Find research datasets worth reusing

openother-openOct 2022View details →

sammsherman27/CoralReefSharkRayIUCN: Data and Code Used in Sherman et al. 2022 - Half a century of rising extinction risk of coral reef sharks and rays

Code and data to reproduce analyses in Sherman et al. 2022 Half a century of rising extinction risk of coral reef sharks and rays.

opencc-zeroDec 2022View details →

Rapid resource depletion on coral reefs disrupts competitor recognition processes among butterflyfish species

Avoiding costly fights can help conserve energy needed to survive rapid environmental change. Competitor recognition processes help resolve contests without escalating to attack, yet we have limited understanding of how they are affected by resource depletion and potential effects on species coexistence. Using a mass coral mortality event as a natural experiment and 3,770 field observations of butterflyfish encounters, we test how rapid resource depletion could disrupt recognition processes in butterflyfishes. Following resource loss, heterospecifics approached each other more closely before initiating aggression, fewer contests were resolved by signalling, and the energy invested in attacks was greater. In contrast, behaviour towards conspecifics did not change. As predicted by theory, conspecifics approached one another more closely and were more consistent in attack intensity yet, contrary to expectations, resolution of contests via signalling was more common among heterospecifics. Phylogenetic relatedness or body size did not predict these outcomes. Our results suggest that competitor recognition processes for heterospecifics became less accurate after mass coral mortality, which we hypothesise is due to altered resource overlaps following dietary shifts. Our work implies that competitor recognition is common among heterospecifics, and disruption of this system could lead to suboptimal decision-making, exacerbating sublethal impacts of food scarcity.

opencc-zeroDec 2022View details →

Cleaning stations in coral reefs – matching services to reef-dwelling and pelagic clients?

Cleaning, the removal of parasites and dead tissue from clients, is common in the Sea. Reef-based cleaning stations are visited by many fish clients, some by both resident and visitor pelagic species, while others are visited solely by resident species. Nonetheless, no distinction has ever been made between the potentially different cleaning stations. Here we describe two distinct categories of cleaning stations: Pelagic Cleaning Stations (PCS) and Residential Cleaning Stations (RCS). We suggest that the two station types differ not only in their clientele but also in the characteristics of their cleaning services. We examined the behaviour of the cleaner wrasse, Labroides dimidiatus, at six cleaning stations on isolated knolls in Palawan, Philippines – three stations that are routinely visited by pelagic manta rays (i.e., PCS), and three stations that service only resident clients (i.e., RCS). Our results indicate PCS have a higher number of cleaners per station, that also forage at greater distances from the focal point of the station. These distinct patterns may be due to the effectiveness of the cleaning process for both the clients and the cleaners. Our findings may aid in the identification and conservation of shark and manta cleaning stations.

opencc-zeroJan 2023View details →

Data for: Increasing hypoxia on global coral reefs under ocean warming

Ocean deoxygenation is predicted to threaten marine ecosystems globally. However, current and future oxygen concentrations and the occurrence of hypoxic events on coral reefs remain underexplored. Here, using autonomous sensor data to explore oxygen variability and hypoxia exposure at 32 representative reef sites, we reveal that hypoxia is already pervasive on many reefs. 84% of reefs experienced weak to moderate (≤153 to ≤92 μmol O2 kg-1) hypoxia and 13% experienced severe (≤61 μmol O2 kg-1) hypoxia. Under different climate change scenarios based on 4 Shared Socioeconomic Pathways (SSPs), we show that projected ocean warming and deoxygenation will increase the duration, intensity, and severity of hypoxia, with more than 94% and 31% of reefs experiencing weak to moderate and severe hypoxia, respectively, by 2100 under SSP5-8.5. This projected oxygen loss could have negative consequences for coral reef taxa due to the key role of oxygen in organism functioning and fitness.

opencc-zeroFeb 2023View details →

NOAA NCCOS Assessment: Agency priorities for mapping coral reef ecosystems in Hawaiʻi, 2022-07-08 to 2022-08-01

Description NOAA's Coral Reef Conservation Program (CRCP) has identified a need for priority locations based on emerging management requirements in shallow coral reef areas (up to 40 meters) surrounding the main Hawaiian Islands. The priorities provided by participating agencies will inform research and monitoring activities, address current and future management needs, and maximize opportunities to leverage and complement existing regional efforts. To meet this need, NOAA’s National Centers for Coastal Ocean Science (NCCOS) developed a systematic, quantitative approach and online GIS application to gather seafloor mapping priorities from researchers and coral reef managers. Participants placed virtual coins into a grid overlaid on the project area to express the location of their mapping priorities. They also used pull-down menus to indicate specific mapping data needs and the rationale for their selections. Participants’ inputs were compiled and analyzed to identify high priority areas along with their justifications and requirements. A total of 17 participant groups entered their mapping priorities into the online tool. Identifying these high priority areas provide a critical spatial framework for prioritizing mapping efforts in shallow coral reef ecosystems in Hawaiʻi. Purpose: The overall goal of the project was to systematically gather and quantify suggestions for mapping needs to support management of shallow coral reef ecosystems along the coasts of the main Hawaiian Islands. This dataset supports these goals by compiling input from a diversity of regional experts on their recommended priorities for mapping data collection. Methods: An advisory group was established which included individuals from NOAA CRCP and NOAA Fisheries. This advisory team customized the prioritization process specifically to meet the needs of CRCP and local coral reef manager priorities. In the online prioritization tool, the study area was divided into 1786 hexagonal grid cells 2.6 km2 in size. Existing relevant spatial datasets (e.g., bathymetry, protected areas, etc.) were provided as a digital atlas to help participants understand information and data gaps within the project area and to identify locations they wanted to prioritize for future data collections. Each participant was provided with 540 virtual coins to place into grid cells to denote their mapping needs. They were instructed to place more coins in grid cells that were higher priority. A maximum of 54 coins could be placed into an individual grid cell by each respondent. Participants also selected from a drop-down list of predefined management uses from the following list: endangered species management (e.g.,), habitat restoration, monitoring, coastal vulnerability planning, watershed management, fisheries management, consultations and permitting, emergency response, and spatial protection and management. Respondents also selected what map product requirements were needed in priority cells by selecting a minimum of one, to a maximum of two choices from the following list: delineations of large topographic features, delineations of hard vs. soft bottom, models of habitat suitability for key taxa or communities, delineations of substrate type (e.g. sand, mud, coral, rock), models of presence/absence or density of corals, identification of coral species and their local environments, documentation of individual specimen condition. Coin values were summarized and mapped to identify high priority areas, reasons for those priorities, and information needs. This ESRI shapefile contains the 2.6 km2 grid cells used in this prioritization and their associated coin values overall, as well as by management use and map product requirement. Other summary values include the number of participants, number of participating groups, number of management uses, and number of map product requirements. Additionally, coins for microscale (identification of coral species and their local environments and documentation of individual specimen condition), mesoscale (delineations of substrate type, models of presence/absence/density of corals), and regional (delineations of topographic features, delineations of hard vs. soft bottom, models of habitat suitability) requirements were summarized. Also included is a ranking of each grid cell based on the total number of coins, management uses, and participating groups allocating coins in the respective cell. For a complete description of the process and analysis see: Kraus et al. 2023, in prep.

opencc-zeroMar 2023View details →

Multi-decadal stability of fish productivity despite increasing coral reef degradation

1. Under current trajectories, it is unlikely that the coral reefs of the future will resemble those of the past. As multiple stressors, such as climate change and coastal development, continue to impact coral reefs, understanding the changes in ecosystem functioning is imperative to protect key ecosystem services. 2. We used a 26-year dataset of benthic reef fishes (including cryptobenthic fishes) to identify multi-decadal trends in fish biomass production on a degraded coral reef. We converted fish abundances into estimates of community productivity to track the long-term trend of fish biomass production through time. 3. Following the first mass coral bleaching event in 1998, the abundance, standing biomass, and productivity of fish communities remained remarkably constant through time, despite the occurrence of multiple stressors, including extreme sedimentation, cyclones, and mass coral bleaching events. Species richness declined following the 1998 bleaching event, but rebounded to pre-bleaching levels and also remained relatively stable. 4. Although the species composition of the communities changed over time, these new community configurations still maintain a steady level of fish biomass production. While these highly dynamic and increasingly degraded systems can still provide some critical ecosystem functions, it is unclear whether these patterns will remain stable over future decades.

opencc-zeroJun 2023View details →

Data from: The role of fish feces for nutrient cycling on coral reefs

Consumers play an important role in biogeochemical cycles through the consumption and release of essential elements such as carbon (C), nitrogen (N), and phosphorus (P). Indeed, a large proportion of consumed elements are released into the environment in inorganic (i.e., excretion) or organic form (i.e., egestion). On coral reefs, fishes represent the bulk of consumer biomass and thus play a key role in the recycling of nutrients. In recent years, excretion rates have been studied intensively, but less is known about the rate and quality of coral reef fish egestion. In this study, we quantify the elemental contents of fish feces, estimate absorption efficiencies and compare egestion and excretion rates for 51 coral reef fish species. We show that elemental concentrations decrease remarkably little from food to feces. This is due to extremely low absorption efficiencies, resulting in the egestion of large amounts of energy and nutrients. Moreover, we show that while the quality of fish feces varies across trophic guilds, it remains highly variable within trophic guilds. Finally, we demonstrate that the release of N and P through egestion outweighs the amount of nutrients recycled through excretion. Our study highlights the need to incorporate animal egestion into assessments of ecosystem functioning and food web structure.

opencc-by-4.0Jun 2023View details →

Malaysian Coral Reef Ecosystem Resilience

This dataset is based on coral reef resilience project conducted in Peninsular Malaysia islands. These islands are Pulau Perhentian, Pulau Redang, Pulau Tioman and Kepulauan Mersing. In this research, a list of prioritized resilience factors and anthropogenic stressed were examined to understand the resilience of the selected sites.  The project was funded by National Oceanic and Atmospheric Administration (NOAA) Coral Reef Conservation Program (CRCP). Please see the terms and conditions below for the usage of the data: 1. Disclaimer: Data produced under this award and made available to the public must be accompanied by the following statement: "These data and related items of information have not been formally disseminated by NOAA, and do not represent any agency determination, view, or policy." 2. Data Citation: Publications based on data, and new products derived from source data, must cite the data used according to the conventions of the Publisher, using unambiguous labels such as Digital Object Identifiers (DOIs). All data and derived products that are used to support the conclusions of a peer-reviewed publication must be made available in a form that permits verification and reproducibility of the results.

opencc-by-4.0May 2023View details →

Historical coral reef benthic cover for the Western Indian Ocean (1970-2008)

Benthic cover data (percent cover) for the Western Indian Ocean. Data have been extracted from published sources through a systematic literature review, and compiled with previously unpublished datasets. Data was collected prior to 2008 through quantitative coral reef surveys (e.g., Line or Point-Intercept-Transects, photo or visual quadrats) and visual estimates. Particular attention was given to compiling live hard coral cover and macro and turf algae cover data due to their importance as principal measures of coral reef health. Data are from 10 Western Indian Ocean countries and territories: Kenya, Seychelles, Tanzania, Mozambique, Comoros, Mayotte, Madagascar, Reunion, Mauritius and South Africa. Data were extracted from grey literature (technical reports, books, and book chapters), scientific journal papers (articles and reviews) and project reports.  Data were generally reported as summarised mean cover values at a monitoring site level. Data aggregated at broader geographic scales was also included (e.g., “northern Kenya”), or other classes (e.g., “unspecified 9 sites (protected)”).  Data found in more than one publication were identified and cross-referenced to the other sources. Locations were ordered hierarchically by Country, Sector, Site and Station. In some cases, the same site or station may have multiple entries for the same year because of surveys of different reef zones or depths, and this information is provided to enable a distinction to be made. The exact date or year of survey was not clear in a few publications, and this has been recorded in the Year column as either combined years, e.g. 1998/99, general time period, e.g. mid - 1990s, or if no information is available, as ‘n.d’.

opencc-zeroJul 2023View details →

Recurring bleaching events disrupt the spatial properties of coral reef benthic communities across scales

Marine heatwaves are causing recurring coral bleaching events on tropical reefs that are driving ecosystem change. Yet little is known about how bleaching and subsequent coral mortality impacts the spatial properties of tropical seascapes, such as patterns of organism spatial clustering and heterogeneity across scales. Changes in these spatial properties can offer insight into ecosystem recovery potential following disturbance. Here we repeatedly quantified coral reef benthic spatial properties around the circumference of an uninhabited tropical island in the central Pacific over a 9-year period that included a minor and severe marine heatwave. Benthic communities showed increased biotic homogenisation following both minor and mass bleaching, becoming more taxonomically similar with less diverse intra-island community composition. Hard coral cover, which was highly spatially clustered around the island prior to bleaching, became less spatially clustered following minor bleaching and was indiscernible from a random distribution across all scales (100–2000 m) following mass bleaching. Interestingly, the reduced degree of hard coral cover spatial clustering was already evident by the onset of mass bleaching and before any dramatic wholesale loss in island-mean coral cover occurred. Reductions in hard coral spatial clustering may therefore offer an early indication of the ecosystem becoming degraded prior to mass coral mortality. In contrast, the spatial clustering of competitive fleshy macroalgae remained unchanged through both bleaching events, while crustose coralline algae and fleshy turf algae became more spatially clustered at larger scales (200–700 m) following mass bleaching. Overall, benthic community spatial patterning became less predictable following bleaching and was no longer reflective of gradients in long-term environmental drivers that typically structure these remote reefs. Our findings provide novel insights into how climate-driven marine heatwaves can impact the spatial properties of coral reef communities over multiple scales.

opencc-zeroAug 2023View details →

NOAA NCCOS Assessment: Agency priorities for mapping coral reef ecosystems in Guam and the Commonwealth of the Northern Mariana Islands, 2023-02-22 to 2023-06-12

Description: NOAA's Coral Reef Conservation Program (CRCP has identified a need for priority locations based on emerging management requirements in shallow coral reef areas (up to 40 meters) surrounding Guam and the Commonwealth of the Northern Mariana Islands (CNMI). The priorities provided by participating agencies will inform research and monitoring activities, address current and future management needs, and maximize opportunities to leverage and complement existing regional efforts. To meet this need, NOAA’s National Centers for Coastal Ocean Science (NCCOS) developed a systematic, quantitative approach and online GIS application to gather seafloor mapping priorities from researchers and coral reef managers. Participants placed virtual coins into a grid overlaid on the project area to express the location of their mapping priorities. They also used pull-down menus to indicate specific mapping data needs and the rationale for their selections. Participants’ inputs were compiled and analyzed to identify high priority areas along with their justifications and requirements. A total of seven participant groups entered their mapping priorities into the online tool for Guam and ten participant groups for CNMI. Identifying these high priority areas provide a critical spatial framework for prioritizing mapping efforts in shallow coral reef ecosystems in Guam and CNMI. Purpose: The overall goal of the project was to systematically gather and quantify suggestions for mapping needs to support management of shallow coral reef ecosystems along the coasts of the Guam and CNMI. This dataset supports these goals by compiling input from a diversity of regional experts on their recommended priorities for mapping data collection. Methods: An advisory group was established which included individuals from NOAA CRCP and NOAA Fisheries. This advisory team customized the prioritization process specifically to meet the needs of CRCP and local coral reef manager priorities. In the online prioritization tool, the Guam study area was divided into 153 hexagonal grid cells 2.6 km2 in size. The CNMI study area was divided into 330 hexagonal grid cells 2.6 km2 in size. Existing relevant spatial datasets (e.g., bathymetry, Sanctuary Protection Areas, etc.) were provided as a digital atlas to help participants understand information and data gaps within the project area and to identify locations they wanted to prioritize for future data collections. Each Guam participant was provided with 50 virtual coins to place into grid cells that they wished to prioritize. Each CNMI participant was provided with 110 coins. They were instructed to place more coins in grid cells that were higher priorities. A maximum of 5 coins could be placed into an individual grid cell in Guam by each respondent, and a maximum of 11 coins could be place into an individual grid cell in CNMI. Respondents also reported why these locations were important by selecting a minimum of one, and a maximum of two, management uses from the following list: endangered species management (e.g.,), habitat restoration, monitoring, coastal vulnerability planning, watershed management, fisheries management, consultations and permitting, emergency response, and spatial protection and management. Respondents also reported requirements of data were needed in priority cells. A minimum of one, to a maximum of two choices were selected from the following list: delineations of large topographic features, delineations of hard vs. soft bottom, models of habitat suitability for key taxa or communities, delineations of substrate type (e.g. sand, mud, coral, rock), models of presence/absence or density of corals, identification of coral species and their local environments, documentation of individual specimen condition. Coin values were summarized and mapped to identify high priority areas, reasons for those priorities, and information needs. This ESRI shapefiles contain the 2.6 km2 grid cells used in this prioritization and their associated coin values overall, as well as by management use, data product, and mapping methodology. Other summary values include the number of participants, number of participating groups, number of management uses, and number of data requirements. Additionally, coins for microscale (identification of coral species and their local environments and documentation of individual specimen condition), mesoscale (delineations of substrate type, models of presence/absence/density of corals), and regional (delineations of topographic features, delineations of hard vs. soft bottom, models of habitat suitability) requirements were summarized. Also included is a ranking of each grid cell based on the total number of coins, management uses, and participating groups allocating coins in the respective cell. For a complete description of the process and analysis see: Hile et al. 2023, in prep.

opencc-by-4.0Aug 2023View details →

Implementing the iCORAL (version 1.0) coral reef CaCO3 production module in the iLOVECLIM climate model - model outputs

This dataset contains the model outputs used in the figures in the paper entitled "Implementing the iCORAL (version 1.0) coral reef CaCO3 production module in the iLOVECLIM climate model" submitted to GMD. For the description of the model and simulations we refer to this article. Provided files: <ul> <li>Surface values of temperature (temp), salinity (salt), phosphate (opo4) and aragonite saturation state (omega) for:</li> </ul> The modern period (mean of 2000-2010): temp_modern.nc, salt_modern.nc, opo4_modern.nc, omega_modern.nc The pre-industrial (PI, mean of last 100 years of the simulation): temp_PI.nc, salt_PI.nc, opo4_PI.nc, omega_PI.nc <ul> <li>Coral location for:</li> </ul> Imin=50 μE/m2/s: coral_location_Imin50.nc Imin=300 μE/m2/s: coral_location_Imin300.nc The values indicate: 4 = presence of corals in the model simulation (coral area less or equal to 5% of the grid cell area) but not in observations 3 = presence of corals in both model and observational data 2 = presence of corals in observational data but not in the model simulation 1 = presence of corals in the model simulation (coral area more than 5% of the grid cell area)  but not in observations <ul> <li>Global coral reef area (103 km2) and Imin (the minimum light intensity necessary for reef growth, µE m-2 s-1): Total_area_vs_Imin.txt</li> <li>Global coral reef carbonate production (Pg CaCO3 yr-1) and Imin (the minimum light intensity necessary for reef growth, µE m-2 s-1): Total_prod_vs_Imin.txt</li> <li>Global coral reef carbonate production (Pg CaCO3 yr-1) and Ik (the saturating light intensity, µE m-2 s-1): Total_prod_vs_Ik.txt</li> <li>Global coral reef carbonate production (Pg CaCO3 yr-1) and gmax (the maximum production growth): Total_prod_vs_gmax.txt</li> <li>Global carbonate production (Pg CaCO3 yr-1) and global coral reef area (103 km2): Total_prod_vs_total_area.txt</li> <li>Root mean square error (RMSE, kg CaCO3 m-2 yr-1) between the simulations and the observational data of regional production (Perry et al., 2018) and global production (Pg CaCO3 yr-1): Total_production_vs_rmse_Perry.txt</li> <li>Root mean square error (RMSE, kg CaCO3 m-2 yr-1) between the simulations and the observational data of regional production (Perry et al., 2018) and coral reef area (103 km2): Total_area_vs_rmse_Perry.txt</li> </ul>

opencc-by-4.0Sep 2023View details →

18S sequences from eDNA surveys of a coral reef in the Maldives

18S sequence data for eDNA samples collected in the Maldives and the associated metadata and tag codes. The title of the study/publication is: Field collections and environmental DNA surveys reveal topographic complexity of coral reefs as a predictor of cryptobenthic biodiversity across small spatial scales

Figure 10. - Different fish abundance dynamic profiles between 1983 and 2014 in Long term monitoring of coral and fish assemblages (1983-2014) in Tiahura reefs, Moorea, French Polynesia

Figure 10. - Different fish abundance dynamic profiles between 1983 and 2014 on the outer slope at Tiahura sector in Moorea.

Figure 6 in Long term monitoring of coral and fish assemblages (1983-2014) in Tiahura reefs, Moorea, French Polynesia

Figure 6. - Commercial fish abundance at Tiahura sector in Moorea for the barrier reef and outer slope. Second-degree polynomial models were fitted to data (*: 0.01 <p ≤ 0.05, **: 0.001 <p≤ 0.01).

Figure 4 in Long term monitoring of coral and fish assemblages (1983-2014) in Tiahura reefs, Moorea, French Polynesia

Figure 4. - Total fish abundance at Tiahura sector in Moorea for the fringing reef. Second degree polynomial models were fitted to data (*: 0.01 <p ≤ 0.05, **: 0.001 <p ≤ 0.01).

Figure 9 in Long term monitoring of coral and fish assemblages (1983-2014) in Tiahura reefs, Moorea, French Polynesia

Figure 9. - Herbivorous fish species richness at Tiahura sector in Moorea for the three habitats. Linear models were fitted to data (**: 0.001 <p ≤ 0.01; ***: p ≤ 0.001).

Figure 5 in Long term monitoring of coral and fish assemblages (1983-2014) in Tiahura reefs, Moorea, French Polynesia

Figure 5. - Total fish species richness at Tiahura sector in Moorea for the fringing reef. Linear models were fitted to data (***: p ≤ 0.001).

Figure 8 in Long term monitoring of coral and fish assemblages (1983-2014) in Tiahura reefs, Moorea, French Polynesia

Figure 8. - Herbivorous fish abundance at Tiahura sector in Moorea for the barrier reef and outer slope. Linear models were fitted to data (**: 0.001 <p ≤ 0.01).

Figure 3 in Long term monitoring of coral and fish assemblages (1983-2014) in Tiahura reefs, Moorea, French Polynesia

Figure 3. - Temporal dynamics in coral percentage cover on the outer slope of Tiahura sector from 1979 to 2011. Stars denote the five main disturbances that affected the reef over the study period (COTS: Acanthaster planci outbreak). Dotted lines correspond to linear interpolation of coral percentage cover.