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openCC (other)Jun 2025View details →

UCSB SONGS Mitigation Monitoring: Reef Performance Standard – Fish Production

These data describe annual estimates of the somatic and gonadal tissue production in five species of reef fishes at an artificial reef (Wheeler North Reef in Orange County, CA) and two natural reference reefs (San Mateo Kelp in Orange County, CA and Barn Kelp in San Diego County, CA). Data were collected from 2009 – 2023 as part of a comprehensive mitigation program aimed at evaluating the ability of Wheeler North Reef to compensate for losses of kelp forest habitat and associated biota caused by the operation of the San Onofre Nuclear Generating Station (SONGS).

openCC (other)Jun 2025View details →

UCSB SONGS Mitigation Monitoring: Reef Survey - Fish Size and Abundance

These data describe annual estimates of the size and abundance of fish at three subtidal reefs collected as part of the San Onofre Nuclear Generating Station (SONGS) Mitigation Monitoring Program. Data collection began in 2009 at an artificial reef (Wheeler North Reef in Orange County, CA) and two natural reference reefs (San Mateo Kelp in Orange County, CA and Barn Kelp in San Diego County, CA). In the summer of each year, divers identified, sized, and counted species of fish along fixed transects, and in quadrats uniformly distributed at each reef.

openCustomApr 2016View details →

MCR LTER: Coral Reef: Community Dynamics: Abundance and Species Richness of Fishes Associated with the Coral Porites rus 2000 thru 2011

These data describe the species richness and abundance as part of MCR LTER's reef fish monitoring program to track long-term patterns in species abundance and diversity. This study began in 2000 in the lagoons off of the north shore of the island of Moorea, French Polynesia and the dataset is updated annually. The abundance and life history stage (adults, juveniles or recruits) of all taxa of fishes associated with selected colonies (5-16 colonies per site) of the mound forming coral Porites rus are recorded at seven reef sites located along the north shore of Moorea. These sites are characterized by differences in water depth, distance to the fore reef and the number and types of neighboring corals. Counts are performed by a pair of divers using SCUBA and include semi-cryptic species. The collection of these data was suspended following the last survey conducted in July 2011 due to the extremely low abundance of live P. rus at these locations.

openCC (other)Apr 2025View details →

MCR LTER: Coral Reef: Coupled Natural-Human Systems: GPS-enabled survey of fish in Moorea’s lagoons

This dataset includes counts and sizes of fish within Moorea’s lagoons, with more than 130,000 fish recorded between 2018 and 2021. In summer of each year observers swim through Moorea’s lagoons, observing a 5-m wide swath and recording species and sizes of fish encountered in every minute of swim (about 10 linear meters of sampling). The fish counts are limited to a fixed species list (57 taxa) which was chosen to capture most of the reef associated species targeted in Moorea’s fishery, as well as important herbivores. Only fish larger than 10 cm were recorded, a size chosen to match the small end of fish observed in the catch. The resulting counts were georeferenced based on simultaneously collecting GPS data. Data are presented here on the scale of a minute of sampling. This scale coincides with benthic data which was simultaneously collected but is presented in a different data set (EDI data package: knb-lter-mcr.4014.1) doi:10.6073/pasta/f1e4cbcd79ebbbb0b0cbb79ab2ff8901 These data were collected as part of CNH-L: Multiscale Dynamics of Coral Reef Fisheries: Feedbacks Between Fishing Practices, Livelihood Strategies, and Shifting Dominance of Coral and Algae (BCS-1714704) with additional support from the Moorea Coral Reef LTER (OCE- 1637396).

openCustomJan 2015View details →

MCR LTER: Coral Reef: Fish Counts versus Coral Diversity for Holbrook, et al. PLoS One 2015

To test the impact of the regional species pool on the coral-fish diversity relationship, the same experiment was conducted in lagoons of Schumann Island in Kimbe Bay, Papua New Guinea (5°31’S, 150°5’E), Lizard Island on the Great Barrier Reef, Australia (14º 41’S, 145º 27’E), and Moorea in French Polynesia (17° 30’S, 149° 50’W). Divers counted individuals of all species observed on or interacting with 45 patch reefs were constructed using six abundant, co-occurring coral species that were major habitat providers for fish. Fish were allowed to naturally colonize over 8-12 months and the patch reefs were surveyed by scuba divers four times during the period. The species of corals used in the experiment were selected to include species that exhibit a broad range of structural morphologies and potential sensitivities to climate change and other environmental stressors. These data support the manuscript: Holbrook, Sally J., Russel J. Schmitt, Vanessa Messmer, Andrew J. Brooks, Maya Srinivasan, Philip L. Munday and Geoffrey P. Jones, Reef Fishes in Biodiversity Hotspots are at Greatest Risk from Loss of Coral Species, accepted 2015, PLoS One.

opencc-by-4.0Jan 2020View details →

A set of six databases used in a study of the biogeography of Greater Caribbean reef fishes entitled: Comparing biodiversity databases: Greater Caribbean reef-fishes as a case study Iliana Chollett1, D. Ross Robertson2 1 Sea Cottage, Louisburgh, Co. Mayo, Ireland 2 Smithsonian Tropical Research Institute, Balboa, Panamá

A set of six databases used in a study of the biogeography of Greater Caribbean reef fishes entitled:   Comparing biodiversity databases: Greater Caribbean reef-fishes as a case study                                    Iliana Chollett, D. Ross Robertson     Database Authors: D Ross Robertson and Ernesto Peña, Smithsonian Tropical Research Institute, Panamá   This set of six databases contains georeferenced location records from six sources as described below.These six sources provided georeferenced records of occurrence of fishes found in the Greater Caribbean study area (6-330 N, 57-1000 W). Each occurrence record consists of a species name and associated latitude and longitude. Databases included in the comparisons made here are from five major online aggregators. Since their content overlaps to some extent, and OBIS, iDigBio and FishNet collaborate with GBIF, their data might be expected to produce similar biogeographic patterns. STRI includes a curated compendium of data from those five aggregators, enriched with data from many additional sources.   Only reef-associated fish species were included in the present analysis. These mostly represent demersal species known to occur on hard bottoms (coral, rock and oyster substrata), but also include species living on rubble, sand and vegetated bottoms within and around the immediate fringes of reefs, and pelagic species regularly found on reefs. All exotic and non-resident species and species other than reef-associated fishes were excluded from all databases prior to comparisons. Non-residents were defined as otherwise widespread species only rarely seen in the study area. Shore-fishes, including what are generally regarded as reef fishes, include those found in the waters of continental and insular shelves, i.e. between 0-200m. Reef-fish assemblages dominated by shallow-water taxa extend down to that depth in the study area (Baldwin et al. 2018). We used the shelf edge as a breakpoint and excluded records in areas deeper than 200m, identifying those areas using the General Bathymetric Chart of the Oceans (Kapoor, 1981; GEBCO Compilation Group, 2019).   Before the analyses, for all databases, duplicate records were deleted. Subsequently, records in the Pacific or on land were deleted. We used the Global Self-consistent, Hierarchical, High-resolution Geography Database (Wessel & Smith, 1996) to identify these areas. The spatial distribution of species-records in each database is shown in Figure 1 of the publication.   Global Biodiversity Information Facility (GBIF, https://www.gbif.org/): GBIF is an international network and research infrastructure aimed at providing open access to data about all types of life on earth. GBIF works through participant nodes using common standards and open-source tools that enable them to share information. Data from among the 49,000+ datasets hosted by GBIF that were used here range from those on museum specimens collected since the 18th century, to published scientific checklists, to curated  local checklists produced by trained science sources such as the Atlantic and Gulf Rapid Assessment Program (https://www.agrra.org/),to geotagged smartphone photos (that act as vouchers allowing verification) shared by amateur and scientific naturalists through iNaturalist (https://www.inaturalist.org/), to unvouchered, unverified and unverifiable observation records from untrained divers such as those contributing to DiveBoard (http://www.diveboard.com). GBIF data are standardized in Darwin Core format. GBIF data were obtained from a polygon of the region of study and subject to taxonomic review and selection after downloading. GBIF data were obtained from a polygon of the study area and subject to taxonomic review after downloading (accessed through the GBIF portal, https://www.gbif.org/, on or about 2019-05-19).   Ocean Biogeographic Information System (OBIS,  <a href="https://obis.org/">https://obis.org/</a>): OBIS is a global open-access data and information clearing-house on marine biodiversity (OBIS, 2019) that was adopted as a project of the Intergovernmental Oceanographic Data and Information Exchange of the Intergovernmental Commission of UNESCO . Its range of sources is similar to that of GBIF. OBIS hosts data from organizations or programs that join it as one of 13 “nodes”, and harvest the data from the IPT (Integrated Publishing Toolkit), where providers publish their data. The IPT is developed and maintained by the GBIF, and OBIS is a major contributor of marine data to GBIF. Data are standardized in Darwin Core format. OBIS data were obtained for the region of study by downloading data on each family, then retaining only data inside the study area, which were then subject to taxonomic review and selection (accessed through the OBIS portal, https://obis.org/, on or about 2019-05-19).   Integrated Digitized Biocollections (iDigBio, https://portal.idigbio.org/portal/search): iDigBio is sponsored by the a US National Science Foundation and run by the University of Florida that provides digital data from public, non-federal, US collections. Data are standardized in a Darwin Core format, and provided “as is”. IDigBio joined the GBIF network in 2017. IDigBio records were downloaded from a polygon of the region of study and subject to taxonomic review and selection (accessed through the iDigBio portal, https://portal.idigbio.org/portal/search, on or about 2019-05-19).   FishNet2 (http://www.fishnet2.net/): FishNet2 is a collaborative effort that aggregates data on fish collections around the world to share and distribute data on specimen holdings from ~75 museums, universities and other institutions. FishNet2 distributes data in Darwin Core, and data are provided “as is”. FishNet2 is part of the network VerNet, which has contributed to GBIF since 2013 and became part of IDigBio in 2016. While FishNet2 has made substantial efforts to georeference location-record data it hosts, many hosted records still lack georeferencing. FishNet2 data were obtained from a polygon of the study area and subject to taxonomic review after downloading (accessed through the Fishnet2 Portal, www.fishnet2.org, 2019-05-19).   FishBase (<a href="http://www.fishbase.org/">http://www.fishbase.org</a>): FishBase is a global biodiversity information system supervise by a consortium of nine non-USA international institutions, and hosts data on fin fishes and elasmobranchs  (Froese & Pauly, 2009). Information presented in FishBase is extracted from the scientific literature, reports and museum or aggregator (GBIF) databases, and standardized by a team of specialists. Data from Fishbase were downloaded for the following ecosystems: Caribbean Sea, Gulf of Mexico, Southeast U.S. Continental Shelf, Atlantic Ocean, Sargasso Sea and Bermuda, and subject to taxonomic review and selection after downloading (2019-05-19).   Smithsonian Tropical Research Institute (STRI; <a href="https://biogeodb.stri.si.edu/caribbean/en/pages">https://biogeodb.stri.si.edu/caribbean/en/pages</a>): The STRI database was compiled by DRR and Ernesto Peña at STRI’s Naos Marine Laboratory, and represents about 15 years accumulation of curated data (see below) from the following sources:  data downloaded at roughly two year intervals from the five aggregators; data from online databases of various museums that supply aggregators (data directly downloaded from a museum sometimes differs from that available in an aggregator from the same museum), including the Swedish Museum of Natural History, the American Museum of Natural History, the Natural History Museum of Denmark, the Gulf Coast Research Laboratory, the Colombian Museum of Natural Marine History, the United States National Museum, and the United States Geological Survey; data from national aggregators of Colombia (Sistema de Información Sobre Biodiversidad de Colombia (https://sibcolombia.net/), and  Sistema de Información Ambiental Marina de Colombia, https://siam.invemar.org.co/), Mexico (La Comisión Nacional para el Conocimiento y Uso de la Biodiversidad, CONABIO;   http://www.conabio.gob.mx/informacion/gis/), and Costa Rica (Museo de Zoologia de la Universidad de Costa Rica, http://museo.biologia.ucr.ac.cr/); verified (by DRR) underwater photographs of fishes taken at known locations; peer reviewed publications containing location information (species descriptions; taxonomic revisions of species, genera and families; regional and local checklists); fisheries reports; digital tagging data for species such as elasmobranchs; diving surveys and collections of local faunas by DRR (e.g. Robertson et al. 2019). In addition selected data from two sources that collect species lists at sites scattered throughout the Greater Caribbean are incorporated: from the Atlantic and Gulf Rapid Reef Assessment program (AGRRA, https://www.agrra.org/: Kramer & Lang, 2003) and from trained citizen scientists who contribute data on fishes to the Reef Environmental Education Foundation’s database (REEF: Pattengill-Semmens & Semmens, 2003). The bibliographic module (https://biogeodb.stri.si.edu/caribbean/en/library) of Robertson & VanTassel (2019) contains ~1700 publications linked to species names, among them the publications from which location data were extracted.   Data from the aggregators is presented “as is” and the aggregators themselves do not do data curation. Duplicates (and occasionally triplicates and quaduplicates) of the same museum record often are included from multiple sources (e.g. the original museum source, derivative checklists, an aggregator), sometimes with slightly different georeferenced coordinates. Data available in one year may subsequently disappear from an aggregator, and different data may be available for the same species under different names (e.g. the old and new names when a species is reassigned to another genus). Errors, sometimes large errors (Robertson, 2008), are common in aggregator data, from museums as well as other sources, and longstanding errors can seem to take on a perpetual existence. For example the damselfish Abudefduf saxatilis is a common and widespread inhabitant of tropical reefs on both sides of the Atlantic, but does not naturally occur outside that ocean. Despite the fact that its taxonomic status and range were resolved ~30 y ago (e.g. see Allen, 1991) museum data presented by the all five aggregators that contributed to the multi-source database used in this study currently (December 10, 2019) show large numbers of records of this species throughout the entire tropical Indo-Pacific, as well as across its native range in the Atlantic. Since many of the databases accumulating on aggregators are derivative (lists derived from records and from other derivative lists) it will become increasingly difficult to eliminate such errors as corrections to data in primary sources do not automatically propagate through the chain of usage by different databases. Due to increasing limitations on resources for taxonomic work, museums themselves have difficulty dealing with errors in specimen identity and location, and old specimens become unidentifiable, specimens never get returned when loaned out, or simply vanish, and entire collections can get destroyed by hurricanes or fires, or get dumped when museums close or experience a major change in mission. Georeferenced location data on fish distributions in the neotropics (and presumably most other areas) hosted by aggregators, particularly GBIF and OBIS, which take data from a broad range of source types, might best be described as messy, and the significant potential for errors in location records and an inability to verify records always needs to be taken into account when incorporating data from aggregators, primary museum sources, and analog sources.   Data considered for inclusion in the STRI database were screened as follows to exclude questionable records.  Data from two databases hosted by OBIS and GBIF were excluded entirely due to lack of reliability: BioGoMx (https://www.gulfbase.org/project/biodiversity-gulf-mexico-biogomx-database) and Diveboard (http://www.diveboard.com).  The only REEF data used were from “expert” REEF recorders on readily identifiable species that are unlikely to be confused with similar species (e.g. data for some genera of sparids, gerreids, labrisomids and gobies that include various sympatric species with very similar appearances, were not used).  After data from aggregators and museum sources were combined into a single database duplicate records were filtered out by rounding all records to three decimal places and eliminating duplicates, a process that inevitably deleted some valid records as well as duplicates. The sizes of the databases and abundance of such duplicates precluded individual manual exclusion. Finally, all location data for each species were revised by DRR by examining the distribution of its georeferenced coordinates overlayed on a digital map of the current known distribution range of that species (for such range information see Carpenter & De Angelis, 2002; Ebert et al., 2013; Last et al., 2016; Robertson & Van Tassell, 2019; IUCN Redlist species accounts for most species considered here: https://www.iucnredlist.org/search). Such revision took into account any recent modifications to taxonomy and distributions due to new data and new publications, or as a result of discussions between DRR and experts in the taxonomy of particular species or genera. Source information of many individual questionable records provided by aggregators with the hosted data was inspected to try and assess their validity. Records thought likely to be erroneous were deleted. Those included inexplicable records lacking adequate documentation located well outside the known distribution range, and records in unlikely habitats (e.g. on land for marine species; in deep water for shallow-water species). This revision process reduced the number of records by about 30%.   Data from the five individual aggregator databases that are used in the comparisons described here were all downloaded from their online portals during May, 2019. However, data from those five aggregators that were incorporated in the STRI database were downloaded in March 2017, with data from other sources described above added to the STRI database intermittently between then and May 2019, when the entire dataset was curated as described above. Hence the five individual aggregator databases analyzed in this study undoubtedly contain data not included in the version of the STRI database used in the present analyses.   Acknowledgements   Data acquisition and construction of the STRI database was supported by funds from STRI, the Smithsonian Marine Science Network, the Smithsonian Publications Fund, the Smithsonian’s Deep Reef Observation Project, the National Geographic Society, the IUCN Red List program, the Harte Research Institute, and CONABIO. We thank REEF and AGRRA for supplying species-location records, various people for taxonomic and location-record information used to construct that database (principal among them C Baldwin, S Brandl, K Conway B Frable, T Menut, T Munroe, R Robins, L Tornabene, J Van Tassell and B Victor), and hundreds of citizen-scientist submarine photographers whose images (see <a href="https://biogeodb.stri.si.edu/caribbean/en/contributors/citizen_scientists">https://biogeodb.stri.si.edu/caribbean/en/contributors/citizen_scientists</a>) acted as vouchers for location records.   References   Allen, G.R. (1991) Damselfishes of the World. Mergus, Melle, 271 p. Baldwin, C.C., Tornabene, L. & Robertson, D.R. (2018) Below the mesophotic. Scientific Reports, 8, 4920. Carpenter, K.E. (Ed) (2002) The living marine resources of the Western Central Atlantic. Vols 1-3, FAO, Rome, 2127 p. Ebert, D.A., Fowler, S., Compagno, L. (2013) Sharks of the World: a fully illustrated guide. Wild Nature Press, Plymouth. 528 p. GEBCO Compilation Group (2019) GEBCO 2019 Grid (doi:10.5285/836f016a-33be-6ddc-e053-6c86abc0788e). Kapoor, D.C. (1981) General bathymetric chart of the oceans (GEBCO). Marine Geodesy, 5, 73–80. Kramer, P.R. & Lang, J.C. (2003) Appendix one: The Atlantic and Gulf Rapid Reef Assessment (AGRRA) Protocols: Former Version 2. 2. Atoll Research Bulletin, 496, 611–624. Last, P. R., White, W.A., de Carvalho, M.R., Séret, B., Stehmann, F.W., & Naylor, J.P. (2016). Rays of the World. CSIRO, Clayton. 790 p. Pattengill-Semmens, C.V. & Semmens, B.X. (2003) Conservation and management applications of the reef volunteer fish monitoring program. Coastal Monitoring through Partnerships: Proceedings of the Fifth Symposium on the Environmental Monitoring and Assessment Program (EMAP) Pensacola Beach, FL, U.S.A., April 24–27, 2001 (ed. by B.D. Melzian), V. Engle), M. McAlister), S. Sandhu), and L.K. Eads), pp. 43–50. Springer Netherlands, Dordrecht. Robertson, D. R. (2008) Global biogeographic databases on marine fishes: caveat emptor. Diversity and Distributions, 14, 891-892 Robertson, D.R,, Dominguez-Dominguez, O., Lopez Arollo, Y.M., Moreno Mendoza. R., Simoes, N. (2019) Reef-associated fishes from the offshore reefs of western Campeche Bank, Mexico, with a discussion of mangroves and seagrass beds as nursery habitats. Zookeys 843: 71-115. <a href="https://doi.org/10.3897/zookeys.843.33873">https://doi.org/10.3897/zookeys.843.33873</a> Robertson, D.R & Van Tassell, J. (2019) Shorefishes of the Greater Caribbean: online information system. Version 2.0. Smithsonian Tropical Research Institute, Balboa, Panamá. <a href="https://biogeodb.stri.si.edu/caribbean/en/pages">https://biogeodb.stri.si.edu/caribbean/en/pages</a>. Wessel, P. & Smith, W.H.F. (1996) A global, self-consistent, hierarchical, high-resolution shoreline database. Journal of Geophysical Research: Solid Earth, 101, 8741–8743.

opencc-by-4.0Dec 2012View details →

Fig. 2 in Fish assemblage of the Mamanguape Environmental Protection Area, NE Brazil: abundance, composition and microhabitat availability along the mangrove-reef gradient

Fig. 2. Ontogenetic patterns of habitat use in Abudefduf saxatilis, Anisotremus surinamensis, Lutjanus alexandrei, and L. jocu along the sub-areas of Mamanguape Mangrove-Reef system, NE Brazil, showing an increase in individual size classes from the Estuarine to the Reef zone. Mann Whitney U Test showed significant size differences between all sub-areas (for A. saxatilis, Transition vs. Reefs: U = 491, Z = -6.02, p = 0.00; for A. surinamensis, Transition vs. Reefs: U = 1338, Z = -6.83, p = 0.00; for L. alexandrei, Peixe-Boi vs. Transition: U = 0.00, Z = -3.39, p = 0.00; and Tanques vs. Transition: U = 0.00, Z = -2.92, p = 0.00; for L. jocu, Peixe-Boi vs. Transition: U = 7.5, Z = -3.38, p = 0.00), except between Tanques and Peixe-Boi for L. alexandrei (U = 65, Z = 0.76, p = 0.46).

opencc-by-4.0Dec 2012View details →

Fig. 3 in Fish assemblage of the Mamanguape Environmental Protection Area, NE Brazil: abundance, composition and microhabitat availability along the mangrove-reef gradient

Fig. 3. Canonical Correspondence Analysis of fishes and environmental parameters from Mamanguape Mangrove-Reef system, NE Brazil: (a) fish species (symbols) in relation to microhabitat categories (vectors) - Eigenvalues: axis 1, 0.56; axis 2, 0,20; r species-environment: axis 1, 0.87; axis 2, 0.56; First two axes accounted for 64.9 % of the variance; (b) fish trophic groups and subareas (symbols) in relation to environmental categories (vectors) - Eigenvalues: axis 1, 0.49; axis 2, 0.39; r species-environment: axis 1, 0.79; axis 2, 0.76; First two axes accounted for 51.6 % of the variance. Monte-Carlo test of all canonical axes were significant (p <0.01), 999 permutations. Abbreviations as follows - fish species: Abusax: Abudefduf saxatilis; Acabah: Acanthurus bahianus; Acacoe: A. coeruleus; Achlin: Achirus lineatus; Anisur: Anisotremus surinamensis; Anivir: A. virginicus; Batsop: Bathygobius soporator; Centrop: Centropomus sp.; Cithspil - Citharichthys spilopterus; Corglau - Coryphopterus glaucofraenum; Dactvol - Dactylopterus volitans; Echnau: Echeneis naucrates; Epiadc: Epinephelus adscensionis; Eucmel: Eucinostomus melanopterus; Haepar: Haemulon parra; Hipprei: Hippocampus reidi; Lutana: Lutjanus analis; Lutale: L. alexandrei; Lutjoc: L. jocu; Micrbra: Microphis brachyurus; Myroce: Myrichthys ocellatus; Rypran: Rypticus randalli; Scarus: Scarus sp.; Sparis: Sparisoma sp.; Sphtes: Sphoeroides testudineus; Stefus: Stegastes fuscus; Stevar: S. variabilis; trophic groups: RH - Roving herbivore; TH - Territorial herbivore; OM - Omnivore; CA - Carnivore; IM - Invertivore of mobile prey.

opencc-by-4.0Dec 2012View details →

Fig. 1 in Fish assemblage of the Mamanguape Environmental Protection Area, NE Brazil: abundance, composition and microhabitat availability along the mangrove-reef gradient

Fig. 1. Mamanguape estuary, State of Paraíba, NE Brazil, showing surveyed sub-areas: 1) Tanques; 2) Peixe-Boi; 3) Cação; 4) Transition; and 5) Reefs. Dashed areas represent sandbanks.

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Context-dependent multimodal behaviour in a coral reef fish: Stage 1 & 2 total duration and count data in behaviour trials

Animals are expected to respond flexibly to changing circumstances, with multimodal signalling providing potential plasticity in social interactions. Whilst numerous studies have documented context-dependent behavioural trade-offs in terrestrial species, far less work has considered such decision-making in fish, especially in natural conditions. Coral reef ecosystems host 25% of all known marine species, making them hotbeds of competition and predation. We conducted experiments with wild Ambon damselfish (Pomacentrus amboinensis) to investigate context-dependent responses to a conspecific intruder; specifically, how nest defence is influenced by an elevated predation risk. We found that nest-defending male Ambon damselfish responded aggressively to a conspecific intruder, spending less time sheltering and more time interacting, as well as signalling both visually and acoustically. In the presence of a model predator compared to a model herbivore, males spent less time interacting with the intruder, with a tendency towards reduced investment in visual displays compensated for by an increase in acoustic signalling instead. We therefore provide ecologically valid evidence that the context experienced by an individual can affect its behavioural responses and multimodal displays towards conspecific threats.

opencc-zeroMar 2024View details →

opencc-by-4.0Nov 2011View details →

Fig. 1 in Dynamics of fish assemblages on a continuous rocky reef and adjacent unconsolidated habitats at Fernando de Noronha Archipelago, tropical western Atlantic

Fig. 1. Map of the Fernando de Noronha Archipelago showing the study area (Porto Beach) and permanent sampling stations.

opencc-by-4.0Nov 2011View details →

Fig. 3 in Dynamics of fish assemblages on a continuous rocky reef and adjacent unconsolidated habitats at Fernando de Noronha Archipelago, tropical western Atlantic

Fig. 3. Canonical plotting of microhabitat characteristics (arrows) and fish species (points). Rug.: rugosity; Crev.: number of crevices; S. height: substratum height; C. algae: percent cover of encrusting coralline algae; Macr.: percent cover of Macroalgae; Turf: percent cover of turf algae; L. coral: percent cover of live coral; Other: percent cover of other organisms; B. rock: percent cover of bare rock; Sand: percent cover of sand and limestone; IHC: index of habitat complexity; Species names are abbreviated as the first three letters of genus and first three letters of specific epithet (see Table 4 for full scientific names).

opencc-by-4.0Mar 2022View details →

Data for "Examining functional impact and trophic morphology of small, sand-sifting fishes on coral reefs"

This data is the product of the study published as "Examining functional impact and trophic morphology of small, sand-sifting fishes on coral reefs " It contains: Feeding depth count of the two fish species used Granulometry on the experimental sediment Gut content analysis of the 8 fish used in the experiment. Measurements of maximum and minimum size of each individual prey item noted. Feeding experiment count data. ID and count data of meiobenthos (benthic meiofauna) found during the feeding experiment. The benthic community was assessed in 3 replicates for each fish individual at each timepoint. See the methods in publications for details or contact the Ole Brodnicke or Camilla Hansen for details.

Fig. 10 in A rare window into a back-reef fish community from the middle Miocene (late Badenian) Medobory Hills barrier reef in western Ukraine, reconstructed mostly by means of otoliths

Fig. 10 Fish teeth from the studied localities: a–e Pshekharus yesinorum Bannikov & Kotlyar, 2015, isolated jaw teeth in lateral (a1, b1, c, d1, e) and dorsal view (a2, b2, d2), arranged in a sequence from distal to proximal positions. f Dasyatis sp., anterior tooth in dorsal (f1), occlusal view (f2), profile (f3) and labial view (f4)

Fig. 7 in A rare window into a back-reef fish community from the middle Miocene (late Badenian) Medobory Hills barrier reef in western Ukraine, reconstructed mostly by means of otoliths

Fig. 7 Otoliths of Gobionellidae: a–e Deltentosteus aff. telleri (Schubert, 1906), 7a Shydlivshchyna, NMNHU-P PI 2553, b (reversed), d Kozatskyi Yar, NMNHU-P PI 2552, c (reversed), e Mlyntsi, NMB P1209. f, g Economidichthys triangularis (Weiler, 1943), f (reversed) Shydlivshchyna, NMB P1210, g (reversed) Mlyntsi, NMNHU-P PI 2554. h, i Knipowitschia polonica Schwarzhans et al., 2020a, 2020b, h Shydlivshchyna, NMNHU-P PI 2562, i Kozatskyi Yar, NMB P1213. j, k Pomatoschistus elegans (Procházka, 1900), j (reversed) Kozatskyi Yar, NMNHU-P PI 2576, k (reversed) Shydlivshchyna, NMB P1222

Fig. 4 in A rare window into a back-reef fish community from the middle Miocene (late Badenian) Medobory Hills barrier reef in western Ukraine, reconstructed mostly by means of otoliths

Fig. 4 Otoliths of Gobius spp.: a–e Gobius bratishkoi n. sp., a holotype, NMNHU-P PI 2555, Kozatskyi Yar, b–e paratypes, b (reversed) Mlyntsi, NMNHU-P PI 2556, c–e (reversed) Kozatskyi Yar, NMB P1211. f Gobius reichenbacherae Schwarzhans, 2014, Shydlivshchyna, NMNHU-P PI 2557 (reversed). g–k Gobius ukrainicus n. sp., j holotype, Shydlivshchyna, NMNHU-P PI 2558, g–i, k paratypes, g, i, k NMNHU-P PI 2560, h (reversed) Mlyntsi, NMNHU-P PI 2559

Fig. 1 in A rare window into a back-reef fish community from the middle Miocene (late Badenian) Medobory Hills barrier reef in western Ukraine, reconstructed mostly by means of otoliths

Fig. 1 Location map and stratigraphy: a schematic map showing the Medobory Reef (after Korolyuk, 1952, and Górka et al., 2012, with modifications) and the studied localities in the vicinities of Horodok, western Ukraine; b schematic geologic cross section of the Badenian sequence through the Medobory region after Wysocka et. al. (2016) and Górka (2018a)

Fig. 13 in A rare window into a back-reef fish community from the middle Miocene (late Badenian) Medobory Hills barrier reef in western Ukraine, reconstructed mostly by means of otoliths

Fig. 13 Late Badenian paleogeography of the Paratethys and distribution of selected non-gobioid otolith-based taxa through the basin. Most common species are shown in bold printing. Asterisk denotes multiple locations, of which Borský Mikuláš represents the richest and most recently described otolith assemblage (Brzobohatý et al., 2022). Double asterisk for Dentex aff. gregarius tentatively includes records of Dentex aff. maroccanus by Brzobohatý et. al. (2022). Triple asterisk for Argyrosomus sp. denotes record of Argyrosomus aff. regius by Brzobohatý et. al. (2022). Paleogeography based on Rögl (1999), Popov et. al. (2004), and KováČ et. al. (2017)

Fig. 9 in A rare window into a back-reef fish community from the middle Miocene (late Badenian) Medobory Hills barrier reef in western Ukraine, reconstructed mostly by means of otoliths

Fig. 9 Otoliths of Haemulidae, Serranidae, Sparidae, Leiognathidae and Caproidae: a (reversed)—Brachydeuterus speronatus (Bassoli, 1906), Kozatskyi Yar, NMNHU-P PI 2549. b, c Serranidae indet., b (broken and repaired), c (reversed), Kozatskyi Yar, NMNHU-P PI 2579. d, e Pshekharus yesinorum Bannikov & Kotlyar, 2015, Mlyntsi, NMNHU-P PI 2578. f (reversed)—Leiognathidae indet., Shydlivshchyna, NMB P1214. g Perciformes indet., Shydlivshchyna, NMB P1221. h (reversed) – Capros aper (Linnaeus, 1758), Mlyntsi, NMB P1206

Fig. 12 in A rare window into a back-reef fish community from the middle Miocene (late Badenian) Medobory Hills barrier reef in western Ukraine, reconstructed mostly by means of otoliths

Fig. 12 Late Badenian paleogeography of the Paratethys and distribution of gobioid otolith-based taxa through the basin. Most common species are shown in bold printing (Gobius reichenbacherae tentatively includes records of Gobius aff. niger by Brzobohatý et al., 2022). Asterisk denotes multiple locations, of which Borský Mikuláš represents the richest and most recently described otolith assemblage (Brzobohatý et al., 2022). Double asterisk denotes species only known in the Vienna Basin from the early Badenian and shown for correlation purposes. Paleogeography based on Rögl (1999), Popov et. al. (2004), and KováČ et. al. (2017)