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Our results show that differences in environmental conditions between inland and coastal sinkholes, caused mainly by the inflow of seawater in the latter, influence the microbial community structure of their sediments. Furthermore, the microbial community structure also varied within the sinkholes and according to the sediment zone sampled, suggesting that a connection between the atmosphere in the outermost location of the sediments and sunlight creates an environment distinct from that found in deeper caves. Together with the different environmental factors that were measured (in situ physicochemical composition of water and sediment) these characteristics could drive niche-specific microbial community structures associated with the sediment zones. Additionally, beta-diversity analysis showed separate clustering of the sediment microbial communities from the coastal and inland sinkholes, and of the WM zone from cavern and cave zones at both sinkholes. Microbial community structure associated with karst environments have shown to be significantly influenced by environmental factors as seen in the Bahamian blue holes19, a coastal sinkhole13, a Floridan anchialine sinkhole20, and sediments from Chinese karst caves21.Microbial communities from karst sediments can be limited by nutrients such as carbon, phosphorus, and nitrogen21, therefore, influencing their structure. Differences in the microbial community composition associated with multiple environmental factors (moisture, type of niche, nitrogen) were also reported in karst cave sediments from China21. Previous studies had shown there was no effect on the alpha diversity of water column assemblages in the Yucatan groundwater associated with the type of sinkhole (inland or coastal)6. However, this observation may be limited due to the low sample number used in the study6. For other karst sinkholes, the microbial community dynamics differ between the water column and the sediments6,22,23,24.The karst caves and sinkholes of the underground river in Yucatan are characterized by low phosphorus concentrations and high levels of nitrate, mostly related to Anthropocentric activities (urban developments, farms and agriculture)3. The inland sinkhole at Noh Mozón showed the highest concentration of nitrate detected in the study and, not surprisingly, the area is surrounded by agricultural fields. The presence of organic matter in the sinkholes from the Yucatan peninsula are highly dependent on the connection between the cave systems, on the levels of exposure to light, and on their morphology3. High concentrations of organic carbon (661 ± 132 μM) and methane (6466 ± 659 nM) have been reported in the top layer of the water masses in coastal sinkholes before13. In this study, the highest concentration of organic carbon was observed in the sediments from the coastal sinkhole, likely originating from the surrounding vegetation and from seawater intrusion. We hypothesize that the differences in nutrients found at these two types of sinkholes influence the structure of their microbial communities.Other environmental factors such as pH and dissolved oxygen (DO), may also contribute significantly to the composition and structure of microbial communities, as seen in freshwater lake sediments22. Davis and Garey20 reported distinct microbial communities with unique functions for each water layer from an anchialine sinkhole from the Florida karst aquifer and suggested that this occurred as a result of the influence of the hydrochemistry, including differences in the concentration carbon and other nutrients from the environment20. Analyses of the sinkhole caves from the Yucatan underwater river support observations that physical and chemical parameters create distinct ecological niches which host unique microbes, as a high abundance of exclusive (not shared) ASVs were observed in the three sediment zones at both locations.The taxonomic diversity from the coastal and inland sinkholes included Chloroflexi, Crenarchaeota, Desulfobacterota, Proteobacteria, Nitrospirota, Bacteroidota, and Firmicutes as the most abundant phyla in the sediment samples, however, there were differences in the relative abundance associated with the type of sinkhole and sediment zone. Some of these phyla (Chloroflexi, Proteobacteria, and Bacteroidetes) have been reported in sediments from freshwater karst sinkholes from Lake Huron25 in water and sediments from other sinkholes in the Yucatan peninsula6, and in the karst caves bacteriome from southwest China21. A study that included coastal marine sediments from two sites in the Yucatan peninsula, showed high abundances of Spirochaeta, Desulfococcus, Clostridium, Psychrobacter26, four genera that were abundant in the coastal sinkhole. However, Desulfococcus, Synechococcus were also abundant in the inland sinkhole. Of the most abundant genera reported for sediments from different marine environments in the Yucatan coast23, Acinetobacter, Desulfotignum, Desulfovibrio, Pseudomonas, Sedimenticola, and Sulfurimonas were also present in the coastal sinkhole while only Pseudomonas and Sedimenticola were also present in the inland sinkhole23. The high number of families shared between the coastal sinkhole and marine sediments from the Yucatan coast, together with the salinity levels registered at the bottom layer of the water column in the coastal sinkhole, suggest an interconnection between these two environments which shapes the microbial communities present in the sediments of caverns and caves of this sinkhole. The genus Nitrospira was abundant in the WM from the coastal sinkhole and in all sediment zones from the inland sinkhole. This genus has been reported as one of the most abundant in the surface of speleothems from El Zapote coastal sinkhole2, and is considered a complete ammonia oxidizer (comammox), meaning it converts ammonia to nitrate through nitrite. A negative correlation between abundance of this genus and salinity has been reported before, which could explain the low concentration of Nitrospira in the cavern and cave from the coastal sinkhole, where the highest salinity was observed27. Connectivity between coastal sinkholes and the ocean, as well as the terrestrial input of soil organic matter (OM) has been reported for the underground karst aquifer in the Yucatan peninsula13. As in other sediments, degradation of OM is carried out by several MFGs including acetogenic bacteria, methanogens, and sulfate reducers13,20,28. When these MFGs were analyzed in coastal and inland sinkholes, differences in their relative abundances were clearly marked by the type of sinkhole and by the sediment zone analyzed, supporting the hypothesis that environmental differences drive microbial community distributions in these niches. The high abundance of sulfate-reducing bacteria (SRB) in the three sediment zones from the coastal sinkhole suggests that sulfate reduction is a predominant function. SRB degrade organic matter using sulfate with sulfide as waste or end-product19,30, originating hydrogen sulfide (H2S)29, which could explain the low concentration of sulfate the hydrogen sulfide (H2S) cloud observed and previously reported in the WM zone of El Zapote coastal sinkhole30. In this study, high levels of sulfate (SO−4) were measured in the water samples from the cavern and cave zones from El Zapote sinkhole, which could be associated with sulfate-rich deposits, such as gypsum beds, which have been reported in other sinkholes from the Yucatan peninsula (up to 2400 mg/L of sulfate concentration)3. However, we do not disregard other possible sources of sulfate, associated with seawater intrusion or as a product of sulfide or sulfur oxidation29,31 by sulfur-oxidizing bacteria detected in this study.The inland sinkhole had a low concentration of sulfate and low abundances of SRB. The high abundance of methanogenic bacteria in the WM zone from the coastal sinkhole detected in the MFG analysis supports the previous hypothesis of acetoclastic methanogenesis due to high inputs of organic matter13. Methylotrophic bacteria were most abundant at the inland sinkhole in the WM zone, suggesting the presence of methyl compounds, such as methane or methanol which can be used as a source of carbon and energy32. High methane concentrations have been quantified in shallow water masses from the Yucatan aquifer system13, consistent with observations from this study. ‘Candidatus Methylomirabilis’ was identified in the sediment of the WM zone from Noh-Mozón and has been previously described as being able to perform nitrite-dependent anaerobic methane oxidation, using methane as electron donor and nitrate and nitrite as electron acceptors33, which would be possible in these sediments considering the low levels of oxygen (average of 2.3 mg/L) detected in the water column above them and assuming this would lead to lower levels of oxygen in the sediments. We hypothesize that bacteria from this genus could be using the nitrite produced by ammonia oxidizing bacteria and archaea observed in this zone (Nitrosomonadaceae, Nitrospiraceae, and Nitrosococcaceae). The low abundance of methanotrophic microbes in the coastal sinkhole (mainly the cavern and cave zones) could be derived from the high concentrations of hydrogen sulfide previously reported at this location, which have been suggested to be toxic to methane-oxidizing microbes34. Therefore, a decrease in the anaerobic oxidation of methane, and a poor methane removal capacity is hypothesized in the sediments from this coastal sinkhole. Further research could focus on the influence of the saline intrusion on methanotrophic microbes and methane levels in El Zapote sinkhole sediments. As expected, photosynthetic bacterial abundances differed with the type of sinkhole and sediment zone. Both sinkholes are so the presence of daylight can start the photosynthetic process which would occur most in the WM zone. However, only the inland sinkhole showed a high abundance of photosynthetic bacteria within its WM zone. The coastal sinkhole water column and sediments would be deprived of photosynthetic bacteria since the water source is the underground aquifer, lacks photosynthesizers. Ammonia oxidizing bacteria (AOB) and archaea (AOA), and nitrite-oxidizing bacteria (NOB) were relatively abundant in the three sediment zones from the inland sinkhole and in the WM from the coastal sinkhole, these observation at the WM from El Zapote agree with previous observations2. Anaerobic ammonium oxidation (anammox) uses nitrite (as a product of nitrate reduction), as electron acceptor35. The high levels of nitrate concentration in the water column from the three sediment zones at the inland sinkhole and at the WM from the coastal sinkhole may influence the abundance of AOB, AOA and NOB in the sediments from these zones, while NH4+ and nitrite values were below detection limit ( More

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The GCBD is stored at figshare23. Below we describe 20 Tables (also see Fig. 3 schematic) that comprise the GCBD: (1) Site_Info_tbl, (2) Sample_Event_tbl, (3) R_Scripts_tbl, (4) Cover_tbl, (5) Bleaching_tbl, (6) Environmental_tbl, (7) Authors_LUT, (8) Bleaching_Level_LUT, (9) City_Town_Name_LUT, (10) Country_Name_LUT, (11) Data_Source_LUT, (12) Ecoregion_Name_LUT, (13) Exposure_LUT, (14) Ocean_Name_LUT, (15) Realm_Name_LUT, (16) State_Island_Province_Name_LUT, (17) Substrate_Type_LUT, (18) Relevant_Papers_tbl, (19) Severity_Code_LUT, and (20) Bleaching_Prevalence_Score_LUT, where LUT stands for look-up table.

1)

Site Information (Site_Info_tbl)
Latitude_Degrees: latitude coordinates in decimal degrees.
Longitude_Degrees: longitude coordinates in decimal degrees.
Ocean_Name: the ocean in which the sampling took place.
Realm_Name: identification of realm as defined by the Marine Ecoregions of the World (MEOW)12.
Ecoregion_Name: identification of the Ecoregions (150) as defined by Veron et al.13.
Country_Name: the country where sampling took place.
State_Island_Province_Name: the state, territory (e.g., Guam) or island group (e.g., Hawaiian Islands) where sampling took place.
City_Town_Name: the region, city, or nearest town, where sampling took place.
Site_Name: the accepted name of the site or the name given by the team that sampled the reef.
Distance_to_Shore: the distance (m) of the sampling site from the nearest land.
Exposure: a site was considered exposed if it had >20 km of fetch, if there were strong seasonal winds, or if the site faced the prevailing winds. Otherwise, the site was considered sheltered or ‘sometimes’. ‘Sometimes’ refers to a few sites with a >20 km fetch through a narrow geographic window, and therefore we considered that the site was potentially exposed during cyclone seasons. We left the category ‘sometimes’ in the database because those sites were not clearly exposed sites, nor were they clearly sheltered sites, and future researchers may be interested in temporary exposure.
Turbidity: kd490 with a 100-km buffer.
Cyclone_Frequency: number of cyclone events from 1964 to 2014.
Comments: comments of any issues with the site or additional information.

2)

Sample Event Information (Sample_Event_tbl)
Site_ID: site ID field from Site_Info_tbl.
Reef_ID: name of reef site that was adopted by sampling group (from ReefCheck).
Quadrat_No: quadrat number (from McClanahan et al.)20.
Date_Day: the date of the sampling event.
Date_Month: the month of sampling event.
Date_Year: the year of sampling event.
Depth: depth (m) of sampling site. Comments: comments of any issue or additional information of sampling event.

3)

R Code (R_Scripts_tbl)
Relevant_Papers_ID: relevant papers ID field from Relevant_Papers_tbl.
Project name: name of project associated with R code.
Paper_Title: title of paper where R code was published.
Code_Name: name of R code file.
Description: description of the R code.
Data_Source: data source ID field from Data_Source_LUT.
R_Code: attachment of R code file.
URL: hyperlink to R code or link to github.

4)

Coral Cover Information (Cover_tbl)
Sample_ID: sampled ID field from Sample_Event_tbl.
Substrate_Type: substrate type ID field from Substrate_LUT.
S1: Reef Check breaks down transects into four 20 m × 5 m segments, point data from segment one of transect.
S2: Reef Check breaks down transects into four 20 m × 5 m segments, point data from segment two of transect.
S3: Reef Check breaks down transects into four 20 m × 5 m segments, point data from segment three of transect.
S4: Reef Check breaks down transects into four 20 m × 5 m segments, point data from segment four of transect.
Perc_hardcoral: percent hard coral cover from McClanahan et al.20 data source.
Perc_macroalgae: percent macroalgae cover from McClanahan et al.20 data source.
Average_Ellipse_Transect: calculated percent hard coral cover per 10 m × 1 m transect using ellipse equation.
Average_Ellipse_Site: calculated percent hard coral cover per site using ellipse equation.
Comments: comments of any issue or additional information of sampling event

5)

Bleaching Information (Bleaching_tbl)
Sample_ID: sample ID field from Sample_Event_tbl.
Bleaching_Level: Reef Check data, coral population or coral colony.
S1: Reef Check breaks down transects into four 20 m × 5 m segments, percent bleaching from segment one of transect.
S2: Reef Check breaks down transects into four 20 m × 5 m segments, percent bleaching from segment two of transect.
S3: Reef Check breaks down transects into four 20 m × 5 m segments, percent bleaching from segment three of transect.
S4: Reef Check breaks down transects into four 20 m × 5 m segments, percent bleaching from segment four of transect.
Percent_Bleaching_RC_Old_Method: old method of determining percent bleaching from Reef_Check.
Severity_Code: coded range of bleaching severity from Donner et al.10.
Percent_Bleached: percent of coral bleaching.
Number_Bleached_colonies: number of bleached corals from McClanahan et al.20 data source.
Bleaching_intensity: from McClanahan et al.20 data source.
Bleaching_Prevalence_Score: coded range of bleaching prevalence from Safaie et al.21.

6)

Environmental Parameter Information (Environmental_tbl)
Sample_ID: sample ID field from Sample_Event_tbl.
ClimSST: CoRTAD. [Climatological Sea-Surface Temperature (SST)] based on weekly SSTs for the study time frame, created using a harmonics approach.
Temperature_ Kelvin: CoRTAD. SST in Kelvin.
Temperature_Mean: CoRTAD. Mean SST in degrees Celsius.
Temperature_Minimum: CoRTAD. Minimum SST in degrees Celsius.
Temperature_Maximum: CoRTAD. Maximum SST in degrees Celsius.
Temperature_Kelvin_Standard_Deviation: CoRTAD. Standard deviation of SST in Kelvin.
Windspeed: CoRTAD. meters per hour.
SSTA: CoRTAD. (Sea-Surface Temperature Anomaly) weekly SST minus weekly climatological SST.
SSTA_Standard_Deviation: CoRTAD. The Standard Deviation of weekly SSTA in degrees Celsius over the entire period.
SSTA_Mean: CoRTAD. The mean SSTA in degrees Celsius over the entire period.
SSTA_Minimum: CoRTAD. The minimum SSTA in degrees Celsius over the entire period.
SSTA_Maximum: CoRTAD. The maximum SSTA in degrees Celsius over the entire period.
SSTA_Frequency: CoRTAD. (Sea Surface Temperature Anomaly Frequency) number of times over the previous 52 weeks that SSTA  >  = 1 degree Celsius.
SSTA_Frequency_Standard_Deviation: CoRTAD. The standard deviation of SSTA Frequency in degrees Celsius over the entire time period of 40 years.
SSTA_FrequencyMax: CoRTAD. The maximum SSTA Frequency in degrees Celsius over the entire time period.
SSTA_FrequencyMean: CoRTAD. The mean SSTA Frequency in degrees Celsius over the entire time period of 40 years.
SSTA_DHW: CoRTAD. (Sea Surface Temperature Degree Heating Weeks) sum of previous 12 weeks when SSTA  >  = 1 degree Celsius.
SSTA_DHW_Standard_Deviation: CoRTAD. The standard deviation SSTA DHW in degrees Celsius over the entire period.
SSTA_DHWMax: CoRTAD. The maximum SSTA DHW in degrees Celsius over the entire time period of 40 years.
SSTA_DHWMean: CoRTAD. The mean SSTA DHW in degrees Celsius over the entire time period of 40 years.
TSA: CoRTAD. (Thermal Stress Anomaly) weekly SSTs minus the maximum of weekly climatological SSTs in degrees Celsius.
TSA_Standard_Deviation: CoRTAD. The standard deviation of TSA in degrees Celsius over the entire time period of 40 years.
TSA_Minimum: CoRTAD. The minimum TSA in degrees Celsius over the entire time period of 40 years.
TSA_Maximum: CoRTAD. The maximum TSA in degrees Celsius over the entire time period of 40 years.
TSA_Mean: CoRTAD. The mean TSA in degrees Celsius over the entire time period of 40 years.
TSA_Frequency: CoRTAD. The number of times over previous 52 weeks that TSA  >  = 1 degree Celsius.
TSA_Frequency_Standard_Deviation: CoRTAD. The standard deviation of frequency of TSA in degrees Celsius over the entire time period of 40 years.
TSA_FrequencyMax: CoRTAD. The maximum TSA frequency in degrees Celsius over the entire time period of 40 years.
TSA_FrequencyMean: CoRTAD. The mean TSA frequency in degrees Celsius over the entire time period of 40 years.
TSA_DHW: CoRTAD. (Thermal Stress Anomaly Degree Heating Weeks) sum of previous 12 weeks when TSA  >  = 1 degree Celsius.
TSA_DHW_Standard_Deviation: CoRTAD. The standard deviation of TSA DHW in degrees Celsius over the entire time period of 40 years.
TSA_DHWMax: CoRTAD. The maximum TSA DHW in degrees Celsius over the entire time period of 40 years.
TSA_DHWMean: CoRTAD. The mean TSA DHW in degrees Celsius over the entire time period of 40 years.

7)

Author Names (Authors_LUT)
Last_Name: author’s last name.
First_Name: author’s first name.
Middle_Initial: author’s middle initial.

8)

Bleaching Level Information (Bleaching_Level_LUT)
Bleaching_Level: Reef Check data, coral population or coral colony.

9)

City, Town Names (City_Town_Name_LUT)
City_Town_Name: the region, city, or town, where sampling took place.

10)

Country names (Country_Name_LUT)
Country_Name: name of the country where sampling took place.

11)

Data Source Information (Data_Source_LUT)
Data_Source: name of source of original data set.
Sample_Method: Description of the sampling methods used to collect the data. If more than one method was used then we stated that an amalgamation of methods were used to collect the data, and the original papers are found in “Relevant_Papers_tbl”, and can be referenced therein.

12)

Ecoregion Names (Ecoregion_Name_LUT)
Ecoregion_Name: name of Ecoregion from Veron et al.13.

13)

Exposure Type (Exposure_LUT)
Exposure_Type: site exposure to fetch.

14)

Ocean Name Information (Ocean_Name_LUT)
Ocean_Name: name of ocean where sampling took place.

15)

Name of Realm (Realm_Name_LUT)
Realm_Name: name of realm as identified by the Marine Ecoregions of the World (MEOW)12.

16)

State, Island, Province Name (State_Island_Province_Name_LUT)
State_Island_Province_Name, Name of the state, territory (e.g. Guam) or island group (e.g. Hawaiian Islands) where sampling took place.

17)

Substrate Type (Substrate_Type_LUT)
Substrate_Type: type of substrate from Reef Check data.

18)

Relevant Publications (Relevant_Papers_tbl)
Data_Source: source associated with publication.
Author_ID: author ID field from Authors_LUT.
Title: title of published work.
Journal_Name: name of publication journal.
Year_Published: year of publication.
Volume: volume number of journal.
Issue: issue number of journal.
Pages: page range of publication.
URL: hyperlink to publication.
DOI: DOI number of publication.
pdf: pdf attachment of publication.

19)

Severity Index Code (Severity_Code_LUT)
Severity_Code: coded range of bleaching severity from Donner et al.10.

20)

Bleaching Prevalence Code (Bleaching_Prevalence_Score_LUT)

Bleaching_Prevalence_Score: coded range of bleaching prevalence from Safaie et al. 21. More