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49 results for “Coral Reef Habitat”
MCR LTER: Coral Reef: Growth-predation risk trade-offs constrain the local distribution of a thicket-forming staghorn coral to marginal reef habitats; Data for Ladd et al., 2025, Scientific Reports.
This dataset is in support of the manuscript: Growth-predation risk tradeoffs constrain the local distribution of a thicket-forming staghorn coral to marginal reef habitats. These data were collected to 1) document how Acropora pulchra is distributed around the island of Moorea, and 2) to better understand the ecological processes that shape that distribution. Data include 1) results from surveys around the island of Moorea documenting the presence and size distribution of Acropora pulchra thickets, 2) results from an experiment measuring the growth and survivorship of Acropora pulchra fragments in the presence and absence of fish predators at nearshore fringing reef sites and adjacent sites in the mid lagoon (n = 20 sites in total), and 3) ancillary data on nitrogen content and dN15 in the tissue of the macroalgae Turbinaria ornata, sediment accumulation, and corallivore biomass at the experimental sites. All data were collected in 2016 and 2017.
MCR LTER: Coral Reef Resilience: North Shore Herbivorous Fish Counts, Habitat Associations, and Substrate, 2010
These data describe the species abundance, size distributions, and habitat associations of roving herbivorous fishes (fishes belonging to the families, Acanthuridae, Scaridae, and Siganidae) found in different habitats in the lagoon and forereef on the north shore of Moorea. Adult fishes and large juveniles were counted (and their size estimated) by a SCUBA diver or snorkeler on thirty-four 50 m by 5 m wide transects. After counting large fishes, the entire transect was swam a second time, with the diver looking exclusively for small juvenile fishes on a 1 m swath. In addition to recording the species identity and estimated size of each juvenile encountered, the diver also recorded the particular microhabitat each individual or group of individuals was associated with. Finally, to quantify the relative availability of different types of microhabitat, the diver conducted point contacts where the primary benthic substrate was identified at regular (1 m) intervals on the same transect. This material is based upon work supported by the U.S. National Science Foundation under Grant No. OCE 16-37396 (and earlier awards) as well as a generous gift from the Gordon and Betty Moore Foundation. Research was completed under permits issued by the French Polynesian Government (Délégation à la Recherche) and the Haut-commissariat de la République en Polynésie Francaise (DTRT) (Protocole d'Accueil 2005-2018). This work represents a contribution of the Moorea Coral Reef (MCR) LTER Site.
MCR LTER: Coral Reef: Habitat Utilization and Pairing Patterns of Mutualistic Shrimps and Gobies from 7 Indo-Pacific regions
We analyzed network level specialization for eight Indo-Pacific networks of obligate, mutualistic gobies and shrimps, and elucidated ecological and evolutionary factors driving specialization. To accomplish this we collected and analyzed data on species pairings in Moorea, French Polynesia (lat. -17.49, long. -149.84), Kenting, Taiwan (lat. 21.95, long. 120.76), and Kimbe Bay, New Britain, Papua New Guinea (PNG; lat. -5.50, long. 150.12), and combined these observations with previously published data from Seychelles Islands (Polunin and Lubbock 1977), Great Barrier Reef, Australia (Cummins 1979), Red Sea, Israel (Karplus et al. 1981), Japan (Yanagisawa 1984), and the Gulf of Thailand, Thailand (Nakasone and Manthachitra 1986). We also systematically collected and analyzed habitat data for shrimps and gobies in Moorea, Taiwan, and PNG. We found specialization was affected by variability in habitat use for both gobies and shrimps and by phylogenetic history for shrimps. Habitat use was phylogenetically conserved among shrimp, and thus effects of shrimp phylogeny on partner choice were mediated in part by habitat. By contrast, habitat use and pairing patterns in gobies were not related to phylogenetic history. This asymmetry appears to result from evolutionary constraints on partner use in shrimps and convergence among distantly-related gobies to utilize burrows provided by multiple shrimp species. Results indicate that the evolution of mutualism is affected by life history characteristics that transcend environments and that different factors constrain interactions in disparate ecosystems. These data are associated with this publication: Thompson AR, Adam TC, Hultgren KM, Thacker CE (in press). Ecology and evolution affect network structure in an intimate marine mutualism. The American Naturalist. This is a collection of short term studies spanning 1972 to 2011.
MCR LTER: Coral Reef Resilience: Juvenile Parrotfish Habitat Associations at North Shore Fringe and Backreef in March 2011
These data describe habitat associations of juvenile parrotfish (Scaridae) encountered during systematic searches at LTER 1 and LTER 2 fringing reef and back reef sites during March 2011. At each site SCUBA divers or snorkelers identified, counted, and estimated the sizes of juvenile parrotfish and recorded the microhabitat that each individual or group of individuals was associated with on two 100 m x 10 m wide transects (n = 8 transects total). Upon encountering a juvenile or group of juveniles, the surveyor recorded the microhabitat type that fishes were first seen to be closest to. They also closely observed the behavior of fishes to see if they were utilizing a particular microhabitat as shelter, and if so this was also recorded. Several groups of fishes first observed to be grazing on hard substrate or on macroalgae quickly retreated into the nearby coral Porites rus when approached. Hence for these individuals we considered the initial habitat they were associated with (e.g., hard substrate or macroalgae) to be their primary microhabitat, but also noted that they were associated with Porites rus for shelter.
Fig. 6 in Decadal status of Acanthaster planci (Linnaeus, 1758) along the coral reef habitat of Andaman and Nicobar Islands
Fig. 6 — Substrate specificity of A. planci (CoTS) in Andaman and Nicobar Islands (a - Dorsal view of A. planci; b - Ventral view of A. planci; c & d - Animal grazing on Acroporidae corals; e - Animal grazing on Poritidae corals; f - Animal in coral crevice; g - Animal grazing on sponges and algae; and h - Feeding scar on aroporid corals due to A. planci
Fig. 4 in Decadal status of Acanthaster planci (Linnaeus, 1758) along the coral reef habitat of Andaman and Nicobar Islands
Fig. 4 — PCA of A. planci (CoTS) population in Andaman and Nicobar Islands (N&MA- North & Middle Andaman, SA- South Andaman, N-Nicobar)
Figure 3. Structurally complex high rugosity coral-dominated reef habitat. Image shows fixed transect 01 from the start pin looking toward a 180 in Fishes of War in the Pacific National Historic Park
Figure 3. Structurally complex high rugosity coral-dominated reef habitat. Image shows fixed transect 01 from the start pin looking toward a 180° heading in the Asan Beach unit (NPS photo).
Figure 1 in First report of Drupella cornus Röding, 1798 (Gastropoda: Muricidae), a biological indicator of coral reef habitat of Lakshadweep Archipelago, India
Figure 1. Drupella cornus Röding, 1798, collected at benthic coral reef habitat of Minicoy Island, Lakshadweep.
Fig. 2 in Use Of Intertidal Mangrove And Sea Wall Habitats By Coral Reef Fishes In The Wakatobi Marine Park, Indonesia
Fig. 2. Number of species seen at the two intertidal sites, and the number showing low (<33%), medium (33-67%) and high (>67%) site-fidelity
Fig. 1 in Use Of Intertidal Mangrove And Sea Wall Habitats By Coral Reef Fishes In The Wakatobi Marine Park, Indonesia
Fig. 1. Map of study sites. The arrow points to Hoga Island off the northeast coast of Kaledupa Island. The entire Tukangbesi Archipelago lies within the Wakatobi National Marine Park.
Data from: Dietary resilience of coral reef fishes to habitat degradation
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Data from: Niche breadth and divergence in sympatric cryptic coral species (Pocillopora spp.) across habitats within reefs and among algal symbionts
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Fig. 3 in Decadal status of Acanthaster planci (Linnaeus, 1758) along the coral reef habitat of Andaman and Nicobar Islands
Fig. 3 — Depth-wise occurrence of A. planci (CoTS) in Andaman and Nicobar Islands
Fig. 2 in Decadal status of Acanthaster planci (Linnaeus, 1758) along the coral reef habitat of Andaman and Nicobar Islands
Fig. 2 — Zone-wise occurrence map of A. planci (CoTS) in Andaman and Nicobar Islands
Fig. 1 in Decadal status of Acanthaster planci (Linnaeus, 1758) along the coral reef habitat of Andaman and Nicobar Islands
Fig. 1 — Occurrence of A. planci (CoTS) in Andaman and Nicobar Islands
Fig. 5 in Decadal status of Acanthaster planci (Linnaeus, 1758) along the coral reef habitat of Andaman and Nicobar Islands
Fig. 5 — Substrate specificity of A. planci (CoTS) in reef habitat of Andaman and Nicobar Islands
Data from: Integrating a UAV-derived DEM in object-based image analysis increases habitat classification accuracy on coral reefs
<p>Very shallow coral reefs (< 5 m deep) are naturally exposed to strong sea surface temperature variations, UV radiation and other stressors exacerbated by climate change, raising great concern over their future. As such, accurate and ecologically informative coral reef maps are fundamental for their management and conservation. Since traditional mapping and monitoring methods fall short in very shallow habitats, shallow reefs are increasingly mapped with Unmanned Aerial Vehicles (UAVs). UAV-imagery is commonly processed with Structure-from-Motion (SfM) to create orthomosaics and Digital Elevation Models (DEMs) spanning several hundred metres. Techniques to convert these SfM products to ecologically relevant habitat maps are still relatively underdeveloped. Here we demonstrate that incorporating geomorphometric variables (the DEM and its derivatives) in addition to spectral information (the orthomosaic) can greatly enhance the accuracy of automatic habitat classification. Therefore, we mapped three very shallow reef areas off KAUST on the Saudi Arabian Red Sea coast with an RTK-ready UAV. Imagery was processed with SfM, and classified through Object-Based Image Analysis (OBIA). Within our OBIA workflow, we observed overall accuracy increases of up to 11% when training a Random Forest classifier on both spectral and geomorphometric variables as opposed to traditional methods that only use spectral information. Our work highlights the potential of incorporating a UAV's DEM in OBIA for benthic habitat mapping, a promising but still scarcely exploited asset.</p>
Coexisting mangrove-coral habitat use by reef fishes in the Caribbean
<p>We conducted visual fish surveys in coexisting mangrove-coral (CMC) habitats in Panama to analyze the effect of coral presence in mangrove habitats on the fish assemblage. Our study revealed that CMC habitats harbor distinct fish assemblages compared to mangrove habitats without coral, with greater species richness and increased herbivore abundance.</p>
Data from: Integrating a UAV-derived DEM in object-based image analysis increases habitat classification accuracy on coral reefs
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Reef cover classification (v1): internal coral reef class descriptors for global coral reef habitat mapping
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OpenNeuro
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