Data from: Natural thermal stress-hardening of corals through cold temperature pulses in the Thai Andaman Sea
Data files
Feb 13, 2024 version files 8.53 MB
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EnvPriming_data.zip
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README.md
Abstract
Stress-hardening by environmental priming could increase the odds for corals to resist ocean warming. Natural environmental fluctuations, such as those observed on offshore reefs in the Andaman Sea, provide an ideal natural environment to study these effects. Here, internal waves (IW) generate short cold-water pulses that peak from January to June and are absent from August to November. Additionally, only western shores of islands are exposed to this stress-hardening stimulus of IWs, while eastern shores remain sheltered. Therefore, this study examined (1) whether exposed corals were more heat stress resistant than their sheltered conspecifics and (2) whether this trait would persist during the season of stimulus absence. We exemplify that thermal regimes featuring cold-temperature pulses successfully induced thermal stress-hardening in corals. Corals from the IW-sheltered shore responded strongly to heat stress irrespective of the season, while stress responses of IW-exposed corals were either undetectable (during stimulus presence) or very weak (during stimulus absence). However, this demonstrates the relevance of stimulus re-occurrence in maintaining heat resistance. Furthermore, priming stimuli do not need to exceed certain upper thermal thresholds to be effective and we argue that cooling pulses represent a safer stress-hardening regimen potentially implemented in conservation strategies since it avoids warming-stress accumulation.
README: Natural thermal stress-hardening of corals through cold temperature pulses in the Thai Andaman Sea
https://doi.org/10.5061/dryad.c866t1gd1
Description of the data and file structure
This dataset includes all data for the manuscript "Natural thermal stress-hardening in corals: Cold-water pulses boost heat resistance" by Wall M./Roik A. et al. which investigated the phenomenon of stress-hardening through environmental priming in corals during two distinct seasons. Data were collected at the Andaman Sea coast of Thailand.
This data collection contains environmental data (temperature °C, HOBO Pendant Temperature/Light 8K Data Logger, Onset, USA), coral bleaching score data (decline of coral tissue coloration, assessed as established in Siebeck et al., 2006), and the effective quantum efficiency (yield Φ PSII, pulse amplitude-modulated fluorometer Diving-PAM, Walz, Germany).
The two latter variables are metrics that capture the coral stress response and were assessed during short-term heat stress assays (the mothofology is also described in details in Doering et al. 2021).
The stress response data were the delta values of pre-heat stess and post-heat stress measurements. The stress response data were analyzed comparing between reef sites of origin and seasons using effect sizes (following the instruction to the R package dabestR v0.2.3 6 (Ho et al., 2019)).
Additionally, linear-Model based analyses were conducted with the response data (following instructions in the package nlme v4 3.1-148 and lme4 v1.1-23, R).
All analyses were performed in R studio. Visualizations were generated via ggplot2 and assembled in Adobe Illustrator. These figures are also shared herein.
DATA FILE STRUCTURE
EnvironPrim_Data.tar.gz
EnvPriming_ReadMe.md
---EnvPriming_data
+---Data
| Input_Data_delta_BSC.xlsx # Input data for downstream analyses. Contains the delta values of bleaching score averages calculated from the max. and min. values recorded at each asesssement time point. Delta values are mostly negative, i.e. = indicating coral bleaching and delcining health = stress response; the data is organzsed into 4 tabs by coral species and season; ; All acronyms in the headers and tabs are explained in the LEGEND SECTION below
| Input_Data_delta_PAM.xlsx # Input data for downstream analyses. Contains the delta values of the effective quantum efficiency (yield Φ PSII) measured by a diving-PAM (pulse amplitude-modulated fluorometer); the data is organized into 4 tabs by coral species and season; All acronyms in the headers and tabs are explained in the LEGEND SECTION below
| Rawdata_BSC.xlsx # Original collected data (transcript from underwater proof field sheets). Contains bleaching scores recorded during the heat stress assays, see score scala by Siebeck et al., 2006 (we use internsity scores 1-6). At each assessment the minimum and the maximum score of a fragment were recorded; All acronyms in the headers and tabs are explained in the LEGEND SECTION below
| Rawdata_PAM.xlsx # Original collected data (transcript from underwater proof field sheets). Contains effective quantum efficiencies (yield Φ PSII) measured by a diving-PAM (pulse amplitude-modulated fluorometer); At each assessment the 3 measurements per coral fragment were recorded; All acronyms in the headers and tabs are explained in the LEGEND SECTION below
+---Effectsizes_output
| Fig_3_CB.tif # calculated effect sizes from dabestR are represented along a color gradient in this heatmap
| Fig_4_CB.tif # this figure is a composition of all "Cumming estimation plot" from dabestR sorted by coral species and season
| Fig_3-4_Tables.xlsx # the tabs contain: TAB1) raw output from the dabestR analyses (bleaching score data); TAB2) raw output from the dabestR analyses (diving-PAM data); TBA3) the output from Tab1) and Tab2) organized in a summary table; TAB4)summary table form Tab3) rearranged for plotting the values in heatmaps
| Fig3_Rcode.html # R code produces the elements for the heatmap in Fig_3, R code, versions and results
| Fig4_Rcode_bsc.html # R code for dabestR conducted with bleaching score data, R code, versions and results
| Fig4_Rcode_pam.html # R code for dabestR conducted with diving-PAM data, R code, versions and results
+---LMs_output
| Rcode_MixedModels_bsc_poc_apr_Sep2021FinalV1.html # Statistical analysis of delta-bleaching score , R code, versions and results
| Rcode_MixedModels_bsc_poc_nov_Sep2021FinalV1.html # Statistical analysis of delta-bleaching score , R code, versions and results
| Rcode_MixedModels_bsc_por_apr_Sep2021FinalV1.html # Statistical analysis of delta-bleaching score , R code, versions and results
| Rcode_MixedModels_bsc_por_nov_Sep2021FinalV1.html # Statistical analysis of delta-bleaching score , R code, versions and results
| Rcode_MixedModels_pam_poc_apr_Sep2021FinalV1.html # Statistical analysis of Delta-Y (effective quantum yield), R code, versions and results
| Rcode_MixedModels_pam_poc_nov_Sep2021FinalV1.html # Statistical analysis of Delta-Y (effective quantum yield), R code, versions and results
| Rcode_MixedModels_pam_por_apr_Sep2021FinalV1.html # Statistical analysis of Delta-Y (effective quantum yield), R code, versions and results
| Rcode_MixedModels_pam_por_nov_Sep2021FinalV1.html # Statistical analysis of Delta-Y (effective quantum yield), R code, versions and results
+---Temperature
| Fig_2_CB.tif # Timeseries plot of temperature records from the study sites; created in R environment
| Input_Data_Temperature.xlsx # In situ temperatures in the study sites RE and RW (one site presented per tab) recorded in Celsius using HOBO Pendant loggers
| Fig_2_Rcode_Temperature.R # R Code that generates Fig_2, R code, versions and results
LEGEND
POC = Pocillopora sp. (coral species)
POR = Porites sp. (coral species)
season 1 = April 2018 (season of internal waves peak)
season 2 = November 2018 (season of internal waves absence)
apr = April
nov = November
site = study site / reef location where corals were collected
RW = Ko Racha West Shore 7.595530°N, 98.354320°E
RE = Ko Racha East Shore 7.598910°N, 98.373100°E
treatment = temperature exposure treatment of the short term heat stress assays (also see Doering et al. 2021)
A = ambient temperature treatment of 29 °C (control treatment)
H = heat exposure of 34 °C
colony = indicated the coral colony number
N = Replicate number
tank = Experimental tanks "A1", "A2", "H1", "H2"
deltaBSCboth = delta values of pre-heat and post-heat bleaching score measurements
deltaY = delta values of pre-heat and post-heat measurements by PAM (i.e., effective quantum efficiency (yield Φ PSII) measured by a diving-PAM, pulse amplitude-modulated fluorometer)
Y 1-4 = technical replicates of effective quantum yield measurements Y1, Y2, Y3, Y4 (diving-PAM)
NA = value not available
HM = heatmap
IW = internal waves
LMs = Linear Models
PAM = pulse amplitude-modulated fluorometer
Timestamp = date and time of temperature record from the HOBO Pendant loggers dd/mm/yy hh:mm
Temperature = recorded in situ temperatures in Celsius
REFERENCES
Doering, T., Wall, M., Putchim, L., Rattanawongwan, T., Schroeder, R., Hentschel, U., & Roik, A. (2021). Towards enhancing coral heat tolerance: a “microbiome transplantation” treatment using inoculations of homogenized coral tissues. Microbiome, 9(1), 102. https://doi.org/10.1186/s40168-021-01053-6
Ho, J., Tumkaya, T., Aryal, S., Choi, H., & Claridge-Chang, A. (2019). Moving beyond P values: data analysis with estimation graphics. Nature Methods, 16(7), 565–566. https://doi.org/10.1038/s41592-019-0470-3
Siebeck, U. E., Marshall, N. J., Klüter, A., & Hoegh-Guldberg, O. (2006). Monitoring coral bleaching using a colour reference card. Coral Reefs, 25(3), 453–460. https://doi.org/10.1007/s00338-006-0123-8
Authors:data preparation and data curation
Dr. Marlene Wall, https://orcid.org/0000-0003-2885-1301
Dr. Anna Roik, https://orcid.org/0000-0002-8293-8339
Sharing/Access information
The original preprint can be accessed from here: https://www.biorxiv.org/content/10.1101/2023.06.12.544549v1
Supplementary material can be downloaded here: https://www.biorxiv.org/content/10.1101/2023.06.12.544549v1.supplementary-material
Methods
Study sites and coral collection
Study sites were located at Racha Island in the Andaman Sea off the coast of Thailand, both at 15 m water depth (Figure 1 A-B). A reef on the western shore was chosen (7.595530°N, 98.354320°E, Figure 1 B) where internal wave (IW) forcing as a potential stress-hardening stimulus induced environmental variability through frequent upwelling of deep, cool, and nutrient rich water onto the shelf (Schmidt et al., 2016; Wall et al., 2012). A reef on the eastern shore, sheltered from the stimulus of IWs, was chosen to represent a low variability reef (7.598910°N, 98.373100°E, Figure 1 B). Temperature fluctuations were monitored in situ as a proxy for IW impact and environmental variability. Temperature loggers (HOBO Pendant Temperature/Light 8K Data Logger, Onset, USA) were deployed at the study sites one month before heat stress assays were performed. At each study site, visually healthy coral colonies of Pocillopora sp. and Porites sp. were permanently tagged to assess their thermal resistance levels during the two seasons (n = 8 to n = 18, Figure 1 C, Table S1). These two coral species are cosmopolitan reef-builders in Thailand and within the entire Indo-Pacific region (Brown & Phongsuwan, 2012; Jain et al., 2023; Schmidt et al., 2012). Coral fragments were collected at the end of April 2018, during the season of highest IW intensity, and at the end of October (Porites sp.) and November (Pocillopora sp.), during the seasonal absence of the IW stimulus. Two fragments (Porites sp.: ø ~ 6 cm; Pocillopora sp.: length ~ 5 cm) per colony were collected using a chisel and a hammer (Table S1).
Short-term heat stress assays
Collected fragments were instantly transported to the Phuket Marine Biological Center (Phuket, Thailand) where they were maintained in two 500 L flow-through tanks with a flow rate of 2.8 ± 1.31 L/min until the start of each heat stress assay. Another 500 L source tank constantly supplied both flow-through tanks with 5 μm-filtered seawater from the reef adjacent to the research center. Its temperature was held at constant 29.43 ± 0.32 °C using a temperature-controlling device including a chiller and a heater (Titanium Heater 100 W, Schego, Germany; Temperature Switch TS 125, HTRONIC, Germany; Aqua Medic Titan 1500 Chiller, Germany). LED lights (135 W, Hydra Fiftytwo HD LED, Aqua Illumination, USA) mimicked the average light conditions of the sampling sites (Text S1).
For each heat stress assay (Figure 1 D), two 40 L experimental tanks were set up inside each of the 500 L flow-through tanks that were used as temperature-controlling water baths (Table S2). The seawater of all four experimental tanks was supplied by daily, manual 50% water changes from the source tank. Each experimental tank was equipped with a temperature-controlling device, one heater, air supply, a small current pump and a temperature logger (Temperature Switch TS 125, HTRONIC, Germany; Titanium Heater 100 W, Schego, Germany; Koralia nano 900 L/h, Hydor, Italy; HOBO Pendant Temperature/Light 8K Data Logger, Onset, USA). Two coral fragments per coral colony were randomly distributed among the four tanks “34 °C” (n = 2) and “29 °C” (n = 2), resulting in one fragment per colony per treatment. The 34 °C-treatment was established over the course of one day by ramping temperatures from 29 °C to 34 °C for 4 h, holding at 34 °C for 5 h or 6 h (Pocillopora sp.) or for 6 h or 7 h (Porites sp.), and decreasing temperatures to 29 °C within 4 h. After the heat exposure, corals were maintained at ambient temperatures of 29 °C for 10 h until the next day. While Pocillopora sp. fragments were subjected to the short-term heat exposure once, resulting in a 24 h experiment, Porites sp. corals were exposed to the treatment over two consecutive days resulting in a duration of 72 h (Figure 1 D).
Coral stress response variables
We measured two variables that assessed the thermal stress response of each fragment before and after each heat stress assay (timepoints (1) and (2) in Figure 1 D). Tissue coloration, a proxy for microalgal symbiont cell density in coral tissues and therefore an indicator of holobiont health and coral bleaching severity, was assessed using a “bleaching score”. The coloration of each individual fragment was visually categorized on the scale from 1 (bleached, pale tissues) to 6 (healthy, dark tissues) using a coral bleaching chart (Siebeck et al., 2006). A minimum and maximum score was recorded per fragment and averaged. Photosynthetic efficiency of microalgal symbionts was determined by measuring effective quantum efficiency (yield Φ PSII = (Fm’ – F) / Fm’ = ΔF / Fm’, (Genty et al., 1989) of electron transport using a pulse amplitude-modulated fluorometer (Diving-PAM, Walz, Germany).
Statistical analyses
∆-values of each measured thermal stress response variable (end – start of each experimental part) were calculated to reflect their change over time. Based on these ∆-values, effect sizes were estimated using dabestR v0.2.3 6 (Ho et al., 2019). Effects of the high temperature treatment (“Heat” vs. “Ambient”) were compared between the sites of origin (“IW exposed shore” and “IW sheltered shore”) and between the seasons (“Season of IW stimulus presence” and “Season of IW stimulus absence”). Statistical significance was tested in R (R Core Team, 2013) using linear mixed effect models (nlme v4 3.1-148 and lme4 v1.1-23 package). Where applicable, coral colony genotype was used as a random factor.
References
Brown, B., & Phongsuwan, N. (2012). Delayed mortality in bleached massive corals on intertidal reef flats around Phuket, Andaman Sea, Thailand. Phuket Marine Biological Center Research Bulletin, 48(April 2010), 43–48.
Wall, M., Schmidt, G. M., Janjang, P., Khokiattiwong, S., & Richter, C. (2012). Differential Impact of Monsoon and Large Amplitude Internal Waves on Coral Reef Development in the Andaman Sea. PloS One, 7(11), e50207. https://doi.org/10.1371/journal.pone.0050207
Schmidt, G. M., Wall, M., Taylor, M., Jantzen, C., & Richter, C. (2016). Large-amplitude internal waves sustain coral health during thermal stress. Coral Reefs , 1–13. https://doi.org/10.1007/s00338-016-1450-z
Siebeck, U. E., Marshall, N. J., Klüter, A., & Hoegh-Guldberg, O. (2006). Monitoring coral bleaching using a colour reference card. Coral Reefs , 25(3), 453–460. https://doi.org/10.1007/s00338-006-0123-8
Ho, J., Tumkaya, T., Aryal, S., Choi, H., & Claridge-Chang, A. (2019). Moving beyond P values: data analysis with estimation graphics. Nature Methods, 16(7), 565–566. https://doi.org/10.1038/s41592-019-0470-3
Genty, B., Briantais, J.-M., & Baker, N. R. (1989). The relationship between the quantum yield of photosynthetic electron transport and quenching of chlorophyll fluorescence. Biochimica et Biophysica Acta (BBA) - General Subjects, 990(1), 87–92. https://doi.org/10.1016/S0304-4165(89)80016-9
Jain, T., Buapet, P., Ying, L., & Yucharoen, M. (2023). Differing Responses of Three Scleractinian Corals from Phuket Coast in the Andaman Sea to Experimental Warming and Hypoxia. Journal of Marine Science and Engineering, 11(2), 403. https://doi.org/10.3390/jmse11020403