This is the accepted version of the article: Yañez Serrano, Ana Maria; Bourtsoukidis, Efstratios; Gomes Alves, Eliane; [et al.]. «Amazonian biogenic volatile organic compounds under global change». Global Change Biology, Vol. 26, issue 9 (Sep. 2020), p. 4722-4751. DOI 10.1111/gcb.15185 This version is avaible at https://ddd.uab.cat/record/232212 under the terms of the license 1 Amazonian Biogenic Volatile Organic Compounds under Global Change 2 A.M. Yáñez-Serrano1,2, E. Bourtsoukidis3, E.G. Alves4, M. Bauwens5, T. Stavrakou5, J. Llusia1,2, 3 I. Filella1,2, A. Guenther6, J. Williams3, P. Artaxo7, K. Sindelarova8, J. Doubalova8,9, J. 4 Kesselmeier3, J. Peñuelas1,2. 5 [1]{CREAF, E08193 Cerdanyola del Vallès, Catalonia, Spain} 6 [2]{CSIC, Global Ecology Unit, CREAF‐CSIC‐UAB, E08193 Cerdanyola del Vallès, Catalonia, Spain} 7 [3]{Atmospheric Chemistry and Multiphase Chemistry Departments, Max Planck Institute for Chemistry, P. O. 8 Box 3060, 55128, Mainz, Germany} 9 [4]{Department of Biogeochemical Processes, Max Planck Institute for Biogeochemistry, Hans-Knöll-Straße 10 10, 07745, Jena, Germany} 11 [5]{Royal Belgian Institute for Space Aeronomy, Avenue Circulaire 3, 1180, Brussels, Belgium} 12 [6]{Department of Earth System Science, University of California, Irvine 92697, USA} 13 [7]{Instituto de Física, Universidade de Sao Paulo (USP), Rua do Matão, Travessa R, 187, CEP 05508-900, São 14 Paulo, SP, Brasil} 15 [8]{Charles University, Faculty of Mathematics and Physics, Dept. of Atmospheric Physics, Prague, Czechia} 16 [9]{Czech Hydrometeorological Institute, Modelling and Assessment Dept., Prague, Czechia} 17 18 Correspondence e-mail: ayanezserrano@yahoo.es 19 Keywords: Biogenic volatile organic compounds, BVOCs, Amazonia, air chemistry, climate, 20 ecological interactions, depositional processes, land use, land cover, global change 21 22 Abstract 23 Biogenic volatile organic compounds (BVOCs) play important roles at cellular, foliar, ecosystem, and 24 atmospheric levels. The Amazonian rainforest represents one of the major global sources of BVOCs, so its study 25 is essential for understanding BVOC dynamics. It also provides insights into the role of such large and biodiverse 26 forest ecosystem in regional and global atmospheric chemistry and climate. We review the current information on 27 Amazonian BVOCs and identify future research priorities exploring biogenic emissions and drivers, ecological 28 interactions, atmospheric impacts, depositional processes, and modifications to BVOC dynamics due to changes 29 in climate and land cover. A feedback loop between Amazonian BVOCs and the trends of climate and land-use 30 changes in Amazonia is then constructed. Satellite observations and model simulation time series demonstrate the 31 validity of the proposed loop showing a combined effect of climate change and deforestation on BVOC emission 32 in Amazonia. A decreasing trend of isoprene during the wet season, most likely due to forest biomass loss, and 33 an increasing trend of the sesquiterpene to isoprene ratio during the dry season, suggest increasing temperature 34 stress induced emissions due to climate change. 35 36 1. Introduction 37 Biogenic volatile organic compounds (BVOCs) are emitted by vegetation, bacteria, algae, fungi, and 38 animals. Their rates of emission vary greatly in response to biotic (e.g. herbivory) and abiotic 39 (meteorological) factors (Šimpraga et al., 2019). They have diverse roles at multiple scales, from 40 cellular protection and defence at the foliar level, through chemical signalling at regional level, up to 41 influencing rainfall at the ecosystems scale (Laothawornkitkul et al., 2009). BVOCs profoundly affect 42 biosphere-atmosphere interactions by atmospheric reactivity, aerosol growth processes, and cloud 43 formation, and therefore radiative balance (Kulmala et al., 2013; Nölscher et al., 2016; Pöschl et al., 44 2010). As BVOCs are precursors of aerosols, they can impact the regional radiative forcing directly 45 through aerosol scattering and indirectly by influencing cloud processes. Furthermore, higher cloud 46 cover leads into increased diffuse radiation, boosting net primary productivity and thereby BVOC 47 emissions (Rap et al., 2018). However, BVOCs can have further impacts on the radiative forcing by 48 their influence on tropospheric ozone formation or by increasing the lifetime of methane by suppression 49 of its major sink, the OH radical (Peñuelas & Llusià, 2003). 50 Vegetation is the largest source of BVOC emissions, with tropical trees responsible for ca. 80% of 51 global terpenoid emissions and 50% of other BVOC emissions (Guenther et al., 2012). With half of the 52 global tropical forests, Amazonia is the largest remaining pristine continental area (Andreae et al., 2015; 53 Pöhlker et al., 2019). Amazonia stores 50% of tropical-forest carbon, plays a vital role in the global 54 cycles of energy, water, and carbon, and has the largest biodiversity in the world (Levine et al., 2016; 55 Malhi et al., 2008; Swift et al., 1998; ter Steege et al., 2013). This dynamic system emits large quantities 56 of chemically diverse BVOCs to the atmosphere, with implications both within and above Amazonian 57 forest canopies. Amazonia is highly sensitive to changes in climate and land use due to its strong energy 58 and biochemical cycling (Levine et al., 2016). It has been established that recent human action is already 59 altering Amazonian conditions and feedbacks (Sena et al., 2018; Shrivastava et al., 2019), complicating 60 the understanding of BVOCs in this region. In fact, BVOC emission decrease due to forest conversion 61 to croplands in the tropics has been shown to result in a positive radiative forcing (Jia et al., 2019; Scott 62 et al., 2018). Additionally, the impact of Amazonian BVOCs on global primary production through 63 diffuse radiation has large implications for the global carbon balance (Rap et al., 2018). Furthermore, 64 by participating in cloud formation processes, Amazonian BVOCs play a key role in the regional 65 hydrological cycle, since Amazonian rainforests contribute to precipitation throughout the South 66 American continent (Boers et al., 2017; Rocha et al., 2018). Therefore, it is critical to understand the 67 BVOC response to environmental stresses caused by changes in climate and land use in Amazonia, and 68 how these changes will feedback into the Earth system (Peñuelas & Staudt, 2010). 69 We here review the recent advances in Amazonian BVOC research and estimate potential future BVOC 70 dynamics using information currently available for emission processes, resulting ecological interactions 71 and atmospheric impacts, depositional processes, and effects and feedbacks of climate and land use 72 change. We propose a feedback loop, which is supported by satellite observations and model 73 simulations of BVOC fluxes, to identify research priorities in Amazonian BVOCs. 74 2. Advances on BVOC scientific research in Amazonia 75 a. History of measurements 76 Measurements of BVOCs in Amazonian ecosystems are logistically difficult due to accessibility, and 77 power constrains. Research on this topic began in the 1970s and 1980s, when tethered balloon 78 observations demonstrated that Amazonia is a major source of BVOC emissions to the atmosphere 79 (Crutzen et al., 1985; Greenberg & Zimmerman, 1984; Zimmerman et al., 1988) providing 80 understanding into atmospheric chemistry (Grosjean, 1995). The establishment of the Large-Scale 81 Biosphere-Atmosphere Experiment in Amazonia (LBA) provided the first large-scale estimates of 82 isoprene emissions and oxidation products from data collected by aircraft and tower-based stations 83 (Kesselmeier et al., 2009). Nevertheless, understanding of the controlling processes was still scarce due 84 to the lack of data on temporal and spatial variability and the very limited number of BVOCs species 85 studied (Kesselmeier et al., 2009). The most commonly used prominent technique in early studies was 86 BVOC collection in cartridges, followed by transportation of field samples to laboratories outside of 87 Amazonia for analysis by gas chromatography. The logistical difficulties for sample transport were 88 addressed by establishing more locations for tower-based measurements, long term field campaigns, 89 new sampling approaches such as the use of drones (McKinney et al., 2019), along with more advanced 90 analytical tools such as proton-transfer-reaction mass spectrometry (Bracho-Nunez et al., 2013; Crutzen 91 et al., 2000; Fuentes et al., 2016; Jardine et al., 2011b, 2011a, 2011c, 2014, 2016b; Karl et al., 2009; 92 Kesselmeier et al., 2009; Kuhn et al., 2007; Liu et al., 2016; Rinne et al., 2002; Williams et al., 2001; 93 Yáñez-Serrano et al., 2015), the comparative reactivity method (CRM) (Nölscher et al., 2016; 94 Pfannerstill et al., 2018; Sinha et al., 2008), photoionization detector (PID) (Harley et al., 2004), semi- 95 volatile thermal desorption aerosol gas chromatography (SV-TAG) (Yee et al., 2018), and isoprene 96 portable monitoring system (T. Taylor personal communication). Extensive campaigns and projects 97 such as GoAmazon and ATTO provided integrated investigations of emissions, chemistry, transport, 98 and cloud processes (Andreae et al., 2015; Martin et al., 2017). Seasonality was clearly addressed (Alves 99 et al., 2016, 2018; Nölscher et al., 2016; Yáñez-Serrano et al., 2015, 2018b) and greater effort was 100 expended towards obtaining a mechanistic understanding that was provided by foliar-level 101 measurements under natural and controlled experiments (Alves et al., 2014; Bourtsoukidis et al., 2018; 102 Bracho-Nunez et al., 2012, 2013). Despite the increasing number of observation datasets and efforts 103 toward addressing horizontal heterogeneity (Batista et al., 2019), comparing ecosystems remains 104 difficult due to the spatial diversity of Amazonia (see S.I.1) and the inadequate information over 105 controlling processes. Figure 1 shows the number and location of BVOC measurements available since 106 1984, when the first measurements were published, showing the lack of spatial variability in the 107 Amazonian BVOC studies to date. 108 b. History of modelling 109 There are still too few observations of BVOC emissions for accurate representation of the regional 110 variability, resulting in large uncertainty in model predictions. Initially, the BVOC emissions algorithm 111 proposed by Guenther et al., (1995) included light- and temperature-dependent emissions of isoprene, 112 but all other emissions were regarded as only temperature-dependent, a potentially misleading 113 assumption (Kesselmeier & Staudt, 1999). The algorithm was updated in 1999 by a simple leaf-age 114 activity factor to determine the dependence on meteorological conditions. The Model of Emissions of 115 Gases and Aerosols from Nature (MEGAN) then simulated net emission rates, accounting for losses of 116 primary emissions (Guenther et al., 2006), with the latest update adding a longer list of compounds and 117 their emission factors (Guenther et al., 2012; Sindelarova et al., 2014). Further BVOC emissions 118 modelling included Organizing Carbon and Hydrology in Dynamic EcosystEm (ORCHIDEE) (Messina 119 et al., 2016) and Lund-Potsdam-Jena-General Ecosystem Simulator (LPJ-GUESS) (Acosta Navarro et 120 al., 2014). Amazonian modelling has thus been improved, but a reliable predictive framework for 121 emission capacities in Amazonia requires an improved mechanistic understanding of BVOC variation 122 across plant populations and of their interactions with other living organisms and abiotic factors (Alves 123 et al., 2018; Kuhn et al., 2004a; Salazar et al., 2018; Taylor et al., 2018). 124 c. Satellite applications 125 Amazonian isoprene fluxes can be derived at regional, or global scales via satellite measurements 126 (Barkley et al., 2009, 2013; Bauwens et al., 2016; Fu et al., 2019; Gu et al., 2017). This can improve 127 our knowledge of the dynamics in scale and time. Formaldehyde is formed during the oxidation of most 128 VOCs released in the atmosphere. It is a major intermediate product in isoprene oxidation, and therefore 129 satellite observations of formaldehyde (HCHO) have been used to infer isoprene emissions at global 130 and regional scales (Millet et al., 2008; Pamler et al., 2003; Stavrakou et al., 2009). The variability of 131 emissions estimated with these satellite data generally lies within the variability of the surface 132 observations. Direct observations of isoprene recently acquired by the satellite-borne Cross-track Infrared 133 Sounder (CrIS) (Fu et al., 2019) will open new avenues in the isoprene emission estimation from 134 satellites. A global study using these data found a regional reduction (-2% y-1) of biogenic emissions 135 over Amazonia during the period of 2005 to 2013 but no plausible cause could be identified (Bauwens 136 et al., 2016). 137 3. Emission 138 The BVOCs in the Amazonian rainforest have many sources, with vegetation being the most prominent 139 (Kesselmeier et al., 2009) (Figure 2). A large variety of BVOCs are emitted from Amazonian 140 ecosystems. Isoprene is the most strongly emitted compound, with reported ambient mixing ratios of 141 0.5-15 ppb and fluxes of 0.7-12.1 mg m-2ground h-1, although other isoprenoids have been reported such 142 as monoterpenes (with mixing ratios typically below 1 ppb but in some cases up to 5.5 ppb (Greenberg 143 & Zimmerman, 1984; Kesselmeier et al., 2002b)), sesquiterpenes (SQT) (with mixing ratios up to 0.16 144 ppb), and even diterpenes (0.0002 ppb) (Yee et al., 2018). Methanol is the second most emitted 145 compound, with measured mixing ratios reported up to 6 ppb (Kesselmeier et al., 2002b; Yáñez-Serrano 146 et al., 2015). Other oxygenated compounds have also been reported, such as acetaldehyde, acetone, 147 methyl ethyl ketone (MEK) (Bracho-Nunez et al., 2012; Rottenberger et al., 2008; Yáñez-Serrano et 148 al., 2016), ethanol (Bracho-Nunez et al., 2012; Rottenberger et al., 2008), formaldehyde (Karl et al., 149 2009; Kesselmeier et al., 2000), acetic and formic acid (Jardine et al., 2011b; Kuhn et al., 2002a), green- 150 leaf volatiles (GLVs) (Jardine et al., 2015b), isoprene oxidation products (including methyl vinyl ketone 151 (MVK), methacrolein (MACR), isoprene hydroperoxide (ISOPOOH), and hydroxyacetone (Karl et al., 152 2009), aromatics (Paralovo et al., 2015), sulphurous compounds such as dimethyl sulphide (Jardine et 153 al., 2014) as well as chlorine compounds such as methyl chloride and chloroform (Gebhardt et al., 2008; 154 Gregory et al., 1986; Yokouchi et al., 2002) (Table 1, figure 3 and 4). Additionally, the emission, and 155 consequent atmospheric abundance is given as the sum of enantiomers due to analytical constrains, yet 156 BVOCs are generated by enzymes and are therefore chiral. Although chemically identical, they can 157 induce differing biological responses. Thus examining the different enantiomers would lead to a 158 doubling of information (Williams et al., 2007). 159 Vegetation emits BVOCs, as de novo compounds from recently photosynthesised carbon or as 160 volatilised compounds from storage pools or resins and waxes (Kesselmeier & Staudt, 1999). These 161 emissions may represent a substantial loss of carbon previously assimilated by photosynthesis (up to 162 2% of carbon fixed for tropical forests) (Kesselmeier et al., 2002a). Isoprene is the most common de 163 novo biosynthesised compound, with isoprene-emitting plants found as a typical component in tropical 164 forests (Harley et al., 2004; Šimpraga et al., 2019; Taylor et al., 2018). Further species, such as 165 monoterpenes are also released de novo from leaves, glands, and resin ducts (Kesselmeier & Staudt, 166 1999) in Amazonia (Jardine et al., 2015a; Kuhn et al., 2002b; Piva et al., 2019; Yáñez-Serrano et al., 167 2018b). 168 169 In addition to living vegetation, leaf litter is an important source of BVOCs (Greenberg et al., 2012), 170 particularly during the start of the dry season when litterfall peaks, and decomposition is further aided 171 by wetness with the upcoming wet season. Little is known about this BVOC source in Amazonia, but 172 monoterpene addition to soils from leaf fall and excreted from plant resins and roots have been reported 173 elsewhere (Delory et al., 2016; Marmulla & Harder, 2014), suggesting a potential, unquantified role of 174 Amazonian ecosystems with a rapid turnover of biomass. 175 Soils are a poorly explored BVOC source in the Amazonian rainforest, including their microorganisms, 176 roots, and surface reactions (Tang et al., 2019). SQTs have recently been found to be strongly emitted 177 by soil bacteria (Bourtsoukidis et al., 2018), with responses to soil conditions, because microorganisms 178 are highly spatially heterogeneous (Buscardo et al., 2018), dynamic and able to produce and consume 179 BVOCs strongly interacting within the soil ecosystem. Also reduced sulphur compounds such as 180 dimethyl sulphide, carbon disulphide or carbonyl sulphide can be released by soils (Bunk et al., 2017), 181 including Amazonian soils (Jardine et al., 2014). 182 Similar to soil, microorganisms in the phyllosphere (both endo- and epiphytic) can be an important 183 source of BVOCs. The phyllosphere contains bacteria, fungi, bryophytes, and lichens and are extremely 184 diverse in tropical forests (Roy & Banerjee, 2018). Little is known about the relationship between the 185 phyllosphere and BVOCs, but typical colonizers of the phyllosphere can emit and metabolise BVOCs 186 (Farré-Armengol et al., 2016a; Kesselmeier et al., 1999; Rundell et al., 2015), therefore, the contribution 187 of phyllospheric emissions to net ecosystem emission may be important given their abundance in 188 rainforests (Roy & Banerjee, 2018). In addition to phyllospheric interactions, other processes at the 189 foliar level can be a source of BVOC emissions to the atmosphere, e.g. oxidation products formed 190 interactions at the surface of leaves (Jud et al., 2016) and adsorption/desorption onto/from surfaces. 191 Lastly, animals are a relatively unexplored source of BVOCs in Amazonian rainforests. In particular, 192 arthropods such as ants and termites contribute 1/3 of the animal biomass in Amazonian upland forests, 193 constituting several tonnes per hectare (Rinker & Lowman, 2004). Induced volatile emissions from 194 animals, such as emissions from wood-eating termites of different social ranks (Himuro et al., 2011), 195 or emissions of formic acid from ants for defensive purposes (Brütsch et al., 2017), have been reported. 196 However, the types and magnitudes of the emissions from Amazonian ecosystems have not been really 197 deepened since the reports by Zimmerman et al., (1982) or Khare et al., (1999). 198 The emission rates of BVOCs from all the aforementioned sources may vary considerably as a function 199 of driving factors. Temperature is a key driver of BVOC emissions, both for plants and soils, because 200 it promotes enzymatic reactions in pathways of BVOC biosynthesis and their diffusion in biological 201 tissues and soil substrates (Llusià & Peñuelas, 2000). For example, monoterpenes have been described 202 as leaf “thermometers”, increasing in emission with temperature (Jardine et al., 2017). Emissions of 203 SQTs and methanol are also temperature-dependent (Alves et al., 2016; Jardine et al., 2011c, 2016b) 204 and isoprene has been found to protect against thermal stress in Amazonia (Garcia et al., 2019). Soil 205 temperature is also a determinant because it increases decomposition and subsequent BVOC emission, 206 but such processes have not been adequately addressed. 207 Photosynthetically active radiation and its relationship to photosynthesis are essential drivers for 208 compounds emitted de novo, including isoprene and monoterpenes such as cis-β-ocimene (Alves et al., 209 2014; Harley et al., 2004; Jardine et al., 2013, 2015a, 2017; Kesselmeier & Staudt, 1999; Kuhn et al., 210 2002b, 2004a; Llusià & Peñuelas, 2000). For example, isoprene emissions from Hymenaea courbaril 211 have been strongly correlated with gross primary productivity under non-stress conditions (Kuhn et al., 212 2004b) and protect plants under high solar radiation conditions (Garcia et al., 2019). Rapidly changing 213 light conditions, e.g. during a sudden thunderstorm, can also induce emissions of acetaldehyde and 214 ethanol (Holzinger et al., 2000). The effect of solar radiation on soils has not been well explored, but 215 radiation would both heat the surface and decrease the water content due to evaporation, though only 216 about one third of the radiation that arrives at the top of the canopy reaches the soil (Alves et al., 2016). 217 The availability of water within ecosystems affects BVOC production, whether as humidity, foliar 218 uptake, or content in soil. Drought reduces stomatal conductance, decreases intracellular CO2 mixing 219 ratios and as a result, increases isoprene emissions (Pegoraro et al., 2004a), although this is dependent 220 on the severity of drought (Niinemets, 2010; Otu‐Larbi et al., 2020; Pegoraro et al., 2004b; Potosnak et 221 al., 2014). GLV emission can be stimulated at high temperatures and under drought conditions (Jardine 222 et al., 2015b; Pfannerstill et al., 2018). The general reduction of BVOC emissions by plants due to 223 drought depends on both changes in plant physiology and to lower foliar biomass. Emissions from 224 Amazonian soils depend on moisture, because bacteria may become activated by water, with an 225 emission burst after a large rainfall event and an optimal pattern of emissions, where SQT emissions 226 are the highest under moderate levels of soil water (Bourtsoukidis et al., 2018). The soil water also 227 affects the gas permeability of the soil. The soil water content is therefore an essential parameter for 228 BVOC production and release from Amazonian soils. 229 The atmospheric abundance of gaseous constituents is an additional regulator of BVOC emissions. The 230 mixing ratios of BVOCs in the atmosphere, particularly of oxygenated compounds that are 231 bidirectionally exchanged (Niinemets et al., 2014), is driven by a compensation point (i.e. a compound 232 is emitted if the foliar concentration is higher than the ambient mixing ratios, otherwise the plant will 233 take up the compound), as has been observed in Amazonia (Jardine et al., 2011b; Kuhn et al., 2002a; 234 Rottenberger et al., 2004). The amount of oxidants in the atmosphere can induce emissions to quench 235 oxidation (Jardine et al., 2011a, 2015a; Peñuelas & Llusià, 2001) and oxidise BVOCs generating 236 oxidation products. Biotic and abiotic stressors at the foliar level lead to the formation of reactive 237 oxygen species (ROS), altering plant BVOC emissions coordinated to quench the ROS (Jardine & 238 Jardine, 2016; Sampaio Filho et al., 2018). Regional and global models currently have a module for 239 deposition and another for emissions. For these bidirectional exchange compounds such modules must 240 be combined. One step forward in this matter is the addition of a bidirectional exchange compound 241 class in the MEGAN model (Guenther et al., 2012). 242 Increasing atmospheric CO2 mixing ratios can affect BVOC emissions (Possell et al., 2005; Wilkinson 243 et al., 2009) directly, with higher biomass due to higher substrate availability (Lerdau et al., 1994), and 244 thus higher foliar surface area for BVOC emission, as demonstrated for monoterpene emissions (Staudt 245 et al., 2001). However, no information on these processes is available for Amazonian ecosystems. These 246 increasing CO2 mixing ratios can also indirectly suppress the emission of compounds such as isoprene 247 (Young et al., 2009), due to a competition of phosphoenolpyruvate (PEP) (Fasbender et al., 2018; 248 Possell et al., 2005; Rosenstiel et al., 2003), which at the same time may be offset by warming and 249 increased growth (Garcia et al., 2019; Sharkey & Monson, 2017). 250 Phenology, ontogeny, and canopy structure play important roles in BVOC emissions in Amazonian 251 rainforests (Alves et al., 2018; Kuhn et al., 2004b; Wei et al., 2018). The quantity of BVOCs emitted 252 by leaves varies with the stage of maturity as a consequence of resource availability (maturity) and 253 defensive demand (bud break and early stages) (Kuhn et al., 2004b). For example, young Vismia 254 Guianensis leaves emit higher quantity of methanol than mature leaves (Jardine et al., 2016b), whereas 255 mature leaves Vismia Guianensis and Eschweilera coriacea have been found to higher emissions than 256 other leaf ages (Alves et al., 2014, 2016; Jardine et al., 2016b); and light-dependent monoterpenes are 257 emitted exclusively during the period between bud-break and foliar maturity for Hymenaea courbaril 258 (Kuhn et al., 2004b). Additionally, canopy structure plays a role in BVOC dynamics as shown with 259 high sesquiterpene emissions in the lower canopy (Alves et al., 2016). Foliar flushing in Central 260 Amazonia peaks during the transition from the wet to the dry season, with a consequent peak in leaf 261 litter and foliar turnover at the onset of the dry season (Goulden et al., 2004; Huete et al., 2006; Roberts 262 et al., 1998). This factor has been reported to be essential for modelling BVOC emission in Amazonia 263 (Alves et al., 2018). 264 Nutrient availability is another important driver of BVOC emissions (Fernández-Martínez et al., 2018). 265 In this regard, the role of litterfall have recently been demonstrated to be important for supplying soil 266 with nutrients that affect microbial composition in Amazonian ecosystems (Buscardo et al., 2018), but 267 no information is available with respect to the effect of nutrient availability on BVOC dynamics at 268 canopy level in Amazonia. 269 Biotic factors such as pathogens, herbivores, herbivorous predators, pollinators, and phyllospheric 270 organisms influence the emission rates of BVOCs. Plants emit BVOCs as defensive mechanisms or for 271 signalling within plants and ecosystems (Šimpraga et al., 2019). Alterations to these biological controls 272 can thus affect the average BVOC emissions from plants. Little is known about the role of the 273 phyllosphere in BVOC dynamics in the Amazonian rainforest, but some possible implications can be 274 derived from studies elsewhere. The phyllosphere affects plant biogeography and ecosystem function, 275 thereby affecting plant physiology. The phyllosphere reduces the amount of photosynthesis by blocking 276 light (Huete et al., 2006), protects plants against heat (Stuntz et al., 2002), can retain water in the leaves 277 (Coley et al., 1993; Stuntz et al., 2002), fixes nitrogen, and protects plants against herbivores and abiotic 278 stresses by the production of phytohormones and other secondary metabolites (Roy & Banerjee, 2018). 279 The phyllosphere is also subjected to environmental conditions that can alter its role from beneficial to 280 pathogenic. Such environmental conditions can be leaching, changes in temperature, variations in 281 exposure to sunlight, ROS concentration (Bringel & Couée, 2015), the phyllospheric cover itself, effects 282 of irrigation, cohabitation, foliar texture, and phenology (Coley et al., 1993; Saikkonen et al., 1998). 283 Lastly, species diversity can influence the total emission of BVOCs, as has been reported for terpenoids, 284 with substantial variation within species (Guenther, 2013). In Amazonia, an elevation gradient in 285 isoprene emissions was attributed to the plant species distribution which differ topographically (Gu et 286 al., 2017). The Amazonian rainforest contains a variety of ecosystems, from upland forests to flooded 287 or seasonally flooded forests (see SI for more information). Differences in environmental conditions 288 and adaptive strategies can be implied from differences in BVOC emission (Bracho-Nunez et al., 2012). 289 Investigation on the effects of root anoxia on BVOC exchange is thus important for understanding the 290 functioning of Amazonian ecosystems. Plants may react to flooding with fermentation, accompanied 291 by emissions of ethanol and acetaldehyde to remove the large amounts of ethanol produced under root 292 anoxia (Bracho-Nunez et al., 2012; Kreuzwieser et al., 1999; Rottenberger et al., 2008). The quantities 293 and ratios of such emissions can indicate the metabolic and morphologic adaptations of flooded 294 ecosystems (Parolin et al., 2004). 295 The vast amount of BVOC sources in the Amazonian rainforest (i.e. diverse species of insects, 296 vegetation, soil and phyllosphere microorganisms) is regulated by a plethora of biotic and abiotic 297 emission drivers (i.e. temperature, radiation, water and nutrient availability, ambient CO 2 and BVOC 298 mixing ratios) leading to a strong seasonality (Alves et al., 2016, 2018; Barkley et al., 2009; Kesselmeier 299 et al., 2002b; Kuhn et al., 2004a; Yáñez-Serrano et al., 2015, 2018b). While increasing research 300 addresses BVOC emissions over single or combined emission drivers, the large-scale biodiversity and 301 interplay of biotic and abiotic processes remains challenging. Within such large ecosystems, ecological 302 interactions may have an important, but poorly explored, role in regulating the BVOC emissions of the 303 Amazon rainforest. Table 1: Isoprene ambient mixing ratios reported in literature over Amazonian ecosystems in a within or above canopy and season basis. Data is organized by height with a line separating between within canopy mixing ratios and above canopy mixing ratios and between seasons. We considered 35m to be the average top of the Amazonian canopy. Values reported are in ppb and as presented in literature. They are usually means or medians. The values in parenthesis represent either standard deviation or interquartile range when available. Where only graphical data was available we used the software Plot Digitizer to derive means and standard deviations. The locations are classified according to the area where the measurements were taken, namely, Central Amazonia, Western Amazonia, South-western Amazonia, Guyana Shield and Central-east Amazonia. The techniques are PTR-MS: Proton Transfer Reaction Mass Spectrometer; GC-MS: Gas Chromatography Mass Spectrometer, GC-FID: Gas Chromatography Flame Ionization Detector and IEC: Ion-Exchange Chromatography. The seasons are specified together with the exact timing of sampling: Dry, dry season; Wet, wet season; D-t-W, transition from dry to wet season; and W-t-D, transition from wet to dry season. X stands for laboratory experiments or satellite retrievals. For a more extended table with all reported values for Amazonian ecosystems in ppb, please refer to Table1 in S.I.2. Note that in some cases fluxes in mg m-2 h-1 are reported (these cases are identified by (flux), or by an *). The compounds are presented in the following order: Acetaldehyde, acetic acid, acetone, acetonitrile, acetylene, benzaldehyde, benzene, butanal, butane, butene, 1,4-cyclohexadiene, p-cymene, decanal, dichloromethane, diterpenes, dimethylsulphide, estragole, ethane, ethanol, ethylbenzene, ethylene, formaldehyde, formic acid, heptane, 1-heptene, 2-heptene, hexane, hexanol, hexene, hydrogen sulphide, hydroxyacetone (flux), isoprene (flux), linalool, methyl ethyl ketone (MEK), methanol, 2-methyl-2-butene, methyl chloroform, 2-methyl-furan, 3-methyl-furan, 6-methyl-5-heptene-2-one, methyl mecarptan, methyliodide, total monoterpenes, total monoterpene (flux), methyl vinyl ketone and methacrolein (MVK+MACR), MVK+MACR (flux), nonanal, octane, pentanal (flux), pentane, propane, propylene, propyne, total sesquiterpenes, total sesquiterpene (flux), styrene, sulphur dioxide, α-terpineol, toluene and m-, p- and o-xylene. Isoprene Height Isoprene Site Season Technique Reference Observations (m) (ppb) Central Amazonia Dry 0.05 3.13 PTR-MS (Yáñez-Serrano et al., 2015) Central Amazonia Dry 0.5 3.77 PTR-MS (Yáñez-Serrano et al., 2015) Central Amazonia Dry 1 2.77(0.4) GC-FID (Rasmussen & Khalil, 1988) Daytime mean (11:00-15:00, LT). Canister sampling. Near ground level. Western Amazonia Dry 2 3.31 GC-MS (Helmig et al., 1998) Daytime mean. Central Amazonia Dry 4 5.35 PTR-MS (Yáñez-Serrano et al., 2015) Central Amazonia Dry 0-30 2.40(1-5.24) GC-FID (Greenberg & Zimmerman, 1984) Daytime mean. Canister sampling. Near ground to 30m Central Amazonia Dry 24 19.9(2.0) PTR-MS (Andreae et al., 2015) Daytime mean. Central Amazonia Dry 24 7.62 PTR-MS (Yáñez-Serrano et al., 2015) Central Amazonia Dry 30 2.65(1.39-3.38) GC-FID (Zimmerman et al., 1988) 24 h median. Sampling on teflon bag on tethered balloon (30m). Central Amazonia Dry 38 6.13 PTR-MS (Yáñez-Serrano et al., 2015) Central Amazonia Dry 40 2.68(0.9) PTR-MS (Alves et al., 2016) Daytime mean (10:00-14:00, LT). Central Amazonia Dry 40 7.94(1.67) PTR-MS (Wei et al., 2018) Daytime mean. Afternoon values. Fluxes 30 ºC and 1000 µmol m-2 s-1. Cartridge on Disjunct Eddy Central Amazonia Dry 45 5 max. GC-MS (Rinne et al., 2002) Accumulation. Southwestern Amazonia Dry 50 4.6(2.7) GC-FID (Aquino, 2006) Daytime mean (11:00-16:00, LT). Canister sampling. Central Amazonia Dry 51 3.4(1.8) GC-FID (Kuhn et al., 2007) Daytime mean (10:00-15:00, LT). Cartridge on Relaxed Eddy Accumulation. Central Amazonia Dry 53 5.72 PTR-MS (Yáñez-Serrano et al., 2015) Central Amazonia Dry 54 7.80 PTR-MS (Rizzo et al., 2010) Maximum at noon. Disjunct Eddy Covariance. Central Amazonia Dry 55 7.8(3.7) PTR-MS (Karl et al., 2007) Daytime mean (12:00-14:00, LT). Disjunct Eddy Covariance. Southwestern Amazonia Dry 60 4.0(2.5) GC-FID (Aquino, 2006) Daytime mean (11:00-16:00, LT). Canister sampling. Central Amazonia Dry 79 4.81 PTR-MS (Yáñez-Serrano et al., 2015) Central Amazonia Dry 305 1.73(1.03-2.15) GC-FID (Zimmerman et al., 1988) 24 h median. Sampling on teflon bag on tethered balloon (305m). Western Amazonia Dry 91-1167 1.69 GC-MS (Helmig et al., 1998) Daytime mean. Central Amazonia Dry 100-1200 5.5(2.6) PTR-MS (Karl et al., 2007) Daytime mean (10:00-11:30, LT). Mixed Layer Gradient. Central Amazonia Dry 150-1500 1.5(0.75) GC-FID (Rasmussen & Khalil, 1988) Daytime. Canister sampling. Aircraft flights. Central Amazonia Dry 35-2000 2.27(0.38-4.08) GC-FID (Greenberg & Zimmerman, 1984) Daytime mean. Canister sampling. Flights from treetop to 2 km. Western Amazonia Dry 1481-1554 0.16 GC-MS (Helmig et al., 1998) Daytime mean. Central Amazonia Dry 2000-17000 0.19(0.14-0.22) GC-FID (Greenberg & Zimmerman, 1984) Daytime mean. Canister sampling. Flights from 2km to Tropopause. Central Amazonia Dry & D-t-W 2 1.54(1.37) PTR-MS (Jardine et al., 2011a) Central Amazonia Dry & D-t-W 11 2.86(1.61) PTR-MS (Jardine et al., 2011a) Central Amazonia Dry & D-t-W 17 2.86(1.53) PTR-MS (Jardine et al., 2011a) Central Amazonia Dry & D-t-W 24 2.71(1.37) PTR-MS (Jardine et al., 2011a) Southwestern Amazonia Dry & D-t-W 08-52 9.5(4) GC-FID (Kesselmeier et al., 2002b) Daytime mean (11:00-18:00, LT). Central Amazonia Dry & D-t-W 30 2.47(1.26) PTR-MS (Jardine et al., 2011a) Central Amazonia Dry & D-t-W 40 2.36(1.26) PTR-MS (Jardine et al., 2011a) Central Amazonia Dry & Wet 40 2.5(2.2) PTR-MS (Fuentes et al., 2016) Central Amazonia D-t-W 40 2.65(1.33) PTR-MS (Alves et al., 2016) Daytime mean (10:00-14:00, LT). Central Amazonia D-t-W 40 6.76(2.35) PTR-MS (Wei et al., 2018) Daytime mean. Southwestern Amazonia D-t-W 50 3.4(1.2) GC-FID (Aquino, 2006) Daytime mean (11:00-16:00, LT). Canister sampling. Southwestern Amazonia D-t-W 60 3.0(0.5) GC-FID (Aquino, 2006) Daytime mean (11:00-16:00, LT). Canister sampling. Central Amazonia Wet 0 6.90 GC-MS (Kesselmeier et al., 2000) Daytime mean (15:00, LT). Central Amazonia Wet 0.05 0.57 PTR-MS (Yáñez-Serrano et al., 2015) Central Amazonia Wet 0.5 0.57 PTR-MS (Yáñez-Serrano et al., 2015) Central Amazonia Wet 1 3.2(0.9) GC-MS (da Silva, 2010) Daytime mean (07:00-17:00, LT). Cartridge sampling. Central Amazonia Wet 1.5 4.33(2.02) GC-MS (Kesselmeier et al., 2000) Daytime mean (09:30-16:00, LT). Outside forest. Central Amazonia Wet 1.5 3.01(0.85) GC-MS (Kesselmeier et al., 2000) Daytime mean (09:30-16:00, LT). Inside canopy. Central Amazonia Wet 4 0.86 PTR-MS (Yáñez-Serrano et al., 2015) Central-East Amazonia Wet 8.1 0.13(0.61) GC-MS (Jardine et al., 2016a) Nighttime mean. Central-East Amazonia Wet 8.1 8.95(4.2) GC-MS (Jardine et al., 2016a) Daytime mean. Central Amazonia Wet 10 4.6(0.94) GC-MS (da Silva, 2010) Daytime mean (07:00-17:00, LT). Cartridge sampling. Central Amazonia Wet 20 6.17(1.03) GC-MS (da Silva, 2010) Daytime mean (07:00-17:00, LT). Cartridge sampling. Central Amazonia Wet 24 2.29 PTR-MS (Yáñez-Serrano et al., 2015) Central Amazonia Wet 30 7.90 GC-MS (Kesselmeier et al., 2000) Daytime mean (14:00, LT). Central Amazonia Wet 38 2.39 PTR-MS (Yáñez-Serrano et al., 2015) Central Amazonia Wet 40 1.66(0.9) PTR-MS (Alves et al., 2016) Daytime mean (10:00-14:00, LT). Central Amazonia Wet 40 4.66(2.21) PTR-MS (Wei et al., 2018) Daytime medan. Central Amazonia Wet 50 6.3(1.32) GC-MS (Kesselmeier et al., 2000) Daytime mean (12:00-16:00, LT). Southwestern Amazonia Wet 50 4.5(0.9) GC-FID (Aquino, 2006) Daytime mean (11:00-16:00, LT). Canister sampling. Central Amazonia Wet 53 1.85 PTR-MS (Yáñez-Serrano et al., 2015) Southwestern Amazonia Wet 60 4.0(1.2) GC-FID (Aquino, 2006) Daytime mean (11:00-16:00, LT). Canister sampling. Central Amazonia Wet 60 2.40 GC-MS/FID (Batista et al., 2019) Mean of overall dataset. Slope forest. Cartridge sampling with drones. Central Amazonia Wet 60 4.40 GC-MS/FID (Batista et al., 2019) Mean of overall dataset. Plateu forest. Cartridge sampling with drones. Central Amazonia Wet 79 1.69 PTR-MS (Yáñez-Serrano et al., 2015) Central Amazonia Wet 200-500 ~3 GC-MS (Kesselmeier et al., 2000) 24 hr mean. Sampling with thetered balloon. Guyana Shield Wet 400 ~2.3 GC-FID (Gregory et al., 1986) Canister sampling. Central Amazonia Wet 500 ~3 PTR-MS (Martin et al., 2017) During periods of clean conditions (above threshold). Daytime median and interquartiles (12:00-15:00, LT). Cartridge sampling on tethered Central Amazonia Wet 200-1000 2.86(2.25-3.64) GC-MS (Greenberg et al., 2004) balloon. Daytime median and interquartiles (12:00-15:00, LT). Cartridge sampling on tethered Southwestern Amazonia Wet 200-1000 6.89(2.78-7.73) GC-MS (Greenberg et al., 2004) balloon. Daytime median and interquartiles (12:00-15:00, LT). Cartridge sampling on tethered Central Amazonia Wet 200-1000 0.74(0.6-1) GC-MS (Greenberg et al., 2004) balloon. Guyana Shield Wet 3000 3.30 PTR-MS (Warneke et al., 2006) Guyana Shield Wet 3000 1.70 PTR-MS (Williams et al., 2001) Southwestern Amazonia W-t-D 25 ~4 GC-FID (Kuhn et al., 2002b) Southwestern Amazonia W-t-D 08-52 3.7(0.6) GC-FID (Kesselmeier et al., 2002b) Daytime mean (11:00-18:00, LT). Central Amazonia W-t-D 40 4.17(1.81) PTR-MS (Wei et al., 2018) Daytime mean. Southwestern Amazonia W-t-D 50 2.1(2.0) GC-FID (Aquino, 2006) Daytime mean (11:00-16:00, LT). Canister sampling. Southwestern Amazonia W-t-D 60 1.8(1.8) GC-FID (Aquino, 2006) Daytime mean (11:00-16:00, LT). Canister sampling. Central Amazonia W-t-D 100 2.38(1.16) GC-FID (Kuhn et al., 2010) Mean vertical profiles of isoprene and α-pinene from 8 background flights. Satellite X (Barkley et al., 2009) Satellite X (Bauwens et al., 2016) Southwestern Amazonia Dry Leaf level X GC-FID/MS (Kuhn et al., 2004b) Southwestern Amazonia Dry Leaf level X GC-FID/MS (Kuhn et al., 2004a) Leaf level X (Bracho-Nunez et al., 2012) Leaf level X (Bracho-Nunez et al., 2013) Leaf level X (Garcia et al., 2019) Leaf level X (Harley et al., 2004) Leaf level X (Jardine et al., 2013) Leaf level X (Jardine et al., 2016b) Leaf level X (Pegoraro et al., 2005) Leaf level X (Taylor et al., 2019) Leaf level X (Taylor et al., 2018) 1 4. Ecological interactions 2 BVOCs are assumed to play a strong role in ecological interactions in Amazonia (Figure 2). BVOC sources 3 create volatile blends that can serve to identify the species of a recipient (Piva et al., 2019), allowing us to 4 understand the nature of such communication (e.g. the identity and density of an attacking herbivore; Pinto- 5 Zevallos et al., 2018), and can also direct the evolution of plant chemical diversity (Salazar et al., 2018). 6 Signalling within plants can be based on cascading signals of jasmonates, salicylates, and ethylene, but also 7 other types of BVOCs such as GLV, methanol or isoprenoids (Filella et al., 2006; Matsui, 2016; Matsui et 8 al., 2012; Seco et al., 2011). The function of their emission can be involved in: inducing the production of 9 BVOCs that can downregulate floral volatiles to produce BVOCs associated with fruit ripening, inducing 10 BVOC production for defensive purposes, or for individual plant coexistence (Kigathi et al., 2019; Ninkovic 11 et al., 2019). However, to our knowledge, these processes have not been investigated in Amazonia. 12 Another type of signalling occurs between plants and other living organisms in ecosystems for reproduction, 13 defence, awareness of neighbouring plants, and modulating adaptation and evolution (Fine et al., 2004; 14 Laothawornkitkul et al., 2009; Salazar et al., 2018). Plants emit floral blends to attract specific pollinators to 15 aid reproduction. As rewards for pollination they offer pollen, and also resins, although the latter more rarely, 16 as for some Amazonian Clusia species (Bittrich & Amaral, 1997). Guarana trees emit higher amounts of (E)- 17 β-ocimene during night to attract nocturnal bees (Krug et al., 2018). The preferences of bees for collecting 18 pollen from other Amazonian plant species are nevertheless still unclear (Kaminski & Absy, 2006). 19 Furthermore, the role of phyllospheric floral bacteria has been pointed out to be of importance for BVOC 20 emissions (Peñuelas et al., 2014), although no information is available for the Amazonian rainforest. Other 21 types of communication associated with reproduction involve the production of fruit odours for seed 22 dispersal (Laothawornkitkul et al., 2009), for the seeds of a plant or of neighbouring plants (Gfeller et al., 23 2019), particularly in Amazonia with seed-ant mutualism (Youngsteadt et al., 2009). 24 BVOCs emitted for defensive purposes have characteristic blends, in both abundance and chemical diversity, 25 are species-specific (Courtois et al., 2009; Sharifi et al., 2018), serve an awareness role with neighbouring 26 plants (De Moraes et al., 2001; Kessler & Baldwin, 2001), and can affect plant chemical diversity (Salazar 27 et al., 2018). Such interactions can also occur between aboveground plants and roots, with important 28 implications for BVOC interactions within the soil ecosystem (Delory et al., 2016). Herbivory in tropical 29 rainforests has been estimated to consume 12-30% of the foliar area annually, with insects dominating foliar 30 consumption, at 680 kg ha-1 y-1 (Rinker & Lowman, 2004). The role of BVOC emission in the Amazonian 31 rainforest induced by herbivory is thus expected to be substantial but has not been characterized on regional 32 scales. 33 Plants, including their roots, can emit BVOCs to attract predators of herbivores (Aartsma et al., 2017; Sharifi 34 et al., 2018). SQTs are good attractors of plant bodyguards (Rasmann et al., 2005) whereas isoprene repels 35 them (Loivamäki et al., 2008). For example, the Amazonian ant Allomerus octoarticulatus can be attracted 36 to damage from herbivory by its mutualistic plant Hirtella myrmecophila (Romero & Izzo, 2004), showing 37 the complex interaction between plants and ants. In fact, the relationship between ants and plant size in 38 Amazonia can shape arthropod communities (Izzo & Vasconcelos, 2005). The extent of the damage from 39 herbivory feeds back on the defensive blends, as for cassava (Pinto-Zevallos et al., 2018), sometimes 40 jeopardising the plant’s protection (von Dahl et al., 2006). 41 Plants, microbes, and animals can emit BVOCs as direct toxins, deterrents, or repellents against herbivores 42 (De Moraes et al., 2001; Kessler & Baldwin, 2001; Laothawornkitkul et al., 2009; Prestwich, 1984; 43 Saikkonen et al., 1998; Sharifi et al., 2018). For example, Formicinae ants emit formic acid as a defensive 44 strategy (Brütsch et al., 2017) or GLV plant emissions can prime neighbouring plants against herbivores 45 (Engelberth et al., 2004). On the other hand, signalling can be negative, like isoprene that serves as a negative 46 cue, informing insects where not to forage (Gershenzon, 2008; Laothawornkitkul et al., 2008). 47 Protection against pathogens and sealing wounds are also drivers for BVOC emissions (Laothawornkitkul et 48 al., 2009; Ninkovic et al., 2019; Šimpraga et al., 2019). For example, the biosynthesis of natural rubber by 49 Hevea brasiliensis is stimulated by wounding, releasing methyl jasmonate and ethylene (Duan et al., 2010), 50 which is then oxidized during latex coagulation, sealing the wound (Piva et al., 2018). Nicotiana tabacum 51 plants emit methyl salicylate when pathogenic infections are present, inducing the expression of defensive 52 genes in neighbouring plants (Shulaev et al., 1997) and phytopathogenes can turn plants into sources of 53 carbonyl sulphide (Bloem et al., 2012) rather than sinks as generally seen (Whelan et al., 2018). The role of 54 the phyllosphere in defence against pathogens has been established for Amazonia (Azevedo et al., 2000; 55 Gazis & Chaverri, 2015; Sia et al., 2013; Vaz et al., 2018), where pathogenic disease such as anthracnose 56 can be especially important for modulating the expansion and production of guarana plantations (Bogas et 57 al., 2015). BVOC emissions to protect against pathogens may thus be important for identifying plant 58 diseases. 59 Lastly, abiotic factors driving BVOC emission can also alter ecological interactions. Amazonian plants have 60 been shown to protect themselves against excessive heat: by emitting isoprene (Jardine et al., 2016b) and 61 distinct monoterpene species (Jardine et al., 2017), by oxidizing isoprene within leaf tissues and therefore 62 releasing MVK+MACR (Jardine et al., 2011a), or by emitting GLV due to high temperatures and drought 63 as part of induced senescence processes (Jardine et al., 2015b). There are other abiotic factors altering 64 ecological interactions. In Amazonia, rain can alter sesquiterpene speciation from soils (Bourtsoukidis et al., 65 2018). Ozone can affect plant physiology (Loreto et al., 2004). BVOC oxidation can disrupt plant olfactory 66 cues (Vuorinen et al., 2004). Masking of BVOCs or ovipositional stimulants induced by herbivory may affect 67 the range of the signal (Farré-Armengol et al., 2016b; Pinto et al., 2010). SQTs emitted by soils and 68 vegetation have been shown to quench ozone within the canopy of an Amazonian rainforest (Bourtsoukidis 69 et al., 2018; Jardine et al., 2011c). Thus, the abundance of ambient ozone regulates the distance over which 70 the ecological BVOC signals are transported (Conchou et al., 2019). In fact, given the toxicity of ozone, trees 71 have been shown to emit reactive BVOCs to quench the ozone levels (Bourtsoukidis et al., 2012). 72 Additionally, ozone mixing ratios increase after biomass burning and urban pollution plumes in Amazonia 73 (Wei et al., 2019), so these processes could be important for plant fitness and ecological interactions in the 74 future Amazonia. At last, atmospheric CO2 increase is expected to alter ecological interactions either by 75 increasing BVOC emissions due to higher substrate availability, decrease BVOC emissions due to BVOC 76 synthases competition in biosynthesis, or due to a modification of the emitted compounds (Yuan et al., 2009). 77 While the role of BVOCs in ecological interactions is widely accepted, it is currently unknown how these 78 will regulate the cumulative BVOC release from Amazonia. Disturbing established communication links 79 among trees and between trees and insects may have unforeseen consequences for the ecosystem and species 80 protection from pathogens. Anthropogenic activity alters ecological interactions; therefore, the rapidly 81 changing atmospheric conditions may be a highly important piece of the puzzle in understanding the BVOC 82 dynamics within Amazonia. 83 5. Atmospheric impact 84 The impact of Amazonian BVOCs on atmospheric chemistry is highly dynamic, with strong diel and seasonal 85 characteristics. The vast emissions of reactive BVOCs, in combination with high emissions of other trace 86 gases, insolation, high temperature and humidity, and high OH concentrations make the Amazonian 87 atmosphere a tropical photoreactor (Andreae, 2001). BVOCs emitted to the Amazonian atmosphere are 88 rapidly oxidized by OH radicals during the day and more slowly by ozone, or by NO3 radicals at night 89 (Paulson & Orlando, 1996). Some of the BVOCs emitted are very reactive, such as isoprene towards OH 90 (Nölscher et al., 2016) and SQTs towards O3 (Jardine et al., 2011b). Isoprene, in particular, can deplete 91 tropical OH concentrations, thus indirectly affecting BVOC oxidation (Taraborrelli et al., 2012) and the 92 lifetimes of climate relevant gases such as methane. 93 OH reactivity is a measurable parameter quantifying the total loss frequency of OH radicals in the 94 atmosphere, including BVOCs and other reactive trace gases. It can be used to assess how comprehensively 95 the reactivity of BVOCs can be accounted for in Amazonia. The difference between the calculated OH 96 reactivity vs. the observed OH reactivity indicates that there is a large portion of unexplained reactivity (OH 97 missing reactivity) possibly due to unmeasured compounds not accounted for in the calculation of OH 98 reactivity from the sum of the individual compounds. Missing reactivity measured at a single Amazonian 99 rainforest location was strongly seasonal, being lower during the wet season (10 s-1; missing OH reactivity 100 of 5-15%) and higher during the dry season (62 s-1; missing OH reactivity of up to 79%), suggesting that 101 more unknown reactive compounds are present in the atmosphere during the dry season (Nölscher et al., 102 2016; Yang et al., 2016). Lower reactivity leads to a more oxidative atmosphere in the wet season, with high 103 deposition of oxidation products onto wet surfaces and possible enhanced microbial activity on foliar 104 surfaces that could influence the OH reactivity budget (Nölscher et al., 2016). 105 The gas-phase oxidation of BVOCs can form new particles by nucleation (Kirkby et al., 2016), or the 106 oxidised BVOCs can condense onto pre-existing particles, undergo heterogeneous reactions on particle 107 surfaces, be processed in clouds, or undergo further atmospheric degradation and deposition. Photochemistry 108 is an important Amazonian source of oxygenated VOCs (Yáñez-Serrano et al., 2015), particularly for short- 109 chain compounds (Seco et al., 2007). A recent study has demonstrated the strong role of isoprene oxidation, 110 which contributes ca. 20% of the organic aerosols (OAs) produced in Amazonia (Schulz et al., 2018). The 111 contribution of other BVOCs to aerosol formation in the tropical rainforest is more difficult to estimate, but 112 SQTs have been estimated to contribute 0.4-5% to submicron OAs (Yee et al., 2018). Shrivastava et al. 113 (2019) recently reported that isoprene and terpenes can contribute almost half of the Amazonian biogenic 114 secondary organic aerosols (SOAs). 115 Aerosols have profound implications on the radiation balance locally, regionally and globally, either directly 116 by scattering (Artaxo et al., 2013a; Kulmala et al., 2013) or absorbing solar radiation (Boucher et al., 2013) 117 or indirectly by impacting cloud and rain formation processes. Furthermore, they can boost global primary 118 production up to 25% for Amazonian ecosystems via diffuse radiation fertilization (Cirino et al., 2014; Koren 119 et al., 2012; Rap et al., 2018). Therefore, the presence of BVOCs influences the associated albedo by 120 modifying the number and size of cloud condensation nuclei (CCN) and cloud droplets, affecting how the 121 clouds reflect and absorb light (Boucher et al., 2013) and thus the radiation balance (Andreae & Crutzen, 122 1997; Artaxo et al., 2009; Sena et al., 2013) and hydrological cycle (Sheil, 2018). BVOCs and their role in 123 SOAs, dominant type the fine-mode aerosol mass (Martin et al., 2010), could ultimately affect the radiative 124 cooling of the Earth (Ehn et al., 2014), particularly in Amazonia where sulphur compounds are at low 125 concentrations (Kirkby et al., 2016) and the radiation balance is driven by organic aerosols (Artaxo et al., 126 2013a). A significant fraction of SOAs can act as CCN formed from BVOCs in the Amazonian wet season 127 (Pöschl et al., 2010). The low CCN particle concentrations lead to larger cloud droplets producing clouds at 128 lower altitudes that have higher rain efficiency (Rosenfeld, 1999), intensifying the role of BVOCs in aerosol 129 and cloud dynamics. The formation of new particles at the planetary boundary layer has not been observed 130 in Amazonia. BVOC species are instead elevated by deep convection and converted into condensable species 131 in the upper troposphere, forming new aerosol particles and increasing the loading of OAs, which can then 132 be transported down to the planetary boundary layer (Andreae et al., 2018; Schulz et al., 2018; Figure 2). 133 BVOCs can also affect radiative forcing by their degradation in the atmosphere (with CO2 as an end product) 134 and by their perturbation of the lifetime of other greenhouse gases such as methane, ozone (Guenther, 2002), 135 and further reactive gases such as CO (Collins et al., 2002). This is estimated to add 0.16 Pg C y-1 to the 136 amount of global atmospheric CO2 (Suntharalingam et al., 2005), which can increase CO2 levels by 0.07 ppm 137 y-1, and can have a significant impact on the results of inverse model investigations of CO 2 sources. Because 138 BVOCs deplete OH faster than methane (for which the primary sink is OH), methane will have a longer 139 lifetime in the atmosphere (Collins et al., 2002). Alternatively, tropospheric ozone is formed via BVOC 140 oxidation when sufficient NOx is available, adding to the radiative forcing of greenhouse gases. 141 NOx levels are low (ca. 0.4 ppb) in the atmosphere over the undisturbed Amazonian rainforest (Liu et al., 142 2016), particularly during the wet season when air masses arrive predominantly from the northeast over 143 mostly pristine rainforest (Pöhlker et al., 2019). NO from soils that reacts with O3 to form NO2 inside the 144 canopy is the main source of NOx. This NO2 is deposited on the leaves of the very dense rainforest canopy, 145 reducing the contribution of soil NO emissions to the levels of NOx above the canopy (Jacob & Wofsy, 146 1990). The direct loss by reaction of O3 with BVOCs outcompetes O3 formation under these pristine 147 conditions, thereby leading to a decrease in O3 (Jacob & Wofsy, 1990; Scott et al., 2018). O3 budgets are thus 148 mainly controlled by transport from above (downdrafts from convective storms (Dias-Júnior et al., 2017; 149 Gerken et al., 2016) and deposition to the canopy, with little net effect from photochemistry (Jacob & Wofsy, 150 1990). 151 NOx levels increase significantly during the dry season due to changes in wind direction from the easterly 152 and southeasterly fetch regions, transporting considerable amounts of pollution from burning biomass and 153 human activities (Bela et al., 2015; Pacifico et al., 2015). Consequently, O3 levels also increase during this 154 season (8-15 ppb in the wet season, 15-50 ppb in the dry season at midday) (Andreae et al., 2015; Artaxo et 155 al., 2013a, Figure 5). The concentrations of trace gases and particles are thus strongly seasonal. In fact, an 156 increase in NOx mixing ratios (to >1 ppb) can affect the oxidative pathways (i.e. HO2 or NO pathway; Liu 157 et al., 2016) of BVOC peroxy radicals, thus altering photochemistry, even in this region where NOx levels 158 are generally low. The central Amazonia plume has been reported to significantly increase O3 levels by 35% 159 at 70 km downwind of Manaus, whereas NOx levels increased by <20% relative to remote areas, indicating 160 the strong role of BVOC oxidation in forming O3, in areas where NOx levels have increased due to pollution 161 (maxima of up to 6 ppb; Wei et al., 2019). Enhanced urban pollution and plumes from burning biomass alter 162 BVOC emissions by inducing further emissions of highly reactive BVOCs (Bolsoni et al., 2018) and thus, 163 altering the dynamics of natural aerosols, with an increase in SOAs formed by BVOC oxidation (Shrivastava 164 et al., 2019). The burning of biomass can profoundly alter SOA composition, although increases in organic 165 submicron particulate matter during the dry season are also due to increased BVOC emissions combined 166 with reduced deposition (de Sá et al., 2019; Williams et al., 2016). 167 Canopy structure is another very important parameter in determining the impact of BVOCs in the 168 atmosphere. The dense and tall canopy of the Amazonian rainforest can stratify air masses, with an 169 intermittent coupling of the upper canopy and the atmosphere above. Air is poorly mixed within the canopy, 170 particularly at night when conditions are stable, with occasional exceptions of periods with bursts of 171 intermittent turbulence (Freire et al., 2017). The lower part of the canopy is characterized by a thermal 172 inversion, hindering mixing between the canopy and the forest floor (Nölscher et al., 2016; Santana et al., 173 2018).This feature can affect the residence times of emitted BVOCs and their turbulent transport out of the 174 forest canopy (Bakwin et al., 1990; Fitzjarrald et al., 1988; Gerken et al., 2017). BVOCs can thus remain 175 trapped within the canopy, becoming oxidised before reaching the atmosphere above. For example, 50-70% 176 of O3 reactivity within the canopy has been attributed to the ozonolysis of highly reactive SQTs 177 (Bourtsoukidis et al., 2018; Jardine et al., 2011c; Yee et al., 2018). 178 Isoprene oxidation by OH produces, among many other products, isoprene peroxide radicals (ISOPOO). 179 These radicals can react with HO2 to form isoprene hydroxyhydroperoxides (ISOPOOH) or with nitric oxide 180 (NO) to produce mostly methyl vinyl ketone and methacrolein. Both pathways (HO2 and NO) are important 181 in Amazonia, despite their strong seasonality (Liu et al., 2016). The formation of isoprene epoxydiols can 182 lead to the growth/formation of SOAs, mostly in the upper troposphere (Schulz et al., 2018). ISOPOOH 183 levels can nevertheless decrease in polluted conditions (Liu et al., 2016), with implications for OA levels, 184 because higher NOx levels can suppress the production of SOAs derived from isoprene epoxydiols (IEPOX) 185 (de Sá et al., 2017; Schulz et al., 2018). Isoprene was previously thought to yield very low quantities of 186 condensable material under low NOx levels (Pandis et al., 1991). More recently, gas-phase IEPOX, second- 187 generation products of isoprene oxidation under RO2+HO2 chemistry (Surratt et al., 2010), and reactive 188 uptake have been proposed as an additional pathway. The IEPOX may be responsible for the production of 189 observed SOA isoprene tracers, such as 2-methyltetrols found in the particle phase of Amazonian samples 190 (Carlton et al., 2009; Claeys et al., 2004; Kroll et al., 2005). 191 In summary, BVOCs can have very strong impacts on the atmospheric chemistry over Amazonia. BVOC 192 emissions determine oxidant regimes, as they modulate the major atmospheric oxidant, OH, and they can 193 lead to pollutant production (e.g. tropospheric ozone) when the pristine Amazonian conditions are altered. 194 6. Depositional processes 195 Deposition of BVOCs can be divided into wet and dry deposition onto surfaces, biological uptake, and 196 physicochemical processes at the leaf-atmosphere interface (Figure 2). In Amazonia, wet deposition can be 197 an important sink for trace gases. Polar compounds are particularly well washed off by rain. Moreover, 198 BVOC oxidation products can be formed in the water layer of leaves and other surfaces. This process is 199 especially important during the wet season and periods of rain and contributes to the observed general 200 decrease in the concentrations of trace gases. For example, organic acids such as formic and acetic acid can 201 contribute up to 90% of rain acidity in Amazonia (Andreae & Andreae, 1988; Jardine et al., 2011b). Dry 202 deposition depends on the movement of air, the vertical stability of the boundary layer, the chemical 203 properties of the species, and the nature of the depositional surface (Stickler et al., 2007), which may be 204 important in Amazonia, particularly at night with 78% of isoprene lost to surface deposition (Wei et al., 205 2018). Further information is needed to understand dry deposition in Amazonian ecosystems, which may 206 have been underestimated as has been demonstrated over a dense tropical rainforest in Costa Rica (Karl et 207 al., 2004). 208 Vegetation takes up compounds via stomatal or non-stomatal processes, where re-metabolisation can occur 209 (Matsui, 2016). The ambient mixing ratio of a compound regulates its uptake or emission depending on the 210 compensation point. Compensation points for Amazonian ecosystems have been reported to be <0.6 ppb for 211 acetaldehyde and formaldehyde (Rottenberger et al., 2004) and <0.3 for formic and acetic acid (Kuhn et al., 212 2002a) based on leaf level measurements. Data estimated on an ecosystem level were found to range around 213 1.4 and 2.1 ppb for formic and acetic acid, respectively (Jardine et al., 2011b). In view of the possible bio- 214 facilitation for plant VOC uptake (Matsui, 2016), more information is needed to understand the function of 215 bi-directional BVOC exchange by Amazonian ecosystems. 216 Bacteria are another sink or source for BVOCs. They can take up BVOCs as a source of carbon (Ginkel et 217 al., 1987) when levels are not toxic and can detoxify BVOCs above toxic levels (Marmulla & Harder, 2014). 218 For example, isoprene can be taken up by tropical soils (Cleveland & Yavitt, 1997), depending on the 219 atmospheric mixing ratio of isoprene and with decreasing rates of uptake under drought conditions (Pegoraro 220 et al., 2005). Bacterial communities in the phyllosphere may also be a BVOC sink (Farré-Armengol et al., 221 2016a). Phenol degradation has been observed in phyllospheric communities elsewhere (Sandhu et al., 2007). 222 All these phyllospheric sink processes for BVOCs could be especially important in Amazonia, given its 223 abundant phyllospheric communities. 224 Processes taking place at the leaf surface such as oxidation and adsorption/desorption are important for 225 ecological interactions, plant physiology, and accounting for gross and net BVOC emissions. Oxidation can 226 occur in the stomatal cavity or at the leaf surface as it serves to quench ROS damage in vegetation. Examples 227 have been reported for monoterpenes (Loreto et al., 2004), by semi-volatile organic compounds exuded by 228 glandular trichomes (Jud et al., 2016), and specifically in Amazonia for isoprene (Jardine et al., 2011a). This 229 oxidation can lead to the production of oxygenated BVOCs such as ketones and aldehydes (Jardine et al., 230 2011a; Jud et al., 2016; Pinto et al., 2010). This within-leaf oxidation process is of particular importance for 231 dry deposition estimates worldwide. When fast metabolic conversion of oxygenated BVOCs was 232 incorporated into a global chemistry transport model, Amazonia showed an increased annual dry deposition 233 flux of 75% (Karl et al., 2010). 234 Adsorption/desorption can occur on surfaces, such as plant cuticles (Müller & Riederer, 2005) and water 235 films and may be important in humid places such as Amazonia, even though their functioning is not yet fully 236 understood. Water layers on the upper surfaces of leaves may strongly influence the absorption of water by 237 leaves, stomatal conductance, pathogenic infection, nutrient leaching, and adsorption of pollutants (Aryal & 238 Neuner, 2010). Oxygenated BVOCs may thus be adsorbed onto water films and are then released upon the 239 evaporation of the films. This process may occur in wet environments such as Amazonia. 240 In summary, BVOC deposition is dependent on many factors, including the nature and concentration of the 241 compound and the existent meteorology. Despite high uncertainties, in an attempt to quantify the magnitude 242 of BVOC deposition, we used approximations from literature. Dry deposition has been estimated to occur 243 onto leaf surfaces as well as to soil surfaces with shares of 70% and 30%, respectively (Karl et al., 2010). 244 These estimates are expected to be higher for leaf surfaces in Amazonia due its larger leaf area. On the other 245 hand, in Amazonia, rain wet deposition occurs 90% to soil surfaces, with only 10% being intercepted by 246 vegetation (Czikowsky & Fitzjarrald, 2009). In addition, fog wet deposition is expected to occur at high 247 percentage values (Shimadera et al., 2011), although no estimates have been found so far for Amazonia. A 248 proper characterization of Amazonian BVOC deposition flux could result in higher estimates of gross BVOC 249 production, larger than previously thought. The aforementioned processes may account for active and partly 250 unexplored sinks, which have to be considered in regional and global modelling exercises. 251 7. Climate change, land-use change, and feedbacks 252 Amazonian ecosystems may be moving towards tipping points. For example, a temperature increase of 4°C 253 or deforestation exceeding 40% of the forested area (Nobre et al., 2016) due to human intervention as land- 254 use change possibly lead to savannisation (Marengo et al., 2011) and limit rainfall in synergistic interactions 255 with the impacts of climate change. 256 Climate change is expected to alter Amazonian ecosystems, since increased warming will be combined with 257 decreased precipitation (IPCC, 2013). Accompanying effects are drought associated with El Niño–Southern 258 Oscillation (ENSO) anomalies and changes in the surface temperature of the Atlantic Ocean (Leitold et al., 259 2018), increased frequency and intensity of heat waves (Perkins-Kirkpatrick & Gibson, 2017), and increased 260 duration and intensity of dry (Adams et al., 2017) and intensity of wet (Leite‐Filho et al., 2019; Mori and 261 Becker, 1991) seasons. Increasing temperatures and drought (Aragão et al., 2018; Feldpausch et al., 2016; 262 Leitold et al., 2018; Li et al., 2008; Marengo et al., 2016; Pfannerstill et al., 2018; Yang et al., 2018) and 263 intensified dry seasons (Sena et al., 2018), which are slowly drying Amazonia (Esquivel‐Muelbert et al., 264 2018), have already been observed. 265 These conditions of thermal and drought stress have multiple effects in Amazonian ecosystems. An 266 intensified dry season can particularly increase the frequency of fires (Silva Junior et al., 2019), reduce net 267 primary productivity, and accelerate canopy turnover (Leitold et al., 2018). Drier conditions can lead to an 268 overall decrease in BVOC production (although drought may induce transient GLV emission (Jardine et al., 269 2015b) (Figure 6). Other effects are higher irradiance due to lower cloud cover (Sena et al., 2018) and higher 270 temperatures, which ultimately lead to a net increase in BVOC production (Jardine et al., 2017; Pfannerstill 271 et al., 2018) of both BVOCs associated with stress (Jardine et al., 2015b) and other unknown highly reactive 272 compounds (Pfannerstill et al., 2018). If threshold limits for heat and radiation are exceeded, increased tree 273 mortality will naturally reduce BVOC emissions. Altered ecological interactions (e.g. insect outbreaks or 274 altered floral compositions) and increasing pollution can modify BVOC emissions, with unforeseen 275 consequences. However, an intensified wet season, could lead to stronger storms (Nelson et al., 1994) and 276 floods (Barichivich et al., 2018), increasing BVOC production associated with root anoxia. Tree mortality 277 associated with storms (Aleixo et al., 2019) have potential implications for atmospheric chemistry because 278 of increased BVOC emission associated with anoxia from floods. 279 These effects ultimately lead to increased tree mortality (Aleixo et al., 2019; Brando et al., 2019) aggravated 280 by deforestation, and, therefore, to decreased BVOC production due to biomass reduction, which further 281 feeds back on a changing climate by altering ecological interactions and aerosol dynamics. Additionally, the 282 loss of biodiversity (Nobre et al., 2016) caused by climate change (Chapin III et al., 2000) and deforestation 283 (Barlow et al., 2007) can alter ecological interactions and associated BVOC emissions. 284 Agricultural practices, including but not limited to biomass burning, and urbanisation are the two main 285 impacts of land-use change affecting Amazonia. Twenty percent of the original forest in the Brazilian 286 Amazonia has been cleared in the last three decades (Bullock et al., 2020; Davidson et al., 2012), particularly 287 from the so-called arc of deforestation in southern and southwestern Amazonia (Leite‐Filho et al., 2019; 288 Pöhlker et al., 2019), with a sharply increasing trend during the past several years. Deforestation has implied 289 substantial environmental changes (Davidson et al., 2012) and forest disturbance (Bullock et al., 2020), such 290 as water stress due to shallower roots (Huete et al., 2006) that causes an energy imbalance, loss of 291 biodiversity, changes to carbon storage (Huete et al., 2006), and an overall decrease in BVOC emissions due 292 to the loss of biomass (Scott et al., 2018). Biomass burning also profoundly affects the oxidation pathways 293 of BVOCs and increases emissions of air pollutants (Bulbovas et al., 2014) by clearing land mainly for soy 294 production (Bulbovas et al., 2007), oil palm production (Jardine et al., 2016a) and cattle ranching (Figure 5). 295 Soy crops are very sensitive to tropospheric ozone (Bulbovas et al., 2007), so higher ozone mixing ratios 296 will feed back to more deforestation to counteract decreased soy productivity (Pimentel, 2011). 297 Increasing urbanisation (Richards & VanWey, 2015) and rural development (Nobre et al., 2016) are also 298 drivers of land-use change in Amazonia. The urban population of the region has increased from about 1 299 million to 11 million in the last 50 years (1960–2010) (Medeiros et al., 2017). In central Amazonia, the city 300 of Manaus has 2 million inhabitants, and pollution sources include vehicular emissions, refinery operations, 301 and electricity generation. Even though anthropogenic emissions are lower than for other regions around the 302 world, Amazonian air chemistry is highly sensitive, amplified by the high solar irradiance and concentrations 303 of water vapour in an environment with plentiful BVOC emissions. NOx and ozone production are much 304 higher in urban plumes (Kuhn et al., 2010; Trebs et al., 2012; Wei et al., 2019) and have profound impacts 305 on atmospheric chemistry and physics by increasing biogenic SOA production by 60-200% (Shrivastava et 306 al., 2019) and altering gaseous (Liu et al., 2016) and particle (de Sá et al., 2017) chemical pathways. A 307 programmed change from fuel oil and diesel to natural gas is nevertheless projected to improve urban air 308 quality (Medeiros et al., 2017). 309 At a global scale BVOC emissions may increase in a warmer climate (Peñuelas & Staudt, 2010) due to higher 310 plant metabolism and diffusion, but in Amazonia, the effects of climate could increase the emission of stress- 311 related BVOCs and the effects of land-use change could lead to a decrease in BVOCs due to loss in biomass. 312 An increase of BVOCs due to warmer temperatures would lead to more SOA having a cooling impact 313 through the direct light scattering or indirectly by the increase in cloud cover. This would lead to a negative 314 radiative forcing. Additionally, more SOA would lead to more diffuse radiation, boosting GPP (Rap et al., 315 2018) and thus the uptake of atmospheric CO2. On the other hand, an increase in BVOCs would lead to an 316 increase of the CH4 lifetime. In the presence of sufficient NOx, an increase in tropospheric ozone could be a 317 consequence resulting in a warming effect. A decrease in BVOC emissions, however, would have opposite 318 effects on the radiative balance. Moreover, the net effects of altered ecological interactions (Niederbacher et 319 al., 2015), higher oxidation capacity, changes in species composition, and increased flooding on BVOC 320 responses remain unknown for Amazonian ecosystems. Unfortunately, there is almost no information about 321 the impact of BVOCs in the Amazonian hydrological cycle, with effects for the rest of the South American 322 continent (Boers et al., 2017; Rocha et al., 2018). Thus, a substantial change in Amazonian BVOC emission 323 may have strong climatic impacts at a regional and even at global levels, but there are large uncertainties in 324 current estimates. 325 8. Recent evolution of isoprene emissions in Amazonia 326 We investigated the evolution of isoprene fluxes in Amazonia using modelled isoprene emissions from the 327 CAMS-GLOB-BIO dataset (Granier et al., 2019), and satellite-based estimates (Bauwens et al., 2016) for 328 2005-2014. The CAMS-GLOB-BIO global dataset is based on the Model of Emissions of Gases and 329 Aerosols from Nature (MEGANv2.10; Guenther et al., 2012) and includes monthly isoprene emissions at 330 0.5ºx0.5º resolution. The MEGAN model was driven by re-analysed ERA-Interim meteorological fields (Dee 331 et al., 2011). Global annual land cover was provided by the ESA-CCI dataset (Climate Change Initiative of 332 the European Space Agency, ESA, 2017), processed in order to be consistent with plant functional types 333 (PFT) used in the MEGAN model (see S.I.3). On the other hand, for the satellite data we used formaldehyde 334 columns from the OMI satellite sensor and an inverse modelling framework (see S.I.4.). Both techniques 335 were used successfully for estimating isoprene fluxes in this region in the past (Barkley et al., 2009; Pacifico 336 et al., 2011). Seasonal and inter-annual variations of the modelled and satellite-based isoprene fluxes over 337 the Amazonian region (5°N-13°S, 46-77°W) are shown in Figure 7. Both approaches display similar 338 magnitudes and seasonal patterns, with slightly higher fluxes for modelled isoprene. The decrease of isoprene 339 fluxes during the wet season is observed in the complete time series of modelled isoprene (1992-2015) 340 (Figure S.I.2). Since biomass burning during the dry season affects the formaldehyde columns, only wet 341 season data are used for the trend calculation, but it has to be noted that both modelled and satellite isoprene 342 fluxes show a decrease for the reported period. The decrease of isoprene fluxes during the wet season can be 343 partly attributed to large and rapid changes in land cover (Acosta Navarro et al., 2014). Even though the rate 344 of deforestation decreased in the period of 2005-2014 (Artaxo et al., 2013b), studies point out that drought- 345 related fires may have increased during this period (Aragão et al., 2018). In fact, satellite observations suggest 346 a widespread forest degradation due to deforestation (Bullock et al., 2020). 347 The modelled isoprene flux indicates an increase of isoprene emissions during the dry season for 1992-2015, 348 with peaking fluxes in El Niño years (1997, 2015; Figure S.I.2). Given that sesquiterpenes are temperature- 349 dependent and emitted as a plant response to environmental stresses (Zhao et al., 2017), we have calculated 350 the sesquiterpene to isoprene ratio as a proxy of environmental stress (Figure 8). The ratio significantly 351 increases over time, suggesting that Amazonian forest is undergoing increased heat stress due to climate 352 warming. 353 These results underline the combined effect of climate change and land use change affecting BVOC fluxes. 354 During the dry season, strong environmental stresses to Amazonian vegetation occur at higher intensity and 355 frequency over time. This view is supported by the increasing ratio of sesquiterpene to isoprene fluxes. 356 During the wet season, the decrease in isoprene emissions may be partly explained by the rainforest loss due 357 to deforestation, although further analysis is needed to prove this hypothesis. 358 9. Research priorities 359 Kesselmeier et al. (2009) identified several research priorities that need to be addressed to better understand 360 BVOC dynamics in Amazonia. However, some of them remain unaddressed even one decade later. Intensive 361 efforts towards integrated investigations of emissions, chemistry, transport, and cloud processes, with 362 campaigns such as Brazilian-Air 2010, GOAMAZON (2014-2015), ACRIDICON (2014), and ATTO (2012- 363 present), which comprised observations from tower-based measurements (at TT34, K34, ATTO) and 364 aircraft-based studies (ACRIDICON and GOAMAZON) have been made or planned for the near future 365 (CAFÉ-Brazil 2020). These studies provided essential information, particularly in understanding the fate of 366 emitted isoprene in the atmosphere. Many studies have now addressed a wide range of biogenic VOCs, 367 including oxygenated BVOCs, aromatic compounds, sulfurous compounds, and oxidation products (Alves 368 et al., 2016; Bourtsoukidis et al., 2018; Jardine et al., 2011b, 2011a, 2014, 2015a, 2015b, 2017; Liu et al., 369 2016; Paralovo et al., 2015; Yáñez-Serrano et al., 2015, 2016, 2018b; Yee et al., 2018), although new studies 370 should aim to characterize unknown reactive compounds to better understand atmospheric reactivity, 371 particularly in the dry season (Nölscher et al., 2016; Pfannerstill et al., 2018). Progress has been made in 372 understanding of the impact of BVOCs on oxidant and aerosol distributions (Andreae et al., 2018; de Sá et 373 al., 2017, 2019; Liu et al., 2016; Nölscher et al., 2016; Pfannerstill et al., 2018; Schulz et al., 2018; 374 Shrivastava et al., 2019), the processes controlling the seasonal (Alves et al., 2016, 2018; Wei et al., 2018; 375 Yáñez-Serrano et al., 2015, 2018a) and spatial (Barkley et al., 2009, 2011; Bauwens et al., 2016; Salazar et 376 al., 2018; Taylor et al., 2018, 2019) variations of BVOCs, flooding (Bracho-Nunez et al., 2012), and 377 ecological interactions (Salazar et al., 2018). However, more process-based studies are essential, such as 378 those using laboratory and enclosure methods, to understand mechanistically what is happening at foliar 379 surfaces, including phyllospheric processes, BVOC sink processes, relationships between BVOCs and the 380 carbon and water cycles, ecological interactions, and the response of BVOCs to climate change and 381 deforestation in Amazonia. Model simulations could thus become more process-based, reducing the 382 uncertainty of predictions. For example, strong efforts are currently being made to understand BVOC 383 variation across plant populations beyond plant functional type, which is too broad to represent variability 384 in Amazonian ecosystems (Taylor et al., 2018). 385 Understanding how BVOC emissions would affect CCN and rain formation, including rain acidity (Jardine 386 et al., 2011b), is important as clouds can have an effect on the radiative forcing by reflecting radiation and 387 by increasing diffuse radiation thereby increasing GPP, as well as having impacts on the hydrological cycle 388 (Koren et al., 2012). But the effect of increased flooding, as a response to climate change, must also be 389 understood at an ecosystem level, particularly the role of anoxia BVOCs in CH4 and CO2 cycles in flooded 390 ecosystems. More effort is needed to obtain a more regional and long-term vision of BVOCs in Amazonia, 391 which can only be approached with synergistic investigations of different Amazonian ecosystems, to 392 understand the timing and duration of the response dependency of BVOC dynamics. This review 393 demonstrates the necessity of understanding the signals of BVOC feedback loops in response to climate and 394 land-use changes in Amazonia, for which understanding the potential impacts of the role of BVOCs in 395 ecological interactions is crucial, a subject rarely studied in Amazonia despite its enormous biological 396 productivity and biodiversity. Understanding how these interactions can be modulated by climate change is 397 also critical. Some ecological theories have been proposed to account for hyperdominant species in 398 Amazonia (ter Steege et al., 2013), which study the evolution and distribution of defensive compounds as a 399 function of species composition. For example, Protium genus produces large quantities of phenolics, which 400 may increase colonisation of its species (Salazar et al., 2018). This approach may be used to study the 401 ecological interactions of BVOCs in Amazonia. Climate change and pollution increase the oxidative capacity 402 of the Amazonian atmosphere (Nölscher et al., 2016; Pfannerstill et al., 2018; Yáñez-Serrano et al., 2015), 403 but the signals of the BVOC responses in the feedback loops remain unknown. Similarly, the signal of the 404 BVOC response to an intensified wet season remains unknown. The responses of BVOCs to global change 405 in Amazonia, either as a direct response to stress (e.g. increase drought, increase in UVB or nutrient 406 availability) or as an indirect response due to the extinction of BVOC sources (e.g. tree mortality or 407 agricultural expansion), are key research priorities for understanding how Amazonian ecosystems function 408 and how they will be modified in the future. This review suggests that warming and associated drying, 409 combined with the rate of deforestation, deforestation and associated drying is and will be the most 410 determinant in the fate of BVOCs in Amazonia (both for chemistry and physics), impacting the radiative 411 forcing of the atmosphere and the hydrological cycle. Deforestation is a major threat to Amazonia, with 412 >10000 km2 between the period between August 2018 and July 2019, the highest annual loss since 2008 413 (Barlow et al., 2020). Even the most optimistic climatic scenarios where forest protection policies are 414 implemented predict substantial deforestation in Amazonia (Pöhlker et al., 2019; Soares-Filho et al., 2006). 415 This trend indicates a major loss of forest biomass, potentially reaching threshold levels with difficult 416 recovery. This loss will affect not only the tropical and extra tropical carbon and water cycles, but also the 417 BVOC exchange between the surface and the atmosphere. Actions such as large-scale forest restoration 418 (Bastin et al., 2019) and the promotion of services (Šimpraga et al., 2019) provided by Amazonian 419 ecosystems may therefore help to mitigate these impacts of deforestation. Human action will thus delineate 420 also the future of BVOCs in Amazonia. 421 422 10. Acknowledgments 423 AMYS, JP, IF and JL acknowledge funding for their research provided by the Spanish Government grant 424 CGL2016-79835-P, the European Research Council Synergy grant ERC-SyG-2013-610028 IMBALANCE- 425 P and the Catalan Government grant SGR 2017-1005. Furthermore, AMYS acknowledges the Spanish 426 Ministry of Education and Science for her Juan de la Cierva-Incorporación grant. She also truly thanks 427 Paloma Yañez for her help in the design of Figure 6. Research on the satellite-derived emission estimates 428 was supported by the SOLFEO project funded by the European Space Agency (ESA), by the TROVA 429 PRODEX and the ALBERI STEREO III projects funded via the Belgian Science Policy Office (BELSPO). 430 AG acknowledges his funding source: US NSF AGS award #1829074. PA acknowledge support from 431 FAPESP – Fundação de Apoio à Pesquisa do Estado de São Paulo, grant number 2017/17047-0. JW and EB 432 acknowledge the support by the German Federal Ministry of Education and Research (BMBF contract 433 01LB1001A and 01LK1602B) and the Brazilian Ministério da Ciência, Tecnologia e Inovação 434 (MCTI/FINEP contract 01.11.01248.00) as well as the Amazon State University (UEA), FAPESP, CNPq, 435 FAPEAM, LBA/INPA, and SDS/CEUC/RDS-Uatumã. E.G.A. was funded by a BMBF (Bundesministerium 436 für Bildung und Forschung). 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This graph was derived from the information of Table 1 and S.I.1. 1483 1484 Figure 2: Schematic showing the BVOC dynamics in a pristine Amazonian atmosphere, including sources and 1485 interactions, BVOC oxidation in the atmosphere, and subsequent aerosol production influencing cloud droplet 1486 formation and cloud dynamics. CCN stands for cloud condensation nuclei and SOA stands for secondary organic 1487 aerosol. 1488 1489 1490 Figure 3: Whiskers box plot of all measured ambient concentrations (in ppb) of BVOCs in Amazonia to date. The 1491 ends of the box are the upper and lower quartiles showing the interquartile range, and the median is marked by a 1492 horizontal line inside the box. The whiskers are the two lines outside the box that extend to the highest and lowest 1493 observations. 1494 1495 Figure 4: Whiskers box plot of all measured ecosystem fluxes (in mg m -2 h-1) of BVOCs in Amazonia to date. The 1496 ends of the box are the upper and lower quartiles showing the interquartile range, and the median is marked 1497 by a horizontal line inside the box. The whiskers are the two lines outside the box that extend to the highest 1498 and lowest observations. 1499 1500 1501 Figure 5: Schematic showing BVOC dynamics in a polluted Amazonian atmosphere, including BVOC sources and 1502 interactions, interaction with anthropogenic volatile organic compounds (AVOCs), BVOC oxidation in the atmosphere, 1503 and subsequent aerosol and cloud dynamics. CCN stands for cloud condensation nuclei and SOA stands for secondary 1504 organic aerosol. 1505 1506 1507 Figure 6: Proposed feedback loops for the impacts of climate and land-use changes in Amazonian BVOCs and how 1508 these impacts will feed back into the system. The dashed arrows represent the situation where threshold limits are 1509 reached (i.e. heat can stimulate BVOC emissions until the point where heat is detrimental to plant fitness, thereby 1510 decreasing BVOC emissions). Red colour stands for promoting and blue colour for inhibiting. Grey arrows indicate 1511 inconclusive/unknown effects. LULCC stands for Land Use Land Cover Change. 1512 1513 Figure 7: Monthly top-down isoprene flux estimates based on global model simulations using MEGAN (top) and based 1514 on the OMI satellite formaldehyde columns (bottom) over 2005-2014 averaged over the Amazon region. Grey dots 1515 represent yearly averages whereas the blue dots represent the wet season average. 1516 1517 1518 Figure 8: Time series of the sesquiterpene to isoprene ratio fluxes from model simulations. Dots represent 1519 yearly averages from which the trend is calculated. Grey dots represent yearly averages. 1520 1521