# A screening analysis of foliar terpene emissions of 36 rainforest tree species in French Guiana and their relationships with seasonality

Joan Llusià, Dolores Asensio, Jordi Sardans, Iolanda Filella, Guille Peguero, Oriol Grau, Romà Ogaya, Ifigenia Urbina, Albert Gargallo-Garriga, Lore Verryckt, et al.

<figure><img src="image_1.png" /></figure>

## ► To cite this version:

Joan Llusià, Dolores Asensio, Jordi Sardans, Iolanda Filella, Guille Peguero, et al. A screening analysis of foliar terpene emissions of 36 rainforest tree species in French Guiana and their relationships with seasonality. Trees - Structure and Function, 2024, 38 (4), pp.997-1012. 10.1007/s00468-024-02530-9. hal-04894275

HAL Id: hal-04894275

https://hal.inrae.fr/hal-04894275v1

Submitted on 19 Feb 2025

HAL is a multi-disciplinary open access
archive for the deposit and dissemination of sci-
entific research documents, whether they are pub-
lished or not. The documents may come from
teaching and research institutions in France or
abroad, or from public or private research centers.

L'archive ouverte pluridisciplinaire HAL, est
destinée au dépôt et à la diffusion de documents
scientifiques de niveau recherche, publiés ou non,
émanant des établissements d'enseignement et de
recherche français ou étrangers, des laboratoires
publics ou privés.

<figure><img src="image_2.png" /></figure>

Distributed under a Creative Commons Attribution 4.0 International License
1 A screening analysis of foliar terpene emissions of 36 rainforest tree species in French Guiana

2 and their relationships with seasonality

3

4 Joan Llusià<sup>a,b*</sup>, Dolores Asensio<sup>a,b</sup>, Jordi Sardans<sup>a,b</sup>, Iolanda Filella<sup>a,b</sup>, Guille Peguero<sup>a,b</sup>, Oriol Grau<sup>a,b</sup>, Romà

5 Ogaya<sup>a,b</sup>, Ifigenia Urbina<sup>a,b</sup>, Albert Gargallo-Garriga<sup>a,b</sup>, Lore T. Verryckt<sup>c</sup>, Leandro Van Langenhove<sup>c</sup>, Laëtitia M.

6 Brechet<sup>e,f</sup>, Elodie Courtois<sup>d</sup>, Clément Stahl<sup>e</sup>, Ivan A. Janssens<sup>c</sup>, Josep Peñuelas<sup>a,b</sup>

7

8 <sup>a</sup> CREAF, Campus Universitat Autònoma de Barcelona, Cerdanyola del Vallès, Barcelona 08193, Catalonia, Spain.

9 <sup>b</sup> CSIC, Global Ecology Unit CREAF-CSIC-UAB, Bellaterra, Barcelona 08193, Catalonia, Spain.

10 <sup>c</sup> Department of Biology, Research Group PLECO (Plant and Ecosystems), University of Antwerp, Universiteitsplein 1, 2610, Wilrijk, Belgium.

11 <sup>d</sup> Laboratoire Ecologie, Evolution, interactions des systèmes amazoniens (LEEISA), Université de Guyane, CNRS, IFREMER, 97300 Cayenne, French Guiana.

12 <sup>e</sup> INRAE, UMR Ecology of Guiana Forests (Ecofog), AgroParisTech, Cirad, CNRS, Université des Antilles, Université de Guyane, 97387 Kourou, French Guiana.

13 <sup>f</sup> Center of Excellence Global Change Ecology, Department of Biology University of Antwerp, Universiteitsplein 1, 2610 Wilrijk, Belgium

14

15

16 * Corresponding author at: CREAF, Campus Universitat Autònoma de Barcelona, Cerdanyola del Vallès, Barcelona 08193, Catalonia, Spain.

17

E-mail address: j.llusia@creaf.uab.cat (J. Llusià).

18

24 Abstract

25 Key message Inventory and Seasonal Variation of Terpene Emissions from Tropical Trees in French Guiana:

26 Implications for Environmental and Ecological Roles.

27 **Abstract** A limited understanding of foliar terpene emissions from different tree species is prominent in diverse tropical forests. We conducted a study in French Guiana, screening BVOC emissions from 36 tropical woody species. We focused on 32 species in the dry season and 33 in the wet season, documenting terpene emissions for the first time in some of these tree species. Our findings show that 93.8% emitted terpenes in the dry season, while only 33.3% did so in the wet season.

31 Terpene emissions ranged from 0.01-80.9 µg g-1 h-1 in the dry season and 0-11.7 µg g-1 h-1 in the wet season, consistent with previous reports. We identified and quantified 23 terpene compounds, including 19 monoterpenes and 4 sesquiterpenes. Additionally, 2 non-terpenoid compounds were detected: 2,2,4,6,6-pentamethylheptane (with no detected emissions in the dry season) and toluene. Among the monoterpenes, the most abundant were α-terpinolene, limonene, α-pinene, β-ocimene, and sabinene. As for sesquiterpenes, β-caryophyllene, α-caryophyllene, and α-copaene were observed during the dry season, while during the wet season, α-terpinolene predominated, followed by limonene, α-pinene, sabinene, β-caryophyllene, and α-copaene. Isoprene was detected in most of the species studied in both seasons.
Sesquiterpene emissions displayed a notable phylogenetic pattern, whereas total terpenes and monoterpenes did not; however, total terpenes and monoterpenes exhibited a significant seasonal influence.

Our study demonstrates that seasonality strongly influences BVOC production in tropical trees, with higher emissions in the dry season. These findings imply that various factors and conditions influence tree emissions in this tropical forest, affecting their ecological, environmental, and climatic roles, as well as the implementation of atmospheric chemistry models.

**Keywords** biogenic volatile organic compounds (BVOCs) emissions · chemical diversity · monoterpenes · sesquiterpenes · tropical forest · seasonality

## Introduction

Biogenic Volatile Organic Compounds (BVOCs), which include a variety of organic compounds, are emitted by various organisms such as bacteria, fungi, marine life, plants, and even humans (Wheatley 2002; Morath et al. 2012; Bourtsoukidis et al. 2018; Lawson et al. 2020; Edtbauer et al. 2021). On the other hand, phyllospheric emissions, originating from the leaf surface, also contribute to BVOC emissions, with processes like oxidation and adsorption/desorption playing significant roles (Kembel et al. 2014; Koskella 2020; Farré-Armengol et al. 2016; Kesselmeier et al. 1999; Rundell et al. 2015). These compounds range from short-chain methanol (with C1) to longer-chain hemiterpenes like isoprene (with C5), terpenes like monoterpenes (MTs, with C10), sesquiterpenes (SQTs, with C15), and diterpenes (DTs, with C20) exhibiting a wide array of functional groups (Kesselmeier and Staudt 1999; Heiden et al. 1999; Guenther 2013; Yáñez-Serrano et al. 2020). Among BVOCs, terpenoids, including hemiterpenes, have garnered considerable attention in ecophysiology studies (Llusià and Peñuelas 2000; Peñuelas et al. 2005; Owen and Peñuelas 2005; Yáñez-Serrano et al. 2018; Misztal et al. 2015).

The production and release of BVOCs are influenced by both biotic and abiotic factors. Biotic factors involve interactions with other organisms (Kegge and Pierik 2010), while abiotic factors include environmental conditions like air temperature, humidity, light intensity, water availability, and seasonal variations (Dement et al. 1975; Tingey et al. 1980; Hansted et al. 1994; Llusià and Peñuelas 1999; Staudt and Seufert 1995; Loreto et al. 1996; Seufert 1997; Jardine et al. 2020; Peñuelas and Llusià 1997, 1999). Air temperature, particularly crucial for regulating BVOC emissions, affects enzymatic reactions involved in BVOC biosynthesis and their diffusion in biological tissues (Llusià and Peñuelas 2000). Temperature not only influences the emission rates of MTs but also affects their composition, acting as a "thermometer" to measure these changes. Changes in monoterpene composition, especially the increase in β-ocimenes and the decrease in α-pinene, may reflect the response of plants to thermal stress and their ability to adapt to warmer conditions (Jardine et al. 2017). Additionally, air humidity, light intensity and quality, water availability, and seasonal changes contribute to the complex dynamics of BVOC production and emission (Kuhn et al. 2002; Holzinger et al. 2000; Jardine et al. 2015, 2020).
70

The impacts of these factors on BVOCs can vary depending on the specific climatic zone and the plant species present.

71

Notably, even within the same plant species, different populations or individuals can display adaptations to thrive in diverse climatic conditions, showcasing their capacity to adjust BVOC production and emission in response to environmental changes (Kigathi et al., 2019; Picazo-Aragonés et al., 2020).

72

73

74

BVOCs play essential ecological roles, including plant defense mechanisms, plant-insect interactions, and ecosystem
biodiversity maintenance (Raguso 2008; Farré-Armengol et al. 2015; Borges et al. 2008; Peñuelas and Llusià 2001;
Pichersky and Gershenzon 2002; Vickers et al. 2009). They can act as antioxidants, protect against oxidative stress, and aid
in coping with environmental stressors like heat damage (Sharkey and Singsaas 1995; Peñuelas and Llusià 2002; Loreto et
al. 2004; Munné-Bosch et al. 2004; Copolovici et al. 2005; Peñuelas et al. 2005; Medori et al. 2012; Centrito et al. 2014;
Salomon et al. 2016; Dumanovic et al. 2021), protecting cell membranes from peroxidation and reactive oxygen species
(Loreto and Velikova 2001; Loreto et al. 2004; Munné-Bosch et al. 2004; Llusià et al. 2005; Peñuelas and Munné-Bosch
2005; Salomon et al. 2016; Dumanovic et al. 2021), providing a competitive advantage in harsh environments. This
protective capacity of BVOCs would explain that, despite the adverse environmental conditions that negatively affect
photosynthesis and transpiration, it does not result in a reduction in the production and emission rates of BVOCs. Isoprene,
for instance, plays a crucial role in tropical forest survival under climatic stress (Taylor et al. 2018), underscoring the
ecological importance of BVOC emissions. The opportunistic emissions hypothesis sees these functions as evolved from
these volatile compounds once they are byproducts of primary metabolism (Peñuelas and Llusià 2004; Owen and Peñuelas
2005).

75

76

77

78

79

80

81

82

83

84

85

86

87

88

Moreover, BVOC emissions significantly affect atmospheric chemistry and climate by influencing aerosol formation, cloud formation, precipitation patterns, and temperature regulation (Andreae and Crutzen 1997; Singh and Zimmerman 1992; Kulmala et al. 2009; Peñuelas and Staudt 2010). They also have implications for air quality, reacting with other pollutants to form secondary pollutants like tropospheric ozone formation and particulate matter (Laothawornkitkul et al. 2009).

89

90

91

92

93

In tropical forests such as French Guiana's, terpene production and emission rates are likely to vary seasonally in response to temperature and water availability fluctuations. Considering their ecological significance in tropical forests and their influence on atmospheric chemistry and climate, coupled with the scarcity of information regarding their emissions from tropical plant species (Courtois et al., 2009, 2016; Alves et al., 2016; Mu et al., 2022; Bourtsoukidis et al., 2024), our study was prompted.

94

95

96

97

98

Thus, our objective is twofold: (i) to analyze terpene emissions from various tree species in French Guiana, including those that have not been previously studied (Table S8), and (ii) to investigate the influence of seasonality on the production and emission rates of any BVOCs, specifically comparing the dry and wet seasons.

100

101
102 **Materials and methods**

103 **Site description and sampling**

104 The screening campaign was conducted in French Guiana on the Guiana Shield, one of three South American cratons (Gibbs and Barron 1993) (Fig. 1) and part of the Amazonian rainforest, one of the largest undisturbed areas of tropical forest in the world (Hansen et al. 2013). This tropical region rests on a Precambrian geological substrate that is particularly low in phosphorus content, especially if compared to the generally younger, nutrient-rich soils of western Amazonia (Hammond 2005; Grau et al. 2017). Fieldwork was performed at two research stations, Nouragues (Bongers 2001) (04°05′N, 52°40′W) and Paracou (Gourlet-Fleury et al. 2004) (05°18′N, 52°53′W) in well-conserved old-growth tropical forests. Sampling was conducted in 2015 on May 28–June 11 in Paracou and June 14–July 1 in Nouragues (wet season), and on October 5–22 in Paracou and October 24–November 8 in Nouragues (dry season).

112 Mean annual air temperature is 26°C (Bongers 2001; Gourlet-Fleury et al. 2004), and precipitation is similar, although slightly lower in Paracou (annual average of 2990 and 3100 mm in Paracou and Nouragues, respectively; Bongers 2001; Aguilos et al. 2019).

115 The tropical climate of French Guiana is characterized by important interannual variability in the short dry seasons, with the amount of precipitation between August and November varying from 102.2 to 532.0 mm, and long wet seasons lasting from December to July, with cumulative annual rainfall varying from 1900 to 2800 mm (Aguilos et al. 2018). This is due to the north/south movement of the Inter-Tropical Convergence Zone (Aceituno et al. 2009).

119 Soil water content and nutrient availabilities vary with topographical position in this French Guianese tropical forests (Epron et al. 2006; Ferry et al. 2010; Stahl et al. 2011; Allié et al. 2015). Local spatial variation (less than 200 m) creates specific habitats that differ in terms of soil characteristics, aboveground vegetation (Sabatier et al. 1997) and forest structure (Baraloto et al. 2007; Allié et al. 2015) and dynamics (Ferry et al. 2010; Courtois et al. 2018).

123 Nouragues has sandy soils of variable depth originating from weathered granite (van der Meer and Bongers 1996), while Paracou has shale floors with pegmatite veins of a Precambrian metamorphic formation known as the Bonidoro series (Epron et al. 2006). The soils of both sites are classified as nutrient-poor Acrisols (FAO-ISRIC-ISSS 1998) (Nachtergaele et al. 2000).

127 The selected trees were among the most abundant and mature tree species in the two studied areas (Table S1, Verryckt et al. 2022). We also used a fully resolved and dated Bayesian phylogeny, previously derived at the sampling sites (Baraloto et al. 2012). In addition to the previously mentioned selection criteria, it was taken into account that they were adult trees and of a similar diameter depending on the species. Thirty-six tree species were included in the sampling. Among these, 32 species were sampled during the dry season, while 33 species were sampled during the wet season (Figures 2 and 3; Table S1 and S7). The number of samples per species is indicated in Table S7. Certain species could not be sampled during specific seasons. In the dry season, *Carapa surinamensis*, *Dipteryx odorata*, *Pouteria eugeniifolia*, and
Vochysia sabatieri were not sampled. In the wet season, *Tetragastris panamensis*, *Moronobea coccinea*, and *Symphonia globulifera* could not be sampled. This discrepancy arises because the leaves of these species were not in ideal conditions to be sampled (Table S7). Additionally, the species names were verified based on the list published in Stegee et al. (2019) (see Table S8). It should be noted that in this list, *Aniba roseaodora* appears as *A. rosiodora*, *Eugenia culcullata* as *E. cucullata*, and *Tetragastris panamensis* is not included.

To obtain the branches that were used for perform gas exchange measurements and collect BVOC samples, we collaborated with expert tree climbers to collect sunlit branches between 1 and 2 meters long. Two branches were cut from each sampled tree. To avoid cavitation, we immediately immersed approximately 20 cm of the cut end in water, cutting about 7 cm of the branch into the water. For transport to the laboratory, we carefully placed the harvested branches in plastic bags with damp paper (Verryckt et al. 2020ab). Throughout the sampling process, the branches remained submerged in water. Transport time from the forest to the laboratory varied depending on the location. In Nouragues it ranged between 20 and 30 minutes, while in Paracou it lasted between 1 and 2 hours. We studied the variation of the effects of branch excision and transport among branches at the different heights in the canopy. When the branch had acclimated to its new environmental conditions—which took on average 20 min—light-saturated leaf net photosynthetic rates did not significantly differ between the excised and intact branches. We therefore conclude that branch excision did not affect the measurement of gas exchange, provided that the branch is recut under water and is allowed sufficient time to acclimate to its new environmental conditions, as we did (Verryckt et al. 2020ab).

Upon arrival at the laboratory, we meticulously selected twigs with the seemingly healthiest leaves, following the procedure mentioned earlier. Subsequently, these selected twigs were recut underwater at the base to prevent cavitation and then immersed in plastic cups filled with water. To ensure stability during the acclimatization period, they were sealed inside transparent plastic bags for approximately 24 hours at 23-25 °C (Niinemets et al. 2005, 2009; Llusià et al. 2010a, 2014). For VOC sampling, three twigs were collected from each branch as replicates. Thus, a total of 6 twigs per tree were sampled. All leaf handling steps were carried out with utmost care to avoid causing wounds or other alterations that could lead to artifacts in VOC emission determination. Tests were conducted to compare the response of leaves on cut branches with those on uncut branches, and it was observed that the differences in photosynthetic activity and transpiration were not significant (Verryckt et al. 2020a, 2021).

Furthermore, samples without leaves were taken, thus characterizing the contribution of VOCs from the sampling system. These samples obtained from the system were used as blanks, subtracted from those obtained with leaves in the calculations described later on.

163

164

165
166 Soil water content and soil temperature

167 Soil water content and temperature were measured in the same BVOC sampling period, at a depth of 10 cm at five points in
168 the 50x50 m tree sample plots. Soil moisture was measured with an HH2 soil moisture meter connected to an ML2x soil
169 moisture sensor (Delta-T Devices Ltd, Cambridge, England), while soil temperature was measured with a digital soil
170 thermometer (TO 15, Jules Richard instruments, Argenteuil, France) (Table S2).

171

172 Sampling of BVOC emissions

173 Measurements of BVOC emissions were conducted in the laboratory on a pre-cut branch with attached leaves, as
174 previously mentioned. These measurements were carried out using a Licor-6400XT gas-exchange system coupled with a
175 leaf chamber equipped with environmental control capabilities.

176 All tubes and accessories used for BVOC sampling were constructed of PFA Teflon (Cole Parmer, USA).
177 Hydrocarbon-free ambient air was delivered to the gas inlet of the LI-6400XT using a capillary-grade hydrocarbon trap
178 (Restek, USA). BVOC emissions were measured at a quantum flux density of 1000 µmol m⁻² s⁻¹ under standard
179 temperature conditions (30°C) with controlled CO₂ concentrations of 400 ppm. Given that, all tree species had leaves with a
180 surface area greater than that of the chamber surface; the leaves were clamped on an area of the limb without prominent
181 ribs. The 6400-40 is designed with a uniform, integrated LED light source and PAM fluorimeter that easily attaches to the
182 LI-6400XT sensor head, giving the user complete control of the environment surrounding the 2-cm² leaf area. The flow in
183 the cuvette was an average of 675 ml min⁻¹ in the two seasons.

184 The air exiting the cuvette was pumped through custom-made sampling tubes, comprised of stainless steel tubes (89
185 mm in length and 6.4 mm in external diameter), which were equipped with adsorbents (115 mg of Tenax® TA and 230 mg
186 of SulfiCarb®). These tubes were separated by sorbent-retaining springs, fixed using gauze-retaining springs, and sealed
187 with airtight caps (Markes International Inc., Wilmington, USA). Air samples were collected using a Qmax air-sampling
188 pump (Supelco, Bellefonte, Pennsylvania). The flow was measured with a Bios Defender 510 flowmeter (Bios International
189 Corporation, Butler, USA) and adjusted with a valve. The sampling time was 20 min and the flow was 360 ± 3 mL min⁻¹.
190 The hydrophobic properties of the activated adsorbents minimized any sample displacement by water. The terpenes were
191 not chemically transformed in these tubes, as demonstrated by reference to trapped standards (α-pinene, β-pinene,
192 camphene, myrcene, *p*-cymene, limonene, sabinene, camphor, α-humulene and dodecane). Prior to terpene sampling, the
193 tubes were conditioned twice for 30 min at 350°C with a stream of 100 mL min⁻¹ of purified helium. The trapping and
194 desorption efficiency of standards such as α-pinene, β-pinene and limonene was 99%. Blank samples of air with no plants
195 in the cuvette were collected in the tubes for 20 min immediately before each measurement. The terpene content of the
196 blank samples was subtracted from the samples collected from plants in order to calculate the rates of terpene emission.
All the leaves used for VOC sampling were collected and the specific leaf area (SLA) was obtained by dividing the fresh leaf area by its dry weight. Leaf area was measured with the LI-3100C Leaf Area Meter (LI-COR, Lincoln, NE, USA), after which the leaves were dried for at least 48 h and weighed.

200

## BVOC analysis

The emitted BVOCs trapped in the sorbent tubes were sampled using an automatic sample processor (TD Auto sampler, Series 2 Ultra, Markes International Inc. Wilmington, USA) and thermally desorbed using a coupled injector with a cryotrap (Unity, Series 2, Markes International Inc. Wilmington, USA) connected to a Gas Chromatograph (7890A, Agilent Technologies, Santa Clara, USA) with a mass spectrometer detector (5975C inert MSD with Triple-Axis Detector, Agilent Technologies). A full-scan (between 35 to 350 m/z) method was used in the chromatographic analyses.

Pre-desorption conditions consisted of a pre-purge time of 0.1 min, with a split of 20 mL min⁻¹, and a dry purge of 2 min. Then, BVOCs were desorbed with a flow path temperature of 200 °C, minimum carrier pressure of 0.5 KPa, and a GC cycle time of 30 min, optimal time to recover maximum sample; the standby split was 25 mL min⁻¹. Sample desorption time was 30 min at 320 °C with the trap maintained in-line, with a flow rate of 50 mL min⁻¹ and a split of 2 mL min⁻¹; the cryotrap low temperature was -25 °C. Prior to heating, traps were held in a pre-cryotrap fire purge for 2 min. The cryotrap flow rate was 50 mL min⁻¹, with a split of 10 mL min⁻¹, and the heating rate was 40 °C s⁻¹ to a cryotrap high of 320 °C maintained for 7 min, with a split of 5 mL min⁻¹.

Then, the cryofocused desorbed samples were injected into a GC column (Agilent Tech., HP 5MS, 30 m x 0.25 µm x 0.25 mm) using a transfer line at 250°C. Following sample injection at 35 °C (initial time: 3 min), the column temperature was increased stepwise by 15 °C min⁻¹ to 150 °C, by 50 °C min⁻¹ to 250 °C for 5 min, and by 30 °C min⁻¹ to 280 °C for 5 min, and was maintained at each time for 5 min. The total run time was 30 min, the helium column flow rate was 1 mL min⁻¹.

219

## Terpene identification and quantification

Terpene identification was performed by comparing the derived mass spectra with published results (Wiley275 and Nist05a libraries) and known standards such as those mentioned below for quantification. Quantification of peaks was conducted using the fragmentation product with mass 93 (Blanch et al. 2012; Llusià et al. 2012; Hellén et al. 2024), while calibration curves were prepared using commercial standards for some of the most abundant recorded compounds: four monoterpenes (α-pinene, 3-carene, β-pinene and limonene) and one sesquiterpene (α-caryophyllene) (Fluka Chemie AG, Buchs, Switzerland). These standards were adsorbed on cartridges similar to those used for the samples by means of a valve coupled to the chromatograph and a flow of Helium 5.0 like the one used for the flows generated by the Qmax pump. They
228 were then desorbed and analysed following the same protocol as used for the samples. Terpene calibration curves for
229 signals and concentrations were always highly correlated ($r^2 \ge 0.95$) and the sensitivity of the most abundant terpenes were
230 similar (differences were < 5%). The response factor for the MTs was an average of the standard MTs and only that of the
231 $\alpha$-caryophyllene for the sesquiterpenes. We estimate a 5% error in the quantification given by the response variation of
232 each standard with respect to each other. For isoprene, we used a Linde gas standard (1 ppm) of which we made three
233 dilutions to obtain its calibration curve.

234 To prepare the liquid standards, three different dilutions were made: 1 µL of the pure standard was diluted in 1000 µL
235 of pentane and then 100 µL of this standard were taken and diluted in another 1000 µL of pentane. From this second
236 dilution another 100 µL were taken and diluted in 1000 µL of pentane.

237 In addition, we also prepared standards from a standard at 500 ppb of a 50-L bottle (Reimer Environmental, Inc.,
238 Miami, USA). We injected 15, 25 and 35 mL into three sampling tubes using the same valve as mentioned above. In each
239 sequence (of 30 tubes) of analysis, a series of three standards (one for each concentration) of the gas standard were added at
240 the beginning, and at the end of series 3 (one for each concentration) of the liquid standard (previously gassed). To avoid
241 interference in samples due to contamination, the standards were arranged from lowest to highest concentrations. In
242 addition, the analysis of the sequences always started with an empty tube followed by a tube with the same adsorbents
243 taken from the field but not sampled to test for possible contamination during the process.

244 To calculate the micrograms (µg) of terpenes per gram (g) of dry matter and per hour, we used the following formula:
245 [(AUs / svs) – (AUb / svb)] x [(rf x Fch x 60 min) / (AUrf x g d.m. x st)] Equ. 1.

246 In this equation, the variables represent the following:

247 • AUs and Aub: Arbitrary units of area of the air sampled from the cuvette and of the blank air sample (area units).

248 • Svs and svb: Volume of air sampled from the cuvette with leaves and as blank (milliliters, mL).

249 • rf: Response factor calculated from the calibration curves (micrograms, µg).

250 • Fch: Flow rate in the sampling chamber (milliliters per minute, mL min⁻¹).

251 • AUrf: Arbitrary units of area corresponding to the response factor (arbitrary units).

252 • g d.m.: Grams of dry matter (g).

253 • st: Sampling time (minutes, min).

254 The Shapiro-Wilk test (N > 30) showed that the data of the variables (i.e. emissions of total BVOCs, monoterpenes and
255 sesquiterpenes) were normally distributed (P > 0.05).

257 We used Bayesian phylogenetic linear mixed-effects models implemented in the MCMCglmm R package (Hadfield
258 2010) (Table S6) to test for the effects of season while controlling for the potential effects of intraspecific plasticity and
phylogenetic ancestry on the foliar variables. In these analyses season was included as a fixed factor, and phylogenetic relationships and species identities as random factors. The phylogenetic term accounted for the variability related with shared ancestry, while the species term accounted for species-specific traits independent of shared ancestry. Thus, both random factors accounted for the variance explained by heritability and by the plastic expression of species' emission capacities.

We computed the phylogenetic signal as Pagel's λ to assess the importance of phylogenetic ancestry on the emission of BVOCs. The corresponding *P*-values were based on the variance in phylogenetically independent contrasts relative to tip-shuffling randomization, as implemented in the *phylosig* function in the R *phytools* package (Revell 2012). Pagel's λ (1999) provides a quantitative phylogenetic measure in which λ is a scaling parameter for the correlations between species in relation to the correlation expected under Brownian evolution. λ has a natural scale between zero (no correlation between species) and 1.0 (correlation between species equal to the expected Brownian correlation). λ itself is not a correlation but, rather, a scaling factor for a correlation, so λ > 1.0 is theoretically possible. However, depending on the structure of the tree, λ >> 1.0 is not usually defined.

Terpene emission rates were expressed as µg g⁻¹ d.m. h⁻¹.

273

## 274 Results

275 Environmental conditions

The French Guiana monthly average rainfall in 2015 was 237 ± 44 mm during the wet season (December–August) and 47.5 ± 11.1 mm during the dry season (September–November), with the maximum rainfall falling in May (532 mm) and the minimum in October (33 mm). The field campaign during the dry season was conducted with 32.8 mm of rainfall. Mean air temperature during the rainy season was 27–28°C, with a maximum of 28°C in December. During the dry season the maximum temperatures were 28–28.5°C, with minimum temperatures recorded in February (26.5°C). The overall air temperature remains steady throughout the year in French Guiana.

Soil water content and temperature values correspond to measurements made in the experimental plots. The average soil water content was 20.2 ± 0.3% in the dry season and 32.3 ± 0.2% in the wet season (Fig. 1 and Table S2). The average soil temperature in the dry season was 26.5 ± 0.1°C and in wet season 23.7 ± 0.01°C (Fig. 1 and Table S2).

285

286 BVOC emission rates

Total BVOC emissions varied from 0.01 to 80.9 µg g⁻¹ d.m. h⁻¹ in the dry season and from 0 to 11.7 µg g⁻¹ d.m. h⁻¹ in the wet season, indicating considerable variation based on environmental conditions (Fig. 2, 3, 4, and S1, and Table S3 and S4). The values for total BVOCs they were 5.7 ± 0.6 and 1.3 ± 0.7 µg g⁻¹ d.m. h⁻¹ while, for total terpenes were 5.4 ± 0.6 and 0.5 ± 0.7 µg g⁻¹ d.m. h⁻¹, in dry and wet season respectively. The majority of both total BVOCs and terpenes were

290
mainly emitted during the dry season (see Figs. 4 and S1). These differences were statistically significant, with ANOVA analysis showing P < 0.0001. Sample sizes were 285 in the dry season and 219 in the wet season. Of the monoterpenes, the most abundant were α-terpinolene, limonene, α-pinene, t-β-ocimene and sabinene. Of the sesquiterpenes, β-caryophyllene, α-caryophyllene and α-copaene were observed during the dry season, while during the wet season, α-terpinolene predominated, followed by limonene, α-pinene, sabinene, β-caryophyllene and α-copaene (Figs. 3A, 4 and Table S3). Isoprene was detected in most of the species studied in both seasons (Figs. 3B, 4 and S1, and Table S3). However, in three tree species (*Gustavia hexapétala* (1.8 ± 1.6 vs 0 ± 0 µg g⁻¹ d.m. h⁻¹), *Eugenia culcullata* (3.1 ± 1.1 vs 0.4 ± 0.1 µg g⁻¹ d.m. h⁻¹) and *Dycorinia guianensis* (1.2 ± 0.8 vs 0 ± 0 µg g⁻¹ d.m. h⁻¹)) was significantly higher in the wet season than in the dry season (P < 0.01). Only *Aniba rosaeodora* emitted more isoprene in the dry season than in the wet season (2.2 ± 2.0 vs 0 ± 0 µg g⁻¹ d.m. h⁻¹) (Fig. 3B).

Among the BVOCs detected, the main non-terpenoid compounds were 2,2,4,6,6-pentamethyl heptane (with no detected emissions in the dry season and 0.3 ± 0.1 µg g⁻¹ d.m. h⁻¹ in the wet season) and toluene (0.1 ± 0.02 µg g⁻¹ d.m. h⁻¹ in the dry season and 0.012 ± 0.007 µg g⁻¹ d.m. h⁻¹ in the wet season) (Fig. 4 and Table S4). Notably, 2,2,4,6,6-pentamethyl heptane exhibited a strong correlation with isoprene during the wet season (r² = 0.23, P < 0.0001, N = 219), while toluene showed a correlation with α-pinene during the dry season (r² = 0.15, P < 0.01, N = 285).

The emission rates of the terpenes and toluene followed a similar pattern to the total BVOCs, except for 2,2,4,6,6-pentamethyl heptane, which was primarily emitted during the wet season (Fig. 4 and Table S4). Among the emitted BVOCs, α-terpinolene, limonene, α-pinene, t-β-ocimene (MT), β-caryophyllene, and α-caryophyllene (SQT) were the most abundant, especially in the dry season (Fig. 3A and 4). Additionally, there was a group of unidentified sesquiterpenes emitted, collectively surpassing the previously mentioned BVOCs, also in the dry season (Fig. 3A).

Figure 2 displays all the tree species studied along with their average terpene emissions during both the dry and wet seasons. Among these species, 27.6% were classified as high terpene emitters, 51.7% as intermediate emitters, and 20.7% as low emitters. The remaining species were categorized as very low emitters (Fig. 2A). Notably, 90.6% of the species emitted terpenes during the dry season, whereas only 36.4% emitted terpenes during the wet season. The percentages for monoterpenes mirrored those of the total terpenes. However, sesquiterpenes were emitted by 75% of the species in the dry season and only by 15.6% in the wet season (Figs. 2 and 3).

Specifically, 2,2,4,6,6-pentamethyl heptane was emitted by 31.3% of the tree species exclusively during the wet season, while toluene was emitted by 37.5% of the species during the dry season and by 6.3% of the species during the wet season (Table S4). Monoterpenes generally predominated over sesquiterpenes, except in the case of the tree species *Eperua grandiflora* (Fig. 2B, C). Notably, a significant phylogenetic signal, as assessed by Pagel's λ, was observed only for sesquiterpenes (Table S5).
322

Discussion

323

324

325

326

327

328

329

330

331

332

333

334

335

336

337

338

339

340

341

342

343

344

345

346

347

348

Our results emphasized the species-specificity of BVOC emissions and the varying tree species responses to seasonal and environmental conditions (Gomes-Alves et al. 2022; Khun et al. 2002; Mishra and Sinha 2020). The majority of the species emitted terpenes, isoprene, and other BVOCs (Figs. 2 and 3; Table S3). However, the emitted quantities were relatively low compared to similar studies in other ecosystems such as the Mediterranean forests (Llusià et al. 2013) but comparable to those observed in analogous tropical environments (Llusià et al. 2010a, 2014). In the Amazon rainforest, various studies have explored BVOC emissions and their fluctuations. Jardine et al. (2015) studied the speciation of 12 monoterpenes and their vertically resolved ambient air mixing ratios in a central Amazon rainforest and their reactive potential of some of them. Specifically, they observed the highly reactive cis-β-ocimene (160 ppt), trans-β-ocimene (79 ppt) and terpinolene (32 ppt), which represented approximately 21% of the total monoterpene composition and 55% of the rate of ozonolysis of monoterpenes from the upper part of the canopy. Leaf-level emissions of highly reactive monoterpenes accounted for up to 1.9% of photosynthesis, confirming light-dependent emissions in several genera of Amazonian trees, corroborating the present study accounting the qualitatively results. Jardine et al. (2017) utilized monoterpenes as an indicator to gauge the central Amazon rainforest's response to climate warming and found that monoterpene emissions increase with temperature, especially β-ocymene, corroborating our results of higher emissions in the dry season (Figs. 3A, 4, S1 and Tables S3 and S4). And in another study (Yáñez-Serrano et al., 2018), conducted in the Amazon rainforest, the chemical speciation of monoterpenes, was investigated using samples collected during the dry season of October 2015 at the Amazon Tall Tower Observatory (ATTO). A distinct differentiation in chemical composition between day and night was found, with α-pinene being more abundant during the day and limonene predominating at night. Reactivity calculations revealed that higher abundance does not always correlate with greater reactivity, and modeling simulations indicated the need for further research to fully understand the processes of monoterpene exchange in the tropical forest canopy. This study highlights the importance of chemical speciation in understanding the role of monoterpenes in atmospheric chemistry and the carbon cycle in tropical forest ecosystems. Furthermore, Byron et al. (2022) investigated the chemical speciation of chiral monoterpenes in a tropical rainforest ecosystem, revealing distinct diel emission peaks and shifts in emissions in response to drought conditions. Their findings emphasize the importance of considering enantiomeric distribution in understanding monoterpene emission mechanisms and predicting atmospheric feedbacks in forest ecosystems, which complements our understanding of BVOC emissions.

349

350

351

352

353

Gomes-Alves et al. (2022) investigated the variability of isoprenoid emission patterns, including isoprene, in Amazonian ecosystems in response to ecophysiological and environmental factors. They conducted measurements of isoprenoid emission capacities across seasons and environmental gradients for three dominant tree species in the central Amazon. Contrary to the common perception that isoprene emissions predominantly occur under water stress and high temperatures, their results align with those of Gomes-Alves et al. (2022), who documented higher isoprene emissions
354

355

356

357

358

359

360

during the wet season, challenging previous assumptions (Taylor et al. 2018) across all tree species. They suggested that the decreased emissions during the dry season could represent a plastic response to escalating abiotic stress, such as heat and drought, coupled with reduced substrate availability for isoprenoid synthesis. The study proposed that shifts in emission composition, characterized by elevated isoprene emissions during the wet season, might serve as a physiological adaptation to optimize plant performance under prevailing wet season conditions. These findings contrast with the higher terpene emissions observed in the driest and hottest seasons, indicating potential differences in emission behavior between isoprene and other isoprenoids, necessitating separate consideration in seasonal emission studies.

361

362

363

364

365

366

367

368

369

In their study, Gomes-Alves et al. (2022) noted a significant decrease in isoprenoid emission capacity during the transition from the wet to the dry season, coinciding with heightened abiotic stress due to heat and drought in the Amazon rainforest. Moreover, they observed an increase in emissions of heavier isoprenoids, such as monoterpenes and sesquiterpenes, during this seasonal transition, suggesting a plastic response of plants to changing conditions. This adaptation in the composition of isoprenoid emissions may represent a strategy to mitigate abiotic stress and sustain essential plant functions. Additionally, previous research has demonstrated the variability of plant responses in isoprenoid emission rates in relation to climatic and ecological factors (Staudt et al. 2017). It has also been observed that moderate drought can lead to an increase in isoprenoid emission rates as plants adapt to water stress (Dani et al., 2014). However, under conditions of extreme drought, these rates have been shown to decline substantially (Llusià and Peñuelas, 1998).

370

371

372

373

374

375

Furthermore, the study by Byron et al. (2022) examined the response of monoterpene emissions to drought in a tropical rainforest ecosystem. They found that, during a controlled drought experiment, monoterpene emissions exhibited distinct diurnal peaks and changes in the composition of α-pinene enantiomers. Additionally, as drought progressed, the emission source of (-)-α-pinene shifted towards storage pools, promoting cloud formation. This alteration in monoterpene emission composition may be linked to the plant's ability to adapt to water and thermal stress, supporting the hypothesis of a plastic response to drought.

376

377

378

379

In summary, these findings suggest that plants can adjust their terpene emissions, including isoprenoids, as an adaptive strategy to cope with abiotic stress during the dry season in tropical rainforests. The ability to modulate the composition of terpene emissions could have significant implications for atmospheric chemistry and climate feedback processes in these ecosystems.

380

381

382

383

384

Given the present climate change scenario with altered rainfall patterns (Dore 2005), and recognizing that moderate drought conditions amplify BVOC emissions (Niinemets 2010), a negative feedback effect might occur, particularly regarding increased aridity. During moderate drought conditions, heightened terpenes in the atmosphere could potentially enhance rainfall, alleviating, to some degree, the detrimental impacts of climate change in these areas (Llusià and Peñuelas 1998; Llusià et al. 2006, 2008, 2010b; Blanch et al. 2007, 2009).
385

386

387

388

389

390

391

392

393

394

395

396

397

398

399

400

401

402

403

404

405

406

407

408

409

410

411

412

413

414

415

416

It is noteworthy that non-terpene compounds like toluene and 2,2,4,6,6-pentamethyl heptane were detected (Heiden et al. 1999; Zhiqun et al. 2017; Misztal et al. 2015). α-Pinene emission rates also showed a correlation with these factors, especially during the dry season (Fig. 4). This study also presents the first report of 2,2,4,6,6-pentamethyl heptane emission from the leaves of several tropical tree species (Khun et al. 2002; Courtois et al. 2009). This BVOC is known to have allopathic effects, implying a role in plant defense (Zhiqun et al. 2017).

BVOC emissions are thus sensitive to taxonomy and environmental factors, including temperature, light, and moisture availability. Considering the increasing occurrence of drought periods in tropical areas due to climate change, understanding the potential implications for BVOC emissions is crucial. Drought stress can significantly affect plant physiology and metabolism, potentially altering the quantity and composition of BVOC emissions.

The findings of this study contribute to the characterization of BVOC emissions from some tropical tree species and, therefore, to our understanding of the complex interactions between climate change, drought, tree species and BVOC emissions. By considering the potential effects of drought on BVOC emissions and their implications for atmospheric chemistry and climate processes, we can develop a more comprehensive understanding of the role of BVOCs in the context of climate change and its impact on drought periods in tropical areas (Dore 2005; Fubao et al. 2018).

## Conclusions and final remarks

This study reports the results of the emissions of different BVOCs by 36 tree species in the tropical forests of French Guiana and confirms that there are significant seasonal differences, on average, for BVOCs emitted. On average, emissions in the dry season were higher than in the wet season; as well, the proportion of each type of BVOCs in each season was found to be different. Species' shared ancestry had a significant effect on sesquiterpene (Liang et al. 2021) emissions but not on the total terpenes or monoterpenes.

This study provides strong evidence of higher rates of foliar terpene emissions from tropical trees in the dry season than in the wet season. Our results underscore the potential role of this variation in the capacity of terpene emissions to act as a buffer effect on climate change (Engelhart et al. 2008). More BVOC emissions under increased drought could partly counteract the severity of droughts by favoring cloud formation and precipitation (Jardine et al. 2020).

As these compounds have important roles in atmospheric chemistry, aerosol formation, and plant-atmosphere interaction, further research in this field will help improve our understanding of biogeochemical processes and address important issues related to climate change and air quality.

## Authorship contribution statement

AG-G Manuscript review. CS, DA, GP, LB and RO Support in field work and manuscript review. EC, IU, LVL and OG Support in field work. IAJ Planning and development of the experiment, supervision of the collection of the samples. IF
417

418

419

420

421

422

423

Planning and development of the experiment. Manuscript review. **JLI** Collection of samples of BVOCs and their analysis and writing of the document. **JP** Planning and development of the experiment, supervision of the collection of the samples and analyses and manuscript review. **JS** Planning and development of the experiment, supervision of the collection of the samples. Analysis of the Bayesian phylogeny. Manuscript review. **LTV** Support in field and laboratory work, manuscript review. All authors read and commented on the paper.

423

## Acknowledgements

424

425

426

427

428

429

430

431

This research was supported by the Spanish Government project TED2021-132627B-I00 funded by MCIN, AEI/10.13039/501100011033 and by the European Union NextGenerationEU/PRTR, Fundación Ramón Areces project CIVP20A6621, the Catalan Government project SGR2021-1333, and the ERC Synergy project SyG-2013-610028 IMBALANCE-P. We would like to thank staff at the Nouragues research station, managed by USR mixte LEEISA (CNRS; Cayenne), and the Paracou research station, managed by UMR Ecofog (CIRAD, INRAE; Kourou). Both of these research stations receive support from *Investissement d'Avenir* grants managed by Agence Nationale de la Recherche (CEBA: ANR-10-LABX-25-01, ANAEE-France: ANR-11-INBS-0001). We are also grateful to Anna Escolà and Pere-Roc Fernández for their dedicated work as field and laboratory technicians in French Guiana.

432

433

## Declarations

434

435

**Conflict of interest** The authors declare that they have no known competing financial interests or personal relationships that could influence the work reported in this paper.

436

437

## References

438

439

Aceituno P, Prieto MR, Solari ME, Martínez A Poveda G. and Falvey M (2009) The 1877-78 El Niño episode: Climate anomalies in South America and associated impacts. Climatic Change 92:389-416

440

Aguilos M, Hérault B, Burban B, Wagner F, Bonal D (2018) What drives long-term variations in carbon flux and balance in a tropical rainforest in French Guiana? *Agr Forest Meteorol* 253:114-123.
https://doi.org/10.1016/j.agrformet.2018.02.009

441

442

Aguilos M, Stahl C, Burban B, Hérault B, Courtois E, Coste S, et al. (2019) Interannual and seasonal variations in ecosystem transpiration and water use efficiency in a tropical rainforest. *Forests* 10:14.
https://doi.org/10.3390/f10010014

444

445

446

Allié E, Pélissier R, Engel J, Petronelli P, Freycon V, Deblauwe V, Soucémarianadin L, Weigel J, Baraloto C (2015) Pervasive local-scale tree-soil habitat association in a tropical forest community. *PLoS One*, 10(11), e0141488

447
448 Alves EG, Jardine K, Tota J, Jardine A, Yánez-Serrano AM, Karl T, Tavares J, Nelson B, Gu D, Stavrakou T, Martin S,
449 Artaxo P, Manzi A, Guenther A (2016) Seasonality of isoprenoid emissions from a primary rainforest in central
450 Amazonia. Atmos Chem Phys 16(6):3903-3925
451 Andreae MO, Crutzen PJ (1997) Atmospheric aerosols: Biogeochemical sources and role in atmospheric chemistry.
452 Science 276:1052-1058
453 Baraloto C, Hardy OJ, Paine CET, Dexter KG, Cruaud C, Dunning LT, Gonzalez MA, Molino JF, Sabatier D, Savolainen
454 V, Chave J (2012) Using functional traits and phylogenetic trees to examine the assembly of tropical tree communities. J
455 Ecol 100(3):690-701. https://doi.org/10.1111/j.1365-2745.2012.01966.x
456 Baraloto C, Morneau F, Bonal D, Blanc L, Ferry B (2007) Seasonal water stress tolerance and habitat associations within
457 four neotropical tree genera. Ecology 88:478-489
458 Blanch J, Peñuelas J, Llusià J (2007) Sensitivity of terpene emissions to drought and fertilization in terpene-storing Pinus
459 halepensis and non-storing *Quercus ilex*. Physiol Plantarum 131:211-225.
460 Blanch J, Peñuelas J, Sardans J, Llusià J (2009) Drought, warming and soil fertilization effects on leaf volatile terpene
461 concentrations in *Pinus halepensis* and *Quercus ilex*. Acta Phys Plant 31:207-218
462 Blanch S, Sampedro L, Llusià J, Moreira X, Zas R, Peñuelas J (2012) Effects of phosphorus availability and genetic
463 variation of leaf terpene content and emission rate in *Pinus pinaster* seedlings susceptible and resistant to the pine weevil,
464 *Hylobius abietis*. Plant Biol 14:66-72. https://doi.org/10.1111/j.1438-8677.2011.00492.x
465 Bongers F (2001) Nouragues: dynamics and plant-animal interactions in a Neotropical rainforest. Berlin: Springer
466 Borges RM, Bessière JM, Hossaert-McKey M (2008) The chemical ecology of seed dispersal in monoecious and dioecious
467 figs. Funct Ecol 22(3):484-493
468 Bourtsoukidis E, Behrendt T, Yáñez-Serrano AM, Hellén H., Diamantopoulos E., Catão E., ... Williams J (2018) Strong
469 sesquiterpene emissions from Amazonian soils. Nature communications 9(1): 2226
470 Bourtsoukidis E, Pozzer A, Williams J, Makowski D, Peñuelas J, Matthaios VN, ... Sciare J (2024) High temperature
471 sensitivity of monoterpene emissions from global vegetation. Communications Earth & Environment 5(1): 23
472 Byron J, Kreuzwieser J, Purser G, van Haren J, Ladd SN, Meredith LK, ...Williams J (2022) Chiral monoterpenes reveal
473 forest emission mechanisms and drought responses. Nature 609: 307-312
474 Centritto M, Haworth M, Marino G, Pallozzi E, Tsonev T, Velikova V, Nogues I, Loreto F (2014) Isoprene emission aids
475 recovery of photosynthetic performance in transgenic Nicotiana tabacum following high intensity acute UV-B exposure.
476 Plant Sci 226:82-91
477 Copolovici LO, Filella I, Llusià J, Niinemets Ü, Peñuelas J (2005) The capacity for thermal protection of photosynthetic
478 electron transport varies for different monoterpenes in *Quercus ilex*. Plant Physiol 139: 485-96
479 Courtois EA, Paine CE, Blandinieres PA, Stien D, Bessiere JM, Houel E, Baraloto C, Chave J (2009) Diversity of the volatile organic compounds emitted by 55 species of tropical trees: a survey in French Guiana. J chem ecol 35(11): 1349-1362

482 Courtois EA, Dexter KG, Paine CET, Stien D, Engel J, Baraloto C, Chave J (2016) Evolutionary patterns of volatile terpene emissions across 202 tropical tree species. Ecol Evol 6(9): 2854-2864

484 Courtois EA, Stahl C, Van den Berge J, Bréchet L, Van Langenhove L, Richter A, Urbina I, Soong JL, Peñuelas J, Janssens IA (2018) Spatial variation of soil CO₂, CH₄ and N₂O fluxes across topographical positions in tropical forests of the Guiana Shield. Ecosystems 21(7): 1445-1458

487 Dani KGS, Jamie IM, Prentice IC, Atwell BJ (2014) Increased ratio of electron transport to net assimilation rate supports elevated isoprenoid emission rate in eucalypts under drought. Plant Physiology 166(2): 1059-1072

489 Dement WA, Tyson BJ, Mooney HA (1975) Mechanism of monoterpene volatilization in Salvia mellifera. Phytochemistry 14(12):2555-2557

491 Dore MH (2005) Climate change and changes in global precipitation patterns: what do we know? Environ int 31(8): 1167-1181

493 Dumanović J, Nepovimova E, Natić M, Kuca K, Jaćević V (2021) The significance of reactive oxygen species and antioxidant defense system in plants: A concise overview. Front Plant Sci 11: 552-969

495 Edtbauer A, Pfannerstill EY, Pires FAP, Barbosa CGG, Rodriguez-Caballero E, Zannoni N, Alves RP, Wolff S, Tsokankunku A, Aptroot A, Oliveira Sá M de, Araújo AC de, Sörgel M, Mota de Oliveira S, Weber B Williams J (2021) Cryptogamic organisms are a substantial source and sink for volatile organic compounds in the Amazon region. Commun Earth Environ 2(1): 1-14

499 Engelhart GJ, Asa-Awuku A, Nenes A, Pandis SN (2008) CCN activity and droplet growth kinetics of fresh and aged monoterpene secondary organic aerosol, Atmos Chem Phys 8:3937-3949. https://doi.org/10.5194/acp-8-3937-2008

501 Epron D, Bosc A, Bonal D, Freycon V (2006) Spatial variation of soil respiration across a topographic gradient in a tropical rain forest in French Guiana. J Trop Ecol 22:565-74. https://doi.org/10.1017/S0266467406003415

503 FAO-ISRIC-ISSS (1998) World reference base for soil resources. FOOD AND AGRICULTURE ORGANIZATION OF THE UNITED NATIONS Rome 1998. 84 World Soil Resources Reports. International Society of Soil Science ISSS-AISS-IBG. International Soil Reference and Information Centre ISRIC. Food and Agriculture Organization of the United Nations. M-41. ISBN 92-5-104141-5

507 Farré-Armengol G, Filella I, Llusià J, Peñuelas J (2015) Relationships among floral VOC emissions, floral rewards and visits of pollinators in five plant species of a Mediterranean shrubland. Plant Ecol Evol 148: 90-99 (Supplementary materials).
Farré-Armengol G, Filella I, Llusia J, Peñuelas J (2016) Bidirectional interaction between phyllospheric microbiotas and plant volatile emissions. Trends Plant Sci 21(10): 854-860. https://doi.org/10.1016/J.TPLANTS.2016.06.005

Ferry B, Morneau F, Bontemps JD, Blanc L, Freycon V (2010) Higher tree falls rates on slopes and waterlogged soils result in lower stand biomass and productivity in a tropical rain forest. J Ecol 98(1): 106-116

Fubao S, Roderick ML, Farquhar GD (2018) Rainfall statistics, stationarity, and climate change. Proceedings of the National Academy of Sciences 115.10: 2305-2310

Gibbs AK, Barron CN (1993) The geology of the Guiana Shield. Oxford: Oxford University Press

Gomes-Alves E, Taylor T, Robin M, Pinheiro Oliveira D, Schietti J, Duvoisin Júnior S, Zannoni N, Williams J, Hartmann C, Gonçalves JFC, Schöngart J, Wittmann F, Piedade MTF (2022) Seasonal shifts in isoprenoid emission composition from three hyperdominant tree species in central Amazonia. Plant Biol 24(5): 721-733

Gourlet-Fleury S, Guehl JM, Laroussinie O (2004) Ecology and management of a Neotropical rainforest. Lessons drawn from Paracou, a long-term experimental research site in French Guiana. Paris: Elsevier. ISBN 2-84299-455-8

Grau O, Peñuelas J, Ferry B, Freycon V, Blanc L, Desprez M, Baraloto C, Chave J, Descroix A, Dourdain A, Guitet S, Janssens IA, Sardans J, Hérault B (2017) Nutrient-cycling mechanisms other than the direct absorption from soil may control forest structure and dynamics in poor Amazonian soils. Sci Rep-UK 7:45017. https://doi.org/10.1038/srep45017

Guenther A (2013) Biological and chemical diversity of biogenic volatile organic emissions into the atmosphere. Int Scho Res Not

Hadfield JD (2010) MCMC methods for multi-response generalized linear mixed models: the MCMCglmm R package. J stat softw 33:1-22

Hammond D (2005) Tropical Forests of the Guiana Shield: Ancient Forests in a Modern World, CABI Publishing, Cambridge.

Hansen MC, Potapov PV, Moore R, Hancher M, Turubanova S, Tyukavina A, Thau D, Stehman S, Goetz S, Loveland T (2013) High-resolution global maps of 21st-century forest cover change. Science 342: 850-853

Hansted L, Jakobsen HB, Olsen CE (1994) Influence of temperature on the rhythmic emission of volatiles from Ribes nigrum flowers in situ. Plant, Cell Environ 17(9): 1069-1072

Heiden AC, Kobel K, Komenda M, Koppmann R, Shao M, Wildt J (1999) Toluene emissions from plants. Geophys Res Let 26(9): 1283-1286. https://doi.org/10.1029/1999GL900220

Hellén H, Tykkä T, Schallhart S, Stratigou, E, Salameh, T, Iturrate-Garcia, M (2024) Measurements of atmospheric C 10–C 15 biogenic volatile organic compounds (BVOCs) with sorbent tubes. Atmospheric Measurement Techniques 17(1): 315-333
540

Holzinger R, Sandoval-Soto L, Rottenberger S, Crutzen PJ, Kesselmeier J (2000) Emissions of volatile organic compounds from *Quercus ilex* L. measured by Proton Transfer Reaction Mass Spectrometry under different environmental conditions. J Geophys Res-Atmos 105(D16): 20573-20579. https://doi.org/10.1029/2000JD900296

541

542

543

Jardine AB, Jardine KJ, Fuentes JD, Martin ST, Martins G, Durgante F, Carneiro V, Higuchi N, Manzi AO, Chambers JQ (2015) Highly reactive light-dependent monoterpenes in the Amazon. Geophys Res Let 42(5):1576-1583

544

545

Jardine KJ, Jardine AB, Holm JA, Lombardozzi DL, Negron-Juarez RI, Martin ST, Beller HR, Gimenez BO, Higuchi N, Chambers JQ (2017) Monoterpene "thermometer" of tropical forest-atmosphere response to climate warming. Plant Cell Environ 40: 441-452. https://doi.org/10.1111/pce.12879

546

547

548

Jardine KJ, Zorzanelli RF, Gimenez BO, de Oliveira Piva LR, Teixeira A, Fontes CG, Robles E, Higuchi N, Chambers JQ, Martin ST (2020) Leaf isoprene and monoterpene emission distribution across hyperdominant tree genera in the Amazon basin. Phytochemistry 175: 112366

549

550

551

Kegge W, Pierik R (2010) Biogenic volatile organic compounds and plant competition. Trends Plant Sci 15(3): 126-132

552

Kembel SW, O'Connor TK, Arnold HK, Hubbell SP, Wright SJ, Green JL (2014) Relationships between phyllosphere bacterial communities and plant functional traits in a Neotropical forest. P Natl Acad Sci 111(38): 13715-13720

553

554

Kesselmeier J, Staudt M (1999) Biogenic Volatile Organic Compounds VOC: An Overview on Emission, Physiology and Ecology. J Atmos Chem 33: 23-88. https://doi.org/10.1023/A:1006127516791

555

556

Kesselmeier J, Wilske B, Muth S, Bode K, Wolf A (1999) Exchange of oxygenated volatile organic compounds between boreal lichens and the atmosphere. LAURILA T, LINDFORS V. Biogenic VOC emissions and photochemistry in the boreal regions of Europe, CEC Air Pollution Research Report. Luxembourg: Official Publication of the European Commission 70: 57-71

557

558

559

560

Kigathi, RN, Weisser WW, Reichelt M, Gershenzon J, Unsicker SB (2019) Plant volatile emission depends on the species composition of the neighboring plant community. BMC plant biology 19: 1-17

561

562

Koskella B (2020) The phyllosphere. Current Biol 30(19): R1143-R1146

563

Kuhn U, Rottenberger S, Biesenthal T, Wolf A, Schebeske G, Ciccioli P, Brancaleoni E, Frattoni M, Tavares TM, Kesselmeier J (2002) Isoprene and monoterpene emissions of Amazonian tree species during the wet season: Direct and indirect investigations on controlling environmental functions. J Geophys Res-Atmos 107(D20): LBA-38

564

565

566

Kulmala M, Suni T, Lehtinen KEJ, Dal Maso M, Boy M, Reissell A, Laothawornkitkul J, Taylor JE, Paul ND, Hewitt CN (2009) Biogenic volatile organic compounds in the Earth system. New Phytol 183(1): 27-51

567

568

Laothawornkitkul J, Taylor JE, Paul ND, Hewitt CN (2009) Biogenic volatile organic compounds in the Earth system. New Phytol 183(1): 27-51

569

570

Lawson CA, Seymour JR, Possell M, Suggett DJ, Raina JB (2020) The volatilomes of Symbiodiniaceae-associated bacteria are influenced by chemicals derived from their algal partner. Front Marine Sci 7: 106

571
572 Liang D, Li W, Yan X, Caiyin Q, Zhao G, Qiao J (2021) Molecular and Functional Evolution of the Spermatophyte

573 Sesquiterpene Synthases. Int J Mol Sci 22(12): 6348

574 Llusià J, Peñuelas J (1998) Changes in terpene content and emission in potted Mediterranean woody plants under severe

575 drought. Can J Bot 76: 1366-1373

576 Llusià J, Peñuelas J (1999) *Pinus halepensis* and *Quercus ilex* terpene emission rates as affected by temperature and

577 humidity. Biol Plantarum 42(2): 317-320

578 Llusià J, Peñuelas J (2000) Seasonal patterns of terpene content and emission from seven Mediterranean woody species in

579 field conditions. Am J Bot 87: 133-140

580 Llusià J, Peñuelas J (2001) Emission of volatile organic compounds by apple trees in response to spider mite attack and

581 attraction of predatory mites. Exp App Acarol 25(1): 65-77

582 Llusia J, Peñuelas J, Alessio G, Estiarte M (2006) Seasonal contrasting changes of foliar concentrations of terpenes and

583 other volatile organic compounds in four dominant species of a Mediterranean shrubland submitted to a field

584 experimental drought and warming. Physiol Plantarum 127: 632-649

585 Llusià J, Peñuelas J, Alessio GA, Estiarte M (2008) Contrasting Species-Specific, Compound-Specific, Seasonal, and

586 Interannual Response of Foliar Isoprenoid Emissions to Experimental Drought in a Mediterranean Shrubland. Int J Plant

587 Sci 169: 637-645

588 Llusià J, Peñuelas J, Asensio D, Munné-Bosch S (2005) Airborne limonene confers limited thermotolerance to *Quercus ilex*.

589 Physiol Plantarum 123: 40-48

590 Llusià J, Peñuelas J, Guenther A, Rapparini F (2013) Seasonal variations in terpene emission factors of dominant species in

591 four ecosystems in NE Spain. Atmospheric Environment 70: 149-158

592 Llusià J, Peñuelas J, Ogaya R, Alessio G (2010b) Annual and seasonal changes in foliar terpene content and emission rates

593 in *Cistus albidus* L. submitted to soil drought in Prades forest (Catalonia, NE Spain). Acta Phys Plant 32: 387-394. DOI

594 10.1007/s11738-009-0416-y

595 Llusià J, Peñuelas J, Sardans J, Owen S, Niinemets Ü (2010a) Measurement of volatile terpene emissions in 70 dominant

596 vascular plant species in Hawaii: aliens emit more than natives. Global Ecol Biogeogr 19: 863-874. DOI 10.1111/j.1466-

597 8238.2010.00557.x

598 Llusià J, Peñuelas J, Seco R, Filella I (2012) Seasonal changes in the daily emission rates of terpenes by *Quercus ilex* and

599 the atmospheric concentrations of terpenes in the natural park of Montseny, NE Spain. J Atmos Chem 69: 215-230

600 Llusià J, Sardans J, Niinemets Ü, Owen SM, Peñuelas J (2014) A screening study of leaf terpene emissions of 43 rainforest

601 species in Danum Valley Conservation Area (Borneo) and their relationships with chemical and morphological leaf traits.

602 Plant Biosys 148: 307-317
603

604

605

606

607

608

609

610

611

612

613

614

615

616

617

618

619

620

621

622

623

624

625

626

627

628

629

630

631

632

633

Loreto F, Ciccioli P, Cecinato A, Brancaleoni E, Frattoni M, Tricoli D (1996) Influence of environmental factors and air composition on the emission of [alpha]-pinene from *Quercus ilex* leaves. Plant Physiol 110(1): 267-275

Loreto F, Pinelli P, Manes F, Kollist H (2004) Impact of ozone on monoterpene emissions and evidences for an isoprene-like antioxidant action of monoterpenes emitted by *Quercus ilex* (L.) leaves. Tree Physiol 24: 361-367

Loreto F, Velikova V (2001) Isoprene produced by leaves protects the photosynthetic apparatus against ozone damage, quenches ozone products, and reduces lipid peroxidation of cellular membranes. Plant Physiol 127: 1781-1787

Medori M, Michelini L, Nogues I, Loreto F, Calfapietra C (2012) The impact of root temperature on photosynthesis and isoprene emission in three different plant species. The Scientific World Journal 2012

Mishra AK, Sinha V (2020) Emission drivers and variability of ambient isoprene, formaldehyde and acetaldehyde in north-west India during monsoon season. Environ Poll 267: 115538

Misztal PK, Hewitt CN, Wildt J, Blande JD, Eller AS, Fares S, ... Goldstein AH (2015) Atmospheric benzenoid emissions from plants rival those from fossil fuels. Scientific reports 5: 12064

Morath SU, Hung R, Bennett JW (2012) Fungal volatile organic compounds: a review with emphasis on their biotechnological potential. Fungal Biol Rev 26(2-3): 73-83

Mu Z, Llusià J, Zeng J, Zhang Y, Asensio D, Yang K, Yi Z, Wang X, Peñuelas J (2022) An overview of the isoprenoid emissions from tropical plant species. Frontiers Plant Sci 13: 833030. https://doi.org/10.3389/fpls.2022.833030

Munné-Bosch S, Peñuelas J (2004) Drought-induced oxidative stress in strawberry tree (*Arbutus unedo* L.) growing in Mediterranean field conditions. Plant Sci 166(4): 1105-1110

Nachtergaele FO, Spaargaren O, Deckers JA, Ahrens B (2000) New developments in soil classification: world reference base for soil resources. Geoderma 96(4): 345-357

Niinemets Ü (2010) Mild versus severe stress and BVOCs: thresholds, priming and consequences. Trends Plant Sci 15(3): 145-153

Niinemets Ü, Cescatti A, Rodeghiero M, Tosens T (2005) Leaf internal diffusion conductance limits photosynthesis more strongly in older leaves of Mediterranean evergreen broad-leaved species. Plant, Cell and Environment 28: 1552-1566

Niinemets Ü, Wright I, Evans JR (2009) Leaf mesophyll diffusion conductance in 35 Australian sclerophylls covering a broad range of foliage structural and physiological variation. Journal of Experimental Botany 60: 2433-2449

Owen SM, Peñuelas J (2005) Opportunistic emissions of volatile isoprenoids. Trends Plant Sci 10(9): 420-426

Peñuelas J, Llusià J (1997) Effects of carbon dioxide, water supply, and seasonality on terpene content and emission by Rosmarinus officinalis. J Chem Ecol 23(4): 979-993

Peñuelas J, Llusià J (1999) Seasonal Emission of Monoterpenes by the Mediterranean tree *Quercus ilex* in field conditions: relations with photosynthetic rates, temperature and volatility. Physiol Plantarum 105: 641-647
634 Peñuelas J, Llusià J (2001) The complexity of factors driving volatile organic compound emissions by plants. Biol

635 Plantarum 44: 481-487

636 Peñuelas J, Llusià J (2002) Linking photorespiration, monoterpenes and thermotolerance in Quercus. New Phytol 155(2):

637 227-237

638 Peñuelas J, Llusià J (2003) BVOCs: Plant defense against climate warming? Trends Plant Sci 8(3): 105-109

639 Peñuelas J, Llusià J (2004) Plant VOC emissions: making use of the unavoidable. Trends Ecol Evol 19(8): 402-404

640 Peñuelas J, Llusià J, Asensio D, Munné-Bosch S (2005) Linking isoprene with plant thermotolerance, antioxidants and

641 monoterpane emissions. Plant, Cell Environ 28: 278-286

642 Peñuelas J, Munné-Bosch S (2005) Isoprenoids: an evolutionary pool for photoprotection. Trends Plant Sci 10 (4): 166-169

643 Peñuelas J, Sardans J, Llusià J, Owen S, Carnicer J, Giambelluca TW, Rezende EL, Waite M, Niinemets Ü (2010) Faster

644 returns on "leaf economics" and different biogeochemical niche in invasive compared with native plant species. Global

645 Change Biol 16: 2171-2185. doi: 10.1111/j.1365-2486.-2009.02054.x

646 Peñuelas J, Sardans J, Llusià J, Silva J, Owen S, Bala-Ola Bernadus, Linatoc AC, Dalimin MN, Niinemets Ü (2013) Foliar

647 chemistry and standing folivory of early and late-successional species in a Bornean rainforest. Plant Ecol Divers 6: 245-

648 256

649 Peñuelas J, Staudt M (2010) BVOCs and global change. Trends Plant Sci 15(3): 133-144

650 Picazo-Aragonés J, Terrab A, Balao F (2020) Plant volatile organic compounds evolution: transcriptional regulation,

651 epigenetics and polyploidy. International Journal of Molecular Sciences 21(23): 8956

652 Pichersky E, Gershenzon J (2002) The formation and function of plant volatiles: perfumes for pollinator attraction and

653 defense. Curr Opin Plant Biol 5(3): 237-243

654 Raguso RA (2008) Start making scents: the challenge of integrating chemistry into pollination ecology. Entomologia

655 experimentalis et applicata 128(1): 196-207

656 Revell L, Phytools J (2012) an R package for phylogenetic comparative biology (and other things). Methods Ecol Evol 3:

657 217-223

658 Rundell SM, Spakowicz DJ, Narváez-Trujillo A, Strobel SA (2015) The biological diversity and production of volatile

659 organic compounds by stem-inhabiting endophytic fungi of ecuador. J Fungi 1(3): 384-396.

660 https://doi.org/10.3390/jof1030384

661 Sabatier D, Grimaldi M, Prévost MF, Guillaume J, Godron M, Dosso M, Curmi, P (1997) The influence of soil cover

662 organization on the floristic and structural heterogeneity of a Guianan rain forest. Plant ecology 131(1): 81-108

663 Salomon MV, Purpora R, Bottini R, Piccoli P (2016) Rhizosphere associated bacteria trigger accumulation of terpenes in

664 leaves of Vitis vinifera L. cv. Malbec that protect cells against reactive oxygen species. Plant Physiol Biochem 106: 295-

665 304
666 Seufert G (1997) BEMA: a European commission project on biogenic emissions in the Mediterranean area. Atmos
667 Environ-UK

668 Sharkey TD, Singsaas EL (1995) Why plants emit isoprene. Nature 374(6525): 769-769

669 Singh HB, Zimmerman PB (1992) Atmospheric distribution and sources of nonmethane hydrocarbons. In: Gaseous
670 pollutants: Characterization and cycling 177-235

671 Stahl C, Burban B, Goret JY, Bonal D (2011) Seasonal variations in stem CO2 efflux in the Neotropical rainforest of
672 French Guiana. Ann For Sci 68(4): 771-782

673 Staudt M, Seufert G (1995) Light-dependent emission of monoterpenes by holm oak (*Quercus ilex* L.).
674 Naturwissenschaften 82(2): 89-92

675 Staudt, M, Morin, X, Chuine I (2017) Contrasting direct and indirect effects of warming and drought on isoprenoid
676 emissions from Mediterranean oaks. Regional environmental change 17: 2121-2133

677 SteegeTH, Mota de Oliveira S, Pitman NC, Sabatier D, Antonelli A, Guevara Andino JE, ... Salomão RP (2019) Towards a
dynamic list of Amazonian tree species. Scientific reports 9(1): 3501

679 Taylor TC, McMahon SM, Smith MN, Boyle B, Violle C, Haren J, Simova I, Meir P, Ferreira LV, Camargo PB, Costa
680 ACL, Enquist BJ, Saleska SR (2018) Isoprene emission structures tropical tree biogeography and community assembly
681 responses to climate. New Phytol 220: 435-446

682 Tingey DT, Manning M, Grothaus LC, Burns WF (1980) Influence of light and temperature on monoterpene emission rates
683 from slash pine. Plant Physiol 65(5): 797-801

684 Van der Meer PJ, Bongers F (1996) Patterns of tree-fall and branch-fall in a tropical rain forest in French Guiana. J Ecol
685 19-29. https://www.jstor.org/stable/2261696

686 Verryckt L, Vicca S, Van Langenhove L, Stahl C, Asensio D, Urbina I, Ogaya R, Llusà J, Grau O, Peguero G, Gargallo-
687 Garriga A, Courtois EA., Margalef O, Portillo-Estrada M, Ciais P, Obersteiner M, Fuchslueger L, Lugli LF, Fernandez-
688 Garberí P-R, Vallicrosa H, Verlinden M, Ranits C, Vermeir P, Coste S, Verbruggen E, Bréchet L, Sardans J, Chave J,
689 Peñuelas J, Janssens IA (2021) Vertical profiles of leaf photosynthesis and leaf traits, and soil nutrients in two tropical
690 rainforests in French Guiana before and after a three-year nitrogen and phosphorus addition experiment. Earth System
691 Data doi: 10.5194/essd-2021-142

692 Verryckt LT, Ellsworth DS, Vicca S, Van Langenhove L, Peñuelas J, Ciais P, Posada JM, Stahl C, Coste S, Courtois EA,
693 Obersteiner M, Chave J, Janssens IA (2020b) Can light-saturated photosynthesis in lowland tropical forests be estimated
694 by one light level? Biotropica 52:1184-1194. Doi: 10.1111/btp.12817

695 Verryckt LT, Van Langenhove L, Ciais P, Courtois EA, Vicca S, Peñuelas J, Stahl C, Coste S, Ellsworth DS, Posada JM,
696 Obersteiner M, Chave J, Janssens IA (2020a) Coping with branch excision when measuring leaf net photosynthetic rates
697 in a lowland tropical forest. Biotropica 52(4): 608-615
698 Verryckt LT, Vicca S, Van Langenhove L, Stahl C, Asensio D, Urbina I, Ogaya R, Llusià J, Grau O, Peguero G, Gargallo-Garriga A, Courtois EA, Margalef O, Portillo-Estrada M, Ciais P, Obersteiner M, Fuchslueger L, Lugli LF, Fernandez-Garberí PR, Vallicrosa H, Verlinden M, Ranits C, Vermeir P, Coste S, Verbruggen E, Bréchet L, Sardans J, Chave J, Peñuelas J, Janssens IA (2022) Vertical profiles of leaf photosynthesis and leaf traits and soil nutrients in two tropical rainforests in French Guiana before and after a 3-year nitrogen and phosphorus addition experiment. Earth Syst Sci Data 14(1): 5-18

704 Vickers CE, Gershenzon J, Lerdau MT, Loreto F (2009) A unified mechanism of action for volatile isoprenoids in plant abiotic stress. Nat Chem Biol 5(5): 283-291

706 Wheatley RE (2002) The consequences of volatile organic compound mediated bacterial and fungal interactions. Anton Leeuw 81(1): 357-364

708 Yáñez-Serrano AM, Bourtsoukidis E, Alves EG, Bauwens M, Stavrakou T, Llusià J, Filella I, Guenther A, Williams J, Artaxo P, Sindelarova K, Doubalova J, Kesselmeier J, Peñuelas J (2020) Amazonian Biogenic Volatile Organic Compounds under Global Change. Glob Change Biol 26: 4722-4751. doi: 10.1111/gcb.15185

711 Yáñez-Serrano AM, Fasbender L, Kreuzwieser J, Dubbert D, Haberstroh S, Lobo-do-Vale R, Caldeira MC, Werner C (2018) Volatile diterpene emission by two Mediterranean Cistaceae shrubs. Sci Rep-UK 8(1): 6855

713 Yáñez-Serrano AM, Nölscher AC, Bourtsoukidis E, Gomes Alves E, Ganzeveld L, Bonn B,...Kesselmeier, J. (2018) Monoterpene chemical speciation in a tropical rainforest: variation with season, height, and time of day at the Amazon Tall Tower Observatory (ATTO). Atmospheric Chemistry and Physics 18(5): 3403-3418

716 Zhiqun T, Jian Z, Junli Y, Chunzi W, Danju Z (2017) Allelopathic effects of volatile organic compounds from Eucalyptus grandis rhizosphere soil on Eisenia fetida assessed using avoidance bioassays, enzyme activity, and comet assays. Chemosphere 173: 307-317

719

720

721

722

723

724

725
<figure><img src="image_3.png" /><figcaption>**Fig. 1.** Mean soil water content (%) and soil temperature (°C) (± standard error) in French Guiana, South America. The picture was taken during the 2015 wet season at the Nouragues Ecological Research Station.</figcaption></figure>

726

727

728

729

730

731

732
<figure><img src="image_4.png" /><figcaption>**Fig. 2.** Mean terpene emissions (± standard deviation) for A) total terpenes, B) monoterpenes and C) sesquiterpenes from 36 tropical tree species in French Guiana. Asterisks indicate significant differences between seasons, \* P < 0.01, \*\* P < 0.001, \*\*\* P < 0.00001; N = 285 and 219 in the dry and wet season, respectively. Nda stands for no data available.</figcaption></figure>
<figure><img src="image_5.png" /></figure>

<figure><img src="image_6.png" /></figure>

**Fig. 3.** Mean terpene emissions (± standard error) for A) Total terpenes and B) the isoprene group from 36 tropical tree species in French Guiana. Asterisks indicate significant differences between seasons, \* P < 0.01, \*\* P < 0.001, \*\*\* P < 0.00001; N = 285 and 219 in the dry and wet season, respectively. "N" refers to the sample size, representing the number of observations available in each season. "Nda" stands for no data available.
<figure><img src="image_7.png" /><figcaption>**Fig. 4.** Mean biogenic volatile organic compound (BVOC) emissions (± standard error) from 36 tropical tree species in French Guiana. Asterisks indicate significant differences between seasons: \* P < 0.01, \*\* P < 0.001, \*\*\* P < 0.00001; N = 285 and 219 in the dry and wet seasons, respectively. In this context, "N" represents the sample size, indicating the number of observations available for each season.</figcaption></figure>
<figure><img src="image_8.png" /><figcaption>750
751 **Fig. S1.** Means of the different types of BVOCs emitted by 36 tropical tree species in French Guiana. MT: monoterpenes;
752 SQT: sesquiterpenes.</figcaption></figure>
<table><caption>**Table S1.** List of the different tropical tree species studied in the dry and wet seasons in the Nouragues Ecological Research Station and Paracou Experimental Field Station in French Guiana.</caption><thead><tr><th>Season</th><th>Site</th><th>Species</th><th>Family</th></tr></thead><tbody><tr><td rowspan="15">Dry</td><td rowspan="15">Nouragues</td><td>Aniba rosaeodora</td><td>Lauraceae</td></tr><tr><td>Brosimum guianense</td><td>Moraceae</td></tr><tr><td>Chimarrhis turbinata</td><td>Rubiaceae</td></tr><tr><td>Chrysophyllum argenteum</td><td>Sapotaceae</td></tr><tr><td>Couepia caryophylloides</td><td>Chrysobalanaceae</td></tr><tr><td>Dicorynia guianensis</td><td>Fabaceae</td></tr><tr><td>Eperua falcata</td><td>Fabaceae</td></tr><tr><td>Eschweilera coriacea</td><td>Lecythidaceae</td></tr><tr><td>Eschweilera decolorans</td><td>Lecythidaceae</td></tr><tr><td>Eugenia culcullata</td><td>Myrtaceae</td></tr><tr><td>Ferdinandusa paraensis</td><td>Rubiaceae</td></tr><tr><td>Inga nouraguensis</td><td>Fabaceae</td></tr><tr><td>Licania alba</td><td>Chrysobalanaceae</td></tr><tr><td>Paloue guianensis</td><td>Fabaceae</td></tr><tr><td>Pouteria retinervis</td><td>Sapotaceae</td></tr><tr><td>Pradosia ptychandra</td><td>Sapotaceae</td></tr><tr><td>Protium decandrum</td><td>Burseraceae</td></tr><tr><td>Sextonia rubra</td><td>Lauraceae</td></tr><tr><td>Talisia praealta</td><td>Sapindaceae</td></tr><tr><td>Vochysia sabatieri</td><td>Vochysiaceae</td></tr><tr><td>Vouacapoua americana</td><td>Fabaceae</td></tr><tr><td rowspan="15">Paracou</td><td>Carapa surinamensis</td><td>Meliaceae</td></tr><tr><td>Catostemma fragrans</td><td>Malvaceae</td></tr><tr><td>Chaetocarpus schomburgkianus</td><td>Euphorbiaceae</td></tr><tr><td>Chrysophyllum pomiferum</td><td>Sapotaceae</td></tr><tr><td>Dipteryx odorata</td><td>Fabaceae</td></tr><tr><td>Drypetes variabilis</td><td>Putranjivaceae</td></tr><tr><td>Eperua falcata</td><td></td></tr><tr><td>Eperua grandiflora</td><td>Fabaceae</td></tr><tr><td>Eschweilera sagotiana</td><td>Lecythidaceae</td></tr><tr><td>Eschweilera sp</td><td>Lecythidaceae</td></tr><tr><td>Gustavia hexapetala</td><td>Lecythidaceae</td></tr><tr><td>Hebepetalum humiriifolium</td><td>Linaceae</td></tr><tr><td>Licania alba</td><td></td></tr><tr><td>Moronobea coccinea</td><td>Clusiaceae</td></tr><tr><td>Pouteria eugeniifolia</td><td>Sapotaceae</td></tr><tr><td>Symphonia globulifera</td><td>Clusiaceae</td></tr><tr><td>Tetragastris panamensis</td><td>Burseraceae</td></tr><tr><td>Vouacapoua americana</td><td></td></tr><tr><td rowspan="4">Wet</td><td rowspan="4">Nouragues</td><td>Aniba rosaeodora</td><td>Lauraceae</td></tr><tr><td>Agonandra silvatica</td><td></td></tr><tr><td>Brosimum guianense</td><td>Moraceae</td></tr><tr><td>Chimarrhis turbinata</td><td>Rubiaceae</td></tr></tbody></table>
<table><tr><td>Chrysophyllum argenteum</td><td>Sapotaceae</td></tr><tr><td>Couepia caryophylloides</td><td>Chrysobalanaceae</td></tr><tr><td>Dicorynia guianensis</td><td>Fabaceae</td></tr><tr><td>Eperua falcata</td><td>Fabaceae</td></tr><tr><td>Eschweilera coriacea</td><td>Lecythidaceae</td></tr><tr><td>Eschweilera decolorans</td><td>Lecythidaceae</td></tr><tr><td>Eugenia culcullata</td><td>Myrtaceae</td></tr><tr><td>Ferdinandusa paraensis</td><td>Rubiaceae</td></tr><tr><td>Inga nouraguensis</td><td>Fabaceae</td></tr><tr><td>Licania alba</td><td>Chrysobalanaceae</td></tr><tr><td>Paloue guianensis</td><td>Fabaceae</td></tr><tr><td>Pouteria retinervis</td><td>Sapotaceae</td></tr><tr><td>Pradosia ptychandra</td><td>Sapotaceae</td></tr><tr><td>Protium decandrum</td><td>Burseraceae</td></tr><tr><td>Sextonia rubra</td><td>Lauraceae</td></tr><tr><td>Talisia praealta</td><td>Sapindaceae</td></tr><tr><td>Vochysia sabatieri</td><td>Vochysiaceae</td></tr><tr><td>Vouacapoua americana</td><td>Fabaceae</td></tr><tr><td>Paracou</td><td>Meliaceae</td></tr><tr><td>Carapa surinamensis</td><td>Malvaceae</td></tr><tr><td>Catostemma fragrans</td><td>Euphorbiaceae</td></tr><tr><td>Chaetocarpus schomburgkianus</td><td>Euphorbiaceae</td></tr><tr><td>Chrysophyllum argenteum</td><td>Sapotaceae</td></tr><tr><td>Chrysophyllum pomiferum</td><td>Fabaceae</td></tr><tr><td>Dipteryx odorata</td><td>Putranjivaceae</td></tr><tr><td>Drypetes variabilis</td><td>Putranjivaceae</td></tr><tr><td>Eperua falcata</td><td>Fabaceae</td></tr><tr><td>Eperua grandiflora</td><td>Fabaceae</td></tr><tr><td>Eschweilera sagotiana</td><td>Lecythidaceae</td></tr><tr><td>Eschweilera sp</td><td>Lecythidaceae</td></tr><tr><td>Gustavia hexapetala</td><td>Lecythidaceae</td></tr><tr><td>Hebepetalum humiriifolium</td><td>Linaceae</td></tr><tr><td>Licania alba</td><td>Clusiaceae</td></tr><tr><td>Moronobea coccinea</td><td>Sapotaceae</td></tr><tr><td>Pouteria eugeniifolia</td><td>Sapotaceae</td></tr><tr><td>Symphonia globulifera</td><td>Clusiaceae</td></tr><tr><td>Tetragastris panamensis</td><td>Burseraceae</td></tr><tr><td>Vouacapoua americana</td><td>Burseraceae</td></tr></table>
<table><caption>**Table S2.** Mean (± STD) soil water content (%) and soil temperature (°C) around the 36 tropical tree species in French Guiana. Letters indicate significant differences between seasons. N indicates the number of measurements.</caption><thead><tr><th>Specific name</th><th>Season</th><th>Soil water content (%)</th><th>Soil temperature (°C)</th><th>N</th></tr></thead><tbody><tr><td rowspan="2">Protium decandrum</td><td>Dry</td><td>23.6 ± 0a</td><td>26.3 ± 0a</td><td rowspan="6">20</td></tr><tr><td>Wet</td><td>33.1 ± 0b</td><td>23.7 ± 0b</td></tr><tr><td rowspan="2">Inga nouraguensis</td><td>Dry</td><td>23.6 ± 0a</td><td>26.3 ± 0a</td></tr><tr><td>Wet</td><td>33.1 ± 0b</td><td>23.7 ± 0b</td></tr><tr><td rowspan="2">Eperua grandiflora</td><td>Dry</td><td>15.6 ± 1.1a</td><td>26 ± 0.4</td></tr><tr><td>Wet</td><td>28.8 ± 1.5b</td><td>nda</td></tr><tr><td rowspan="2">Eperua falcata</td><td>Dry</td><td>20.3 ± 0.6a</td><td>25 ± 0.07a</td><td rowspan="2">32</td></tr><tr><td>Wet</td><td>34.2 ± 0.7b</td><td>23.7 ± 0b</td></tr><tr><td rowspan="2">Eschweilera coriacea</td><td>Dry</td><td>20.2 ± 0a</td><td>26.2 ± 0a</td><td rowspan="2">6</td></tr><tr><td>Wet</td><td>35.8 ± 0.3b</td><td>23.9 ± 0.05b</td></tr><tr><td rowspan="2">Gustavia hexapetala</td><td>Dry</td><td>21.3 ± 0a</td><td>24.6 ± 0</td><td rowspan="2">6</td></tr><tr><td>Wet</td><td>30.7 ± 0b</td><td>nda</td></tr><tr><td rowspan="2">Brosimum guianense</td><td>Dry</td><td>18.7 ± 0a</td><td>28 ± 0a</td><td rowspan="2">6</td></tr><tr><td>Wet</td><td>35 ± 0b</td><td>23.7 ± 0b</td></tr><tr><td rowspan="2">Couepia caryophylloides</td><td>Dry</td><td>23.4 ± 0a</td><td>29.6 ± 0a</td><td rowspan="2">6</td></tr><tr><td>Wet</td><td>31.5 ± 0b</td><td>23.7 ± 0b</td></tr><tr><td rowspan="2">Eschweilera sagotiana</td><td>Dry</td><td>19.9 ± 1.6a</td><td>27 ± 0.6</td><td rowspan="2">6</td></tr><tr><td>Wet</td><td>32.8 ± 0b</td><td>nda</td></tr><tr><td rowspan="2">Pradosia ptychandra</td><td>Dry</td><td>20.3 ± 0.5a</td><td>28 ± 0a</td><td rowspan="2">6</td></tr><tr><td>Wet</td><td>36.4 ± 0b</td><td>23.6 ± 0b</td></tr><tr><td rowspan="2">Chrysophyllum pomiferum</td><td>Dry</td><td>20.5 ± 0</td><td>25.1 ± 0</td><td rowspan="2">6</td></tr><tr><td>Wet</td><td>nda</td><td>nda</td></tr><tr><td rowspan="2">Vouacapoua americana</td><td>Dry</td><td>22.6 ± 0.5a</td><td>25.4 ± 0.1a</td><td rowspan="2">18</td></tr><tr><td>Wet</td><td>32.1 ± 1b</td><td>23.7 ± 0.03b</td></tr><tr><td rowspan="2">Sextonia rubra</td><td>Dry</td><td>25.4 ± 0a</td><td>28.5 ± 0a</td><td rowspan="2">17</td></tr><tr><td>Wet</td><td>33.4 ± 0b</td><td>23.7 ± 0b</td></tr></tbody></table>
<table><tbody><tr><td rowspan="2">Chrysophyllum argenteum</td><td>Dry</td><td>20.2 ± 0a</td><td>26.2 ± 0a</td><td></td></tr><tr><td>Wet</td><td>32.7 ± 1.3b</td><td>23.9 ± 0b</td><td></td></tr><tr><td colspan="5" style="text-align: center;">6</td></tr><tr><td rowspan="2">Ferdinandusa paraensis</td><td>Dry</td><td>24.2 ± 0a</td><td>27.5 ± 0a</td><td></td></tr><tr><td>Wet</td><td>31.4 ± 0b</td><td>23.3 ± 0b</td><td></td></tr><tr><td rowspan="2">Talisia praealta</td><td>Dry</td><td>25.4 ± 0a</td><td>29 ± 0a</td><td></td></tr><tr><td>Wet</td><td>36.3 ± 0b</td><td>23.5 ± 0b</td><td></td></tr><tr><td rowspan="2">Licania alba</td><td>Dry</td><td>22.5 ± 0.7a</td><td>27.7 ± 0.3a</td><td></td></tr><tr><td>Wet</td><td>33 ± 0.5b</td><td>23.7 ± 0.02b</td><td></td></tr><tr><td colspan="5" style="text-align: center;">40</td></tr><tr><td rowspan="2">Chimarrhis turbinata</td><td>Dry</td><td>25.2 ± 0a</td><td>27.6 ± 0a</td><td></td></tr><tr><td>Wet</td><td>38.1 ± 0b</td><td>23.4 ± 0b</td><td></td></tr><tr><td rowspan="2">Eschweilera sp</td><td>Dry</td><td>12.8 ± 0a</td><td>24.5 ± 0</td><td></td></tr><tr><td>Wet</td><td>27.9 ± 0b</td><td>nda</td><td></td></tr><tr><td rowspan="2">Paloue guianensis</td><td>Dry</td><td>21.8 ± 0a</td><td>28 ± 0a</td><td></td></tr><tr><td>Wet</td><td>36.4 ± 0b</td><td>23.6 ± 0b</td><td></td></tr><tr><td colspan="5" style="text-align: center;">4</td></tr><tr><td rowspan="2">Eugenia culcullata</td><td>Dry</td><td>9 ± 0a</td><td>28.9 ± 0a</td><td></td></tr><tr><td>Wet</td><td>25.3 ± 0b</td><td>23.5 ± 0b</td><td></td></tr><tr><td rowspan="2">Tetragastris panamensis</td><td>Dry</td><td>25.3 ± 0</td><td>25 ± 0</td><td></td></tr><tr><td>Wet</td><td>nda</td><td>nda</td><td></td></tr><tr><td rowspan="2">Dicorynia guianensis</td><td>Dry</td><td>19 ± 0a</td><td>28 ± 0a</td><td></td></tr><tr><td>Wet</td><td>34.4 ± 0.5b</td><td>23.8 ± 0.02b</td><td></td></tr><tr><td rowspan="2">Drypetes variabilis</td><td>Dry</td><td>22.2 ± 0a</td><td>24.8 ± 0</td><td></td></tr><tr><td>Wet</td><td>29.7 ± 0b</td><td>nda</td><td></td></tr><tr><td rowspan="2">Pouteria retinervis</td><td>Dry</td><td>9 ± 0a</td><td>29 ± 0a</td><td></td></tr><tr><td>Wet</td><td>25.3 ± 0b</td><td>23.5 ± 0b</td><td></td></tr><tr><td rowspan="2">Aniba rosaeodora</td><td>Dry</td><td>24.2 ± 0a</td><td>27.5 ± 0a</td><td></td></tr><tr><td>Wet</td><td>31.4 ± 0b</td><td>23.3 ± 0b</td><td></td></tr><tr><td rowspan="2">Chaetocarpus schomburgkianus</td><td>Dry</td><td>13.7 ± 0a</td><td>25.4 ± 0</td><td></td></tr><tr><td>Wet</td><td>27.8 ± 0b</td><td>nda</td><td></td></tr><tr><td rowspan="2">Catostemma fragrans</td><td>Dry</td><td>21.3 ± 0a</td><td>24.6 ± 0</td><td></td></tr><tr><td>Wet</td><td>30.7 ± 0b</td><td>nda</td><td></td></tr><tr><td rowspan="2">Hebepetalum humiriifolium</td><td>Dry</td><td>15 ± 0</td><td>24.7 ± 0</td><td></td></tr><tr><td>Wet</td><td>nda</td><td>nda</td><td></td></tr><tr><td rowspan="2">Moronobea coccinea</td><td>Dry</td><td>9.9 ± 0a</td><td>24.9 ± 0</td><td></td></tr><tr><td>Wet</td><td>26.2 ± 0b</td><td>nda</td><td></td></tr><tr><td rowspan="2">Symphonia globulifera</td><td>Dry</td><td>19.4 ± 0</td><td>24.6 ± 0</td><td></td></tr><tr><td>Wet</td><td>nda</td><td>nda</td><td></td></tr></tbody></table>
<table><tbody><tr><td rowspan="2">Eschweilera<br>decolorans</td><td>Dry</td><td>22.9 ± 0a</td><td>27.3 ± 0a</td></tr><tr><td>Wet</td><td>37.6 ± 0b</td><td>23.9 ± 0b</td></tr><tr><td rowspan="2">Capirona<br>decorticans</td><td>Dry</td><td>nda</td><td>nda</td></tr><tr><td>Wet</td><td>31.5 ± 0</td><td>23.7 ± 0</td></tr><tr><td rowspan="2">Caryocar<br>glabrum</td><td>Dry</td><td>nda</td><td>nda</td></tr><tr><td>Wet</td><td>33.4 ± 0</td><td>23.7 ± 0</td></tr><tr><td rowspan="2">Chrysophyllum<br>sanguinolentum</td><td>Dry</td><td>nda</td><td>nda</td></tr><tr><td>Wet</td><td>31.5 ± 0</td><td>23.7 ± 0</td></tr><tr><td rowspan="2">Helicostylis<br>pedunculata</td><td>Dry</td><td>nda</td><td>nda</td></tr><tr><td>Wet</td><td>36.4 ± 0</td><td>23.6 ± 0</td></tr><tr><td rowspan="2">Hirtella bicornis</td><td>Dry</td><td>nda</td><td>nda</td></tr><tr><td>Wet</td><td>33.4 ± 0</td><td>23.7 ± 0</td></tr><tr><td rowspan="2">Hymanea<br>courbaril</td><td>Dry</td><td>nda</td><td>nda</td></tr><tr><td>Wet</td><td>35.5 ± 0</td><td>23.9 ± 0</td></tr><tr><td rowspan="2">Lecythis poiteaui</td><td>Dry</td><td>nda</td><td>nda</td></tr><tr><td>Wet</td><td>38.1 ± 0</td><td>23.4 ± 0</td></tr><tr><td rowspan="2">Myrcia<br>splendens</td><td>Dry</td><td>nda</td><td>nda</td></tr><tr><td>Wet</td><td>25.3 ± 0</td><td>23.5 ± 0</td></tr><tr><td rowspan="2">Protium opacum</td><td>Dry</td><td>nda</td><td>nda</td></tr><tr><td>Wet</td><td>36.4 ± 0</td><td>23.6 ± 0</td></tr><tr><td rowspan="2">Sloanea sp</td><td>Dry</td><td>nda</td><td>nda</td></tr><tr><td>Wet</td><td>nda</td><td>nda</td></tr><tr><td rowspan="2">Sterculia<br>pruriens</td><td>Dry</td><td>nda</td><td>nda</td></tr><tr><td>Wet</td><td>30.7 ± 0</td><td>nda</td></tr><tr><td rowspan="2">Pouteria<br>eugeniifolia</td><td>Dry</td><td>nda</td><td>nda</td></tr><tr><td>Wet</td><td>27.8 ± 0</td><td>nda</td></tr><tr><td rowspan="2">Carapa<br>surinamensis</td><td>Dry</td><td>nda</td><td>nda</td></tr><tr><td>Wet</td><td>29.7 ± 0</td><td>nda</td></tr><tr><td rowspan="2">Dipteryx odorata</td><td>Dry</td><td>nda</td><td>nda</td></tr><tr><td>Wet</td><td>30.7 ± 0</td><td>nda</td></tr><tr><td rowspan="2">Vochysia<br>sabatieri</td><td>Dry</td><td>nda</td><td>nda</td></tr><tr><td>Wet</td><td>33.4 ± 0</td><td>23.7 ± 0</td></tr></tbody></table>
<table><caption>**Table S3.** Mean (minimum, maximum ± standard deviation and standard error, in µg g⁻¹ d.m. h⁻¹) biogenic volatile organic compounds (BVOCs) and *P*-value of the 36 tropical tree species studied in the dry and wet seasons in French Guiana. N = 285 and 219 for the dry and wet seasons, respectively. MTu: monoterpenes unidentified; SQTsu: Sum of unidentified sesquiterpenes.</caption><thead><tr><th rowspan="2">Season<br>BVOCs</th><th colspan="5">Dry</th><th colspan="5">Wet</th><th rowspan="2">P-value</th></tr><tr><th>Mean</th><th>Min.</th><th>Max.</th><th>Std</th><th>Ste</th><th>Mean</th><th>Min.</th><th>Max.</th><th>Std</th><th>Ste</th></tr></thead><tbody><tr><td>Total BVOCs</td><td>5,5</td><td>0</td><td>80,9</td><td>12,8</td><td>0,8</td><td>0,8</td><td>0</td><td>11,7</td><td>1,9</td><td>0,1</td><td>0.000010</td></tr><tr><td>Total terpenes</td><td>5,4</td><td>0</td><td>80,9</td><td>12,8</td><td>0,8</td><td>0,5</td><td>0</td><td>10,3</td><td>1,5</td><td>0,1</td><td>0.000010</td></tr><tr><td>Total monoterpenes</td><td>2,5</td><td>0</td><td>39,6</td><td>5,7</td><td>0,3</td><td>0,4</td><td>0</td><td>6,6</td><td>1</td><td>0,1</td><td>0.000010</td></tr><tr><td>Other monoterpenes</td><td>0,2</td><td>0</td><td>4,5</td><td>0,6</td><td>0</td><td>0</td><td>0</td><td>2</td><td>0,2</td><td>0</td><td>0.000010</td></tr><tr><td>Total sesquiterpenes</td><td>3</td><td>0</td><td>79,9</td><td>10,3</td><td>0,6</td><td>0,1</td><td>0</td><td>4,4</td><td>0,6</td><td>0</td><td>0.000100</td></tr><tr><td>Other sesquiterpenes</td><td>0,8</td><td>0</td><td>16,7</td><td>2,3</td><td>0,1</td><td>0,1</td><td>0</td><td>4,4</td><td>0,6</td><td>0</td><td>0.000010</td></tr><tr><td>Isoprene</td><td>0,3</td><td>0</td><td>13</td><td>1,2</td><td>0,1</td><td>0,5</td><td>0</td><td>22,9</td><td>2,1</td><td>0,1</td><td>ns</td></tr><tr><td>Heptane-2.2.4.6.6-pentamethyl</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0,3</td><td>0</td><td>5,7</td><td>0,8</td><td>0,1</td><td>0.000010</td></tr><tr><td>Toluene</td><td>0,1</td><td>0</td><td>3,2</td><td>0,3</td><td>0</td><td>0</td><td>0</td><td>1,4</td><td>0,1</td><td>0</td><td>0.010000</td></tr><tr><td>MTu1</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0,3</td><td>0</td><td>0</td><td>ns</td></tr><tr><td>MTu2</td><td>0</td><td>0</td><td>0,4</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>ns</td></tr><tr><td>MTu3</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>ns</td></tr><tr><td>α-Pinene</td><td>0,6</td><td>0</td><td>15,4</td><td>1,5</td><td>0,1</td><td>0,1</td><td>0</td><td>2,5</td><td>0,2</td><td>0</td><td>0.000010</td></tr><tr><td>MTu4</td><td>0</td><td>0</td><td>0,9</td><td>0,1</td><td>0</td><td>0</td><td>0</td><td>0,7</td><td>0,1</td><td>0</td><td>0.020000</td></tr><tr><td>MTu5</td><td>0</td><td>0</td><td>0,6</td><td>0,1</td><td>0</td><td>0</td><td>0</td><td>0,2</td><td>0</td><td>0</td><td>0.000026</td></tr><tr><td>MTu6</td><td>0</td><td>0</td><td>0,2</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>ns</td></tr><tr><td>MTu7</td><td>0,1</td><td>0</td><td>2</td><td>0,2</td><td>0</td><td>0</td><td>0</td><td>0,4</td><td>0</td><td>0</td><td>0.000010</td></tr><tr><td>MTu8</td><td>0,1</td><td>0</td><td>1,8</td><td>0,2</td><td>0</td><td>0</td><td>0</td><td>1,6</td><td>0,1</td><td>0</td><td>0.010000</td></tr><tr><td>Limonene</td><td>0,6</td><td>0</td><td>13,7</td><td>1,7</td><td>0,1</td><td>0,1</td><td>0</td><td>4,9</td><td>0,4</td><td>0</td><td>0.000010</td></tr><tr><td>Sabinene</td><td>0,1</td><td>0</td><td>2,4</td><td>0,3</td><td>0</td><td>0</td><td>0</td><td>2,2</td><td>0,2</td><td>0</td><td>ns</td></tr><tr><td>trans-β-Ocimene</td><td>0,4</td><td>0</td><td>19,8</td><td>1,8</td><td>0,1</td><td>0</td><td>0</td><td>1,8</td><td>0,2</td><td>0</td><td>0.010000</td></tr><tr><td>MTu9</td><td>0</td><td>0</td><td>0,8</td><td>0,1</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0.010000</td></tr><tr><td>MTu10</td><td>0</td><td>0</td><td>0,7</td><td>0,1</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0.001000</td></tr><tr><td>MTu11</td><td>0</td><td>0</td><td>0,5</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>ns</td></tr><tr><td>MTu12</td><td>0</td><td>0</td><td>1,7</td><td>0,1</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>ns</td></tr><tr><td>α-Terpinolene</td><td>0,6</td><td>0</td><td>19,7</td><td>2,6</td><td>0,2</td><td>0,1</td><td>0</td><td>3,6</td><td>0,5</td><td>0</td><td>0.010000</td></tr><tr><td>MTu13</td><td>0</td><td>0</td><td>0,4</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>ns</td></tr><tr><td>MTu14</td><td>0</td><td>0</td><td>0,5</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>ns</td></tr><tr><td>α-Copaene</td><td>0,2</td><td>0</td><td>8,8</td><td>0,9</td><td>0,1</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0.002500</td></tr><tr><td>β-Caryophyllene</td><td>1,4</td><td>0</td><td>54,6</td><td>6,7</td><td>0,4</td><td>0</td><td>0</td><td>1,3</td><td>0,1</td><td>0</td><td>0.002000</td></tr><tr><td>α-Caryophyllene</td><td>0,5</td><td>0</td><td>19,3</td><td>2,4</td><td>0,1</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0.001000</td></tr><tr><td>SQTsu</td><td>0,8</td><td>0</td><td>16,7</td><td>2,3</td><td>0,1</td><td>0,1</td><td>0</td><td>4,4</td><td>0,6</td><td>0</td><td>0.0001</td></tr></tbody></table>
<table><caption>**Table S4.** Mean emissions (± standard error) of the two main non-terpenic volatile compounds emitted by some tropical tree species in French Guiana. Letters indicate significant differences between seasons (*P* < 0.05).</caption><thead><tr><th>Specific name</th><th>Season</th><th>Heptane-2.2.4.6.6-pentamethyl</th><th>Toluene</th></tr></thead><tbody><tr><td rowspan="2">Protium decandrum</td><td>Dry</td><td>0 ± 0</td><td>0.1 ± 0.1a</td></tr><tr><td>Wet</td><td>0 ± 0</td><td>0 ± 0a</td></tr><tr><td rowspan="2">Inga nouraguensis</td><td>Dry</td><td>0 ± 0</td><td>0 ± 0</td></tr><tr><td>Wet</td><td>0 ± 0</td><td>0 ± 0</td></tr><tr><td rowspan="2">Eperua grandiflora</td><td>Dry</td><td>0 ± 0</td><td>0.04 ± 0.02a</td></tr><tr><td>Wet</td><td>0 ± 0</td><td>0 ± 0a</td></tr><tr><td rowspan="2">Eperua falcata</td><td>Dry</td><td>0 ± 0a</td><td>0 ± 0</td></tr><tr><td>Wet</td><td>1.1 ± 0.3b</td><td>0 ± 0</td></tr><tr><td rowspan="2">Eschweilera coriacea</td><td>Dry</td><td>0 ± 0a</td><td>0.03 ± 0.02a</td></tr><tr><td>Wet</td><td>1 ± 0.3b</td><td>0 ± 0a</td></tr><tr><td rowspan="2">Gustavia hexapetala</td><td>Dry</td><td>0 ± 0</td><td>0.5 ± 0.3a</td></tr><tr><td>Wet</td><td>0 ± 0</td><td>0 ± 0b</td></tr><tr><td rowspan="2">Brosimum guianense</td><td>Dry</td><td>0 ± 0a</td><td>0 ± 0</td></tr><tr><td>Wet</td><td>4.1 ± 0.4b</td><td>0 ± 0</td></tr><tr><td rowspan="2">Couepia caryophylloides</td><td>Dry</td><td>0 ± 0</td><td>0 ± 0</td></tr><tr><td>Wet</td><td>0 ± 0</td><td>0 ± 0</td></tr><tr><td rowspan="2">Eschweilera sagotiana</td><td>Dry</td><td>0 ± 0</td><td>0.03 ± 0.02a</td></tr><tr><td>Wet</td><td>0 ± 0</td><td>0 ± 0a</td></tr><tr><td rowspan="2">Pradosia ptychandra</td><td>Dry</td><td>0 ± 0a</td><td>0.2 ± 0.1a</td></tr><tr><td>Wet</td><td>0.7 ± 0.2b</td><td>0.1 ± 0.04a</td></tr><tr><td rowspan="2">Chrysophyllum pomiferum</td><td>Dry</td><td>0 ± 0</td><td>0.04 ± 0.03</td></tr><tr><td>Wet</td><td>nda</td><td>nda</td></tr><tr><td rowspan="2">Vouacapoua americana</td><td>Dry</td><td>0 ± 0</td><td>0 ± 0a</td></tr><tr><td>Wet</td><td>0 ± 0</td><td>0.1 ± 0.1a</td></tr><tr><td rowspan="2">Sextonia rubra</td><td>Dry</td><td>0 ± 0</td><td>0.1 ± 0.1a</td></tr><tr><td>Wet</td><td>0 ± 0</td><td>0 ± 0a</td></tr><tr><td rowspan="2">Chrysophyllum argenteum</td><td>Dry</td><td>0 ± 0a</td><td>0.01 ± 0.01a</td></tr><tr><td>Wet</td><td>0.6 ± 0.3b</td><td>0 ± 0a</td></tr><tr><td rowspan="2">Ferdinandusa paraensis</td><td>Dry</td><td>0 ± 0</td><td>0.1 ± 0.1a</td></tr><tr><td>Wet</td><td>0 ± 0</td><td>0 ± 0a</td></tr><tr><td rowspan="2">Talisia praealta</td><td>Dry</td><td>0 ± 0</td><td>0 ± 0</td></tr><tr><td>Wet</td><td>0 ± 0</td><td>0 ± 0</td></tr><tr><td rowspan="2">Licania alba</td><td>Dry</td><td>0 ± 0a</td><td>0.2 ± 0.1a</td></tr><tr><td>Wet</td><td>0.3 ± 0.1b</td><td>0 ± 0b</td></tr><tr><td rowspan="2">Chimarrhis turbinata</td><td>Dry</td><td>0 ± 0</td><td>0.3 ± 0.3a</td></tr><tr><td>Wet</td><td>0 ± 0</td><td>0 ± 0b</td></tr><tr><td rowspan="2">Eschweilera sp</td><td>Dry</td><td>0 ± 0</td><td>0 ± 0</td></tr><tr><td>Wet</td><td>0 ± 0</td><td>0 ± 0</td></tr><tr><td rowspan="2">Paloue guianensis</td><td>Dry</td><td>0 ± 0a</td><td>0 ± 0</td></tr><tr><td>Wet</td><td>0.6 ± 0.2b</td><td>0 ± 0</td></tr><tr><td>Eugenia culcullata</td><td>Dry</td><td>0 ± 0</td><td>0 ± 0</td></tr></tbody></table>
<table><tbody><tr><td rowspan="2">Tetragastris panamensis</td><td>Wet</td><td>0 ± 0</td><td>0 ± 0</td></tr><tr><td>Dry</td><td>0 ± 0</td><td>0 ± 0</td></tr><tr><td rowspan="2">Dicorynia guianensis</td><td>Wet</td><td>nda</td><td>nda</td></tr><tr><td>Dry</td><td>0 ± 0a</td><td>0 ± 0</td></tr><tr><td rowspan="2">Drypetes variabilis</td><td>Wet</td><td>0.7 ± 0.1b</td><td>0 ± 0</td></tr><tr><td>Dry</td><td>0 ± 0</td><td>0 ± 0</td></tr><tr><td rowspan="2">Pouteria retinervis</td><td>Wet</td><td>0 ± 0</td><td>0 ± 0</td></tr><tr><td>Dry</td><td>0 ± 0</td><td>0 ± 0</td></tr><tr><td rowspan="2">Aniba rosaeodora</td><td>Wet</td><td>0 ± 0</td><td>0 ± 0</td></tr><tr><td>Dry</td><td>0 ± 0</td><td>0 ± 0</td></tr><tr><td rowspan="2">Chaetocarpus schomburgkianus</td><td>Wet</td><td>0.2 ± 0.1b</td><td>0 ± 0</td></tr><tr><td>Dry</td><td>0 ± 0</td><td>0 ± 0</td></tr><tr><td rowspan="2">Catostemma fragrans</td><td>Wet</td><td>0 ± 0</td><td>0 ± 0</td></tr><tr><td>Dry</td><td>0 ± 0</td><td>0 ± 0</td></tr><tr><td rowspan="2">Hebepetalum humiriifolium</td><td>Wet</td><td>0 ± 0</td><td>0 ± 0</td></tr><tr><td>Dry</td><td>0 ± 0</td><td>0 ± 0</td></tr><tr><td rowspan="2">Moronobea coccinea</td><td>Wet</td><td>0 ± 0</td><td>0 ± 0</td></tr><tr><td>Dry</td><td>0 ± 0</td><td>0 ± 0</td></tr><tr><td rowspan="2">Symphonia globulifera</td><td>Wet</td><td>0 ± 0</td><td>0 ± 0</td></tr><tr><td>Dry</td><td>0 ± 0</td><td>0 ± 0</td></tr><tr><td rowspan="2">Eschweilera decolorans</td><td>Wet</td><td>0 ± 0</td><td>0 ± 0</td></tr><tr><td>Dry</td><td>0 ± 0</td><td>0 ± 0</td></tr><tr><td rowspan="2">Pouteria eugeniifolia</td><td>Wet</td><td>0 ± 0</td><td>0 ± 0</td></tr><tr><td>Dry</td><td>0.5 ± 0.3</td><td>0 ± 0</td></tr><tr><td rowspan="2">Carapa surinamensis</td><td>Wet</td><td>0 ± 0</td><td>0 ± 0</td></tr><tr><td>Dry</td><td>0 ± 0</td><td>0 ± 0</td></tr><tr><td rowspan="2">Dipteryx odorata</td><td>Wet</td><td>0 ± 0</td><td>0 ± 0</td></tr><tr><td>Dry</td><td>0 ± 0</td><td>0 ± 0</td></tr><tr><td rowspan="2">Vochysia sabatieri</td><td>Wet</td><td>0 ± 0</td><td>0 ± 0</td></tr><tr><td>Dry</td><td>0 ± 0</td><td>0 ± 0</td></tr></tbody></table>
<table><caption>**Table S5.** Results of the phylogenetic analyses using Pagel's λ and the corresponding *P* values. Significant values (*P* < 0.05) are shown in bold.</caption><thead><tr><th></th><th>Total BVOCs</th><th>Total terpenes</th><th>Total monoterpenes</th><th>Total sesquiterpenes</th></tr></thead><tbody><tr><td>Phylogenetic signal lambda</td><td>0.2</td><td>0.2</td><td>6.6</td><td>0.8</td></tr><tr><td>logL(lambda)</td><td>-104</td><td>-103</td><td>-825</td><td>-827</td></tr><tr><td>LR(lambda=0)</td><td>0.1</td><td>0.1</td><td>-0.001</td><td>673</td></tr><tr><td>P-value (based on LR test)</td><td>0.7</td><td>0.8</td><td>1</td><td>0.01</td></tr></tbody></table>
<table><caption>**Table S6.** Results of the Bayesian phylogenetic linear mixed models with season as fixed factor and phylogeny and species as random factors obtained with the R package *MCMCglmm*. The phylogeny term accounted for variability in the shared ancestry, while the species term accounted for species-specific traits independently of the shared ancestry. Significant values of fixed independent variables (*P* < 0.05) are shown in bold.</caption><thead><tr><th rowspan="2">Variables</th><th colspan="6">Fixed factors</th><th rowspan="2">R<sup>2</sup></th><th colspan="3">Random</th><th rowspan="2">Total model</th></tr><tr><th colspan="6">Statistics Table</th><th>Fixed factors</th><th>R<sup>2</sup><sub>f</sub></th><th>R<sup>2</sup><sub>s</sub></th><th>R<sup>2</sup><sub>r</sub></th></tr></thead><tbody><tr><td>Total terpenes</td><td>post.mean</td><td>l-95% CI</td><td>u-95% CI</td><td>eff.samp</td><td>pMCMC</td><td>0.1</td><td>0.02</td><td>0.01</td><td>0.1</td><td>0.2</td></tr><tr><td></td><td>(Intercept)</td><td>0.1</td><td>-0.2</td><td>0.4</td><td>1700</td><td>0.4</td><td></td><td></td><td></td><td></td></tr><tr><td></td><td>seasonWET</td><td>-0.4</td><td>-0.6</td><td>-0.3</td><td>1700</td><td>&lt;6e-04 ***</td><td></td><td></td><td></td><td></td></tr><tr><td>MTu1</td><td>post.mean</td><td>l-95% CI</td><td>u-95% CI</td><td>eff.samp</td><td>pMCMC</td><td>0.01</td><td>0.0001</td><td>0.00004</td><td>0.01</td><td>0.02</td></tr><tr><td></td><td>(Intercept)</td><td>-0.1</td><td>-0.2</td><td>0.1</td><td>1413</td><td>0.5</td><td></td><td></td><td></td><td></td></tr><tr><td></td><td>seasonWET</td><td>0.1</td><td>-0.1</td><td>0.3</td><td>1863</td><td>0.3</td><td></td><td></td><td></td><td></td></tr><tr><td>Hept-6en-3yn-1ol</td><td>post.mean</td><td>l-95% CI</td><td>u-95% CI</td><td>eff.samp</td><td>pMCMC</td><td>0.02</td><td>0.0001</td><td>0.0004</td><td>0.1</td><td>0.1</td></tr><tr><td></td><td>(Intercept)</td><td>-0.03</td><td>-0.3</td><td>0.2</td><td>2056</td><td>0.8</td><td></td><td></td><td></td><td></td></tr><tr><td></td><td>seasonWET</td><td>0.1</td><td>-0.1</td><td>0.3</td><td>1554</td><td>0.3</td><td></td><td></td><td></td><td></td></tr><tr><td>Toluene</td><td>post.mean</td><td>l-95% CI</td><td>u-95% CI</td><td>eff.samp</td><td>pMCMC</td><td>0.01</td><td>0.0002</td><td>0.0003</td><td>0.02</td><td>0.04</td></tr><tr><td></td><td>(Intercept)</td><td>0.1</td><td>-0.1</td><td>0.2</td><td>1700</td><td>0.3</td><td></td><td></td><td></td><td></td></tr><tr><td></td><td>seasonWET</td><td>-0.2</td><td>-0.4</td><td>-0.1</td><td>1553</td><td>0.01 *</td><td></td><td></td><td></td><td></td></tr><tr><td>MTu1</td><td>post.mean</td><td>l-95% CI</td><td>u-95% CI</td><td>eff.samp</td><td>pMCMC</td><td>0.0045</td><td>0.0001</td><td>0.00004</td><td>0.01</td><td>0.015</td></tr><tr><td></td><td>(Intercept)</td><td>-0.1</td><td>-0.2</td><td>0.1</td><td>1413</td><td>0.5</td><td></td><td></td><td></td><td></td></tr></tbody></table>
<table><tbody><tr><td></td><td>seasonWET</td><td>0.1</td><td>-0.1</td><td>0.3</td><td>1863</td><td>0.3</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>MTu2</td><td></td><td></td><td></td><td></td><td></td><td></td><td>post.mean</td><td>l-95% CI</td><td>u-95% CI</td><td>eff.samp</td><td>pMCMC</td><td>0.01</td><td>0.002</td><td>0.003</td><td>0.1</td><td>0.1</td></tr><tr><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td>(Intercept)</td><td>0.1</td><td>-0.1</td><td>0.3</td><td>1700</td><td>0.4</td><td></td><td></td><td></td><td></td><td></td></tr><tr><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td>seasonWET</td><td>-0.2</td><td>-0.3</td><td>0.004</td><td>1700</td><td>0.1</td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>MTu3</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td>post.mean</td><td>l-95% CI</td><td>u-95% CI</td><td>eff.samp</td><td>pMCMC</td><td>0.006</td><td>0.003</td><td>0.004</td><td>0.08</td><td>0.1</td></tr><tr><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td>(Intercept)</td><td>0.1</td><td>-0.2</td><td>0.3</td><td>1700</td><td>0.5</td><td></td><td></td><td></td><td></td><td></td></tr><tr><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td>seasonWET</td><td>-0.1</td><td>-0.3</td><td>0.03</td><td>1700</td><td>0.2</td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>α-Pinene</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td>post.mean</td><td>l-95% CI</td><td>u-95% CI</td><td>eff.samp</td><td>pMCMC</td><td>0.1</td><td>0.001</td><td>0.001</td><td>0.04</td><td>0.1</td></tr><tr><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td>(Intercept)</td><td>0.2</td><td>-0.01</td><td>0.4</td><td>1700</td><td>0.1</td><td></td><td></td><td></td><td></td><td></td></tr><tr><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td>seasonWET</td><td>-0.4</td><td>-0.6</td><td>-0.3</td><td>1855</td><td>&lt;6e-04 ***</td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>MTu4</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td>post.mean</td><td>l-95% CI</td><td>u-95% CI</td><td>eff.samp</td><td>pMCMC</td><td>0.02</td><td>0.01</td><td>0.07</td><td>0.2</td><td>0.3</td></tr><tr><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td>(Intercept)</td><td>0.2</td><td>-0.2</td><td>0.5</td><td>1700</td><td>0.2</td><td></td><td></td><td></td><td></td><td></td></tr><tr><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td>seasonWET</td><td>-0.3</td><td>-0.4</td><td>-0.1</td><td>1700</td><td>0.002 **</td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>MTu5</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td>post.mean</td><td>l-95% CI</td><td>u-95% CI</td><td>eff.samp</td><td>pMCMC</td><td>0.03</td><td>0.002</td><td>0.003</td><td>0.1</td><td>0.1</td></tr><tr><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td>(Intercept)</td><td>0.1</td><td>-0.1</td><td>0.3</td><td>1700</td><td>0.2</td><td></td><td></td><td></td><td></td><td></td></tr><tr><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td>seasonWET</td><td>-0.4</td><td>-0.5</td><td>-0.2</td><td>1700</td><td>&lt;6e-04 ***</td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>MTu6</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td>post.mean</td><td>l-95% CI</td><td>u-95% CI</td><td>eff.samp</td><td>pMCMC</td><td>0.01</td><td>0.005</td><td>0.004</td><td>0.1</td><td>0.1</td></tr><tr><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td>(Intercept)</td><td>0.1</td><td>-0.2</td><td>0.3</td><td>1519</td><td>0.5</td><td></td><td></td><td></td><td></td><td></td></tr><tr><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td>seasonWET</td><td>-0.2</td><td>-0.3</td><td>-0.01</td><td>1700</td><td>0.05 *</td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>MTu7</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td>post.mean</td><td>l-95% CI</td><td>u-95% CI</td><td>eff.samp</td><td>pMCMC</td><td>0.05</td><td>0.003</td><td>0.01</td><td>0.1</td><td>0.1</td></tr><tr><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td>(Intercept)</td><td>0.2</td><td>-0.04</td><td>0.4</td><td>1824</td><td>0.1</td><td></td><td></td><td></td><td></td><td></td></tr><tr><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td>seasonWET</td><td>-0.4</td><td>-0.6</td><td>-0.3</td><td>1700</td><td>&lt;6e-04 ***</td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>MTu8</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td>post.mean</td><td>l-95% CI</td><td>u-95% CI</td><td>eff.samp</td><td>pMCMC</td><td>0.02</td><td>0.005</td><td>0.01</td><td>0.1</td><td>0.1</td></tr></tbody></table>
(Intercept) 0.1 -0.3 0.4 1463 0.6
seasonWET -0.2 -0.4 -0.05 1700 0.01 **

Limonene

post.mean l-95% CI u-95% CI eff.samp pMCMC 0.04 0.003 0.006 0.1 0.1
(Intercept) 0.2 -0.1 0.4 1700 0.1
seasonWET -0.4 -0.6 -0.2 1700 < 6e-04 ***

Sabinene

post.mean l-95% CI u-95% CI eff.samp 0.01 0.001 0.002 0.05 0.06
pMCMC
(Intercept) 0.04 -0.1 0.2 1700 0.6
seasonWET -0.1 -0.3 0.1 1700 0.2

Trans-β-Ocimene

post.mean l-95% CI u-95% CI eff.samp 0.03 0.02 0.1 0.2 0.3
pMCMC
(Intercept) 0.1 -0.2 0.5 1835 0.3
seasonWET -0.3 -0.4 -0.1 1700 0.001 **

MTu9

post.mean l-95% CI u-95% CI eff.samp 0.01 0.02 0.03 0.2 0.2
pMCMC
(Intercept) 0.1 -0.3 0.5 1392 0.4
seasonWET -0.2 -0.4 -0.04 1700 0.01 *

MTu10

post.mean l-95% CI u-95% CI eff.samp pMCMC 0.02 0.02 0.1 0.2 0.3
(Intercept) 0.1 -0.2 0.5 2087 0.3
seasonWET -0.3 -0.4 -0.1 1700 0.005 **

MTu11

post.mean l-95% CI u-95% CI eff.samp 0.01 0.01 0.01 0.1 0.1
pMCMC
(Intercept) 0.1 -0.3 0.4 2120 0.6
seasonWET -0.1 -0.3 0.05 1700 0.1

MTu12

post.mean l-95% CI u-95% CI eff.samp 0.01 0.002 0.01 0.1 0.2
<table><tbody><tr><td></td><td>pMCMC</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td></td><td>(Intercept)</td><td>0.1</td><td>-0.3</td><td>0.4</td><td>1700</td><td>0.6</td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td></td><td>seasonWET</td><td>-0.1</td><td>-0.3</td><td>0.04</td><td>1700</td><td>0.2</td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td rowspan="3">α-Terpinolene</td><td>pMCMC</td><td>post.mean</td><td>l-95% CI</td><td>u-95% CI</td><td>eff.samp</td><td></td><td>0.02</td><td>0.02</td><td>0.1</td><td>0.2</td><td>0.4</td></tr><tr><td>(Intercept)</td><td>0.1</td><td>-0.2</td><td>0.5</td><td>1700</td><td>0.3</td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>seasonWET</td><td>-0.3</td><td>-0.5</td><td>-0.1</td><td>2067</td><td>0.001 **</td><td></td><td></td><td></td><td></td><td></td></tr><tr><td rowspan="3">MTu13</td><td>pMCMC</td><td>post.mean</td><td>l-95% CI</td><td>u-95% CI</td><td>eff.samp</td><td></td><td>0.01</td><td>0.0004</td><td>0.001</td><td>0.03</td><td>0.04</td></tr><tr><td>(Intercept)</td><td>0.1</td><td>-0.1</td><td>0.3</td><td>1700</td><td>0.3</td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>seasonWET</td><td>-0.2</td><td>-0.4</td><td>-0.01</td><td>1700</td><td>0.1</td><td></td><td></td><td></td><td></td><td></td></tr><tr><td rowspan="3">MTu14</td><td>pMCMC</td><td>post.mean</td><td>l-95% CI</td><td>u-95% CI</td><td>eff.samp</td><td></td><td>0.01</td><td>0.0003</td><td>0.001</td><td>0.03</td><td>0.04</td></tr><tr><td>(Intercept)</td><td>0.04</td><td>-0.1</td><td>0.2</td><td>1700</td><td>0.6</td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>seasonWET</td><td>-0.1</td><td>-0.3</td><td>0.1</td><td>1333</td><td>0.2</td><td></td><td></td><td></td><td></td><td></td></tr><tr><td rowspan="3">α-Copaene</td><td>pMCMC</td><td>post.mean</td><td>l-95% CI</td><td>u-95% CI</td><td>eff.samp</td><td></td><td>0.01</td><td>0.01</td><td>0.01</td><td>0.1</td><td>0.1</td></tr><tr><td>(Intercept)</td><td>0.002</td><td>-0.4</td><td>0.3</td><td>1700</td><td>1</td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>seasonWET</td><td>-0.2</td><td>-0.3</td><td>0.01</td><td>1517</td><td>0.05 *</td><td></td><td></td><td></td><td></td><td></td></tr><tr><td rowspan="3">α-Caryophyllene</td><td>pMCMC</td><td>post.mean</td><td>l-95% CI</td><td>u-95% CI</td><td>eff.samp</td><td></td><td>0.01</td><td>0.01</td><td>0.003</td><td>0.1</td><td>0.1</td></tr><tr><td>(Intercept)</td><td>-0.001</td><td>-0.3</td><td>0.3</td><td>1700</td><td>1</td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>seasonWET</td><td>-0.2</td><td>-0.4</td><td>-0.01</td><td>1806</td><td>0.02 *</td><td></td><td></td><td></td><td></td><td></td></tr><tr><td rowspan="3">SQTsu1</td><td>pMCMC</td><td>post.mean</td><td>l-95% CI</td><td>u-95% CI</td><td>eff.samp</td><td></td><td>0.05</td><td>0.01</td><td>0.06</td><td>0.2</td><td>0.3</td></tr><tr><td>(Intercept)</td><td>0.2</td><td>-0.1</td><td>0.5</td><td>1700</td><td>0.2</td><td></td><td></td><td></td><td></td><td></td></tr></tbody></table>
<table><tbody><tr><td></td><td>seasonWET</td><td>-0.5</td><td>-0.6</td><td>-0.3</td><td>1700</td><td>&lt;6e-04 ***</td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td rowspan="3">Isoprene</td><td>pMCMC</td><td>post.mean</td><td>l-95% CI</td><td>u-95% CI</td><td>eff.samp</td><td></td><td>0.04</td><td>0.003</td><td>0.001</td><td>0.06</td><td>0.1</td></tr><tr><td>(Intercept)</td><td>-0.03</td><td>-0.3</td><td>0.3</td><td>1700</td><td>0.8</td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>seasonWET</td><td>0.1</td><td>-0.04</td><td>0.3</td><td>1700</td><td>0.2</td><td></td><td></td><td></td><td></td><td></td></tr><tr><td rowspan="3">Total Monoterpenes</td><td>pMCMC</td><td>post.mean</td><td>l-95% CI</td><td>u-95% CI</td><td>eff.samp</td><td></td><td>0.07</td><td>0.01</td><td>0.04</td><td>0.2</td><td>0.3</td></tr><tr><td>(Intercept)</td><td>0.3</td><td>0.001</td><td>0.5</td><td>1700</td><td>0.1</td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>seasonWET</td><td>-0.5</td><td>-0.7</td><td>-0.4</td><td>1700</td><td>&lt;6e-04 ***</td><td></td><td></td><td></td><td></td><td></td></tr><tr><td rowspan="3">Total Sesquiterpenes</td><td>pMCMC</td><td>post.mean</td><td>l-95% CI</td><td>u-95% CI</td><td>eff.samp</td><td></td><td>0.03</td><td>0.01</td><td>0.002</td><td>0.1</td><td>0.1</td></tr><tr><td>(Intercept)</td><td>0.1</td><td>-0.2</td><td>0.4</td><td>1700</td><td>0.6</td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>seasonWET</td><td>-0.3</td><td>-0.5</td><td>-0.2</td><td>1574</td><td>&lt;6e-04 ***</td><td></td><td></td><td></td><td></td><td></td></tr></tbody></table>
<table><caption>**Table S7.** Number of mature trees sampled per species at each topographic level and weather station. Phenology indicates if trees are evergreen or deciduous in each season. For more information, see Verryckt et al. (2022).</caption><thead><tr><th rowspan="2">Species</th><th rowspan="2">Topographic level</th><th colspan="2">Number of trees sampled per species</th></tr><tr><th>Dry</th><th>Wet</th></tr></thead><tbody><tr><td>Aniba rosaeodora</td><td>Slope</td><td>1</td><td>1</td></tr><tr><td>Brosimum guianense</td><td>Bottom</td><td>1</td><td>1</td></tr><tr><td>Carapa surinamensis</td><td>Bottom</td><td></td><td>1</td></tr><tr><td>Catostemma fragrans</td><td>Bottom</td><td>1</td><td>1</td></tr><tr><td>Chaetocarpus schomburgkianus</td><td>Top</td><td>1</td><td>1</td></tr><tr><td>Chimarrhis turbinata</td><td>Top</td><td>1</td><td>1</td></tr><tr><td>Chrysophyllum argenteum</td><td>Top</td><td>1</td><td>1</td></tr><tr><td>Chrysophyllum pomiferum</td><td>Top</td><td>1</td><td>1</td></tr><tr><td>Couepia caryophylloides</td><td>Slope</td><td>1</td><td>1</td></tr><tr><td>Dicorynia guianensis</td><td>Bottom</td><td>1</td><td>1</td></tr><tr><td>Dipteryx odorata</td><td>Bottom</td><td></td><td>1</td></tr><tr><td>Drypetes variabilis</td><td>Bottom</td><td>1</td><td>1</td></tr><tr><td>Eperua falcata</td><td>Bottom</td><td>3</td><td>4</td></tr><tr><td>Eperua grandiflora</td><td>Slope</td><td>2</td><td>1</td></tr><tr><td>Eschweilera sp</td><td>Bottom</td><td>1</td><td>1</td></tr><tr><td>Eschweilera coriacea</td><td>Top</td><td>1</td><td>1</td></tr><tr><td>Eschweilera decolorans</td><td>Bottom</td><td>1</td><td>1</td></tr><tr><td>Eschweilera sagotiana</td><td>Slope</td><td>1</td><td></td></tr><tr><td>Eugenia NA</td><td>Top</td><td>1</td><td>1</td></tr><tr><td>Ferdinandusa paraensis</td><td>Slope</td><td>1</td><td>1</td></tr><tr><td>Gustavia hexapetala</td><td>Bottom</td><td>1</td><td>1</td></tr><tr><td>Hebepetalum humiriifolium</td><td>Slope</td><td>1</td><td></td></tr><tr><td>Inga nouraguensis</td><td>Slope</td><td>1</td><td>1</td></tr><tr><td>Licania alba</td><td>Bottom</td><td>2</td><td>3</td></tr><tr><td>Moronobea coccinea</td><td>Top</td><td>1</td><td>1</td></tr><tr><td>Paloue guianensis</td><td>Bottom</td><td>1</td><td>1</td></tr><tr><td>Pouteria eugeniifolia</td><td>Top</td><td></td><td>1</td></tr><tr><td>Pouteria retinervis</td><td>Slope</td><td>1</td><td>1</td></tr><tr><td>Pradosia ptychandra</td><td>Bottom</td><td>1</td><td>1</td></tr><tr><td>Protium decandrum</td><td>Slope</td><td>1</td><td>1</td></tr><tr><td>Sextonia rubra</td><td>Top</td><td>1</td><td>1</td></tr><tr><td>Symphonia globulifera</td><td>Bottom</td><td>1</td><td></td></tr><tr><td>Talisia praealta</td><td>Top</td><td>1</td><td>1</td></tr><tr><td>Tetragastris panamensis</td><td>Slope</td><td>1</td><td></td></tr><tr><td>Vochysia sabatieri</td><td>Top</td><td></td><td>1</td></tr><tr><td>Vouacapoua americana</td><td>Bottom</td><td>1</td><td>1</td></tr></tbody></table>
<table><caption>**Table S8.** List of species sampled in this work and sampled by other authors previously. We want to show that in the present work there are tree species not previously sampled for BVOCs. In the case of Jardine et al. 2020 only gives information about gender.</caption><thead><tr><th>Species</th><th>Present work</th><th>Courtois et al. 2009</th><th>Courtois et al. 2016</th><th>Jardine et al. 2020</th></tr></thead><tbody><tr><td>Aniba rosaeodora <sup>a</sup></td><td>x</td><td></td><td></td><td></td></tr><tr><td>Brosimum guianense</td><td>x</td><td>x</td><td>x</td><td></td></tr><tr><td>Carapa surinamensis</td><td>x</td><td></td><td></td><td></td></tr><tr><td>Catostemma fragrans</td><td>x</td><td></td><td>x</td><td></td></tr><tr><td>Chaetocarpus schomburgkianus</td><td>x</td><td></td><td></td><td></td></tr><tr><td>Chimarrhis turbinata</td><td>x</td><td>x</td><td>x</td><td></td></tr><tr><td>Chrysophyllum argenteum</td><td>x</td><td>x</td><td>x</td><td></td></tr><tr><td>Chrysophyllum pomiferum</td><td>x</td><td></td><td></td><td></td></tr><tr><td>Couepia caryophylloides</td><td>x</td><td></td><td></td><td></td></tr><tr><td>Dicorynia guianensis</td><td>x</td><td></td><td>x</td><td></td></tr><tr><td>Dipteryx odorata</td><td>x</td><td></td><td>x</td><td></td></tr><tr><td>Drypetes variabilis</td><td>x</td><td></td><td>x</td><td></td></tr><tr><td>Eperua falcata</td><td>x</td><td></td><td>x</td><td></td></tr><tr><td>Eperua grandiflora</td><td>x</td><td></td><td></td><td></td></tr><tr><td>Eschweilera coriacea</td><td>x</td><td>x</td><td>x</td><td></td></tr><tr><td>Eschweilera decolorans</td><td>x</td><td></td><td>x</td><td></td></tr><tr><td>Eschweilera sagotiana</td><td>x</td><td></td><td>x</td><td></td></tr><tr><td>Eschweilera sp</td><td>x</td><td></td><td></td><td>x</td></tr><tr><td>Eugenia culcullata <sup>b</sup></td><td>x</td><td></td><td>x</td><td></td></tr><tr><td>Ferdinandusa paraensis</td><td>x</td><td></td><td></td><td></td></tr><tr><td>Gustavia hexapetala</td><td>x</td><td></td><td>x</td><td></td></tr><tr><td>Hebepetalum humiriifolium</td><td>x</td><td></td><td>x</td><td></td></tr><tr><td>Inga nouraguensis</td><td>x</td><td></td><td></td><td>x</td></tr><tr><td>Licania alba</td><td>x</td><td></td><td></td><td>x</td></tr><tr><td>Moronobea coccinea</td><td>x</td><td></td><td>x</td><td></td></tr><tr><td>Paloue guianensis</td><td>x</td><td></td><td></td><td></td></tr><tr><td>Pouteria eugeniifolia</td><td>x</td><td></td><td></td><td>x</td></tr><tr><td>Pouteria retinervis</td><td>x</td><td></td><td></td><td>x</td></tr><tr><td>Pradosia ptychandra</td><td>x</td><td></td><td>x</td><td></td></tr><tr><td>Protium decandrum</td><td>x</td><td>x</td><td>x</td><td>x</td></tr><tr><td>Sextonia rubra</td><td>x</td><td>x</td><td>x</td><td></td></tr><tr><td>Symphonia globulifera</td><td>x</td><td></td><td>x</td><td></td></tr><tr><td>Talisia praealta</td><td>x</td><td></td><td></td><td></td></tr><tr><td>Tetragastris panamensis <sup>c</sup></td><td>x</td><td>x</td><td>x</td><td></td></tr><tr><td>Vochysia sabatieri</td><td>x</td><td></td><td></td><td></td></tr><tr><td>Vouacapoua americana</td><td>x</td><td>x</td><td>x</td><td></td></tr></tbody></table>

All names verified in Steege et al. 2019, except for **a**: which appears as *Aniba rosiodora*; **b**: *Eugenia cucullata*; **c**: Does not appear in the list.