SW and SE-NW wind speed components

in medium waves (41%) and periods of 3.8 and respectively. Velasco & Fritsch (1987) show

.3 days (Fig. 11D). In 2013 Urticaceae showed that in the midsection of Argentina mesoscale

5

even variability in all bandwidths of the synoptic- convective systems (MCC) are triggered by moist

scale (Table 3), with maximum densities in periods air masses frequently advancing poleward or

3

.6 and 5.6 days (Fig. 12D). These results are in weak disturbances passing by in the summertime

agreement with those of Bianchi (1994), wherein westerlies. These recurring systems also show

a pioneering study using the Fourier spectrum considerable monthly and year to year variability

analysis methodology, she found short-wave pollen but in some cases, they produce an MCC almost

periods ranging from 24 hours to 3.7 days in the every other night. Moreover, O’Rourke (1990)

atmosphere of Mar del Plata city (Argentina). already found that increasing wind speed and

Unfortunately, the study did not comprise longer gustiness associated with convective rain events

wavelengths.

may be responsible for the increase of airborne

Presumably, the medium to long synoptic waves pollen concentrations. These frequencies cover the

are the ones that provide the greatest variability entire range of the synoptic frequencies analysed in

and probably carry out the greatest modulation of this paper and could be the source of the claimed

pollen dispersal and transport. For this reason, the coincidence between wind components and the

density spectra of the airborne pollen concentration arboreal pollen mentioned above. As a result, this

show similarities with those of the meteorological scale must be studied in more detail to understand

variables analysed. This is an expected result due the processes involved in the intra seasonal

to the strong association between airborne pollen variability of airborne pollen concentration,

concentration and most of the meteorological dispersal, and transport as well as in the case of all

variables reported in the literature (Vázquez et the other time scales.

al., 2003; Altintaş et al., 2004; Majeed et al.,

2

018). Some authors also conﬁrm the association

between synoptic-scale characteristics and airborne conclusions

pollen concentrations (Gassmann & Pérez, 2006;

Hernández-Ceballos et al., 2011). Hernández-

This study presents the preliminary analysis

Ceballos et al. (2011) found an association between of the relationship between the meteorological

episodes of high concentration of olive pollen and variables and the airborne pollen concentration of

the presence of synoptic systems in SW Spain. the mayor pollen types of a city in the agricultural

Although they did not study their recurrence, their and livestock production center of Argentina.

results show that they occur in periods between 3 The pollination periods show a delay in 2013

and 10 days in agreement with our results. Makra compared to the previous year, presumably related

et al. (2007) also found increases in airborne to a greater amount of cumulative heat units in

282

C. F. Pérez et. al. - Seasonal and intraseasonal pollen variations in Sunchales

2

012. However, the integral pollen for the period bibliogRaPhy

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