Philippa Kaur

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Study site
Experiments were conducted in the Reserva Particular do Patrimônio Natural (RPPN) Santuário do Caraça, a private conservation unit in the southern portion of the Espinhaço Mountain range, Minas Gerais state, Brazil. The climate is seasonal, with a rainy period from October to March, and a dry period from April to September. Mean air temperatures vary between 13 and 29oC26.
The focal species of this study was Ololygon machadoi. The tadpoles of this treefrog have been previously shown to react to both visual and chemical predator cues (from Belostoma testaceopallidum; Melo et al.18) by positioning themselves preferentially on yellow backgrounds where they are disruptive17,18. Ololygon machadoi breeds year-round in many streams in the RPPN, and we used one of these streams (20o05′37″S, 43o29′59″W; 1293 m above sea level), where its tadpoles are abundant, to conduct the experiments. It is a small first order stream27 with sandy or rocky bottoms. Stream bank vegetation is dense, composed of herbs, shrubs and trees. In the vicinities of the point where we conducted the experiments (and up to 150 m upstream) stream width ranges from 2 to 6 m, and stream depth, from just a few centimeters to about 1 m28.
Response to predator cues in the natural habitat
We built three enclosures measuring 40 × 35 cm with a plastic mesh around a metal frame that limited two compartments, one measuring 35 × 35 cm, and another contiguous to it measuring 5 × 35 cm. Both compartments were 15 cm high and were open both below and above. We set the enclosures at a stream section of shallow water and flat rocky bottom, where water filled the enclosures up to about 5 cm (Fig. 4). We placed the enclosures with the small compartment upstream, so that the tadpole in the larger compartment would be exposed to both visual and chemical cues of the predator to be introduced in the smaller compartment. We collected three water bugs (Belostoma testaceopallidum) to be used in the experiments in a nearby stream from the same water basin (20o06′40″S, 43o28′48″W; 1,254 m above sea level). We collected the tadpoles very close to the enclosures (up to 5 m upstream).
Figure. 4

Experimental design showing the water bug predators (Belostoma testaceopallidum, (A) and tadpoles of Ololygon machadoi (B) inside enclosures placed in a stream (C) at the RPPN Santuário do Caraça, Southeastern Brazil, where both species occur. A schematic representation of the experimental enclosures is also shown (D).

Full size image

Before we started each trial, we inspected the area covered by the enclosures to make sure no tadpoles or other animals remained inside. We then sealed the bottom carefully with sand from the same stream and placed one tadpole within each cage, in the larger compartment. We waited 3 min, sufficient for the tadpole to return to normal activity levels after translocation to the enclosures17, and then we recorded whether each tadpole was moving or standing still in 30 s intervals, during 15 min for a total of 30 observations. When tadpoles moved, they always moved on the bottom, never through the water column. After this, we waited another 3 min and repeated the 30 movement records for the next 15 min. We then removed the water bug and repeated another observation turn (waited 3 min, then made 30 movement observations separated by 30 s intervals). After each individual tadpole was tested, we released it downstream, to avoid using the same individual more than once. Tadpoles were all in developmental stage 2529 and measured 20.2 ± 2.4 mm (n = 33 tadpoles measured). We maintained the water bugs in individual recipients with clean stream water and used them randomly in the three enclosures. After all the experiments we collected them for identification.
We tested 3 tadpoles simultaneously, then restarted the whole experiment with other 3 tadpoles, and so on, until we tested 54 tadpoles during three consecutive days (3–5 October, 2018). The weather was sunny with some clouds and short periods of light rain, during which we did not conduct experiments.
Defensive responses based on previous experiences
For this experiment, we collected stage 25 tadpoles at the same stream section and kept them for no more than 2 h in polystyrene boxes with stream water by the nearby (about 1.3 km) lodging of the RPPN Santuário do Caraça, where we conducted the experiments to test the influence of previous experience on tadpole background choice and immobility. We placed individual tadpoles in plastic trays measuring 43 cm length, 30 cm width, 9 cm height, with half the bottom covered by a picture of a natural yellow background (rocks in its natural habitat). The other half was covered with the same picture manipulated digitally to match the hues and luminance of natural dark backgrounds, as in17. We filled the trays with tap water that comes straight from the main stream at the reserve, replacing the water at every trial. For each trial, we waited 3 min. after tadpole placement in the center of the tray, then we observed tadpoles for 30 min, recording their background every minute. After that, we applied one of three treatments during a 5-min interval: (1) an aversive stimulus was applied to the tadpole every time it positioned itself on the yellow background, or (2) on the dark background or (3) no stimulus was applied (control). The aversive stimulus consisted in one person approaching a wood stick slowly towards the tadpole until it reacted fleeing. After the treatments, we conducted another 30 min of observations recording tadpole background every minute. The tadpoles were all returned to their original stream after the experiments. We tested 2 tadpoles in each treatment simultaneously and then repeated the trials until tests of 30 tadpoles for each treatment (total 90 tadpoles) were completed. Experiments were performed from 4 to 6 October 2016. Experiments were conducted in the shade with natural light, and all days were sunny.
All the procedures were performed in accordance with relevant guidelines/regulations adopted by the responsible institutions: Sisbio/ICMBio (45302-1, 62316-1) authorized animal manipulation in situ and the Ethical Committee of the Pontifícia Universidade Católica de Minas Gerais (032/2016, 003/2018) approved the experimental procedures in accordance with animal welfare guidelines. The water bugs were identified as Belostoma testaceopallidum Latreille, 1807, and the collected specimens were deposited in the collection of aquatic insects of the Parasitology Department of the Institute of Biological Sciences (DPIC) of the Federal University of Minas Gerais, Belo Horizonte, Minas Gerais state, Brazil, under the accession number 9498.
Statistical analyses
We compared the level of activity of tadpoles (given by the number of instant positive records of movement) before, during, and after the presence of the water bug in the enclosures in the stream. We also evaluated a possible effect of direct sun incidence or shade on the enclosures30, and its interaction with tadpole activity levels. We built Generalized Linear Mixed Models (GLMM) with the packages “car”31 and “MASS”32 in R33. We considered number of movement records + 1 (to adjust to distributions that must be non-zero) as the dependent variable, phase (before, during, or after the presence of the water bug) and light (sun or shade) as explanatory variables, and individual tadpole as a random variable. Tadpoles might present different reactions to predators based on their previous experiences34. Considering individual as a random variable would also account for possible differences among times of the day and cages on individual behaviour. We built models including each one or both explanatory variables, with or without their interaction. We compared these models with a null model that included only the random variable, in order to identify the variable(s) with the strongest explanatory power.
We also used GLMMs to test for the ability of tadpoles to avoid a background colour after an aversive experience on it. Since tadpoles had to choose between dark and yellow, we arbitrarily used the number of records on dark backgrounds as dependent variable, because the records on yellow would represent the alternative situation (not on dark). We used treatment and phase (before and after the treatments were applied) as fixed variables and tadpole as a random variable. In order to test for the expression of immobility after the aversive stimuli, we considered the number of times tadpoles changed background colour in consecutive observations as a surrogate for tadpole movement (our dependent variable), treatment and phase as fixed variables and tadpole as a random variable.
We used the package MuMIn35 for R33 to select the best models, a procedure recommended to control the overall type I error rate36. We conducted Tukey post hoc tests with the package emmeans37. More

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Field sampling design
To determine if there was within-individual plasticity in floral traits between spring and summer conditions, 50 plants of each of four populations from SE Spain (Supplementary Table 1) were marked at the onset of the flowering period in late February–early March 2018. The phenotype of two flowers per individual was quantified (see below). We revisited each population during summer (June 2018) and the same floral traits were quantified in the summer flowers of those plants still flowering (117 plants; Supplementary Table 1).
Experimental design
We performed an experiment testing the effect of temperature and photoperiod in floral plasticity. It included three treatments: (1) Treatment 1, where 30 plants flowered first in conditions mimicking the spring temperature and photoperiod of Mediterranean Spain (day/night = 10/14 h, temperature = 20/10 °C, average daily temperature = 14.2 °C; see Supplementary Table 1), and afterwards in conditions mimicking a mild summer (day/night = 16/8 h, temperature = 30/20 °C, average daily temperature = 23.8 °C). (2) Treatment 2, where 30 plants flowered first in spring conditions and afterwards in hot summer conditions (day/night = 16/8 h, temperature = 35/25 °C, average daily temperature = 28.8 °C). (3) Treatment 3 (control) where 15 plants flowered first in spring conditions, and afterwards they flowered again in spring conditions. For all treatments, we removed flowers before starting the second round of flowering.
We experimentally tested the occurrence of reverse plasticity by performing a Treatment 4 in which 15 plants from Treatment 1 that flowered both during spring and summer conditions were again submitted to a period mimicking spring conditions (Supplementary Table 1).
Floral traits
We measured, both in field and experimental conditions, three floral traits during spring (or under experimental spring conditions) and in summer (or under experimental hot summer conditions). These traits were corolla size, corolla shape and corolla colour.
Corolla size of each studied flower was estimated by means of two traits: (1) corolla diameter, estimated as the distance in mm between the edge of two opposite petals. (2) Corolla tube length, the distance in mm between the corolla tube aperture and the base of the sepals. These variables were measured by using a digital calliper with ±0.1 mm of error.
Corolla shape variation was studied using geometric morphometric tools based on a landmark-based methodology43. For this, in each of the two selected flowers per individual plant studied in each of the four populations, we took a digital photo of the front view and planar position. We defined 32 co-planar landmarks covering the corolla shape and using midrib, primary and secondary veins and petal extremes and connections21,44. From the two-dimensional coordinates of landmarks, we extracted shape information and computed the generalized orthogonal least-squares Procrustes averages using the generalized procrustes analysis (GPA) superposition method. Due to the intrinsic symmetry pattern exhibited by Brassicaceae flowers, we did the analyses considering both the symmetric and asymmetric components of the shape45,46,47. We performed a principal component analysis (PCA) on the GPA-aligned specimens, and afterwards, we did a canonical variate analysis (CVA) to explore the difference in shape between season and populations43,47. Geometric morphometric analyses were performed in the R packages ‘geomorph’48, ‘Morpho’47 and ‘shapes’49,50.
To explore the relative position of the corolla shape of spring and summer flowers in the morphospace created by the species most related phylogenetically with M. arvensis, we performed a phylomorphospace. This analysis creates a plot of the main principal dimensions (the three first principal components in this case) of a tangent space for the Procrustes shape variables of the pool of species considered in the analysis and superimposed the phylogenetic tree relating this species in this plot51,52. By doing this, this analysis reveals how the shape evolves. To perform this analysis, we collected information on the corolla shape of 72 additional species belonging to the Brassicaceae tribe Brassiceae, the tribe to which M. arvensis belongs (Supplementary Table 3). We followed the same procedure as with M. arvensis, using the same number of landmarks and computing the generalized orthogonal least-squares Procrustes averages using GPA superposition method. In this analysis, we kept separate the spring and summer flowers of M. arvensis. The phylogenetic relationship between these 72 species was obtained by making a supertree using Brassicaceae trees hosted in the repository TreeBASE Web (TreeBase.org)53. We first downloaded individual phylogenetic trees from TreeBASE. Second, we concatenated all these individual trees and made a skeleton supertree. Finally, we pruned this supertree, keeping only the species included in the geometric morphometric analysis, and insert the two ‘pseudospecies’ of M. arvensis (spring and summer) as sister species. Afterwards, we projected the value of the three first components of each species on a 3D phylogenetically explicit plot. The phylogenetic analysis was performed in the R packages ‘treeman’54, ‘phangorn’55, ‘phytools’56 and ‘treebase’53, whereas the phylomorphospace analysis was performed in the R packages ‘geomorph’48.
The corolla colour of M. arvensis is produced by the accumulation of flavonoids57,58. Anthocyanin and non-anthocyanin flavonoids present in the petals of M. arvensis were analysed by ultra-performance liquid chromatography (UPLC) (ACQUITY System I-Class, Waters) coupled with quadrupole time-of-flight mass spectrometry (SYNAPT G2 HDMS Q-TOF, Waters). Analytical separation of flavonoids was performed on an Acquity HSST33 analytical column (150 mm × 2.1 mm internal diameter, 1.8 μm). A mobile phase with a gradient programme combining deionized water with 0.5% of acetic acid as solvent A and acetonitrile with 0.5% of acetic acid as solvent B was used. The initial conditions were 95% A and 5% B and a linear gradient was then established to reach 95% (v/v) of B. The total run time was 15 min and the post-delay time was 5 min. The mobile phase flow rate was 0.4 mL min−1. After chromatographic separation, a high-resolution mass spectrometry analysis was carried out in positive electrospray ionization (ESI+). The ionization source parameters using high-purity nitrogen were set at 600 L h−1 for desolvation gas flow and 30 L h−1 for cone gas flow. Spectra were recorded over the mass/charge (m/z) range of 50–1500. Data were recorded and processed using MassLynx software. The flavonoids present in the petal extracts were characterized according to their retention times, mass spectra and molecular formula, and compared with published data when available. We calculated the relative abundance of each compound in both lilac and white petal samples (N = 5 and 2, respectively) using peak intensities.
Quantification of flavonoids present in flowers of M. arvensis was performed spectrophotometrically. Two flowers of each plant used in field and experimental studies were analysed in each blooming period. We collected the four petals of a flower. Flavonoids were extracted in 1.5 ml of MeOH:HCl (99:1% v-v) and stored at −80 °C in the dark, following the procedure described in ref. 34. Two replicas of 200 μL for each sample were measured in a Multiskan GO microplate spectrophotometer (Thermo Fisher Scientific Inc., MA, USA). Main flavonoid classes present in the petals of M. arvensis are anthocyanins (cyanidin derivatives) and flavonols (kaempferol, quercetin and isorhamnetin derivatives; Supplementary Table 4)57,58. Thus, total anthocyanins and flavonols were quantified as absorbance at 520 and 350 nm, respectively. Their concentrations were calculated using five-point calibration curves of cyanidin-3-glucoside chloride (Sigma-Aldrich, Steinheim, Germany) and kaempferol-3-glucoside standards (Extrasynthese, Genay, France) and expressed as cyanidin-3-glucoside and kaempferol-3-glucoside equivalents in fresh weight (mg g−1 FW), respectively.
Objective quantification of petal colour of lilac and white petals of M. arvensis was performed by measuring their UV–Vis spectral reflectance. A petal of a flower of each colour morph (N = 10) were measured with a Jaz portable spectrometer (Ocean Optics Inc., Dunedin, FL, USA) equipped with a deuterium–tungsten halogen light source (200–2000 nm) and a black metal probe holder (6 mm diameter opening at 45°). Reflectance, relative to a white standard (WS-1-SL), was analysed with SpectraSuite v.10.7.1 software (Ocean Optics). To maximize the amount of light used in reflectance measurements and to reduce occasionally erratic reflectance values at individual nm, we set an integration time of 2 s and smoothing boxcar width of 12, respectively59.
Foliar traits
We measured, both in field and experimental conditions, five leaf traits during spring (or under experimental spring conditions) and in summer (or under experimental hot summer conditions). These traits were the specific leaf area (SLA, m2 kg−1), the leaf dry matter content (LDMC, mg g−1), the carbon-to-nitrogen content of leaves (C:N ratio), the isotopic signature of 13C in leaves (δ13C, ‰), and the CO2 compensation point and the slope of the A–Ci curve.
SLA and LDMC were measured following standard protocols60. For SLA and LDMC we collected three fully expanded and mature leaves without any visible damage (e.g., herbivory, pathogen attack) from the base, midsection and apical part of outer stems (that is, leaves were not shaded by other leaves) and at random aspects. Leaves were rehydrated overnight in the dark and subsequently weighted and scanned. Leaf area was measured using the Midebmp software (Almería, Spain). Leaves were dried in the oven at 60 °C and weighted after 72 h. From these measurements, we calculated the SLA as the one-sided area of the fully rehydrated fresh leaf divided by its dry mass, while the LDMC is the ratio between the leaf dry mass and the fully rehydrated fresh mass.
Carbon isotopic signature (δ13C), as well as the C and N relative content in leaves, were analysed in a couple of fully expanded leaves per plant without any visible damage. Oven-dry leaves were ground in a ball mill MM400 (Retsch GmbH, Haan, Germany) at 3000 rpm for 1 min to obtain a fine powder, which was stored in Eppendorf tubes. We wrapped 0.003 g of each sample in tin capsules D1008 (Elemental Microanalysis, United Kingdom). Leaf δ13C and leaf C and N relative content (in mass percentage) were determined at the Stable Isotope Analysis Lab—Centro de Instrumentación Científica (CIC) of the University of Granada (Spain) with a GC IsoLink—MS—Delta V continuous flow mass spectrometer (MS) system that includes a ISQ-QD single quadrupole MS and a gas chromatographer Trace 1310 (Thermo Fisher Scientific™, Spain). The isotopic abundance was expressed in parts per thousand (‰) as

$$delta = left( {{R}_{{mathrm{sample}}}/{R}_{{mathrm{standard}}}-1} right) times 1000$$
(1)

where Rsample and Rstandard are the molar ratios of heavy (13C) to light (12C) stable isotopes of the sample (Rsample) and an international standard (Rstandard). MS precision was 0.15‰ for carbon, based on replicate analyses of standard reference materials.
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