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Drought reduces the growth and health of tropical rainforest understory plants
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DAVID Y P TNG1,3,*, DEBORAH M G APGAUA1,3, CLAUDIA P PAZ2, RAYMOND W
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DEMPSEY3, LUCAS A CERNUSAK3, MICHAEL J LIDDELL3, SUSAN G W
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LAURANCE3
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1Centre
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Australia
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2Department
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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,
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3Centre
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Engineering, James Cook University, 14-88 McGregor Rd, Smithfield Qld 4878, Australia
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*Corresponding author
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Address: 2710 Gillies Highway, Yungaburra, QLD 4872, Australia
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email:
for Tropical, Environmental and Sustainability Sciences, College of Science and
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Abstract
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Tree saplings and shrubs are frequently overlooked components of tropical rainforest
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biodiversity, and it may be hypothesized that their small stature and shallow root systems
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predisposes them to be vulnerable to drought. However, these purported influences of
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drought on growth, physiological performance and plant traits have yet to be studied in
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simulated drought conditions in the field. We simulated drought using a rainfall exclusion
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experiment in 0.4 ha of lowland tropical rainforest in northeast Australia in 2015. After six
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months, we compared the average change in aboveground biomass and plant health of
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drought-affected tree saplings and understory shrubs with control individuals. We also
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assessed photosynthetic function, plant health and leaf traits in eight target species. Both tree
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saplings and shrubs had significantly lower aboveground biomass in the drought treatment
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compared to the control. Drought-affected individuals of target species exhibited a
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significantly higher incidence of disease and insect attack, reduced photosynthesis, and a
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range of leaf trait changes compared to control individuals. We conclude that reduced growth
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and photosynthetic capability, an increased susceptibility to insect attack, and leaf trait
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changes constitute a near immediate drought response in tropical rainforest tree saplings and
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shrubs. Our results show that these often-overlooked components of tropical rainforest
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biodiversity are likely to be the most rapidly and negatively impacted component of the plant
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community in drought conditions.
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Keywords: drought, leaf economic spectrum, plant functional traits, tropical plant life forms,
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tropical rainforest, throughfall exclusion
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1. Introduction
An understanding of how plants respond to drought is an important cornerstone in the
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study of how plants deal with environmental stresses and has real-world implications in
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agricultural and ecological systems. While the effects of drought on plants are relatively well
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characterized in laboratory conditions and in particular for crop plants in agricultural settings
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(Valladares & Pearcy 1997; Apgaua et al. 2019), investigation of plant performance under
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field conditions is fragmentary (Martínez-Ferri et al. 2000; Schuldt et al. 2011; Meir et al.
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2015a; Binks et al. 2016; Tng et al. 2018). Also complicating such studies is the fact that
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plant response to multiple stresses (e.g. drought, excessive light, heat, etc.) are usually not
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predictable from single-factor studies (Valladares & Pearcy 1997; Corlett 2011, Rowland et
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al. 2015a).
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Reductions in growth and widespread plant mortality are among the most worrisome
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consequence of drought (Allen et al. 2010: Liu et al. 2015). However, susceptibility to
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drought can vary across and within species, and moreover, drought-induced mortality is
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thought to result from one or a combination of three processes: hydraulic failure, gradual
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carbon starvation and/or invertebrate or pathogen attack (Adams et al. 2017; Gely et al.
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2020). The relative contribution of these processes to mortality under drought conditions,
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however, is poorly understood (McDowell et al. 2008, 2013). For instance, droughts may
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promote natural enemy attacks in water-stressed plants by reducing hosts’ natural chemical
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defences and elevating nitrogen, sugars and secondary metabolites in foliage (Mattson et al.
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1987; Larsson 1989; Koricheva et al. 1998). The level of damage to plants from these enemy
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attacks appears to depend on the type of feeding substrate for insects and fungi, and the level
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of water stress severity. Jactel (2012) found taxa that attack both healthy and stressed plants
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caused significantly more damage to foliage than wood in water-stressed trees irrespective of
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drought severity.
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Plant responses to drought are often measured in terms of physiological performance
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(Rennenberg et al. 2006). Traits such as photosynthesis and stomatal conductance are
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routinely measured when studying the effects of water deficit on plants, and most studies
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show a decrease in these measures when plants are exposed to drought (Rennenberg et al.
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2006; Apgaua et al. 2019). However, functional trait-based approaches to tracking plant
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response to drought can also be helpful, providing another aspect to the story. Leaf and wood
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traits such leaf mass per unit area, leaf dry matter content, and wood density are important
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components of the economic spectra in plants (Wright et al. 2004; Chave et al. 2009). While
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plant functional traits are often used in ecosystem-scale studies as predictors of the
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vulnerability or performance of plants when exposed to environmental stressors (Greenwood
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et al. 2017), it is also instructive to examine how these traits respond to environmental
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changes, particularly when the question relates to responses of individual species (Bjorkman
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et al. 2018; Yue et al. 2019; Tng et al. 2018). For instance, it may be hypothesized that plants
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exposed to drought will exhibit a decrease in leaf traits such as leaf fresh weight, leaf fresh
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weight to dry weight ratios, leaf toughness and leaf mass per unit area, due to changes in leaf
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cell turgor pressure and nutrient changes (Chen et al. 2015; Delzon 2015). In turn, these leaf
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functional trait changes may serve as the mechanism that leads to lower physiological
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performance and vulnerability to natural enemies. Quantifying the link between plant
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functional traits and the environment is therefore important for understanding the potential
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impacts of climate change on plant communities.
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Most field studies examining the effects of droughts in tropical rainforest have
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focused on mature trees (Meir et al. 2015a; Schuldt et al. 2011). However, tree saplings and
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understory shrubs can play important roles in maintaining rainforest diversity and vegetation
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dynamics (Royo & Carson 2006), and their responses to drought therefore deserve closer
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examination. Tree saplings, whilst regarded as being more susceptible than mature trees to
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the negative impacts of drought (Niinemets 2010), have rarely been studied under
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experimental field conditions. Likewise, there are also few studies on how drought affects
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smaller plant lifeforms such as understory shrubs (Condit et al. 1995).
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Rainfall exclusion or throughfall infrastructures represent a robust way to
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experimentally induce a drought on a forest stand to investigate plant responses in situ (Meir
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et al. 2015b; Rowland et al. 2015b). However, due to the sheer scale of such endeavours,
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there have only been four tropical rainforest throughfall exclusion infrastructures established
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to date: two in eastern Amazon, both each one ha in size (Nepstad et al. 2007; da Costa et al.
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2010); one in Sulawesi (Schuldt et al. 2011); and, one in tropical Australia (the Daintree
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Drought Experiment: Laurance 2015; this paper). The establishment of the Daintree Drought
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Experiment in tropical Australia provided us with an opportunity to examine the effects of a
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short-term drought (six months) on tropical rainforest tree saplings and shrubs. We
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hypothesized that relative to non-droughted control plants, drought affected tree saplings and
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shrubs would exhibit decreases in aboveground biomass, physiological performance
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measures such as photosynthesis and stomatal conductance, and leaf traits (discussed earlier).
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We also hypothesized that droughted plants would be subjected to higher levels of leaf
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herbivory, insect attack and diseases.
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2. Methods
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2.1. Study site
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Our study site is located at the Daintree Rainforest Observatory (16°06′20′′S
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145°26′40′′E, 50 m a.s.l.; Tng et al., 2016; Fig. 1a) in a lowland rainforest adjacent to the
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Daintree National Park in Cape Tribulation, north-eastern Australia. The Daintree research
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site commenced in 1998 with the installation of an industrial crane (Liebherr 91C) and the
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establishment of a 1 -ha census plot. The site experiences a tropical climate, with mean
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temperatures of 24.4oC and a relatively high annual average rainfall of 4900 mm annum-1
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(Bureau of Meteorology, 2015). The rainfall is highly seasonal with 66% falling between
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January and April, the wet season. The forest type at the site has a complex vertical profile,
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with canopy heights ranging from 24 to 33m (Liddell et al., 2007), and a wide variety of plant
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lifeforms (Tracey, 1982). Soils are developed over metamorphic and granitic colluvium and
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are of relatively high fertility (Bass et al., 2011).
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Fig. 1. Study location (a) in the Daintree Rainforest Observatory, north Queensland, Australia
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and (b) schematic, (c) top-down view with the throughfall exclusion panels visible under the
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tree canopy, and (d) cross-section of the throughfall exclusion experimental setup, showing
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the arrangement of panels and the gutters used respectively to intercept and channel rainfall
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away.
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2.2. The Daintree throughfall exclusion experiment
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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 ha of the plot
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serving as a control experimental patch (Fig. 1b; Laurance 2015). The rainfall exclusion
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infrastructure consists of two 50 x 40 m clear-panel roofing structures which capture and
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remove water from the 0.4 -ha (Fig. 1c). The roofing panels are installed in between rows of
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raised aluminium sheet gutters used to funnel rainwater away. The panels taper at a height of
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c. 2.8m (Fig. 1d), and therefore completely cover all trees sapling, shrub and herb lifeforms
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under that height. Where needed, slits were made in the roofing panel to accommodate all
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stems above 2.8m height, such that their crowns are allowed to emerge through the roofing
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panels.
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2.3.
Understory microclimate and soil moisture
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The presence of roofing structures might lead to modifications in microclimate that
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need to be addressed. To do this we recorded microclimate data from the drought and control
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patches using a portable custom-made manifold. This manifold consisted of a pyranometer
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(Apogee SP-215-L) which measures solar radiation flux density, a temperature and relative
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humidity probe (Model CS215, CMOSens®), and a datalogger (CR200X, Campbell
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Scientific®) mounted on a pole and affixed to a tripod at a height of 1.7m. We set the
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datalogger to log light intensity (W/m2), relative humidity (%) and temperate (˚C)
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measurements every minute for 15 minutes from 36 random spots (18 random spots each in
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the control- and drought-treatment sectors), resulting in 15 data points for each variable per
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spot. Because we were limited by having only one manifold, we collected microclimatic data
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between 1000hrs to 1500hrs over two days in November 2015, alternating between control-
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and drought-treatment sectors after making measurements at any given spot. This enabled us
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to randomize locations during the period of measurements.
We obtained volumetric soil water content from soil moisture censors installed at eight
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soil pits stratified across both control and drought treatments (four pits each). Within each
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soil pit, volumetric soil water content (cm3 cm-3) was measured continuously using time
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domain reflectometry (TDR) probes (CS616, Campbell Scientific, UK) installed to log soil
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moisture at four soil depths: 10, 50, 100, and 150 cm.
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2.4.
Plant growth responses
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To obtain an assessment of overall growth or mortality since the throughfall
infrastructure was implemented, we used nine established 10 m x 2 m rectangular subplots to
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conduct demographic assessments of saplings and shrubs, six of which are now within the
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drought treatment areas of the 1-ha plot and three in the control. The subplots were
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established in May 2015 where every tree sapling (individuals >1cm diameter at a stem
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height of 1.3 m height) and shrub (individuals >0.4 cm diameter at a stem height of 5 cm)
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was tagged, identified, and measured with a calliper at those respective stem heights (Tng et
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al. 2016). To ensure the accuracy of subsequent measurements, we used white liquid paper
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ink to mark the point of measurement on the shrub of sapling individual. The subplots were
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marked out and established whilst the foundations of the throughfall-exclusion infrastructure
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were being installed, so an effort was made to ensure that subplots established in the areas to
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be droughted were situated in-between and parallel to the rows of gutters (inter-gutter width
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of five meters). During the installation of the trough-drainage system of the throughfall-
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exclusion infrastructure, a number of tree saplings and shrub stems had to be trimmed but this
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damage was limited mostly to narrow strips of area just beneath the aluminium gutters and
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did not impact plants within our subplots. However, there was a difference in density
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distribution of saplings and shrubs (excluding palms and tree stems with crowns above the
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panels) within the 1-ha plot due to natural variability. Therefore, the three control and six
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drought treatment subplots respectively had 29 and 22 sapling species (37 spp. total) and 7
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and 6 shrub species (9 spp. total). These species were comprised of 90 and 81 sapling and 65
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and 60 shrub individuals within the control and drought treatment subplots respectively
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(Supplementary Material Table S2).
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We distinguished between tree and shrub life-form for the species within our subplots
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based on their well-documented life history (Hyland et al. 2010) and demographic data from
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the 1-ha long term monitoring plot (Tng et al. 2016). The tree sapling and shrubs we censused
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within the subplots were restricted to individuals within the 0.5-2.5 m height class, which
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ensured that each individual had their crown wholly under the rainfall-exclusion panels. This
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also circumvented any bias due to possible irrigation, albeit minimal, that might occur from
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stem flow in individuals with crowns emerging out above through slits in the panels. The
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same 2.5 m height limit was applied for the target species on which we made trait
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measurements (see later).
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In November 2015, six months after our initial census, we re-censused and re-
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measured the stem diameter and heights of the tree saplings and shrubs within the nine
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subplots, and also visually estimated plant health (see later) on all individuals. Initially, we
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had intended to re-census the sapling and shrub growth after an additional six months (in
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May 2016) but during a field assessment 11 months into the experiment in April 2016, the
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rainfall exclusion panels had begun to develop a layer of algal growth which conspicuously
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reduced the light conditions under the panels and would therefore confound further growth
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analyses.
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2.5.
Plant health and physiological performance
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For a more targeted within species examination of plant responses to drought, we used
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a number of non-destructive methods to parameterize drought responses, following
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Niinemets (2010). These included: (i) quantitative visual estimates of plant health (herbivory,
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disease symptoms and presence of insect pests); (ii) physiological performance measures,
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and; (iii) leaf traits.
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We selected eight target species of common tree saplings and shrubs for which we
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could locate replicates with ease within the overall 0.4 and 0.6 ha drought and control patches
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respectively. Our target species consist of the saplings of five species of mature-phase trees,
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Argyrodendron peralatum (Malvaceae), Cleistanthus myrianthus (Phyllanthaceae),
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Endiandra microneura (Lauraceae), Myristica globosa subsp. muelleri (Myristicaceae),
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Rockinghamia angustifolia (Euphorbiaceae); and three shrubs, Amaracarpus nematopodus,
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Atractocarpus hirtus (Rubiaceae) and Haplostichanthus ramiflorus (Annonaceae) (Table 1).
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For brevity, we henceforth use only genus names when referring to these species.
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Although these targeted species occurred within the nine subplots, we sampled
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individuals outside the subplots for leaf traits to minimize impacts to the long-term
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monitoring setup that may result from collecting leaf material for functional trait analysis.
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Pertinently also, some of the target shrub species occurred only sparingly within the subplots
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and so for this targeted species analysis it was expedient for us to sample outside of the
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subplots to obtain sufficient replication (n = 5-12 individuals per species within each
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treatment) of these species to provide reliable trait estimates.
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Plant health was visually estimated on replicate plants of each target species both
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within and outside the subplots in terms of the overall percentage of the leaves on each
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individual plant with signs of herbivory, disease, and insect attack by at least two observers
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(Table 1). Herbivory was defined as obvious holes or areas of the leaves that had been
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predated on; disease as observable patches of yellow, white or dark discolouration, or
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necrosis on leaves, and; insect attack as the presence of sap sucking insects such as
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mealybugs or scale insects on leaves and/or shoots. Both top and bottom leaf surfaces were
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inspected for symptoms of disease and presence of sap-sucking insects.
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Table 1 Species of targeted tree saplings and shrubs sampled in the control and drought
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treatment for disease symptoms, herbivory, and insect attack after six months of drought
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treatment in a throughfall exclusion experiment at the Daintree Rainforest Observatory, Cape
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Tribulation, Australia.
Species
Family
Control (n)
Drought (n)
Malvaceae
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6
Cleistanthus myrianthus Kurz
Phyllanthaceae
19
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Endiandra microneura C.T.White
Lauraceae
6
15
Myristica globosa subsp. muelleri
Myristicaceae
8
9
Euphorbiaceae
10
13
Rubiaceae
6
8
Rubiaceae
20
12
Annonaceae
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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
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For plant physiological performance indicators, we used leaf photosynthetic rate (A:
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µmol CO2 m-2 s-1) and stomatal conductance (gs: mol H2O m-2 s-1), which we measured
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between 1000hrs to 1500hrs using a LI-6400 Portable Photosynthesis System (LI-COR,
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Lincoln, Nebraska, USA). For this purpose, we took point measurements on one fully
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expanded leaf per individual for five replicate individuals of each of the targeted species
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within the control and drought treatments. Photosynthesis and stomatal conductance
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measurements were conducted in November 2015.
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2.6.
Leaf functional traits
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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.
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2013). Leaf fresh mass (g), dry mass (g), fresh mass: dry mass ratio (g g-1), leaf mass per unit
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area (LMA: g cm-2) were measured from 20 leaf discs per individual collected with a 0.6mm
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hole punch. Leaf toughness was measured using a penetrometer to determine the amount of
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force (in grams: g) needed to penetrate the leaf lamina when applied to three random spots on
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the leaf, avoiding visible secondary and tertiary veins. We deviated from the standard
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protocol of measuring leaf fresh mass: dry mass ratio by measuring the leaf fresh weights
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immediately after collection and without rehydration as we wanted to obtain a more realistic
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measure of leaf hydration status of samples under field conditions.
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2.7.
Data analysis
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To summarize the microclimate data, we averaged the 15 data points at each spot for
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solar irradiance flux density, relative humidity and temperature, and calculated the means of
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these variables for the control- and drought-treatment plots. Because the experiment was
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designed for analysis as a pairwise comparison between the control- and drought-treatments,
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we compared the means of all the microclimate variables using one-tailed t-tests (α = 0.05).
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We examined soil volumetric water content differences between drought and control areas
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using a linear mixed effects model using the package lmerTest with the daily estimates of soil
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volumetric water content considered repeated measures and accounted for as a random factor.
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We then run an analysis of variance on the lmer model to obtain F and P values for the
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contrasts and their interactions. The least square means for the model are presented in
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Supplementary Material Table S1. For visualization purposes, data were averaged for each
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depth at each pit over a six-month period from 1/5/2015.
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For the analysis of the growth data, we pooled the individuals from subplots within
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each treatment, and analyzed the sapling and shrub dataset separately. To parameterize the
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growth response of the saplings and shrubs, we first calculated the aboveground biomass
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(AGB, kg) of each individual sapling or shrub for each census using stem diameters (D: cm),
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plant height (H: cm) and wood density (WD: kg) following an equation by Chave et al.
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(2014), where: AGB = 0.0673 x (D2 x H x WD)0.976. The choice of Chaves equation was
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based on the widespread use of this equation in rainforest tree biomass estimates and the lack
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of any parametric equation for tropical rainforest saplings/shrubs. Where individual plants
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were represented by multiple stems, the AGB for each stem was calculated and then summed
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to obtain the AGB for the individual. Wood density values for most of the species in our
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subplots were obtained from Apgaua et al. (2015, 2017) and supplemented with our
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unpublished data. We then calculated the percentage change in AGB (%ΔAGB) for each
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individual by the following equation: %ΔAGB = [(AGBfinal-AGBinitial)/AGBinitial] x 100,
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where AGBinitial and AGBfinal refers to the aboveground biomass of each individual in the first
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(May 2015) and final census (Nov 2015) respectively.
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To test our hypothesis of whether sapling and shrub individuals within the drought
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subplots in general showed a greater magnitude of responses in terms of insect incidence,
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disease symptoms and herbivory relative to the control, we fitted generalized linear models
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individually for saplings and shrubs. For insect incidence and disease symptoms, we fitted
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zero-inflated generalized linear mixed models, using the glmmTMB package (Brooks et al.
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2017), which fit zero-inflated Poisson models with a single zero-inflation parameter applying
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to all observations. For percentage change in aboveground biomass, insect incidence, disease
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symptoms and herbivory in tree saplings and shrubs in the subplots, we used linear mixed
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effects models with the restricted maximum likelihood estimation, using the nlme package. In
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all models, we used treatment (drought or control) as an explanatory variable and individual
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aboveground biomass in the initial census as a random effect (to account for any size
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dependent effects).
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To test whether there were species specific responses within our eight target species
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in plant health, plant performance, leaf functional traits, and physiological measures, we
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fitted generalized linear models using treatment as the explanatory variable. In the case of
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insect incidence and disease symptoms, we fitted zero-inflation regression models using the
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zeroinfl function in the pscl package, which fits zero-inflated data via the maximum
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likelihood estimation (Zeileis et al. 2008). All analyses were performed in R 3.0 following a
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standard protocol of data exploration (Zuur et al. 2010).
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3. Results
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3.1. Understory microclimate and soil moisture
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Microclimate measures in the control and drought treatments ranged respectively
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between 3.85–99.8 W m-2 and 3.89–166.3 W m-2 for light intensity (Fig. 2a); 78.6–96.6% and
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78.9–98.1% for relative humidity (Fig. 2b), and; 26.1–31.0⁰C and 26.6–31.6⁰C for
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temperature (Fig. 2c). T-tests comparing the means of these measures between control- and
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drought-treatments showed no significant differences (all P > 0.05).
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Fig. 2. Boxplots of microclimate variables of (a) solar irradiance flux density, (b) relative
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humidity, and (c) temperature for random point samples (n = 18 points each) in the control-
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(green symbols) and drought-treatments (brown symbols) in a throughfall exclusion
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experiment at the Daintree Rainforest Observatory, Cape Tribulation, Australia. The (d) soil
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volumetric soil water content (VWC) was measured from 1.5 m long soil probes installed
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within the control and the drought areas (n = 4 soil probes in each) of the study plot during
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the 6-month experimental period. Each box encompasses the 25th to 75th percentiles; the
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median is indicated by the boldest horizontal line and the other horizontal lines outside the
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box indicate the 10th and 90th percentiles. Pairwise differences are indicated (ns = not
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significant; P < 0.05*, P < 0.01**, P < 0.001***).
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Over the six-month study period, the thoroughfall exclusion infrastructure succeeded
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in significantly drying the soils of the top 100 cm of the soil profile compared to the control
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treatment (ANOVA F1,4601 = 1228.57, P < 0.0001). This interaction between drought
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treatment and depth was significant at surface and subsurface depths (ANOVA F3,4599 =
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213.4, P < 0.0001). Soils in the drought experiment were on average 28.6% drier at the
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surface (10cm), 20.2% drier at the subsurface (50 cm), and 9.3% and 3.5% drier at 100 and
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150 cm depths, respectively than in the controls (Fig. 2d). However, at soil depths of 1.5m,
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differences in volumetric water content were not significant (Fig. 2d; See also Supplementary
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Material Table S1 for the least square means for the ANOVA run on the soil pit data).
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3.2. Plant growth responses of tree saplings and shrubs
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During the November 2015 census, we found two dead sapling individuals and one
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dead shrub in the drought treatment subplots, and no dead individuals in the control subplots
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(Table 2; Supplementary Tables S2). Individuals of tree saplings and shrub individuals
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exhibited aboveground biomass increments, reductions or lack of change in both control and
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drought treatment subplots, but in general more individual stems in the control subplots
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exhibited increases (Table 2). There was a net increase in tree sapling aboveground biomass
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in both the control (14.51%) and drought treatment (+5.77%) subplots (Table 2). For shrubs,
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the control subplots exhibited a net increase in aboveground biomass (+17.01%) but the
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drought treatment subplots showed a reduction (-2.56%) (Table 2). Consequently, the net
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percentage change in aboveground biomass for both tree saplings and shrubs transects was
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significantly higher in the control than in the drought treatment subplots (Fig. 3a).
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Table 2. Percentages of tree saplings and shrubs in the subplots showing increases, decreases
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or no changes in aboveground biomass (AGB) between 2015 to 2016 in the control and
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drought treatment in a throughfall exclusion experiment at the Daintree Rainforest
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Observatory, Cape Tribulation, Australia.
Treatment
Control
Drought
ΔAGB
Tree Saplings
Shrubs
No.
%
Net change
No.
%
Net change
Increase
73
82.02
+ 9.33kg (+ 14.51%)
53
81.54
+ 1.03kg (+ 17.09%)
No change
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15.73
12
18.46
Decrease
2
2.25
0
0
Dead
0
0
0
0
Increase
54
65.06
34
56.67
No change
12
14.46
10
16.67
Decrease
17
20.48
15
25
Dead
2
2.41
1
1.67
+ 0.47kg (+ 5.77%)
- 0.24kg (- 2.56%)
365
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366
367
Fig. 3. Boxplots showing changes in lowland tropical rainforest tree saplings (top panel) and
368
shrubs (bottom panel) in terms of (a) percentage change in aboveground biomass (AGB) and
369
the differences in plant health measures: (b) insect incidence (c) disease symptoms, and: (d)
370
herbivory. The number of individuals (n) of tree saplings and shrubs in the three control and
371
six drought subplots was 90 and 65, and 81 and 60 respectively. Each box encompasses the
372
25th to 75th percentiles; the median is indicated by the horizontal line within the box and the
373
other horizontal lines outside the box indicate the 10th and 90th percentiles. Open circles
374
indicate outliers and dots represent individual data points. Significant differences between
375
treatments are indicated (See Table 3 for statistics).
376
377
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378
Table 3. Parameter estimates (±SE) and random effect variances for linear mixed models
379
fitted for change in aboveground biomass (ΔAGB), percentage of insect incidence, disease
380
symptoms and herbivory on sapling and shrubs as responses, and treatment (control vs.
381
drought) as fixed effects and initial plant aboveground biomass as random effects. For the
382
percentage of insect incidence and disease symptoms, we fitted a zero-inflated generalized
383
linear mixed models, and for herbivory we fitted linear mixed effects models (See Methods)
Parameter
Statistics
Intercept
Drought
Random residual
Estimate
2.087
-0.088
4.44E-16
SE
0.025
0.036
t-value
82.682
-2.414
p-value
>0.001
0.017*
Estimate
-3.613
6.395
SE
0.546
0.595
z-value
-6.617
10.742
p-value
3.67E-11
<2.00E-16***
Estimate
-6.473
6.268
SE
1.046
1.061
z-value
-6.191
5.908
p-value
5.97E-10
3.46E-09***
Estimate
0.659
-0.159
SE
0.051
0.051
t-value
12.990
-3.132
p-value
0
0.002**
Estimate
2.057
-0.079
SE
0.025
0.037
t-value
81.30
-2.154
p-value
>0.001
0.033*
Estimate
-2.898
5.065
SE
0.661
0.700
z-value
-4.382
7.239
p-value
1.17E-05
4.53E-13***
All Saplings
ΔAGB
Disease symptoms
Insect incidence
Herbivory
994.3
596.9
170.187
All Shrubs
ΔAGB
Disease symptoms
0.036
752.5
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Insect incidence
Herbivory
Estimate
-4.536
6.675
SE
0.751
0.788
z-value
-6.041
8.469
p-value
1.53E-09
<2.00E-16***
Estimate
0.691
0.021
SE
0.045
0.065
t-value
15.519
0.328
p-value
0
0.743
596.3
115.040
384
385
386
387
3.3. Herbivory, disease, pests and plant performance
Within the subplots, the tree saplings in the drought treatment exhibited significantly
388
higher incidence of insects (Fig. 3b), leaf disease symptoms (Fig. 3c) and also levels of
389
herbivory (Fig. 3d), than those in the control. Shrubs, likewise, exhibited significantly higher
390
levels of insect incidence (Fig. 3b) and disease symptoms (Fig. 3c) in the drought treatment,
391
but no significant difference in herbivory (Fig. 3d).
392
With the exception of Argyrodendron, all target species examined in the drought
393
treatment exhibited a range of stress symptoms such as a significantly increased incidence of
394
sap-sucking insects (Fig. 4a, c), the appearance of leaf disease (Fig. 4b, d), and herbivory
395
(Fig. 4a, e). In contrast, conspecific individuals in the control-treatment largely appeared to
396
lack these symptoms.
397
398
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399
400
Fig. 4. 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).
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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 <0.05*; p<0.01**;
411
p<0.001***; ns = not significant).
412
413
The most common insect pests we encountered on leaves and shoots of plants in the
414
drought-treatment were mealy bugs (Homoptera: Pseudococcidae) (Fig. 4a), but we also
415
observed scale insects and we noted dark insect faecal pellets (not quantified) on the leaf
416
surfaces of all species investigated in the drought-treatment.
417
Foliar disease symptoms manifested as patches of chlorotic or dead laminar tissue
418
(Fig. 4d) or sometime dark spots. Likewise, for disease symptoms, different species
419
manifested different symptoms. In most tree and shrub species, the leaves appeared chlorotic,
420
but in some shrubs, disease manifested in the form of dark discoloration.
421
Leaf herbivory was observed in plants in both control- and drought-treatments (Fig.
422
4e). Although the mean extent of herbivory was higher in most individuals in the drought-
423
treatment, this difference was only significant for one tree sapling species (Myristica).
424
Plant performance responses varied across treatments, and was not consistent across
425
traits (Fig. 5). Leaf photosynthesis was significantly higher in all species in the control
426
compared to the drought-treatment, except in two shrubs (Amaracarpus and Atractocarpus),
427
where there was no significant difference between treatments (Fig. 5a). This difference in
428
photosynthesis appears to be commensurate with lower mean values for stomatal
429
conductance, although the difference in stomatal conductance was only significant in the case
430
of one subcanopy tree species, Cleistanthus. Conversely, the two shrub species (Amaracarpus
431
and Atractocarpus) which exhibited no differences in photosynthesis, had higher stomatal
432
conductance means in the drought-treatment, although this was not significantly different
433
from the control-treatment (Fig. 5b).
434
435
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436
437
Fig. 5. Means (±S.E) of (a) photosynthetic rate and (b) stomatal conductance in rainforest
438
tree saplings and shrubs in a throughfall exclusion experiment at the Daintree Rainforest
439
Observatory, Cape Tribulation, Australia. Asterisks and letters in parentheses above bars
440
represent significant differences in the means of the measures between individuals in the
441
control and drought treatments (n = 5 individuals treatment-1) (p <0.05*; p<0.01**;
442
p<0.001***; ns = not significant).
443
444
445
3.4. Leaf functional traits
446
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447
Leaf functional traits in general differed significantly between control- and drought-
448
treatments, although some species were not significantly different in the two treatments for
449
some traits (Fig. 6).
450
Relative to the drought treatment, most of the tree and shrub species in the control
451
exhibited significantly higher leaf fresh weight (Fig. 6a) or leaf fresh weight:dry weight ratio
452
(Fig. 6b), indicating more fully hydrated leaves. For leaf mass per unit area, significant
453
differences between treatments were only found in two subcanopy tree species (Myristica and
454
Rockinghamia) and in the shrub species Haplostichanthus (Fig. 6c). Leaf toughness differed
455
significantly in most species except in one mature-phase species (Argyrodendron) and one
456
subcanopy species (Myristica) (Fig. 6d).
457
458
459
Fig. 6. Means (±S.E) of (a) leaf fresh mass (g), (b) leaf fresh mass:dry mass ratios (g g-1), (c)
460
leaf mass per unit area (LMA: g cm3), and (d) leaf toughness (grams: g) of rainforest tree
461
saplings and shrubs in a throughfall exclusion experiment at the Daintree Rainforest
462
Observatory, Cape Tribulation, Australia. Leaf fresh mass, leaf fresh mass: dry mass rations
463
and LMA were based on 20 leaf discs of the same size taken from each individual. Asterisks
464
and letters in parenthesis above bars represent significant differences in the means of the
465
measures between individuals in the control and drought treatments (n = 5-12 individuals
466
treatment-1) (p <0.05*; p<0.01**; p<0.001***; ns = not significant).
467
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468
4. Discussion
469
470
Droughts are likely to differentially affect plants across the vertical strata of tropical
471
rainforests. Previous throughfall exclusion experiments have focused primarily on trees
472
(Schuldt et al. 2011; Meir et al. 2015b; Binks et al. 2016; Tng et al. 2018). Since the topmost
473
soil profiles are the first to desiccate, smaller statured plants with shallow root systems such
474
as tree saplings and shrubs are likely to be impacted prior to fully grown trees. Expanding on
475
these previous studies, our investigation of drought effects on tree saplings and shrubs in the
476
understory forest stratum in situ is a world first.
477
We investigated changes in plant growth, health, physiological performance and leaf
478
traits in tree saplings and shrubs in response to a six-month simulated drought regime under a
479
throughfall exclusion experiment within a lowland tropical rainforest in north Queensland,
480
Australia. While we acknowledge that these experiments can only duplicate water scarcity
481
and not the other environmental factors associated with drought such as elevated
482
temperatures, lower humidity and increased vapor pressure deficit we found across our study
483
subplots a net decline in aboveground biomass increment of individuals in the drought
484
treatment area compared to our control area. Additionally, within our eight target species, we
485
found clear evidence of decline in plant health and physiological function due to drought, and
486
also a suite of species-specific changes in leaf trait measures from baseline values.
487
488
4.1. Declines in plant aboveground biomass increment of saplings and shrubs
489
490
The higher proportion of individuals in the drought subplots with a decline in
491
aboveground biomass compared to the control subplots was notable. While the absolute
492
aboveground biomass estimate provided by an allometric equation developed for mature
493
rainforest trees (Chave et al. 2014), is at best an approximation, the trends are robust. The
494
decline in biomass was mainly due to instances of the shoot dieback or death of side shoots
495
(ramets) in the case of a number of shrubs, and reduced stem diameters. Indeed, stem
496
diameter shrinkage during drought is a well-documented phenomenon in trees and can lead to
497
decreased forest biomass (Klepper et al. 1971; Linder et al. 1987).
498
Our observation that drought-affected plants were more likely to be attacked by sap-
499
sucking insects, or exhibit symptoms of disease is in line with the literature (Larsson 1989;
500
Jactel et al. 2012). In contrast, the low incidence of sap-sucking insects in the control is
501
consistent with previous studies reporting natural levels of food plant utilization by insects
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502
(Hodkinson & Casson 1987). The main sap sucking insects we observed were mealy bugs,
503
which have previously been shown to attack drought-affected plants (Neuenschwander et al.
504
1989; Hennessey et al. 1990; Calatayud et al. 1994). One proposed mechanism that
505
influences the levels of insect infestation on plants during drought is the change in levels of
506
secondary plant defence compounds. During a drought, Calatayud et al. (1994) found that
507
Pseudococcidae infestation in tapioca crops was associated with lower levels of secondary
508
defence compounds that were unfavourable to the insects.
509
There is also substantial evidence in the literature documenting the higher incidence
510
of foliar diseases on water-stressed plants than on normal plants (Schoeneweiss 1986;
511
Hossain et al. 2019; Milici et al. 2020), which in the case of our drought-treatment plants,
512
appear to be related to infestations of sap sucking insects and foliar disease.
513
The changes in the level of herbivory were significantly different between drought
514
and control treatment when the entire dataset of tree saplings or shrubs were considered.
515
However, from closer examination at a target species level it was clear that not all species
516
became more susceptible to herbivory, at least in the six-month duration of drought
517
treatment. Also, unlike insect attack and foliar disease symptoms where the changes were
518
marked, signs of herbivory were always present at a conspicuous background level. We were
519
unable to assess the animals that have been predating leaves, but Gutbrodt et al. (2011) had
520
shown in previous studies that drought may lead to plants being more susceptible to different
521
suites of herbivores relative to plants that are well-watered.
522
523
524
4.2. Physiological and leaf trait changes
As expected, there was a reduced level of photosynthesis in most of the target species
525
under the drought treatment (Corlett 2016; Slot & Poorter 2007; Zlatev & Lidon 2012).
526
Interestingly, we did not observe a commensurate difference in stomatal conductance in these
527
species, which may indicate that the plants are not under higher vapour pressure deficit and
528
are continuing to transpire under the drought, or that plants still had access to sufficient soil
529
water reserves. Also, the reductions in photosynthesis may be associated with insect attack
530
and foliar disease (Buntin et al. 1996; Neves et al. 2006) as patches of leaf lamina affected by
531
disease or necrosis may not be photosynthesizing at their optimal level. Unfortunately,
532
logistical constraints precluded sampling the same individuals for plant health and plant
533
physiology at the same time, we were therefore unable to correlate the plant performance of
534
specific individuals with plant health. Nevertheless, it does not appear to be a coincidence
535
that most of the target species in which we found reductions in photosynthesis also had
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536
significantly higher levels of foliage insect incidence, disease symptoms or herbivory. In
537
accordance, the two target species that did not exhibit significant changes in photosynthesis
538
(Amaracarpus and Atractocarpus) did not show significant signs of disease symptoms or
539
herbivory in the drought treatment.
540
Leaf functional traits responded to drought differently across species. The differences
541
between treatments in leaf fresh weights and leaf fresh weight:dry weight are in line with
542
expectations and clearly show that the drought-treatment has lowered the internal leaf water
543
status in most of the target species except Haplostichanthus. Similar findings have been
544
reported for plants under water deficit conditions (De Roover et al. 2000; Tng et al. 2018).
545
One mechanistic cause of reductions in leaf fresh mass or fresh mass:dry mass ratios may be
546
leaf shrinkage as a result of dehydration (Scoffoni et al. 2014).
547
In terms of leaf mass per unit area and leaf toughness, all study species exhibited a
548
decrease in at least one of these traits, with the exception of the saplings of one canopy tree
549
species (Argyrodendron). These traits are well-established in the literature for their role in
550
conferring mechanical support and resistance to herbivory (Coley 1983; Choong et al. 1992).
551
We can therefore suggest a causal relationship between insect infestation and disease
552
symptoms and lowered leaf mass per unit area or leaf toughness during in the drought-
553
treatment. In support of our suggestion, the single species in our study (Argyrodendron) that
554
exhibited no differences in leaf mass per unit area or leaf toughness also appeared to be
555
relatively free of insect infestations and disease symptoms.
556
557
5. Conclusion
558
559
Drought is expected to have severe negative impacts on tropical forest biodiversity. We
560
present for the first time, the results of a throughfall exclusion experiment investigating the
561
effect of simulated drought on tropical rainforest tree saplings and shrubs under field
562
conditions. Examining multiple responses in a set of tree sapling and shrub species, we found
563
overall that drought led to reduced growth, poorer plant physiological performance, lowered
564
resistance to natural enemies and a change in leaf traits. There were also observable
565
interspecific differences in drought responses. Changes in plant health and leaf traits may act
566
synergistically to eventually lead to further declines in plant physiological function and
567
subsequently mortality. Our results have important implications for understanding the
568
interactions between plant drought responses and suggest that understory rainforest lifeforms
569
will be negatively affected by drought before effects may be observable on trees. The impacts
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570
on the next generation of sub-canopy and canopy trees in the understory will also have knock
571
on effects in terms of the resilience of rainforest communities.
572
573
Conflicts of interest
574
575
The authors declare no conflicts of interest
576
577
Acknowledgements
578
579
This research was supported by an Australian Research Council Future Fellowship
580
(FT130101319) to SGWL. The Australian Research Council had no involvement in the study
581
design; in the collection, analysis and interpretation of data; in the writing of the report; and
582
in the decision to submit the article for publication. DYPT, DMGA and SGWL designed and
583
wrote the paper. DYPT, DMGA, CPP, RWD, LAC did the fieldwork. MJL, LAC, DYPT
584
analysed the data. DYPT, DMGA and SGWL wrote the manuscript and all other authors
585
provided editorial advice.
586
587
Appendix A. Supplementary Material
588
589
Supplementary data associated with this article can be found, in
590
the online version, at />
591
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593
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