Drought reduces the growth and heath of tropical rainforest understory plants

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  • Drought reduces the growth and heath of tropical rainforest understory plants

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1 Drought reduces the growth and health of tropical rainforest understory plants DAVID Y P TNG1,3,*, DEBORAH M G APGAUA1,3, CLAUDIA P PAZ2, RAYMOND W DEMPSEY3, LUCAS A CERNUSAK3, MICHAEL J LIDDELL3, SUSAN G W LAURANCE3 1Centre Australia 2Department Rio Claro, SP 13506-900, Brazil for Rainforest Studies, School for Field Studies, Yungaburra, Queensland 4872, of Ecology, Institute of Biosciences, São Paulo State University, Av 24A 1515, 10 3Centre 11 Engineering, James Cook University, 14-88 McGregor Rd, Smithfield Qld 4878, Australia 12 *Corresponding author 13 Address: 2710 Gillies Highway, Yungaburra, QLD 4872, Australia 14 email: dtng@fieldstudies.org for Tropical, Environmental and Sustainability Sciences, College of Science and 15 16 17 18 19 Electronic copy available at: https://ssrn.com/abstract=3974730 20 Abstract 21 Tree saplings and shrubs are frequently overlooked components of tropical rainforest 22 biodiversity, and it may be hypothesized that their small stature and shallow root systems 23 predisposes them to be vulnerable to drought However, these purported influences of 24 drought on growth, physiological performance and plant traits have yet to be studied in 25 simulated drought conditions in the field We simulated drought using a rainfall exclusion 26 experiment in 0.4 of lowland tropical rainforest in northeast Australia in 2015 After six 27 months, we compared the average change in aboveground biomass and plant health of 28 drought-affected tree saplings and understory shrubs with control individuals We also 29 assessed photosynthetic function, plant health and leaf traits in eight target species Both tree 30 saplings and shrubs had significantly lower aboveground biomass in the drought treatment 31 compared to the control Drought-affected individuals of target species exhibited a 32 significantly higher incidence of disease and insect attack, reduced photosynthesis, and a 33 range of leaf trait changes compared to control individuals We conclude that reduced growth 34 and photosynthetic capability, an increased susceptibility to insect attack, and leaf trait 35 changes constitute a near immediate drought response in tropical rainforest tree saplings and 36 shrubs Our results show that these often-overlooked components of tropical rainforest 37 biodiversity are likely to be the most rapidly and negatively impacted component of the plant 38 community in drought conditions 39 Keywords: drought, leaf economic spectrum, plant functional traits, tropical plant life forms, 40 tropical rainforest, throughfall exclusion 41 42 43 Introduction An understanding of how plants respond to drought is an important cornerstone in the 44 study of how plants deal with environmental stresses and has real-world implications in 45 agricultural and ecological systems While the effects of drought on plants are relatively well 46 characterized in laboratory conditions and in particular for crop plants in agricultural settings 47 (Valladares & Pearcy 1997; Apgaua et al 2019), investigation of plant performance under 48 field conditions is fragmentary (Martínez-Ferri et al 2000; Schuldt et al 2011; Meir et al 49 2015a; Binks et al 2016; Tng et al 2018) Also complicating such studies is the fact that 50 plant response to multiple stresses (e.g drought, excessive light, heat, etc.) are usually not 51 predictable from single-factor studies (Valladares & Pearcy 1997; Corlett 2011, Rowland et 52 al 2015a) Electronic copy available at: https://ssrn.com/abstract=3974730 53 Reductions in growth and widespread plant mortality are among the most worrisome 54 consequence of drought (Allen et al 2010: Liu et al 2015) However, susceptibility to 55 drought can vary across and within species, and moreover, drought-induced mortality is 56 thought to result from one or a combination of three processes: hydraulic failure, gradual 57 carbon starvation and/or invertebrate or pathogen attack (Adams et al 2017; Gely et al 58 2020) The relative contribution of these processes to mortality under drought conditions, 59 however, is poorly understood (McDowell et al 2008, 2013) For instance, droughts may 60 promote natural enemy attacks in water-stressed plants by reducing hosts’ natural chemical 61 defences and elevating nitrogen, sugars and secondary metabolites in foliage (Mattson et al 62 1987; Larsson 1989; Koricheva et al 1998) The level of damage to plants from these enemy 63 attacks appears to depend on the type of feeding substrate for insects and fungi, and the level 64 of water stress severity Jactel (2012) found taxa that attack both healthy and stressed plants 65 caused significantly more damage to foliage than wood in water-stressed trees irrespective of 66 drought severity 67 Plant responses to drought are often measured in terms of physiological performance 68 (Rennenberg et al 2006) Traits such as photosynthesis and stomatal conductance are 69 routinely measured when studying the effects of water deficit on plants, and most studies 70 show a decrease in these measures when plants are exposed to drought (Rennenberg et al 71 2006; Apgaua et al 2019) However, functional trait-based approaches to tracking plant 72 response to drought can also be helpful, providing another aspect to the story Leaf and wood 73 traits such leaf mass per unit area, leaf dry matter content, and wood density are important 74 components of the economic spectra in plants (Wright et al 2004; Chave et al 2009) While 75 plant functional traits are often used in ecosystem-scale studies as predictors of the 76 vulnerability or performance of plants when exposed to environmental stressors (Greenwood 77 et al 2017), it is also instructive to examine how these traits respond to environmental 78 changes, particularly when the question relates to responses of individual species (Bjorkman 79 et al 2018; Yue et al 2019; Tng et al 2018) For instance, it may be hypothesized that plants 80 exposed to drought will exhibit a decrease in leaf traits such as leaf fresh weight, leaf fresh 81 weight to dry weight ratios, leaf toughness and leaf mass per unit area, due to changes in leaf 82 cell turgor pressure and nutrient changes (Chen et al 2015; Delzon 2015) In turn, these leaf 83 functional trait changes may serve as the mechanism that leads to lower physiological 84 performance and vulnerability to natural enemies Quantifying the link between plant 85 functional traits and the environment is therefore important for understanding the potential 86 impacts of climate change on plant communities Electronic copy available at: https://ssrn.com/abstract=3974730 87 Most field studies examining the effects of droughts in tropical rainforest have 88 focused on mature trees (Meir et al 2015a; Schuldt et al 2011) However, tree saplings and 89 understory shrubs can play important roles in maintaining rainforest diversity and vegetation 90 dynamics (Royo & Carson 2006), and their responses to drought therefore deserve closer 91 examination Tree saplings, whilst regarded as being more susceptible than mature trees to 92 the negative impacts of drought (Niinemets 2010), have rarely been studied under 93 experimental field conditions Likewise, there are also few studies on how drought affects 94 smaller plant lifeforms such as understory shrubs (Condit et al 1995) 95 Rainfall exclusion or throughfall infrastructures represent a robust way to 96 experimentally induce a drought on a forest stand to investigate plant responses in situ (Meir 97 et al 2015b; Rowland et al 2015b) However, due to the sheer scale of such endeavours, 98 there have only been four tropical rainforest throughfall exclusion infrastructures established 99 to date: two in eastern Amazon, both each one in size (Nepstad et al 2007; da Costa et al 100 2010); one in Sulawesi (Schuldt et al 2011); and, one in tropical Australia (the Daintree 101 Drought Experiment: Laurance 2015; this paper) The establishment of the Daintree Drought 102 Experiment in tropical Australia provided us with an opportunity to examine the effects of a 103 short-term drought (six months) on tropical rainforest tree saplings and shrubs We 104 hypothesized that relative to non-droughted control plants, drought affected tree saplings and 105 shrubs would exhibit decreases in aboveground biomass, physiological performance 106 measures such as photosynthesis and stomatal conductance, and leaf traits (discussed earlier) 107 We also hypothesized that droughted plants would be subjected to higher levels of leaf 108 herbivory, insect attack and diseases 109 110 Methods 111 112 2.1 Study site 113 114 Our study site is located at the Daintree Rainforest Observatory (16°06′20′′S 115 145°26′40′′E, 50 m a.s.l.; Tng et al., 2016; Fig 1a) in a lowland rainforest adjacent to the 116 Daintree National Park in Cape Tribulation, north-eastern Australia The Daintree research 117 site commenced in 1998 with the installation of an industrial crane (Liebherr 91C) and the 118 establishment of a -ha census plot The site experiences a tropical climate, with mean 119 temperatures of 24.4oC and a relatively high annual average rainfall of 4900 mm annum-1 120 (Bureau of Meteorology, 2015) The rainfall is highly seasonal with 66% falling between Electronic copy available at: https://ssrn.com/abstract=3974730 121 January and April, the wet season The forest type at the site has a complex vertical profile, 122 with canopy heights ranging from 24 to 33m (Liddell et al., 2007), and a wide variety of plant 123 lifeforms (Tracey, 1982) Soils are developed over metamorphic and granitic colluvium and 124 are of relatively high fertility (Bass et al., 2011) 125 126 127 Fig Study location (a) in the Daintree Rainforest Observatory, north Queensland, Australia 128 and (b) schematic, (c) top-down view with the throughfall exclusion panels visible under the 129 tree canopy, and (d) cross-section of the throughfall exclusion experimental setup, showing 130 the arrangement of panels and the gutters used respectively to intercept and channel rainfall 131 away 132 133 134 2.2 The Daintree throughfall exclusion experiment 135 136 137 A throughfall infrastructure to exclude rainfall was implemented in May 2015 in two rectangular 0.2 -ha patches within the 1-ha crane plot, with the remaining 0.6 of the plot Electronic copy available at: https://ssrn.com/abstract=3974730 138 serving as a control experimental patch (Fig 1b; Laurance 2015) The rainfall exclusion 139 infrastructure consists of two 50 x 40 m clear-panel roofing structures which capture and 140 remove water from the 0.4 -ha (Fig 1c) The roofing panels are installed in between rows of 141 raised aluminium sheet gutters used to funnel rainwater away The panels taper at a height of 142 c 2.8m (Fig 1d), and therefore completely cover all trees sapling, shrub and herb lifeforms 143 under that height Where needed, slits were made in the roofing panel to accommodate all 144 stems above 2.8m height, such that their crowns are allowed to emerge through the roofing 145 panels 146 147 2.3 Understory microclimate and soil moisture 148 The presence of roofing structures might lead to modifications in microclimate that 149 150 need to be addressed To this we recorded microclimate data from the drought and control 151 patches using a portable custom-made manifold This manifold consisted of a pyranometer 152 (Apogee SP-215-L) which measures solar radiation flux density, a temperature and relative 153 humidity probe (Model CS215, CMOSens®), and a datalogger (CR200X, Campbell 154 Scientific®) mounted on a pole and affixed to a tripod at a height of 1.7m We set the 155 datalogger to log light intensity (W/m2), relative humidity (%) and temperate (˚C) 156 measurements every minute for 15 minutes from 36 random spots (18 random spots each in 157 the control- and drought-treatment sectors), resulting in 15 data points for each variable per 158 spot Because we were limited by having only one manifold, we collected microclimatic data 159 between 1000hrs to 1500hrs over two days in November 2015, alternating between control- 160 and drought-treatment sectors after making measurements at any given spot This enabled us 161 to randomize locations during the period of measurements We obtained volumetric soil water content from soil moisture censors installed at eight 162 163 soil pits stratified across both control and drought treatments (four pits each) Within each 164 soil pit, volumetric soil water content (cm3 cm-3) was measured continuously using time 165 domain reflectometry (TDR) probes (CS616, Campbell Scientific, UK) installed to log soil 166 moisture at four soil depths: 10, 50, 100, and 150 cm 167 168 2.4 Plant growth responses 169 170 171 To obtain an assessment of overall growth or mortality since the throughfall infrastructure was implemented, we used nine established 10 m x m rectangular subplots to Electronic copy available at: https://ssrn.com/abstract=3974730 172 conduct demographic assessments of saplings and shrubs, six of which are now within the 173 drought treatment areas of the 1-ha plot and three in the control The subplots were 174 established in May 2015 where every tree sapling (individuals >1cm diameter at a stem 175 height of 1.3 m height) and shrub (individuals >0.4 cm diameter at a stem height of cm) 176 was tagged, identified, and measured with a calliper at those respective stem heights (Tng et 177 al 2016) To ensure the accuracy of subsequent measurements, we used white liquid paper 178 ink to mark the point of measurement on the shrub of sapling individual The subplots were 179 marked out and established whilst the foundations of the throughfall-exclusion infrastructure 180 were being installed, so an effort was made to ensure that subplots established in the areas to 181 be droughted were situated in-between and parallel to the rows of gutters (inter-gutter width 182 of five meters) During the installation of the trough-drainage system of the throughfall- 183 exclusion infrastructure, a number of tree saplings and shrub stems had to be trimmed but this 184 damage was limited mostly to narrow strips of area just beneath the aluminium gutters and 185 did not impact plants within our subplots However, there was a difference in density 186 distribution of saplings and shrubs (excluding palms and tree stems with crowns above the 187 panels) within the 1-ha plot due to natural variability Therefore, the three control and six 188 drought treatment subplots respectively had 29 and 22 sapling species (37 spp total) and 189 and shrub species (9 spp total) These species were comprised of 90 and 81 sapling and 65 190 and 60 shrub individuals within the control and drought treatment subplots respectively 191 (Supplementary Material Table S2) 192 We distinguished between tree and shrub life-form for the species within our subplots 193 based on their well-documented life history (Hyland et al 2010) and demographic data from 194 the 1-ha long term monitoring plot (Tng et al 2016) The tree sapling and shrubs we censused 195 within the subplots were restricted to individuals within the 0.5-2.5 m height class, which 196 ensured that each individual had their crown wholly under the rainfall-exclusion panels This 197 also circumvented any bias due to possible irrigation, albeit minimal, that might occur from 198 stem flow in individuals with crowns emerging out above through slits in the panels The 199 same 2.5 m height limit was applied for the target species on which we made trait 200 measurements (see later) 201 In November 2015, six months after our initial census, we re-censused and re- 202 measured the stem diameter and heights of the tree saplings and shrubs within the nine 203 subplots, and also visually estimated plant health (see later) on all individuals Initially, we 204 had intended to re-census the sapling and shrub growth after an additional six months (in 205 May 2016) but during a field assessment 11 months into the experiment in April 2016, the Electronic copy available at: https://ssrn.com/abstract=3974730 206 rainfall exclusion panels had begun to develop a layer of algal growth which conspicuously 207 reduced the light conditions under the panels and would therefore confound further growth 208 analyses 209 210 2.5 Plant health and physiological performance 211 212 For a more targeted within species examination of plant responses to drought, we used 213 a number of non-destructive methods to parameterize drought responses, following 214 Niinemets (2010) These included: (i) quantitative visual estimates of plant health (herbivory, 215 disease symptoms and presence of insect pests); (ii) physiological performance measures, 216 and; (iii) leaf traits 217 We selected eight target species of common tree saplings and shrubs for which we 218 could locate replicates with ease within the overall 0.4 and 0.6 drought and control patches 219 respectively Our target species consist of the saplings of five species of mature-phase trees, 220 Argyrodendron peralatum (Malvaceae), Cleistanthus myrianthus (Phyllanthaceae), 221 Endiandra microneura (Lauraceae), Myristica globosa subsp muelleri (Myristicaceae), 222 Rockinghamia angustifolia (Euphorbiaceae); and three shrubs, Amaracarpus nematopodus, 223 Atractocarpus hirtus (Rubiaceae) and Haplostichanthus ramiflorus (Annonaceae) (Table 1) 224 For brevity, we henceforth use only genus names when referring to these species 225 Although these targeted species occurred within the nine subplots, we sampled 226 individuals outside the subplots for leaf traits to minimize impacts to the long-term 227 monitoring setup that may result from collecting leaf material for functional trait analysis 228 Pertinently also, some of the target shrub species occurred only sparingly within the subplots 229 and so for this targeted species analysis it was expedient for us to sample outside of the 230 subplots to obtain sufficient replication (n = 5-12 individuals per species within each 231 treatment) of these species to provide reliable trait estimates 232 Plant health was visually estimated on replicate plants of each target species both 233 within and outside the subplots in terms of the overall percentage of the leaves on each 234 individual plant with signs of herbivory, disease, and insect attack by at least two observers 235 (Table 1) Herbivory was defined as obvious holes or areas of the leaves that had been 236 predated on; disease as observable patches of yellow, white or dark discolouration, or 237 necrosis on leaves, and; insect attack as the presence of sap sucking insects such as 238 mealybugs or scale insects on leaves and/or shoots Both top and bottom leaf surfaces were 239 inspected for symptoms of disease and presence of sap-sucking insects Electronic copy available at: https://ssrn.com/abstract=3974730 240 Table Species of targeted tree saplings and shrubs sampled in the control and drought 241 treatment for disease symptoms, herbivory, and insect attack after six months of drought 242 treatment in a throughfall exclusion experiment at the Daintree Rainforest Observatory, Cape 243 Tribulation, Australia Species Family Control (n) Drought (n) Malvaceae Cleistanthus myrianthus Kurz Phyllanthaceae 19 26 Endiandra microneura C.T.White Lauraceae 15 Myristica globosa subsp muelleri Myristicaceae Euphorbiaceae 10 13 Rubiaceae Rubiaceae 20 12 Annonaceae 47 45 Tree saplings Argyrodendron peralatum (F.M.Bailey) Edlin ex J.H.Boas (Warb.) W.J.de Wilde Rockinghamia angustifolia (Benth.) Airy Shaw Shrubs Amaracarpus nematopodus (F.Muell.) P.I.Forst Atractocarpus hirtus (F.Muell.) Puttock Haplostichanthus ramiflorus Jessup 244 For plant physiological performance indicators, we used leaf photosynthetic rate (A: 245 246 µmol CO2 m-2 s-1) and stomatal conductance (gs: mol H2O m-2 s-1), which we measured 247 between 1000hrs to 1500hrs using a LI-6400 Portable Photosynthesis System (LI-COR, 248 Lincoln, Nebraska, USA) For this purpose, we took point measurements on one fully 249 expanded leaf per individual for five replicate individuals of each of the targeted species 250 within the control and drought treatments Photosynthesis and stomatal conductance 251 measurements were conducted in November 2015 252 253 2.6 Leaf functional traits 254 255 256 To obtain a measure of leaf functional trait responses, we sampled 5-12 leaf replicates per species from each treatment following a standard protocol (Pérez-Harguindeguy et al Electronic copy available at: https://ssrn.com/abstract=3974730 257 2013) Leaf fresh mass (g), dry mass (g), fresh mass: dry mass ratio (g g-1), leaf mass per unit 258 area (LMA: g cm-2) were measured from 20 leaf discs per individual collected with a 0.6mm 259 hole punch Leaf toughness was measured using a penetrometer to determine the amount of 260 force (in grams: g) needed to penetrate the leaf lamina when applied to three random spots on 261 the leaf, avoiding visible secondary and tertiary veins We deviated from the standard 262 protocol of measuring leaf fresh mass: dry mass ratio by measuring the leaf fresh weights 263 immediately after collection and without rehydration as we wanted to obtain a more realistic 264 measure of leaf hydration status of samples under field conditions 265 266 2.7 Data analysis 267 268 To summarize the microclimate data, we averaged the 15 data points at each spot for 269 solar irradiance flux density, relative humidity and temperature, and calculated the means of 270 these variables for the control- and drought-treatment plots Because the experiment was 271 designed for analysis as a pairwise comparison between the control- and drought-treatments, 272 we compared the means of all the microclimate variables using one-tailed t-tests (α = 0.05) 273 We examined soil volumetric water content differences between drought and control areas 274 using a linear mixed effects model using the package lmerTest with the daily estimates of soil 275 volumetric water content considered repeated measures and accounted for as a random factor 276 We then run an analysis of variance on the lmer model to obtain F and P values for the 277 contrasts and their interactions The least square means for the model are presented in 278 Supplementary Material Table S1 For visualization purposes, data were averaged for each 279 depth at each pit over a six-month period from 1/5/2015 280 For the analysis of the growth data, we pooled the individuals from subplots within 281 each treatment, and analyzed the sapling and shrub dataset separately To parameterize the 282 growth response of the saplings and shrubs, we first calculated the aboveground biomass 283 (AGB, kg) of each individual sapling or shrub for each census using stem diameters (D: cm), 284 plant height (H: cm) and wood density (WD: kg) following an equation by Chave et al 285 (2014), where: AGB = 0.0673 x (D2 x H x WD)0.976 The choice of Chaves equation was 286 based on the widespread use of this equation in rainforest tree biomass estimates and the lack 287 of any parametric equation for tropical rainforest saplings/shrubs Where individual plants 288 were represented by multiple stems, the AGB for each stem was calculated and then summed 289 to obtain the AGB for the individual Wood density values for most of the species in our 290 subplots were obtained from Apgaua et al (2015, 2017) and supplemented with our 10 Electronic copy available at: https://ssrn.com/abstract=3974730 399 400 Fig Indicators of plant health in targeted rainforest tree saplings and shrubs in a 401 throughfall exclusion experiment at the Daintree Rainforest Observatory, Cape Tribulation, 402 Australia Drought-treatment individuals of the subcanopy trees (a) Myristica globosa 403 (Myristicaceae) exhibited an outbreak of Pseudococcidae sap-feeding mealy bugs (white 404 spots on leaf undersurface) and evidence of herbivory, and foliar disease symptoms of 405 chlorosis and necrotic patches manifested in (b) Rockinghamia angustifolia (Euphorbiaceae) 17 Electronic copy available at: https://ssrn.com/abstract=3974730 406 Barplots show control- versus drought-treatment comparisons within species for visual 407 percentage estimates of leaves showing (c) the incidence of sap-sucking insects, (d) presence 408 of disease symptoms, and; (e) herbivory Asterisks and letters in parentheses above bars 409 represent significant differences in the means of the measures between individuals in the 410 control and drought treatments (n = 5–42 individuals treatment-1) (p
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