DOI: 10.5061/dryad.1c59zw3vv
title: Environment and phenology shape local adaptation in thermal performance

description: Populations within species often exhibit variation in traits that reflect
 local adaptation and further shape existing adaptive potential for species
 to respond to climate change. However, our mechanistic understanding of
 how the environment shapes trait variation remains poor. Here, we used
 common garden experiments to quantify thermal performance in eight
 populations of the marine snail Urosalpinx cinerea across thermal
 gradients on the Atlantic and the Pacific coasts of North America. We then
 evaluated the relationship between thermal performance and environmental
 metrics derived from time-series data. Our results reveal a novel pattern
 of “mixed” trait performance adaptation, where thermal optima was
 positively correlated with spawning temperature (cogradient variation),
 while maximum trait performance was negatively correlated with season
 length (countergradient variation). This counterintuitive pattern likely
 arises because of phenological shifts in the spawning season, whereby
 “cold” populations delay spawning until later in the year when
 temperatures are warmer compared to “warm” populations that spawn earlier
 in the year when temperatures are cooler. Our results show that variation
 in thermal performance can be shaped by multiple facets of the environment
 and are linked to organismal phenology and natural history. Understanding
 the impacts of climate change on organisms therefore requires the
 knowledge of how climate change will alter different aspects of the
 thermal environment.
description: (a) Natural History and Environmental
 Context <i>Urosalpinx </i>is a
 predatory snail that is native from Florida to Nova Scotia and was
 introduced to the Pacific coast of North America in the late 1800s via
 American oyster (<i>Crassostrea virginica</i>) culture
 [34,35]. We quantified patterns of thermal performance from populations
 sampled across both the native and introduced coasts because they
 experience radically different thermal regimes. For example, while mean
 temperature and growing season length both decrease strongly from south to
 north along the Atlantic coast of North America, the gradient is much
 weaker and cooler on the Pacific coast [26,36]. Non-native species, such
 as <i>Urosalpinx</i>, provide an opportunity to compare
 intraspecific trait performance across different environmental gradients
 [37].<i> </i>Although demographic history and founder effects
 have the potential to alter population responses to environmental regime
 and can confound interpretation of physiological trait data [38,39], the
 introduction of <i>Urosalpinx</i> to the west coast largely
 ended by the 1900s when transcontinental oyster imports ceased [40,41],
 allowing for 120 years of potential adaptation to the non-native climate
 regime. Further, in San Francisco Bay alone, 1.7 million kg of eastern
 oysters (<i>Crassostrea virginica</i>) were transplanted. Due
 to unregulated collection and transport processes at the time, large
 amounts of <i>Urosalpinx </i>were probably also introduced
 [41], which would greatly decrease the likelihood of a strong genetic
 bottleneck with drastic reduction of genetic diversity compared to source
 populations. Further, because this species undergoes direct development
 (i.e. there is no planktonic larval stage), dispersal and gene flow are
 likely limited among populations, suggesting a high potential for local
 adaptation [13,42]. (b) Broodstock Field
 Collection and Common Garden Experiment We
 examined physiological performance of lab-reared offspring from broodstock
 mothers sourced from eight populations of <i>Urosalpinx</i> to
 evaluate the effects of environmental drivers on local adaptation.
 Experiments were conducted on juveniles that experienced controlled
 environmental conditions for their entire embryonic and juvenile life
 until cessation of experiments described below. To produce juvenile
 <i>Urosalpinx</i>, we collected broodstock adult
 <i>Urosalpinx</i> from eight sites, six from the Atlantic and
 two from the Pacific from March 15-June 9, 2019 (figure 2, table S1,
 [42]).  At each site, we hand-collected at least 30
 adults in the low intertidal to shallow sub-tidal zone from oyster reefs,
 pier pilings, and boulders across a sampling area of 300
 m<sup>2</sup>. We transported Atlantic-collected snails in
 aerated coolers of seawater from collection sites to the University of
 Massachusetts Amherst Gloucester Marine Station. Samples from Humboldt Bay
 and Willapa Bay were collected in a similar fashion except that they were
 overnight shipped in plastic bags with saltwater-moistened paper towels
 and immediately placed in a holding tank upon arrival. No mortalities
 occurred as a result of collection or shipping. We
 maintained broodstock <i>Urosalpinx</i> in a recirculating
 seawater system at the Gloucester Marine Station at 12 °C (salinity 30
 PSU) until needed for experimentation and as other populations were
 collected. Once all populations were established in the lab, we raised the
 water temperature to 20°C over the course of a week (1 °C/day) based on
 previous work indicating this was a suitable spawning temperature<i>
 </i>[2]<i>.</i> Populations were kept separate in
 plastic aquaria with aeration and fed blue mussels (<i>Mytilus
 edulis</i>), acorn barnacles (<i>Semibalanus
 balanoides</i>), and eastern oysters (<i>Crassostrea
 virginica</i>) <i>ad libitum</i>.
 <i>Urosalpinx</i> mothers began laying egg capsules on June
 6<sup>th </sup>2019, with eggs being laid by 4-8 mothers per
 population. We collected egg capsules laid between June
 6<sup>th</sup> and July 4<sup>th</sup>, 2019 and
 kept the egg capsules separated by population in labelled tea strainers
 (Tops Permabrew, Darien, CT). We maintained eggs at 20 °C and 30 PSU and
 checked strainers daily for hatchling emergence. We collected hatchlings
 for use in the common garden experiment within two days of
 hatching. To maintain experimental temperature,
 hatchlings were enclosed within individual, labeled tea strainer halves
 that were floated within 30 L bins of 20 L aerated seawater (salinity = 30
 PSU), which were in turn immersed in temperature-controlled seawater
 tables. These bins served as our temperature sub-replicates; we used three
 bins per experimental temperature. We placed nine snails from each of the
 eight tested populations in the six temperature treatments, distributing
 snails equally across the three replicate bins per temperature treatment
 (see figure S1). Each hatchling had a unique identification number to
 track date of entry into experiment and initial shell size. Hatchlings
 snails were supplied <i>ad libitum</i> with 3-5 mm oyster spat
 (<i>Crassostrea virginica</i>) per hatchling (Muscongus Bay
 Aquaculture, Bremen, Maine) for the duration of the common garden
 experiment. We checked tea strainers every 3-5 days (depending on
 temperature treatment) and all oysters were inspected using a
 stereomicroscope for signs of consumption, indicated by the presence of a
 drill hole (figure S2). During these checks, we replenished prey oysters
 with at least twice the number of observed consumed oysters to ensure
 <i>ad libitum </i>conditions were met. For
 hatchlings, we digitally photographed each snail aperture-down using a
 stereomicroscope (Leica s9i Leica Microsystems GmBH, Wetzlar, Germany) and
 measured shell height from spire tip to distal siphonal canal using ImageJ
 (National Institutes of Health, Bethesda, Maryland) [3]. Digital
 measurement of hatchlings was used to assess initial height as opposed to
 using vernier calipers due to the small size of hatchlings (1.55 mm ±
 0.202, mean ± SD) and the potential for calipers to damage shells. We
 recorded final snail measurements after the duration of the common garden
 experiment using vernier calipers, as snails were now large enough to be
 handled. Details of Environmental Data
 Sources We sourced environmental data from
 NOAA National Data Buoy Center (NBCC), the National Estuarine Research
 Reserve System (NERRS), the University of Virginia, the Pacific Shellfish
 Institute, and the Wiyot Tribe (table S1), based on 1) proximity to
 <i>Urosalpinx </i>collection site, 2) hydrology similarity
 between the data source and the collection site, and 3) completeness of
 annual data. To account for potential outlier years, we identified four
 years of complete annual water temperature data from each site between
 2012 – 2019 to maintain data quality and completeness (table S1). We
 sourced data from all but one site (Skidaway, GA) within 15 km of the
 collection site. Skidaway’s closest environmental data source was only
 complete for one year (2018), and thus we used the next closest and most
 complete dataset 70 km away. The water temperature between the incomplete,
 proximal Georgia data source was highly correlated with the complete,
 distant Georgia data source (slope = 1.02, intercept = -0.501, R2 =
 0.981). To construct <i>Urosalpinx</i>
 thermal performance curves, we conducted a common garden experiment. We
 exposed hatchlings from the 8 populations to 6 chronic experimental
 temperatures (16, 20, 24, 26, 28, and 30°C) chosen to capture
 T<sub>opt </sub>based on past experiments [43]. These
 temperatures are also realistic when compared to habitat temperature
 across populations (min-max: 2–37.5°C). Growth rate was measured using
 snail shell height, which is correlated with body mass [42]. First,
 juvenile snails were measured for an initial shell height and then
 randomly assigned into common garden temperature treatments. Snails were
 less than 24 hours of age (post-hatch) when they entered the common garden
 experiment that lasted for 24 days. On the last day, we measured shell
 height and calculated growth rate as the difference between initial and
 final size. We counted snails that died over the duration of the
 experiment to quantify survivorship in the common garden experiment, but
 these data points were excluded from growth analyses. See Supplementary
 Material S1 for further details about common garden experimental design
 and measurement of <i>Urosalpinx </i>growth rate.
 (c) Environmental
 Predictors In order to quantify environmental
 drivers of variation in growth rates in <i>Urosalpinx</i>, we
 derived nine metrics from four years of temperature data sourced from
 environmental loggers co-located within 14 km of the collection site for
 each population. One exception was the Georgia data logger, which was
 located 70 km away from the collection location but was highly correlated
 with local temperature logger that had a shorter record (Supplementary
 Material S1). We selected four years of temperature data from 2012-2019
 based on the completeness of the record and to maximize temporal overlap
 among sites (table S1 , Supplementary Material S1). From this data, we
 calculated: 1) latitude, 2) summer mean temperature (June 1 – Sept 30), 3)
 upper 25<sup>th</sup> temperature percentile of the summer
 period, 4) upper 10<sup>th</sup> temperature percentile of the
 summer period, 5) maximum recorded temperature, 6) season length (number
 of days) where daily mean exceeded 10°C, 7) season length where daily mean
 exceeded 12.5°C, 8) the mean temperature for the first month of spawning,
 and finally 9) the mean temperature for the maximum period of spawning
 (table S2). We included length of season as a predictor because theory
 predicts organisms exposed to shorter growing seasons (i.e. high
 latitudes) are selected for faster growth [5,6,27]. We selected two likely
 lower temperature limits to calculate season length for
 <i>Urosalpinx</i>, 10°C and 12.5°C, based on reported absolute
 lower limit for feeding [44,45] and a breakpoint in oxygen consumption
 rates [46], respectively. We included mean temperature during spawning, as
 one of our hypotheses of T<sub>opt </sub>behavior with
 environment is that high latitude populations experience warmer spawning
 periods than do low latitude populations [18]. We determined initial and
 maximum spawning periods as reported by [34] from the Atlantic and
 observations from the Pacific [47]; where no records of spawning periods
 could be found for a site, we used the closest neighbor site (table S4).
 We selected this broad range of variables as we did not necessarily know
 <i>a priori</i> which were relevant, and because the grouping
 of correlated predictors in AIC tables indicate what aspects of the
 environment best explain trait adaptation (i.e. season length generally,
 as opposed to season length above a specific threshold). (d)
 Statistical Analysis We used a
 two-step analysis framework to determine the environmental mechanisms
 driving growth rates in <i>Urosalpinx</i> populations in R
 [48]. First, we constructed and fit  nonlinear regression models to
 thermal performance curves with initial snail size as a random effect
 (contributing 2.4% variance, means ranging from 1.44 ± 0.180 to 1.69 ±
 0.204 mm among populations) using the <i>rTPC </i>and
 <i>nls.multstart </i>packages for each population to quantify
 thermal performance curve attributes (T<sub>opt </sub>and MTP,
 temperature at which maximum growth occurs and the maximum growth rate,
 respectively) for each population across the six common garden
 temperatures using the Rezende equation [49,50].  For each of the eight
 populations we fit three models based on the three replicate bins across
 the six common garden temperatures where populations were randomly
 assigned (figure S1). To produce 95% confidence intervals about each model
 prediction, we used non-parametric case resample bootstrapping on each
 population-bin model using <i>rTPC </i>and  (table S5, [49]).
 Once  models were fit to the data, we extracted the thermal optima
 (T<sub>opt</sub>) and maximum trait performance (MTP) of each
 thermal performance curve (table S5, figure S3). We then modeled the
 T<sub>opt</sub> and MTP for each population against a suite of
 environmental metric predictors (table S2) in a model-selection framework
 using generalized linear mixed models with gaussian error distribution and
 with population as a random effect using <i>glmmTMB </i>[51].
 Each environmental predictor was used only once per model to identify
 which predictor best describes patterns in trait performance and to avoid
  the issue of multicollinearity in models with multiple correlated
 predictors (i.e. where VIF &gt; 4; table S3). We used Akaike’s
 Information Criterion (AICc) to select the greatest supported model, with
 a cutoff of ΔAICc &lt; 2 [52]. For MTP, multiple predictors fell
 within the model selection criterion, and so we performed model averaging.
 To evaluate the possibility that analyses were influenced by invasive
 populations from the Pacific, we conducted a sensitivity analysis by
 constructing identical models with Pacific populations excluded. Our
 analyses were not sensitive to the removal of Pacific sites from analysis;
 both the best-supported environmental parameters and the significance
 level (<i>p </i>&lt; 0.05) were maintained for the MTP and
 T<sub>opt </sub>analyses. We therefore present the full
 analysis of Atlantic and Pacific sites in the results. For survival, we
 used type II ANOVA from the <i>car</i> package [53] on
 generalized linear models with a binomial error distribution and logit
 link to analyze if population, common garden temperature, or the
 interactive effects of population and temperature affected
 <i>Urosalpinx </i>survival in the common garden
 experiment.
description: The analyses for this manuscript were performed in R. To view our
 scripts and reproduce our analysis, you must download the latest version
 of R and RStudio. Several files are included in this
 repository, described below. 1) README.md - This ReadMe
 document must be opened in R. Information and metadata from each script
 and data file are outlined here.  2) Uro_ch_2.Rproj - R
 project file  3) data.zip - Zip file of all data used
 in this analysis 4) scripts.zip - Zip file of all R
 scripts used in this analysis