Originally from Denmark, Josephine moved to Townsville in July 2013 to pursue a Bachelor of Sciene - Marine Biology. Since then, she has fallen for both the geographical area but also for the discipline and has obtained an Honours (1A) degree from JCU in 2017. Prior to starting her PhD in March 2019, she worked for her now primiary supervisor as a research technician at AIMS.

Natural variation in heat tolerance, thermal plasticity and performance trade-offs of corals on the Great Barrier Reef

2019 to 2023

Project Description

This project investigates natural variation and plasticity in coral thermal tolerance and associated
trade-offs. Variation in thermal performance will be estimated with an instant heat stress assay in
the field while thermal plasticity and physiological trade-offs will be estimated from thermal
performance curves of corals exposed to a range of temperatures in the laboratory. Understanding
natural variation and trade-offs associated with enhanced thermal tolerance is important for
proposed management interventions such as Assisted Gene Flow. This knowledge is currently
limited, but essential to understand corals’ ability for adaptation and to identify source populations
or individuals with high thermal tolerance.

Project Importance

Coral reefs are threatened by climate change. The current rate of ocean warming is unprecedented in modern times and is likely to challenge coral survival into the future1. This is highlighted by the prevalence of recurrent mass bleaching events across reefs around the world2. The Great Barrier Reef (GBR) experienced back-to-back bleaching 3 in the Austral summers of 2016 and 2017. Coral mortality varied greatly across the Reef; little heat stress experienced in the southern sector and reported losses of coral cover at 50.3% over eight months in the northern sector, resulting in a 30% decline in GBR-wide coral cover4. Even if emissions are curbed according to the Paris Agreement, additional warming of 0.5 - 1oC is projected into the next century 5–7. If we continue on a business-as-usual trajectory (IPCC’s scenario RCP8.5), global mean surface temperature may increase by as much as 3.7oC by 2100 1. Because corals are already challenged by accumulated heating to date4,8. the ability to acclimatize and adapt to warming oceans will play a determining role in their continued survival even under best case scenarios.
The current understanding of thermal thresholds in corals is based largely on observed bleaching thresholds and modelling9. While upper thermal tolerance in corals is generally correlated with environmental temperature regimes10, this tolerance is influenced by an array of factors. Coral thermal tolerance is affected by the (micro)habitat of the coral 11, recent thermal history experienced 12, environmental variability 13 as well as the composition of the symbiotic algae and bacterial communities associated with the coral holobiont 14–19. The plastic physiological capacity and potential for genetic re-organisation (for example symbiont shuffling) within all members of the symbiosis is highlighted by increased tolerance. We must add empirical data on thermal thresholds and optima across multiple species to improve empirical models of coral tolerance and projected responses to climate change. Quantitatively establishing the effects of a range of temperatures on coral performance will play a significant part in understanding holobiont thermal tolerance.

Genetic management efforts are being considered to protect coral populations threatened by ocean warming20,21. Coral restoration practises have previously focused on increasing coral cover at local scale22,23 but there is now a push to investigate large-scale interventions that include genetic approaches to facilitate adaptation to temperature24. Some of these rely on standing genetic variation in naturally adapted coral populations as seeding material; either through direct movement or through interbreeding referred to as Assisted Gene Flow (AGF)25. AGF efforts rely on increasing the frequency of beneficial alleles within the receiving population either through managed translocation of adult individuals or selectively breeding tolerant individuals into the population 26. In corals, AGF can be achieved by interbreeding surviving corals from the northern GBR which have survived a severe bleaching event with corals from cooler yet warming reefs further south21. This could introduce heat-resistant genes into the southern populations if observed tolerance has a genetic basis and is heritable. Given annual spawning and longevity of corals, the transplantation of colonies into receiving populations could benefit the recipient population for decades25. The benefits of AGF are minimised if transplanted coral genotypes cannot successfully cope with the thermal regimes in the receiving populations27. Tolerant populations or individuals must be located to serve as sources of thermally tolerant genetic material. This can be achieved by assessing thermal tolerance and plasticity on multiple reefs across the GBR and correlate the locations of tolerant populations with environmental covariates such as thermal history. The success of AGF and other management interventions relies on understanding local adaptation to thermal environments and potential trade-offs between physiological traits underpinning organism fitness.

Organisms employ two main strategies for responding to climate change; acclimation and/or adaptation. Acclimation describes a change in phenotype as a response to short- and long-term perturbations experienced by an organism within its lifetime28,29. If the environmental changes are substantial enough, the changes result in a mismatch between phenotype and the environment, causing a disruption of homeostasis which affects overall organismal fitness. Phenotypic plasticity (PP), an acclimation response, allows organisms to deal with immediate environmental changes 30–32. For example, barnacles respond to water movement by developing feeding appendages of variable lengths33. Corals may respond to environmental changes by shuffling their symbiont composition14,34 . While several studies have documented rapid acclimation potential in corals 14,35, PP has largely been overlooked in efforts examining short-term physiological acclimation in corals in response to temperature changes. Determining the capacity for PP between coral populations is important for predictive modelling to understand corals’ future under warming scenarios.
Adaptation requires selection pressures on populations to shift frequencies of better-suited genotypes over generations. Hence, increasing thermal tolerance through adaptation will require standing genetic variation generated through mutations within the genome or by neutral effects such as genetic drift and gene flow between populations. High genetic diversity is a common characteristic of coral populations 36 and several traits tend to show high heritability (Table 1). The presence of heritable genetic variation may lead to local adaptation of coral populations in which populations over time have matched their environmental regimes, for example in response to temperature35,37,38, acidity39, and reef habitat40. These studies highlight the potential for local adaptation in corals, an important consideration for the development of novel management methods that seek to facilitate tolerance and/or adaptation through seeding or movement of individuals with enhanced tolerance. However, we do not have a comprehensive understanding of the level of local temperature adaptation across the GBR.

Table 1. Quantitative studies in corals within a population with regards to climate change scenarios.
Reference Species Trait Broad-sense
heritability
H2 Narrow-sense
heritability
h2
Meyer et al. 2009
Acropora millepora LA - 0.49
GE - 0.38
Császár et al. 2010
Acropora millepora GE 0.06-0.18 -
GR 0.19-0.59 -
Dixon et al. 2015
Acropora millepora SU 0.87 -
Baums et al. 2013
Acropora palmata RE/LA - 0.38 ± 0.18
Kenkel et al. 2015
Porites astreoides LA 0.27-0.30 -
SU 0.94 -
Dziedzic et al. 2019
Orbicella faveolata BR - 0.58
Kirk et al. 2018
Platygyra daedalea SU - 0.487-0.748

Traits: GR, growth; SU, survival; LA, larvae growth/settlement; GE, gene expression; RE, reproduction; BR, bleaching response

Thermal performance curves (TPCs) are a classic tool used in biology to quantitatively define the temperature ranges of organisms and thus the plasticity in physiological traits 48. TPCs show organismal performance over a wide range of temperatures and assume similar shapes across organisms; an asymmetrical bell-shape where performance rapidly decreases as temperatures approach either extremes49,50 (Fig.1). Performance metrics used to construct TPCs must relate directly or indirectly to overall organismal fitness50,51. The link between performance metrics and organismal fitness have only been established for a few traits in a couple of species, such as swimming speed in tadpoles52 and locomotor activity in fruit flies53, and therefore presents and important consideration for TPC experiments.

In corals, responses to heat have been more widely studied than responses to cooler temperatures. This focus is in part justified by the projected increases to mean ocean temperatures under climate change scenarios however, it neglects the effects of increasing temperature variability, the interval between thermal anomalies, and the intensity of these changes. Corals in Florida experienced a severe cold anomaly in 2010, leading to widespread bleaching and mortality 54–56 while corals on the GBR experienced back-to-back bleaching in 2016/2017 resulting from increased thermal variability and increased frequency of marine heat waves, respectively. Severe cold and heat events demonstrate the need to understand the ability of corals to cope with thermal stress across the entire thermal spectrum. Commonly, experiments that investigate coral thermal tolerance have not included a thermal treatment range sufficiently wide to make inferences about performance across the environmental temperature range experienced on reefs. Experiments have generally compared one elevated treatment to a control with only a few incorporating between three and five temperatures. Hoey et al (2016) constructed TPCs based on data collected by Jokiel & Coles, 1977 on growth and reproduction in Pocillopora damicornis57. However, the shape of the curve could be accurately resolved from only four temperature treatments. Recently, TPC experiments were conducted at three locations across the GBR by Jurriaans & Hoogenboom (2019) to investigate thermal responses across latitudes. Innovatively, the experiments included 10 temperature treatments and three coral species58. The results were based on short (1day) thermal exposures with few physiological responses quantified but none the less showed consistent differences in TPCs across the latitudinal gradient as would be expected based on literature from other organisms59–61. To properly fit and analyse TPCs it is important to include multiple temperature treatments, moving away from the standard of one elevated and one control treatment.
Trade-offs between physiological traits within individuals may impede organismal performance and fitness in variable environments. In model organisms, studies have shown that heat-tolerant individuals of the fruit fly Drosophila melanogaster were detrimentally cold-sensitive 62. Whether heat-resilience confers decreased cold tolerance in corals remains to be seen. A recent study of coral tolerances has highlighted that individuals which were resilient to one stressor (heat stress) also tended to show resilience to other stressors examined (acidification and/or bacterial challenge) 63, supporting a Jack-of-all-trades hypothesis64,65. Other physiological trade-offs, such as skeletal quality66, growth67 and metabolism changes68, also have important implications for coral performance. It is necessary to quantitatively establish TPCs for a range of coral physiological metrics across species to examine the presence of trade-offs which may impact organismal performance and overall fitness.

While utilising TPCs to obtain a wide-spectrum of information about organismal responses to temperature exposure is crucial, it is currently not feasible to conduct these experiments on more than a few species from single or a few locations. TPC experiments require finely-controlled temperature treatments which are logistically challenging and confined to high-technology aquarium systems. To overcome these logistical challenges, acute heat stress assays are gaining traction as a means of assessing thermal plasticity and capacity in the field with high biological replication 69–71. While these assays employ fewer treatments, the mobility of the system allows greater access to diverse coral populations. The scientific community would be able to share and compare results more readily if a standardised, global approach to heat stress assays was developed.
While the benefits of acute heat stress assays are clear, it is not known how acute thermal responses of corals scale with exposure duration. Short exposure times do not account for time-dependent costs of acclimation and maintaining performance under increased thermal stress while long exposure times allow assessment of acclimation capabilities 60,72. It is therefore unlikely that the two experimental approaches will yield similar absolute thermal thresholds. The relationship between acute and chronic thermal responses need to be investigated to fully understand the benefits and potential costs associated with acute heat stress assays, especially in the context of using these assays to rapidly identify coral populations characterised by high upper thermal tolerance.

The IPCC special report on oceans and cryosphere forecasts a decrease in marine animal biomass, community and species composition shifts, with the greatest magnitude of changes occurring in the tropics. The continued survival of coral reefs as they look today is already at risk73 and this risk is projected to transition to very high even if global climate warming is constrained around 1.5oC 1,6. The report also highlights that fragile ecosystems such as coral reefs will benefit from protection, restoration and carefully-considered management actions with approaches targeting adaptation already projected to significantly lower climate risks locally 1. The success of such genetic management approaches hinges on a clear understanding of the physiological and genetic mechanisms that underpin thermal tolerance and possible trade-offs. The overall project objective is to examine the relationship between coral genotypes, phenotypes and their thermal environments to increase our understanding of thermal adaptation, variability in thermal tolerance, and identify physiological trade-offs associated with increased thermal tolerance.

To address this objective, the specific aims of the project are as follows:
• Aim 1 - Assess growth and survival of two coral species across multiple temperatures.
• Aim 2 - Construct thermal performance curves and identify physiological trade-offs associated with increased thermal tolerance.
• Aim 3 – Assess patterns of natural variation and phenotypic plasticity in thermal tolerance between species, populations and latitudes by quantifying upper heat tolerance across the GBR and identify coral populations ideal for selective breeding initiatives by correlating patterns of thermal tolerance to environmental parameters.
• Aim 4 – Compare upper thermal tolerance results from classic, long-term temperature exposure experiments with acute heat stress experiments.
• Aim 5 – Evaluate genetic mechanisms underlying thermal tolerance by correlating pre-stress gene expression to heat-stress and recovery phenotypes to identify gene expression signatures of tolerance.
Addressing these aims and fulfilling the overall project objective will increase our understanding of the potential for genetic adaptation in corals and allow us to better assess the feasibility of AGF initiatives on the GBR, a key method under investigation to help corals adapt to increasing temperatures. Taken together, this project will greatly increase our current understanding of the physiological, environmental and genetic correlates of coral thermal tolerance.

Section word count: 2161

Project Methods

Aim 1 - Assess growth and survival of two coral species across multiple temperatures.
This study will expose corals to a wide range of temperature treatments to test the following hypotheses:
• Corals will have asymmetric response curves; there will be greater declines in growth and survival in response to heat stress than to cold stress.
• Maximum survival and growth will track ambient temperature ranges and widths will reflect ambient temperature variability
Sample collection and experimental design
An aquarium-based experiment will be conducted in the National SeaSimulator Facility (AIMS) to quantify physiological performance across a 16oC temperature range for two common coral species from the central GBR (Acropora tenuis and Pocillopora verrucosa). Corals will be collected from central reefs in the Townsville region during a fieldtrip in March 2020. Corals will be brought back to SeaSim where they will be fragmented (n = 35 per genet) and allowed to acclimatize for ~3 weeks. Pre-exposure samples will be taken for each individual to determine Symbiodiniacaea community composition. Long-term temperature data for the collection reef will be accessed to determine the environmental thermal regime corals will naturally experience. This data will be used to determine the treatment range which will include each extreme temperature recorded ± 4oC to reach lethal limits. Replicate fragments will be distributed between experimental temperature treatments (likely 16 - 34OC, every 2oC) and tanks (three per treatment) and maintained at treatment for two months. I will include every degree in a 4oC range likely between 24 - 280C rather than every 2 degrees to fully elucidate responses around the mean environmental temperatures where higher resolution is required. Treatments will be designed to ramp slowly to allow corals to acclimatise, while reflecting naturally-occurring temperature changes. Additionally, the treatment temperatures will incorporate diurnal variation of ±0.25 - 0.5oC to mimic reef conditions as this is known to affect coral performance74.

Sample and statistical analysis
Data will be collected on growth and survival during the experiment using non-destructive methods (Table 2). General linear mixed effect models (GLMMs) will be used to statistically test the effects of temperature treatment (independent variable) on coral growth and survival percentage (dependent variables), with species as a fixed effect and genet and tank allocation as random effects. Tukey’s HSD post hoc analysis will be used to identify which treatments were significantly different to one another with a Bonferroni adjustment of the accepted significance level 75,76. If responses to thermal stress do not differ significantly between coral populations from different environments, it is likely due to PP77,78. However, significantly different physiological responses to thermal stress between populations could indicate an underlying genetic cause45.

Result interpretation
Tolerance will be interpreted in terms of probability of survival as a function of temperature51. Colonies will be ranked according to their tolerance with those exhibiting the highest survival probability across the widest thermal range scored as the most tolerant individuals. The colonies which record the lowest survival across the narrowest thermal range will be scored as the most susceptible to thermal stress. Upper and lower lethal limits will be established from these results. Growth is considered a good indicator of organismal fitness in coral79and will be used as a performance metric to construct a TPC. As growth links directly to fitness in coral (larger size = larger reproductive output), the higher growth, the better performance. Performance breadth, performance maintained above 80%59, will be determined from this curve.

Aim 2 – Construct thermal performance curves and identify physiological trade-offs associated with increased thermal tolerance.
This study will use data generated under Aim 1 to assess the presence of trade-offs through multiple regression analyses and will test the following hypotheses:
• Coral genets that show high performance under higher temperatures show decreased performance under colder temperatures and vice versa.
• Trade-offs exist between physiological traits such that coral genets that show high performance in one trait in response to a given treatment will exhibit low performance in another trait within treatments.
Experimental design and statistical analysis
This aim will be fulfilled by the experiment described for aim 1. During the experiment, photosynthesis efficiency, respiration, and calcification will be evaluated using non-destructive methods (Table 2). Coral fragments will then be snap-frozen in liquid nitrogen for later laboratory analyses of common coral performance metrics (Table 2). The effect of treatment on physiological metrics of performance will be tested using GLMMs. TPCs will be constructed based on models presented by Angilletta, (2009) using the Johnson-Lewin function to account for expected model assymetry60 and incorporating recommendations from Sinclair et al., (2016). Physiological metrics which were significantly affected by treatment temperature will be correlated to one another using multiple linear regression analyses76. Thermal tolerance will be interpreted based on the performance recorded for each trait and its desirable state outlined in Table 2.
Aim 3 - Assess patterns of natural variation and phenotypic plasticity in thermal tolerance between species, populations and latitudes by quantifying upper heat tolerance across the GBR and identify coral populations ideal for selective breeding initiatives by correlating patterns of thermal tolerance to environmental parameters.
This study will undertake field-based acute heat stress assays on two species of corals (Acropora tenuis and Pocillopora verrucosa) from 20 reefs using a mobile temperature manipulation tank system to test the following hypotheses:
• Sampling time post onset of heat-stress influences physiological responses.
• The size of the coral fragment used in the experiments does not influence acute heat tolerance.
• Upper heat tolerance will be correlated to environmental thermal regimes.
Experimental design
Experiments will be conducted in the field with the first cruise targeting the far northern GBR (Thursday Island to Lizard Island Nov 22nd 2019 – Dec 15th 2019). The southern sector (Swains and Capricorn Bunker group) will be visited between Jan 2nd 2020 and Jan 23rd 2020. Samples (n = 20 genets per species) of 2 target species (Acropora tenuis and Pocillopora verrucosa) will be collected on SCUBA between 4 - 8m, returned to the vessel, fragmented into four replicates, and distributed across four temperature treatments. Using the mean monthly maximum temperature (MMM) as a control, the treatments are MMM + 3oC, MMM + 6oC, and MMM + 9oC, respectively. The treatment profiles are described in Fig. 2. Two proof of concept experiments will also be undertaken to examine the effects of sampling time post heat exposure (A. tenuis only) and the effect of fragment size on upper thermal tolerance (A. tenuis and P. verrucosa).








Data collection and analysis
Photosynthesis efficiency will be quantified by Pulse Amplitude Fluorometry (PAM)80,81 after a 1 hour low light (max 100 µmol m-2 s-1) incubation at ambient temperature. Following an 11h hold at ambient temperature, samples will be photographed, any mortality recorded, and frozen in liquid nitrogen for later physiological and genetic analyses. The physiological assays undertaken for these samples will be similar to those outlined for aim 2 (Table 2). Environmental data (temperature mean, max, min, and variability, turbidity, salinity) will be obtained from eReefs for each 5km2 quadrat encompassing each reef to correlate thermal tolerance to environmental parameters. I will use spatial generalised linear mixed models82 to account for spatial autocorrelation using CARBayes83 R package.

Aim 4 – Compare upper thermal tolerance results from classic, long-term temperature exposure experiments with acute heat stress experiments.
This study will compare physiological responses to long-term and acute temperature treatments to test the following hypothesis which will validate the acute heat stress approach outlined above:
• The two experimental approaches (acute vs long-term) will identify the same resilient genotypes, however their upper thermal tolerance will differ between approaches.
To address this aim, it is necessary to subject the same coral colonies to acute heat stress experiments and long-term chronic exposure. This aim will utilise the same colonies that were used to address aims 1 and 2 as it is not possible to perform the thermal performance curve experiment more than once due to the logistical constraints. When corals are collected for aims 1 and 2, I will conduct an acute heat stress trial in the field onboard the research vessel immediately following collections. The details of the acute heat stress assays are described under aim 3. This ensures comparability between acute heat stress assays which would potentially be compromised if the acute heat stress assays are not performed until the colonies are returned to SeaSim.

Data collection and analysis
Results from aims 2 and 3 will guide selection of physiological parameters to quantify for this aim. Photosynthesis efficiency along with chlorophyll content and Symbiodiniaceae cell densities will be analysed to account for changes occurring within the symbionts9. Host protein and antioxidative enzyme activities84 will be compared between experimental approaches to examine coral responses. All results will be statistically examined using Wald’s tests with experimental approach as a fixed effect.

Aim 5 - To evaluate genetic mechanisms underlying thermal tolerance by correlating pre-stress gene expression to heat-stress and recovery phenotypes to identify gene expression signatures of tolerance.
This study will rely on field-based assessments of acute thermal tolerance to address the following hypothesis:
• Pre-disturbance gene expression profile can predict stress and recovery phenotypes.
Experimental design, data collection, analysis and interpretation
I will select one A. tenuis population (15 genets, one reef) for this study from those assayed under Objective 2 (Fig.3). The selection will be based on the variability of heat stress phenotypes exhibited following acute heat stress and aims to include a population showing a wide range of phenotypes. RNA will be extracted from 45 samples following Kenkel et al (2014) using the RNAqueous kit (Ambion, Life Technologies)85,86 and then DNAse treated to eliminate DNA contamination. Library preparation will be performed in house, preparing samples for Tag-based RNA Seq87. Data analysis will follow the methods described in Wright et al 2017. Briefly, the returned reads will be trimmed, PCR duplicates removed, and quality filtered88 before being mapped to the reference transcriptome. Mapping will use the R package bowtie289 and reads will then be converted to unique transcript counts (UTCs) prior to analysis. Differential gene expression analysis will be performed on these values using the DESeq2 R package90 and gene expression heatmaps produced with the R package pheatmap91 with hierarchical clustering of expression profiles. As no single gene seemingly confers clear thermal tolerance effects46,47,71,92, interpretation of gene expression data will rely on identifying expression modules, groups of genes which are co-expressed differently under thermal stress93 and control conditions.









Section word count including table 2 on next page; 1951

Trait Sampling method Trait level Fitness link Desired state indicative of tolerance Reference for methodology
Survival Observation Holobiont Direct; fitness only applicable to live coral As high as possible Anthony et al., 200794

Photosynthesis efficiency Non-destructive Symbiodiniaceae Indirect; measure of energy conversion, energy for growth and/or reproduction The higher the better, must avoid overproduction of reactive oxygen species (ROS)95
Nitschke et al., 201881

Growth
Non-destructive Holobiont Direct; relationship between size and reproductive output79
The higher the better Davies, 198996
Pratchett et al., 201597

Respiration/photosynthesis
Calcification Non-destructive Holobiont Indirect; energy for conversion and skeletal growth mechanism The higher the better Strahl et al., 2015 98

Symbiodiniaceae density Destructive Symbiodiniaceae Indirect; potential for energy capture The higher the better; trade-off with chlorophyll content Krediet et al., 201599

Chlorophyll content Destructive Symbiodiniaceae Indirect; photosynthesis and energy harvesting100
The higher the better; trade-off Symbiodiniaceae density Ritchie, 2006101

Protein content Destructive;
Bio-Rad DC protein assay Coral host Indirect; greater energy reserves to survive thermal stress The higher the better102
Tolosa et al., 2011103

Antioxidative enzyme activity Destructive Coral host Indirect; indicator of thermal stress The higher the better, more potential to combat ROS104
Krueger et al., 2015105

Metabolomics Destructive Coral host Indirect; quantification of energetics. Changes detected between control and thermally-stressed corals Hillyer et al., 2018106; Sogin et al., 2016107

Project Results

I have undertaken initial trials with the field-deployed acute heat stress system, testing the system and practicality in the field and the underlying method/principle under aquarium conditions at the SeaSim.
In the field, I conducted a couple of proof-of-concept studies examining the effect of coral fragment size and the effect of sampling time point post heat stress on the thermal physiological responses of two species; Acropora tenuis and Pocillopora damicornis. While sample processing and data analysis is still ongoing, I found that Symbiodiniaceae cell density changed markedly with regards to post-heat sampling time point (Fig. 4). The difference between the control corals (ambient temperature) and the high-treatment corals (35.3oC) became pronounced 9h after the end of heat exposure. This pattern is also reflected in chlorophyll content (Fig. 4). Preliminary investigation of photosynthesis efficiency data however, does not show a similar pattern across the first 4 time point (data not shown).

I also completed a similar experiment conducted in the National Sea Simulator, aiming to validate the acute heat stress principles. I monitored coral growth over time (5 weeks) in response to four heat treatments (30, 32, 34, and 35.5oC) with short-term durations (6h). A. tenuis fragments were weighed prior to the 6h heat treatment and again 10 days and 5 weeks post treatment. Interestingly, both the 30oC and 32oC treatments resulted in increased weight gain detectable 10 days after heat exposure relative to ambient-treated corals whereas corals exposed to 34oC over just 6h recorded growth reductions (Fig 5).

Keywords

Biostatistics,
Climate change,
Controlled Environment,
Coral reefs,
Corals,
Field based,
Genetics,
Management tools,
Manipulative experiments,
Molecular techniques,
Ocean warming,
Physiology,
Temporal change