Tropical rainforests are an important source of isoprenoid and
other volatile organic compound (VOC) emissions to the atmosphere. The
seasonal variation of these compounds is however still poorly understood. In
this study, vertical profiles of mixing ratios of isoprene, total
monoterpenes and total sesquiterpenes, were measured within and above the
canopy, in a primary rainforest in central Amazonia, using a proton transfer
reaction – mass spectrometer (PTR-MS). Fluxes of these compounds from the
canopy into the atmosphere were estimated from PTR-MS measurements by using
an inverse Lagrangian transport model. Measurements were carried out
continuously from September 2010 to January 2011, encompassing the dry and
wet seasons. Mixing ratios were higher during the dry (isoprene –
Terrestrial vegetation emits high quantities of biogenic volatile organic compounds (BVOCs) to the atmosphere (Guenther et al., 2006, 2012), which are removed by oxidation reactions, deposition of reaction products (Lelieveld et al., 2008) and consumption by surfaces (Gray et al., 2014). Emissions and subsequent transformations in the atmosphere have been widely explored by the scientific community. However, there is still a need for improving our understanding of how BVOC emissions and their reaction products vary seasonally and are involved in atmosphere chemistry, biogeochemical cycling and climate at local, regional, and global scales.
Despite a large number of BVOC species that have been identified within
plants and in emissions from plants, the largest part of the global biogenic
emissions and subsequent effect on atmospheric chemistry are thought to be
associated with isoprenoids (Laothawornkitkul et al., 2009). The isoprenoids
are an important class of organic compounds that include isoprene (containing
five carbon atoms –
Isoprene, as the building block of the higher-order isoprenoids, is the
dominant compound in emissions from many landscapes and has the single
largest contribution to total global vegetation BVOC emission, with an
estimated global annual emission of about 400–600
Although models indicate that tropical rainforests are the main source of isoprenoid emissions to the global atmosphere (Guenther et al., 2012), estimates of global annual emissions of isoprenoid still have large uncertainties (Guenther et al., 2006). One approach to constraining these estimates, specifically for isoprene, is the use of remotely sensed concentrations of BVOC oxidation products in the atmosphere in order to make top-down model estimates (Barkley et al., 2008, 2009, 2013; Stavrakou et al., 2009, 2015). This approach has also suggested seasonal patterns in the emissions of this organic compound (Barkley et al., 2009). In addition, seasonal variations of isoprene emissions in the Amazonian rainforest are suggested based on comparison of some studies with intensive campaigns in situ (Table 1). This seasonality may be driven by light and temperature seasonal variation and leaf phenology (Barkley et al., 2009), and seasonal changes in insolation is probably the main driver of leaf phenology (Jones et al., 2014).
Therefore, the objective of this study was to quantify the seasonal variation of mixing ratios and emissions of isoprene, total monoterpenes and total sesquiterpenes in a primary rainforest in central Amazonia and to correlate them to seasonal variations of environmental (temperature and light) and biological (leaf phenology) factors.
Isoprene and monoterpenes from different regions in the Amazonian rainforest: comparison of estimates and direct measurements of mixing ratios and fluxes.
Continued.
Continued.
Continued.
Note: seasons follow determination of each study. For some
studies the exact times of sample collection are not available and then not
reported. Statistics differed among studies. The most of studies showed mean
values but others presented median values and/or just a range of all values
measured.
Precipitation, PAR and air temperature measured at K34 tower
(
Isoprenoid vertical profiles were investigated at the triangular tower (TT34
tower – 2
The period of this study (from 2 September 2010 to 27 January 2011) represents the second half of the dry season (September 2010–October 2010), the dry-to-wet transition season (November 2010), and the beginning of the wet season (December 2010–January 2011). The whole period of measurements includes the period of low precipitation and when precipitation is increasing (Fig. 1b), and when photosynthetically active radiation (PAR) (Fig. 1d) and air temperature (Fig. 1f) are at their peaks. As October 2010 had more precipitation only at the end of the month, for this study October 2010 is also considered as dry season. This is supported by the fact that the length and intensity of the dry season varies from year to year (da Rocha et al., 2009).
Ambient mixing ratio measurements of isoprene, total monoterpenes and total
sesquiterpenes were carried out using a commercial high sensitivity
proton-transfer reaction mass spectrometer (PTR-MS, IONICON, Austria). The
PTR-MS was operated in standard conditions with a drift tube voltage of
600
Fluxes of isoprene, total monoterpenes and total sesquiterpenes – for dry,
dry-to-wet transition, and wet seasons – were estimated using the average
daytime (10:00–14:00, LT) concentration vertical profile throughout the
canopy and applying an inverse Lagrangian transport model (ILT) (Raupach,
1989; Nemitz et al., 2000; Karl et al., 2004, 2009). The source/sink
distributions throughout the canopy were computed according to Eq. (1):
Once fluxes from the isoprenoid vertical profiles were obtained by the ILT,
they were compared with the isoprenoid fluxes estimated by the Model of
Emissions of Gases and Aerosols from Nature (MEGAN 2.1). Isoprenoid emissions
estimated by MEGAN 2.1 are based on a simple mechanistic model that takes
into account the main processes driving variations in emissions (Guenther et
al., 2012). As described by Guenther et al. (2012), the activity factor for
isoprene, monoterpenes and sesquiterpenes (
Photosynthetic photon flux density (PPFD) and air temperature for all model runs were obtained from the K34 tower measurement time series (The Large-Scale Biosphere-Atmosphere Experiment – LBA). LAI inputs were obtained by satellite observations from NASA MODIS during August 2010 to January 2011. The level-4 LAI product is composited every 8 days at 1 km resolution on a sinusoidal grid (MODIS-NASA, 2015).
The main source of errors for applying the ILT is related to the
parameterization of two combined effects: (1) vertical diffusion coefficient
which is based on measured
To account for chemistry (effect 3) we used a simple modification of the
diffusion coefficient based on Hamba (1993), relying on the fact that the
chemical loss will mainly influence the far field of the parameterization.
Based on estimated OH and measured
We have also investigated the effect of (4) – the number of source layers.
If the number of selected source layers is too small, systematic errors of
the calculated integrated fluxes arise. We have investigated this effect and
found that in the present case, 6 source layers are sufficient to capture
Random errors of the ILT parameterization for effects (1) and (2) mostly relate to precision. Systematic errors (3) and (4) mostly relate to accuracy of the parameterization. While there could also be combined effects of random and small systematic errors, that are difficult to assess, we chose an overall conservative error estimate that should reflect precision and accuracy for effects (1) and (2), noting that the 30 % should mostly relate to precision. All the uncertainties are 1 standard error.
With respect to uncertainties in model estimates, one of the first
quantitative estimates of biogenic VOC emissions (Lamb et al., 1987) included
an estimate of uncertainty of 210 % based on the propagation of
uncertainties in emission factors, emission algorithms, amount of biomass,
and land-use distributions. This “factor of 3” uncertainty has
continued to be used as a rough assessment of the uncertainty of biogenic VOC
emission model estimates applied on regional scales. A more recent study
(Hanna et al., 2005) attempted a comprehensive assessment of each model
component and concluded that the 95 % confidence range on the calculated
uncertainty in isoprene emission was about 1 order of magnitude, while the
calculated uncertainty for monoterpenes and other VOC was only
The standard canopy environment model of MEGAN 2.1 was used to model light
penetration into the canopy (Guenther et al., 2006). Model inputs included
the above-canopy PAR measured (every 30
The light penetration was modeled for five canopy layers distributed from the
canopy top to the ground surface. The thickness of each of the five layers
was determined based on the canopy surface area density estimated for every
50
Leaf phenology was estimated based on the observation of leaf flushing events
of the upper crown surfaces of 63 living trees around the K34 tower
(
Top-down isoprene emission estimates over the 0.5
Daytime (10:00–16:00, LT) and nighttime (22:00–04:00, LT) average
vertical profiles of isoprene
Daytime (10:00–16:00, LT) vertical profiles of mixing ratios of
isoprene, total monoterpenes and total sesquiterpenes from the dry season to
the wet season; and estimated surface area density of the canopy at this
study site (ground-based measurements carried out in
March 2004 using LIDAR – Light Detection And
Ranging) (Parker and Fitzjarrald, 2004)
Daytime (10:00–14:00, LT) source-sink distribution inside and above
the canopy, cumulative flux estimation, and relative emission modeled by
MEGAN 2.1 of isoprene
Vertical profiles of isoprenoids were analyzed for daytime and nighttime for all the seasons considered in this study. Isoprene (Fig. 2a, b, c) and total monoterpenes (Fig. 2d, e, f) had higher mixing ratios during daytime (10:00–16:00, LT) than during nighttime (22:00–04:00, LT) for all seasons, supporting the findings that emissions of isoprene (Alves et al., 2014; Harley et al., 2004) and monoterpenes (Bracho-Nunez et al., 2013; Kuhn et al., 2002, 2004a; Jardine et al., 2015) from Amazonian plant species, at least at this site, are primarily light-dependent and stimulated by increasing temperature.
During daytime, isoprene had a maximum mixing ratio within the canopy. By
comparison, at nighttime maximum values occurred above the canopy, and the
vertical profiles were similar to those of nighttime air temperature
(Fig. 2j, k, l). As isoprene is not emitted at night, this maximum nighttime
abundance of isoprene above the canopy may be due to the daytime residual
layer concentrations. In addition, isoprene lifetime increases during
nighttime owing to the decrease of OH (hydroxyl radical) concentrations in
the dark (Goldan et al., 1995) in light of the low concentrations of nitrogen
oxides (
The vertical profile of total sesquiterpene mixing ratios differed from that
of isoprene and total monoterpenes for all seasons. Total sesquiterpenes had
higher mixing ratios near the ground and at the sub-canopy level
(17
Vertical profiles of isoprene had higher mean mixing ratios in the dry
season, followed by the dry-to-wet transition season and wet season (top
panel of Fig. 3a). The reduction of isoprene mixing ratios from the dry
season to dry-to-wet transition season was up to 20 % and from dry season
to wet season was up to 65 %. During the dry season, the higher mixing
ratios and emissions of isoprene have been attributed to the higher
insolation and higher temperatures compared to the wet season and, for this
reason, higher isoprene concentrations at the top of the canopy are expected.
Nevertheless, in contrast to the observations of Yañez-Serrano et
al. (2015), who reported maximum daytime mixing ratios of isoprene at the top
of the canopy for both dry and wet seasons, this study showed the highest
isoprene mixing ratios inside the canopy (11
Isoprene emissions inferred from concentration vertical profiles were
estimated to be highest in the sub-canopy (16
The maximum absorption of PPFD by canopy, calculated based on PPFD penetration profile modeled by the standard MEGAN 2.1 canopy environment model, occurred right above the maximum of estimated surface area density of the canopy, with the absorption of PPFD being higher during the dry season, followed by the wet season and the dry-to-wet transition season (Fig. 3b). This maximum PPFD absorption at the upper canopy agreed with the maximum of isoprene mixing ratios (top panel of Fig. 3a) and emissions (Fig. 4a) during the dry-to-wet transition season. It differed, however, when compared to peaks of isoprene mixing ratios and emissions during the dry season and the wet season.
One reason for this difference could be the isoprene oxidation in the
atmosphere and within plant, especially at the top of the canopy. During the
dry season the ratio of methyl vinyl ketone
Another important factor might be leaf phenology and/or leaf demography. Different tree species have different isoprene emissions rates, and these rates depend upon the leaf ontogenetic stage. Isoprene emitters can flush at different canopy levels seasonally, and changes in within-canopy isoprene vertical profiles would be expected as a result. Moreover, as more leaf flushing was observed at the upper canopy during the wet-to-dry transition and early dry season, this caused leaves in the age group of 3–8 months to reach the highest abundance in late dry season and early wet season (Nelson et al., 2014). The period with the high abundance of leaves in this age group is coincident with the period when gross ecosystem productivity and landscape-scale photosynthetic capacity is most efficient (Restrepo-Coupe et al., 2013). Here, results show maximum isoprene emission at the upper canopy during the dry-to-wet transition season (Fig. 4a), which is coincident with the period of high abundance of healthy efficient leaves at the canopy top (Nelson et al., 2014) and also coincident with the maximum isoprene emission shown in young mature leaves in the dry-to-wet transition season (Alves et al., 2014). Similarly, higher isoprene emissions during the late dry season have also been related to the increase of active biomass in southern Amazonia (Kesselmeier et al., 2002; Kuhn et al., 2004a, b).
Although the isoprene mixing ratios reported here are within the range of previously reported values in central Amazonia for the dry season and the dry-to-wet transition season (Greenberg and Zimmerman, 1984; Rasmussen and Khalil, 1988; Zimmerman et al., 1988) and for the wet season (Yáñez-Serrano et al., 2015), these results are the lowest observed fluxes of isoprene to atmosphere reported for the Amazonia. However, this could be due to features associated with the site of this study, such as the relatively open canopy caused by the proximity to a dirt road and perhaps a relatively low fraction of isoprene emitting species. Isoprene fluxes measured previously at the same tower site during the wet season were similar (Karl et al., 2009).
Total monoterpenes also showed a strong seasonal variation with maximum
mixing ratios during the dry-to-wet season, followed by the dry season and
the wet season (middle panel of Fig. 3a). Taking mixing ratios of the
dry-to-wet transition season as a reference, total monoterpene mixing ratios
showed an increase of up to 20 % from the dry season to the dry-to-wet
transition season, and a decrease of up to 50 % from the dry-to-wet
transition season to the wet season. Although total monoterpene mixing ratios
were somewhat higher in the dry-to-wet transition season than during the dry
season, total monoterpene fluxes inferred by the vertical profiles were
slightly higher during the dry season (
Total monoterpene mixing ratios and fluxes, during the dry season and the dry-to-wet transition season, were similar to values reported for other sites in central Amazonia (Karl et al., 2007; Yáñez-Serrano et al., 2015). However, the monoterpene comparison of reported studies is a difficult endeavor given that some techniques measured total monoterpenes and others measured some specific monoterpene compounds, and also because monoterpene fragmentation during measurements (PTR-MS) could affect the absolute values of these compounds. Therefore, further efforts are needed in order to characterize the seasonal abundance and the seasonal species-specific composition of monoterpenes in the Amazonia.
Average vertical profiles of total sesquiterpene mixing ratios were higher in
the dry-to-wet transition season, followed by the dry season and the wet
season (bottom panel of Fig. 3a). Taking mixing ratios of the dry-to-wet
transition season as a reference, total sesquiterpene mixing ratios increased
up to 30 % from the dry season to the dry-to-wet transition season and
decreased by up to 55 % from the dry-to-wet transition season to the wet
season. During the dry season and the dry-to-wet transition season, the
maximum total sesquiterpene mixing ratios were observed near the ground.
During the wet season, the maximum mixing ratio was at 17
Monthly averages of air temperature and PAR (measured at K34 tower
during 10:00–14:00, LT), and LAI (MODIS, 8-day observations)
Another potential reason for higher mixing ratios of total sesquiterpenes near the ground is that emission could come from surface sources including litter, roots and soil microbes and fungi. Silva (2010) presented surface BVOC emissions at this site, and the results suggested that the litter decomposition could be an important source of sesquiterpenes to the atmosphere. Litter production is higher during the dry than during the wet season (Luizão, 1989), which could lead to higher amounts of litter at the end of the dry season. Rain starting to increase in the dry-to-wet transition could contribute to more decomposition of the litter storage, which can potentially increase sesquiterpene emissions during the processes of decomposition of dead organic matter. Although the ecological functional role of these sesquiterpenes is not known, abiotic emissions from the litter have a specific signature that can be similar to the concentration profile in the green leaf content (Austin et al., 2014) and in sufficient concentration BVOCs can have the capacity of attracting and repelling soil organisms to a specific location (Austin et al., 2014). Therefore, higher sesquiterpene emissions from the litter could be a signal to the fauna related to the decomposition process and represent an important step of the biogeochemical cycling.
Estimated monthly leaf flushing (light green line) (Tavares, 2013), and monthly average of PAR measured from October 2010 to January 2013 at K34 tower (06:00–18:00, LT) (black line). For the period of this study, leaf flushing is also represented by the analysis of canopy images for every 6 days from October 2010 to January 2011 (red circles). Monthly averages of fluxes of isoprene (dark green line) and total monoterpenes (blue line) (estimated for 10:00–14:00, LT, at TT34 tower). Grey areas represent the period of the dry season.
In contrast to the mixing ratios, the source-sink distribution analysis made
from the vertical profiles of total sesquiterpenes indicated that the main
source of these compounds is the canopy (24
Relative emissions can be calculated as emissions normalized to standard
conditions of above-canopy PAR of 1500
To compare the seasonal variation of isoprenoid emissions with changes in
environmental (light and temperature) and biological (LAI) factors in more
detail, monthly fluxes of isoprenoids were compared to PAR at 51
Predictions from MEGAN 2.1 again differed from measured emissions (Fig. 5b, c, d), showing a reduction in emissions from September 2010 to January 2011. Major quantitative differences between ILT and MEGAN estimates can be shown for isoprene in September, when ILT estimates represented only 4 % of the MEGAN estimates; for total monoterpenes in December, when ILT estimates accounted for 14 % of the MEGAN estimates; and for total sesquiterpenes in November, when ILT estimates were 232 % higher than MEGAN estimates. These differences may be related to local effects, especially leaf phenology and changes in the atmospheric oxidative capacity over the seasons. In order to evaluate the potential effect of leaf phenology on emissions, leaf flushing, PAR, isoprene and total monoterpenes at canopy scale were compared in Fig. 6. They closely tracked each other during the 4 months of measurements. For the period of this study, the analysis of canopy images for every 6 days from October 2010 to January 2011 showed a decrease in leaf flushing from the end of the dry season to the wet season, which was similar to the decrease of isoprene and total monoterpene emissions and PAR. Results from 28 months (October 2010–January 2013) of canopy imaging have shown that the highest number of treetops with leaf flushing occurred during the wet-to-dry transition season (June–July), accounting for 35–50 % of treetops with leaf flushing, followed by a subsequent decrease until the end of the wet season (Tavares, 2013) (Fig. 6). Correspondingly, the results of the present study suggest that lowest emissions might be expected in the June–July time period. These results agree with those presented by Barkley et al. (2009) using remote sensing, suggesting that seasonal changes in isoprene emissions may be strongly affected by leaf phenology in the Amazonia.
Comparison of monthly isoprene emissions based on in-situ PTR-MS measurements (inverse Lagrangian transport model) and satellite-derived estimates and MEGAN 2.1 estimates. Satellite-derived estimates are from January 2010 to January 2011, and ground-based estimates are from September 2010 to January 2011. Satellite-derived and MEGAN 2.1 estimates were divided by 2.5 and 5, respectively. Grey area represents the period of the dry season. Error bars represent 1 standard deviation.
In order to verify if the seasonal trend of the isoprene emissions observed
in this study can also be observed in a 0.5
The results reported here are associated with a small footprint area. This together with the huge biodiversity of tropical rainforests makes it impossible to generalize these results to the regional scale. Moreover, although some previous reports have suggested significant seasonal variations of BVOCs based on in situ measurements in different sub-regions of Amazonia, when those investigations (summarized in Table 1) and this study were compared, high variability is apparent among values of mixing ratios and fluxes. This variability could be due to the following: (1) different methodologies, (2) sampling in different seasons, (3) sampling in different regions (e.g., south, north, west, eastern Amazonia), (4) sampling in different ecotones of the same region, (5) different statistical analyses, and (6) perhaps due to small data sets that are not statistically significant to characterize emissions of a specific site.
Although the canopy scale isoprenoid emission measurements presented here differed from those modeled by MEGAN 2.1 (Figs. 4, 5), which assume that variations are driven primarily by light, temperature and leaf area, in terms of seasonal variation, MEGAN 2.1 estimates of isoprene emission agreed fairly well with the satellite-derived isoprene emission, which suggests that other factors at this site could influence isoprene emissions locally. As already mentioned, leaf phenology may cause important effects on local emissions. As MEGAN 2.1 was driven with local variations in PAR and air temperature, and with regional variations of LAI (satellite observations at 1 km resolution), this regional variation in LAI may not represent the local effect of LAI variation on local emissions, since vegetation in Amazonia is phenologically distinct due to the huge biodiversity of this ecosystem (Silva et al., 2013). Furthermore, as the canopy structure might vary seasonally due to leaf phenology/demography, the pattern of light penetration/absorption and then leaf temperature may change as well; thus, this, together with the differences in emissions among species and among leaf ontogenetic stages, could have an important impact on seasonal changes of local emissions.
Besides the effects of light, temperature and leaf phenology/demography, some
efforts have been made to include effects of
Many recently published studies have used the MEGAN model and the majority have focused on improving our understanding of isoprene emissions. Although other models have been developed on the basis of known biochemical processes (Grote et al., 2014; Morfopoulos et al., 2014; Unger et al., 2013), the general framework and processes simulated are similar. The biochemical basis of isoprene production and release must be further understood to develop mechanistic explanations for variation in isoprene emission (Monson et al., 2012), which may reduce uncertainties associated with the responses to environmental factors.
Seasonal variation of isoprene emissions might be explained by the change in energy supply from photosynthesis throughout the seasons (e.g. Grote et al., 2014). This is supported by the generally strong correlation between isoprene emission and gross photosynthetic capacity reported for Amazonian tree species (Kuhn et al., 2004b), and by the fact that higher demography of healthy efficient leaves (Nelson et al., 2014) coincides with the period of most efficient landscape-scale photosynthesis and photosynthetic capacity (Restrepo-Coupe et al., 2013). However, more measurements are needed to examine this relationship which should follow PAR variation. Additionally, since canopy structure may explain some variation in biomass growth over tropical landscapes due to differences in the pattern of light penetration and absorption by the canopies (Stark et al., 2012), measurements of canopy structure may also help to explain some of the differences in isoprenoid emissions among the Amazonian sub-regions.
Therefore, at least for the Amazonian rainforest, models currently do not fully capture seasonal variations in isoprenoid emissions, especially for monoterpenes and sesquiterpenes, which are less investigated compared to isoprene. The scarcity of measurements in Amazonia prevents the development and evaluation of accurate model approaches. Thus, this study strongly encourages future in situ measurements in Amazonia, including at leaf level, in order to verify changes driven by seasonal variations in leaf area, leaf age, phenology and emission response to soil moisture, and the short-term and long-term temperature and light environment.
In this study, we present the first in situ measurements that show a seasonal trend in isoprenoid emissions for a primary rainforest of central Amazonia. Isoprenoid emissions peak at the end of the dry season and at the dry-to-wet transition season. Under conditions of high insolation and high temperatures joined together with the high demography of photosynthetically efficient leaves (Caldararu et al., 2012; Myneni et al., 2007; Nelson et al., 2014; Samanta et al., 2012), isoprenoid metabolic pathways may experience more favorable conditions for synthesizing these compounds in the dry season and the dry-to-wet transition season. This is especially for the case of isoprene and monoterpenes, which are light- and temperature-dependent and are affected by the recent production of photosynthetic substrates.
Although some studies have suggested that there are no seasonal variations in canopy structure and greenness in Amazonia (e.g. Morton et al., 2014), results reported here present a seasonal variation of leaf flushing and suggest maximum leaf demography in the late dry season, which generally agrees with the assumption that a “greenup” during the dry season in Amazonia may drive increasing isoprene emissions as suggested by satellite retrievals (Barkley et al., 2009). Moreover, this study also suggests that seasonal changes in the atmospheric oxidative capacity could have an important impact on the seasonality of at least some isoprenoid concentrations and above canopy emissions, especially for sesquiterpenes. Their quantification is challenged by rapid atmospheric chemical reactions catalyzed by high insolation and higher ozone concentrations in the dry season.
MEGAN 2.1 estimates did not fully capture the behavior observed with the isoprenoid emissions based on in situ PTR-MS measurements (inverse Lagrangian transport model). Model emissions of isoprene and total monoterpenes were overestimated, especially during September 2010 (dry season) and December 2010 (wet season), respectively. Total sesquiterpenes were underestimated during November 2010 (dry-to-wet transition season). This difference between MEGAN 2.1 flux estimates and fluxes estimated by the PTR-MS vertical mixing ratio profiles could be due to experimental errors or the influence of very local effects on the seasonal emissions measured in this site, because satellite-derived isoprene emissions agree fairly well with MEGAN 2.1 emission estimates and the ground observations do not agree with the satellite data or the model, principally in September. Perhaps the isoprene pattern observed at the site is due to a very local effect of leaf flushing by isoprene emitting species around this tower, but this is not seen on the regional scale where there are different species distributions.
Generally, current models assume that seasonal variation of BVOC emissions in the Amazonian rainforest are primarily based on light and temperature variations. These model simulations capture only a part of the actual variation and have uncertainties associated with the insufficient understanding of mechanistic processes involved in the seasonality of these compounds. Nevertheless, because the number of measurements and sites is limited in Amazonia, there is a scarcity of information, which hinders further model improvements. In summary, our results demonstrate strong seasonality and suggest that important processes are taking place during the transition seasons. Also, results reveal the need for long-term and continuous BVOC observations from leaf level to ecosystem level, and also suggest that standardized measurement procedures are required in order to compare the different Amazonian sub-regions. This may advance understanding of the seasonality of BVOC exchanges between forest and atmosphere, providing the information needed to improve BVOC emission estimates for climate and air quality modeling studies.
This work was performed at the National Institute for Amazonian Research and at the State University of Amazonas with funding provided by the CNPq (fellowship provided to E. Alves by the Brazilian government), and financial support for field work was provided by the Philecology Foundation of Fort Worth, Texas, and the National Science Foundation through the AMAZON-PIRE (Partnerships for International Research and Education) award (0730305) and instrumentation support (CHE 0216226). We also thank Scott Saleska for supporting this long field campaign. This research was also supported by the Office of Biological and Environmental Research of the U.S. Department of Energy under Contract No. DE-AC02-05CH11231 as part of their Terrestrial Ecosystem Science Program. The authors would like to acknowledge the advice and support from the Large Biosphere-Atmosphere (LBA) as a part of the Green Ocean Amazon (GoAmazon) 2014/5 project in Manaus, Brazil. T. Stavrakou was supported by the GlobEmission project (No 4000104001/11/I-NB) of the European Space Agency. Edited by: J. Allan