DOI: 10.5061/dryad.05qfttf10
title: Data from: Does local adaptation along a latitudinal cline shape plastic responses to combined thermal and nutritional stress?

description: Thermal and nutritional stress are commonly experienced by animals. This
 will become increasingly so with climate change. Whether populations can
 plastically respond to such changes will determine their survival.
 Plasticity can vary among populations depending on the extent of
 environmental heterogeneity. However, theory conflicts as to whether
 environmental heterogeneity should increase or decrease plasticity. Using
 three locally-adapted populations of Drosophila melanogaster sampled from
 a latitudinal gradient, we investigated whether plastic responses to
 combinations of nutrition and temperature increase or decrease with
 latitude for four traits: egg-adult viability, egg-adult development time,
 and two body size traits. Employing nutritional geometry, we reared larvae
 on 25 diets varying in protein and carbohydrate content at two
 temperatures: 18ºC and 25ºC. Plasticity varied among traits and across the
 three populations. Viability was highly canalized in all three
 populations. The tropical population showed the least plasticity for
 development time, the sub-tropical showed the highest plasticity for wing
 area, and the temperate population showed the highest plasticity for femur
 length. We found no evidence of latitudinal plasticity gradients in either
 direction. Our data highlight that differences in thermal variation and
 resource predictability experienced by populations along a latitudinal
 cline are not sufficient to predict their plasticity. 
description: <i>Fly stocks</i> We used mass
 bred populations collected from tropical (Townsville, latitude:19.29S),
 sub-tropical (Ballina, latitude: 28. 75), and temperate (Melbourne,
 latitude: 37.73) regions along the east coast of Australia (Supplementary
 Figure 1). The flies to seed these populations were collected in April
 2016, and were maintained as mass bred populations at a population size of
 approximately 1500 flies at constant temperature of 25ºC on a 12-hour
 light/dark cycle on yeast-dextrose-potato medium (potato flakes 20g/L;
 dextrose 30g/L; 95 Brewer’s yeast 40 g/L; agar 7g/L; nipagen 6mL/L; and
 propionic acid 2.5 mL/L), for 55 generations prior to the experiments
 described below. <i>Nutritional
 geometry</i> Twenty-five diets were used in this
 study, following Kutz <i>et al.,</i> (2019). These diets were
 one of five protein and carbohydrate (P:C) ratios, 1:8, 1:4, 1:3, 2:3, or
 3:2, made by changing the quantities of inactive yeast, dextrose, and
 potato flakes. Each ratio was prepared at two concentrations of 2547.4kcal
 and 1273.7kcal. The 1273.7kcal was diluted for each ratio sequentially by
 50% to make the remaining three caloric concentrations: 636.84kcal, 318.42
 kcal, 159.21kcal per P:C ratio. To obtain focal flies
 for the experiments, parental flies from each of the three populations
 were acclimated to egg laying chambers containing standard food for 24
 hours, changing the egg plates every 12 hours. Eggs were collected from an
 overnight egg lay, and 20 eggs were transferred from each population into
 vials containing 7ml of each of the experimental diets. We used two
 constant thermal conditions, 18<sup>o</sup>C and
 25<sup>o</sup>C to impose shifts in thermal regime.  These two
 temperatures represent the average winter and summer thermal conditions
 experienced along the east coast of Australia, from temperate Melbourne up
 to tropical Townsville (www.bom.gov.au). Five replicate
 vials for each population, Ballina, Melbourne, and Townsville, and for
 each of the 25 diets were placed at either 25ºC or 18ºC, where they were
 left to develop from egg to adult eclosion.  Temperature and
 humidity-controlled cabinets with 12-hr light and 12-hr dark photoperiod
 were used for the experiment. The vials were moved within the cabinets
 every 12 hours to remove any biases of temperature and light
 gradients. <i>Egg-to-adult development time and
 egg-adult-viability</i> Egg-to-adult development
 time was recorded as the time in hours from the mid-point of egg laying to
 adult eclosion. Once counted, flies were removed from their vial. Vials
 were checked every 12 hours until four consecutive time points yielded no
 flies, after which vials were discarded. Egg-to-adult viability was
 measured as the proportion of adults that emerged from the 20 eggs
 transferred into each replicate vial. <i>Adult
 body size </i> The sizes of <i>D.
 melanogaster</i> body parts differ in their response to nutrition
 and temperature (Kutz et al. 2019; Shingleton et al. 2017). To account for
 these differences, body size was estimated using wing centroid size and
 femur length. Thirty female flies from each treatment were preserved in
 70% ethanol/30% glycerol solution (SH solution) and were subsequently used
 for dissections. We chose to focus on female flies, as the size of their
 body parts is known to be more sensitive to nutrition (Shingleton et al.
 2017), and because assessing sex-specific plasticity was not the focus of
 the present study. Left first legs and left wings were mounted in SH
 solution on a microscope slide and photographed using a Leica M80 stereo
 microscope (Leica, Heerbrugg, Switzerland). All images were processed
 using ImageJ software. Wing area was estimated by calculating the centroid
 size from landmarks from 6 vein positions (Supplementary Figure 2a).
  Femur length was estimated as the distance between two landmarks: the
 anterior-most junction between the femur and coxa, and the posterior-most
 junction between the femur and tibia (Supplementary Figure 2b)
 <i>Statistical analyses</i> The
 response of all traits to temperature and to both the protein and
 carbohydrate composition of the diet was analysed following Kutz,
 <i>et al</i>; 2019. For development time, wing size, and femur
 length, data were fit using linear mixed effects models. Survival
 (egg-to-adult viability) was fit using generalised linear models assuming
 a binomial distribution. Fit of the data was validated by visual
 inspection of the residuals. The full models include the
 following: Y = P +
 P<sup><i>2</i></sup> + C +
 C<sup><i>2</i></sup> + Temp + Pop + P*C + Temp*P +
 Temp*P<sup><i>2</i></sup> + Temp*C +
 Temp*C<sup><i>2</i></sup> + Temp*Pop + Pop*P +
 Pop*P<sup><i>2</i></sup> + Pop*C +
 Pop*C<sup><i>2</i></sup> + Pop*P*C + Temp*P*C +
 Temp*P*Pop + Temp*P<sup><i>2</i></sup>*Pop +
 Temp*C*Pop + Temp*C<sup><i>2</i></sup>*Pop +
 Temp*Pop*P*C , where P is protein, C is carbohydrate,
 Temp is temperature, and Pop is population. Experimental block (for
 development time) and replicate vial (all traits) were included as random
 effects. Analyses were first performed on the full
 dataset for each trait to determine if there were significant interactions
 between protein concentration, carbohydrate concentration, temperature,
 and population. To estimate plasticity, we next scaled the data to a mean
 of 0 with unit standard deviations. We first compared differences in
 plasticity by comparing the shapes of the response surfaces, using partial
 F tests. We then contrasted trait responses to the linear and quadratic
 components of protein and carbohydrate concentration across populations
 and temperature, similar to methods described in Morrissey and Liefting
 (2016) using emtrends from the emmeans package in R. Thin-plate spines
 (TPS) were used to visualize the response surfaces for each trait,
 following Kutz, et al (2019). All statistical analyses were performed in R
 Studio (version 3.4.1, R Development Core Team 157 2017, https://www.r158project.org/).