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12,632 results for “fish”
North Temperate Lakes LTER: Fish Length Frequency 1981 - current
This data set is a derived data set based on fish catch and length data. Data are collected annually to enable us to track the fish assemblages of eleven primary lakes (Allequash, Big Muskellunge, Crystal, Sparkling, Trout, bog lakes 27-02 [Crystal Bog] and 12-15 [Trout Bog], Mendota, Monona, Wingra and Fish). Sampling on Lakes Monona, Wingra, and Fish started in 1995; sampling on other lakes started in 1981. Sampling is done at six littoral zone sites per lake with seine, minnow or crayfish traps, and fyke nets; a boat-mounted electrofishing system samples three littoral transects. Vertically hung gill nets are used to obtain two pelagic samples per lake from the deepest point. A trammel net samples across the thermocline at two sites per lake. In the bog lakes only fyke nets and minnow traps are deployed. Parameters measured include species-level identification and lengths for all fish caught, and scale samples and weight from a subset. Derived data sets include species richness, catch per unit effort, and size distribution by species, lake, and year. Dominant species vary from lake to lake. Perch, rockbass, and bluegill are common, with walleye, large and small mouth basses, northern pike and muskellunge as major piscivores. Cisco have been present in the pelagic waters of four lakes, and the exotic species, rainbow smelt, is present in two. The bog lakes contain mudminnows. Protocol used to generate data: The number of fish caught in each five mm length interval (0<length<5, 5<=length<10, etc.) have been summed over gear. In cases in which only a random subsample of fish were measured, the unmeasured fish have been assigned to the length categories based on the proportions in length categories for the measured fish of the subsample. Day seines were only used in 1981 and have been eliminated from this data set to make sampling effort across years comparable. Beach seining was discontinued after 2019. The only sampling done in 2020 were a single gill-netting repli
Adelie penguin diet composition, fish species and number, 1991-2024
The fundamental long-term objective of the seabird component of the Palmer LTER (PAL) has been to identify and understand the mechanistic processes that regulate the mean fitness (population growth rate) of regional penguin populations. Since the inception of PAL, Adélie penguin populations have effectively collapsed, gentoo penguin populations have increased dramatically and chinstrap penguin populations have remained relatively stable. These trends are spatially and temporally coherent with regional warming and decreasing sea ice duration. Adélie penguins are an ice-obligate polar species whose life history is intimately linked to the presence of sea ice, while chinstrap and gentoo penguins are ice-intolerant species whose life histories evolved in the sub-Antarctic, where sea ice is a less permanent feature of the marine ecosystem. The PAL study region includes five main islands on which Adélie penguin colonies have historically occurred, with each island containing a different number of spatially segregated sub-colonies. These colonies are censused to determine the total number of nests and chicks produced each year, and breeding success. Diet samples are acquired to understand diet composition (e.g., krill, fish) and krill length-frequencies. In general, krill constitute the most important component of the summer diets by mass of these three penguin species, but changes in PAL krill abundances have exhibited no long-term trends and thus far, have failed to explain the divergent patterns in penguin populations evident in our time series. Chick fledging masses are recorded as a cumulative measure of climate, weather, diet, and parental influences on chick health at the end of the breeding season. These data have provided valuable insights into the marine and terrestrial factors that influence Adélie penguin population fitness. No data were collected during the 2021-2022 season due to the Palmer Station pier rebuild.
Data to support "Stochastic density effects on adult fish survival and implications for population fluctuations"
Data on stage-specific abundance of black surfperch (Embiotoca jacksoni), the amount of foraging habitat and the availability of surfperch prey (crustaceans) were collected at fixed sites on the north shore of Santa Cruz Island, California annually (autumn) from 1993-2009. Data are grouped into four regions. Counts of fish distinguished among young-of-year, juveniles (1 year old) and adults (>= 2 years old). These data have been presented in Okamoto, D. K., R. J. Schmitt and S. J. Holbrook. 2016. Sochastic density effects on adult fish survival and implications for population fluctuations. Ecology Letters, 19:153-162. doi: 10.1111/ele.12547.
Data and R Code for 'Domestication via the commensal pathway in a fish-invertebrate mutualism'
<p>This document contains all data and R code required to replicate the analyses in 'Domestication via the commensal pathway in a fish-invertebrate mechanism' as published in Nature Communications. The R Markdown provided includes descriptions of all variables and the code used for the analysis of the following eight datasets:</p> <p>1. Transects<br> 2. Census of farms<br> 3. Paired choice experiments<br> 4. Predation experiment 1<br> 5. Predation experiment 2<br> 6. Timed observations<br> 7. Farm algae composition<br> 8. Longfin damselfish body condition</p> <p>In addition, the R Markdown also includes descriptions of all variables for two additional datasets:</p> <p>9. Estimates of mysid swarm density<br> 10. Mysid waste excretion and nutrient availability</p> <p>A PDF version of the R Markdown with all output is also provided. Please see the methods section of the associated manuscript for further information on data collection and analysis procedures.</p> <p>Author contributions to data collection and analysis: RMB, JMC, ZLC, TLS & WEF collected the data; WEF, RMB, JMC, ZLC & AM implemented the analyses. </p> <p>Correspond with: rohan.m.brooker@gmail.com</p>
Dataset for Fisher et al. (2023). Motion stereo at sea: Dense 3D reconstruction from image sequences monitoring conveyor systems on board fishing vessels. IET Image Processing, 17(2), pp.349-361.
<p>This dataset contains the video clips used to produce the results presented in:</p><p>Fisher, M., French, G., Gorpincenko, A., Holah, H., Clayton, L., Skirrow, R. and Mackiewicz, M., 2023. Motion stereo at sea: Dense 3D reconstruction from image sequences monitoring conveyor systems on board fishing vessels. IET Image Processing, 17(2), pp.349-361.</p>
Long-term monitoring of the fish community in the Minho Estuary (NW Iberian Peninsula)
<p>The dataset contains data from fyke nets deployed in the Minho Estuary (Portugal) from 2010 to 2019. The fyke nets were used for fish sampling and data collection. The sampling frequency varied but, on average, data was collected weekly using five different fyke nets. However, due to technical issues (e.g. lost or damaged fyke nets), the sampling pattern is not constant, with some fyke nets staying underwater for shorter or longer periods, and occasionally having fewer than five fyke nets per parentEventID. The dataset includes various terms such as parentEventID, eventID, eventDate, year, startDayOfYear, endDayOfYear, country, countryCode, geodeticDatum, decimalLatitude, decimalLongitude, coordinateUncertaintyInMeters, DEIMS.iD, habitat, basisOfRecord, samplingProtocol, sampleSizeValue, sampleSizeUnit, samplingEffort, occurrenceStatus, occurrenceID, organismQuantity, organismQuantityType, degreeOfEstablishment, vernacularName, scientificName, acceptedNameUsageID, taxonRank, kingdom, phylum, order, family, genus, and scientificNameAuthorship.</p>
Data from: Selective social interactions and speed-induced leadership in schooling fish
<p>Experimental datasets for the manuscript:</p> <div>Puy, A., Gimeno, E., Torrents, J., Bartashevich, P., Miguel, M. C., Pastor-Satorras, R., & Romanczuk, P. (2024). Selective social interactions and speed-induced leadership in schooling fish. <em>Proceedings of the National Academy of Sciences</em>, <em>121</em>(18), e2309733121.</div> <div> </div> <p>The datasets provide trajectories of fish. There are 2 recordings with N=39 fish (60 minutes duration) and 6 recordings with N=8 fish (30 minutes duration). The columns are as follows:</p> <ul> <li>Time [frame]: Time of the trajectory in frames.</li> <li>X_0 [px]: Position in the x-coordinate in pixels of the trajectory of individual 0.</li> <li>Y_0 [px]: Position in the y-coordinate in pixels of the trajectory of individual 0.</li> <li>X_1 [px]: Position in the x-coordinate in pixels of the trajectory of individual 1.</li> <li>Y_1 [px]: Position in the y-coordinate in pixels of the trajectory of individual 1.</li> <li>...</li> </ul> <p>Conversion to international units:</p> <ul> <li>50 frames = 1 s.</li> <li>2745 px= 100 cm.</li> </ul>
NETTAG+ Data set on adsorption of inorganic (Cu and Pb) and organic (PAHs) pollutants in fishing nets
<p>This data set includes the raw data associated with the article in <em>Marine Pollution Bulletin</em><strong> "</strong>Potential of fishing nets for adsorption of inorganic (Cu and Pb) and organic (PAHs) pollutants"</p>
DATASET: TESTING NICHE EQUIVALENCE IN AMPHIDROMOUS FISH POPULATIONS
<p>Presence records of<em> Galaxias maculatus</em> were collected from 12 locations across five river basins in central-southern Chile during March, May, August, and November of 2019 as part of a study on fish sampling and processing (Ramírez-Álvarez et al. 2022. doi.org/10.1038/s41598-022-06936-8)</p> <p>Isotopic niches defined using a standard ellipse area (SEAc) in isotopic space, represented by a 2D ellipsoidal space (δ13C - δ15N) (see Supporting Information: Standard ellipse area functions - Ramírez-Álvarez et al. 2024. doi:10.1007/s10750-024-05738-5) - Empirical Bayesian Kriging</p> <p>Database of varibles used for niche modelling: isotopic niche and seven abiotic variables selected from 23 predictor variables: (1) 19 climate variables representing 1950–2000 climate averages from WorldClim (http://www.worldclim.org/). (2) Four spatially continuous topographic and hydrological variables from the EarthEnv Project adjusted to the HydroSHEDS river network (http://www.earthenv.org/) (Domisch et al. 2015). Selection of variables was accomplished by analysis of covariance and multicollinearity, using the ENMeval R package (Muscarella et al. 2014): (1) principal component analysis (PCA) to explore relationships among all predictors, evaluating the composition of components (component variables) that accounted for ≥65% of variance explained, (2) pairwise comparisons to detect pairs of variables with strong correlations (Pearson correlation coefficients <0.8), groups with a correlation of less than 0.8 were considered independent, and (3) variance inflation factor (VIF) <10, to reduce the effect of collinearity between predictors (Listed below). A VIF greater than 10 indicates collinearity problems in the model. The vifcor and vifstep functions were employed by calculating two different strategies to exclude highly collinear variables using a stepwise procedure (Muscarella et al. 2014).</p> <div><em>Variable description and ecological question associated, selected variables are marked in bold.</em></div> <div><em>Series 1: Temperature, temperature variations and interaction with precipitation.</em></div> <div>bio1: Annual Mean Temperature; Is the temperature usually suitable? </div> <div><strong>bio2: Mean Diurnal Range; Are the days too warm or too cold?</strong></div> <div>bio3: Isothermality; Do temperatures fluctuate greatly over the course of a month? </div> <div>bio4: Temperature Seasonality (standard deviation); Do temperatures fluctuate greatly over the course of a year?</div> <div>bio5: Min Temperature of Coldest Month; Is the maximum temperature too high?</div> <div>bio6: Min Temperature of Coldest Month; Is the temperature constantly too high?</div> <div><strong>bio7: Temperature Annual Range; Do temperatures fluctuate greatly over the course of a year?</strong></div> <div><strong>bio8: Mean Temperature of Wettest Quarter; Is it too cold or too warm during the rainy season?</strong></div> <div>bio9: Mean Temperature of Driest Quarter; Is it too cold or too warm during the dry season?</div> <div>bio10: Mean Temperature of Warmest Quarter; Are the warmer months too cold?</div> <div><strong>bio11: Mean Temperature of Coldest Quarter; Are the colder months too warm?</strong></div> <div><em>Series 2: Precipitation and Rainfall Patterns</em></div> <div>bio12: Annual Precipitation; Does it rain enough in a year?</div> <div>bio13: Precipitation of Wettest Month; Does it rain a lot during the wettest month?</div> <div><strong>bio14: Precipitation of Driest Month; Does it rain poorly during the driest month?</strong></div> <div>bio15: Precipitation Seasonality (Coefficient of Variation); Would rainfall fluctuate much between seasons?</div> <div>bio16: Precipitation of Wettest Quarter; Does it rain a lot in the rainy season?</div> <div>bio17: Precipitation of Driest Quarter; Is rainfall low during dry seasons?</div> <div>bio18: Precipitation of Warmest Quarter; Does it rain enough during the warmer months?</div> <div>bio19: Precipitation of Coldest Quarter; Does it rain enough during the colder months?</div> <div><em>Series 3: Topology and hydrology</em></div> <div><strong>dem: Average elevation; Does altitude play a role as a topological factor?</strong></div> <div><strong>slope_av: Average slope; Is the slope suitable for the accumulation of small ponds?</strong></div> <div>flow_ac_ac: Accumulation flow; Does enough water accumulate or does it drain too quickly?</div> <div>flow_ac_le: Accumulation flow direction; Does the flow direction support the formation of small ponds?</div> <p>Domisch, S., G. Amatulli & W. Jetz, 2015. Near-global freshwater-specific environmental variables for biodiversity analyses in 1 km resolution. Scientific Data 2(1):150073 doi:10.1038/sdata.2015.73.</p> <p>Muscarella, R., P. J. Galante, M. Soley‐Guardia, R. A. Boria, J. M. Kass, M. Uriarte & R. P. Anderson, 2014. ENM eval: An R package for conducting spatially independent evaluations and estimating optimal model complexity for Maxent ecological niche models. Methods in ecology and evolution 5(11):1198-1205</p>
GO-FISH: Geolocated Ocean-Fishery Identified Spawning Habitats
<p>This dataset represents geocoded spawning regions for 1,045 marine fish species described in the Fishbase (https://www.fishbase.se/) and Science and Conservation of Fish Aggregations (SCRFA, <a href="https://www.scrfa.org/database/">https://www.scrfa.org/database/</a>) datasets. These global databases have painstakingly aggregated the fieldwork of countless biologists and ecologists to summarize our knowledge of fish species. We further constrained geographic locations using AquaMaps (<a href="https://www.aquamaps.org/">https://www.aquamaps.org</a>) to produce 2,931 polygons or groups of polygons, which we call "spawning regions".</p> <p>Reproduction code for the dataset is available at <a href="https://github.com/openmodels/spawning-dataset">https://github.com/openmodels/spawning-dataset</a>, archived at <a href="../records/11098955">https://zenodo.org/records/11098955</a>.</p>
Fishing activities and trajectories for 2 fishing vessels
<p>This data set provides the pseudo-positions in space and time of two fishing vessels and the associated activities (fishing, cruising, stopped, recorded by an on board observer). It supports the analyses provided in a paper published in Methods in Ecology and Evolution and the methods of the R package m2b (https://cran.r-project.org/package=m2b). For privacy concerns, original latitude, longitude, time and vessels id were modified. Spatial data were scaled and centred to a fictional position (R'lyeh position, Lovecraft 1928) keeping the relative geometry unchanged (acceleration, time between two positions....). Time and vessel id were modified in the same manner, keeping the relative properties of the tracks unchanged (time succession, different vessel id...). Vessel id and time are purely fictional and follow the historical context proposed by Lovecraft (1928) in the R'lyeh surroundings. Again, if the absolute spatial and temporal description of the fishing track were changed, their relative mathematical properties are conserved and can support behaviour detection based on relative movement analysis.</p> <p> </p> <p>For the data_vessel.csv file (csv file with header), the variables are</p> <p>x : pseudo longitude</p> <p>y : pseudo latitude</p> <p>t : pseudo time in year-month-day hour:minutes:second format</p> <p>b: fishing activity, namely "fishing", "cruising", "stopped"</p> <p>id: unique id by vessels (fictional names).</p> <p><br> Reference</p> <p>H. P. Lovecraft, "The Call of Cthulhu" (1928)</p> <p> </p>
Lake morphometry mediates the relationship between water color and fish biomass in small boreal lakes
<p>The data are for an analysis of the influence of water color and lake depth on fish biomass small (1-10 ha) lakes in boreal Sweden.</p> <p>AllBorealLakes.csv contains a list of surface areas (variable name hectares, given in hectares) for all lakes greater or equal to 1 hectare surface area in the boreal zone of Sweden. The original lake census comes from the Swedish government (Nisell et al. 2007) and lakes within the boreal zone were extracted based on the boreal zone boundary of Olson et al. (2001). There is also a lake ID number (FID_vivan_) used in the extraction.</p> <p> </p> <p>SmallBorealLakes.csv contains a list of surface areas (variable name hectares, given in hectares) for all lakes greater or equal to 1 hectare surface area and less than or equal to 10 hectares in the boreal zone of Sweden. The original lake census comes from the Swedish government (Nisell et al. 2007) and lakes within the boreal zone were extracted based on the boreal zone boundary of Olson et al. (2001). There is also a lake ID number (FID_vivan_) used in the extraction.</p> <p> </p> <p>SNILLE_ms_data.csv contains data on fish biomass for 16 small boreal lakes. The geographic coordinates (Northing and Easting) are based on the Swedish Grid, see: http://www.lantmateriet.se. Lake surface areas based on the Swedish lake census (Nisell et al. 2007). Mean depth (meters) is based on echo sounding with an integrated GIS (Lowrance m52i). Volumes were calculated by calculating a triangulated irregular network and then mean depth subsequently calculated as volume divided by surface area. kd is the vertical light extinction coefficient (m^-1). We calculated <em>k</em><sub>d</sub> from the slope of the linear regression of the logarithm of photosynthetically active radiation (measured with LI-COR LI-193 spherical quantum sensor) versus measurement depth (measured in approximately 0.5 meter intervals over the deepest part of the lake). The shallowest measure was excluded from the calculation. The values in the table are the average of kd calculated from three visits to each lake (once each approximately in June, July, and August 2014). kd is an indicator of colored dissolved organic carbon and water color (brownness) in this region and there is relatively little contribution of phytoplankton or inorganic particulate. CPUE Catch-per-unit-effort (kg wet weight / net) is an indicator of fish biomass. For each lake, we set 8 multi mesh gill nets (Nordic 12 nets, 30 x 1.5 m; Mesh sizes: 5, 6.25, 8, 10, 12.5, 15.5, 19.5, 24, 29, 35, 43, 55 mm) over one night (approximately 12 hours) in August 2014. Four nets were deployed in the littoral zone perpendicular to the shoreline. These nets were approximately equally spaced. Two floating nets were deployed across the deepest point of the pelagic zone, and two benthic nets were set in the hypolimnion near the deepest point of the lake. Net-specific catches were averaged with weighting based on the relative extent of the different habitat types (see Karlsson et al. 2015). Specifically, the profundal nets were assumed to represent the total hypolimnetic volume and the pelagic nets were assumed to represent the volume above the hypolimnion. The volume of the littoral nets was calculated by subtracting the volume of the pelagic and profundal habitats from the total lake volume. These weighted CPUE values are given in the file. Species identified through gill netting are abbreviated as: P for European perch (<em>Perca fluviatilis</em>), R for common roach (<em>Rutilus rutilus</em>), N for northern pike (<em>Esox lucius</em>), B for burbot (<em>Lota lota</em>)</p> <p>Boreal_Area_kd_data.csv contains a list of estimated vertical light extinction coefficients (kd, m^-1) for lakes in boreal Sweden. Specifically, the values are based on water chemistry data from a national water quality survey conducted in Sweden every five years. Lake surface water (0.5 m) was sampled from above the deepest part of the lake during early autumn when the water column is mixed. Water quality analyses were performed using standard limnological techniques (detailed methods available on the internet at: http://www.slu.se/en/departments/aquatic-sciences-assessment/laboratories/geochemicallaboratory/water-chemical-analyses/) by a certified water analysis laboratory at the Swedish University of Agricultural Sciences. The data are freely available on the Internet at http://www.slu.se/vatten-miljo. Absorbance at 420 nm (D) which is a metric of water color (brownness) was used to calculate absorption coefficients per meter (a, m-1) from the initial measurement: a = (D * 2.303) / L. where L is the optical path length in meters, 0.05 in the case of the monitoring data. We then estimated kd (m^-1) based on the calibration curve reported by Seekell et al. (2015): = kd = 0.3121 + 0.1327a. These values were associated with surface areas from the Swedish lake census (Nisell et al. 2007) using a identification number common to both the Swedish water chemistry and lake census datasets. Finally, the file was trimmed to only include lakes with surface areas greater or equal to 1 hectare and less than or equal to 10 hectares.</p> <p>References:</p> <ul> <li>Nisell, J., A. Lindsjö, and J. Temnerud (2007), Rikstäckande virtuellt vattendrags nätverk för flödesbaserad modellering VIVAN, [In Swedish], Rapport 2007:17, Institutionen för miljöanalys, SLU.</li> <li>Olson DM, Dinerstein E, Wikramanayake ED, Burgess ND, Powell GVN, Underwood EC, D’amico JA, Itoua I, Strand HE, Morrison JC, Loucks CJ, Allnutt TF, Ricketts TH, Kura Y, Lamoreux JF, Wettengel WW, Hedao P, Kassem KR (2001) Terrestrial ecoregions o the world: A new map of life on Earth. <em>BioScience</em> 51:933-938.</li> <li> <p>Karlsson J, Bergström AK, Byström P, Gudasz C, Rodriguez P, Hein C (2015) Terrestrial organic matter input suppresses biomass production in lake ecosystems. <em>Ecology</em> 96:2870-2876. doi: 10.1890/15-0515.1</p> </li> <li> <p>Seekell DA, Lapierre JF, Karlsson J (2015) Trade-offs between light and nutrient availability across gradients of dissolved organic carbon concentration in Swedish lakes: Implications for patterns in primary production. <em>Canadian Journal of Fisheries and Aquatic Sciences</em> 72:1663-1671. doi: 10.1139/cjfas-2015-0187</p> </li> </ul>
Data accompanying the master thesis: A neuronal model for visually evoked startle responses in schooling fish
<p>This dataset contains data that was generated and analyzed for the master thesis "A neuronal model for visually evoked startle responses". All related material, including analysis code, of the master thesis can be found at https://github.com/awakenting/master-thesis.</p>
Perceived increases of fish species in the Mediterranean sea: data from a joint LEK initiative.
<p>The dataset was collected with the the Mediterranean LEK initiative. The initiative was initially conceived by the international basin-wide monitoring program <em>CIESM Tropical Signals</em> (funded by the Albert II of Monaco Foundation) and subsequently adopted by the projects BALMAS (Ballast Water Management System for Adriatic Sea Protection, IPA Adriatic Cross-Border Cooperation Programme; <em>FAO-AdriaMed</em> and <em>FAO-MedSudMed</em>. This action was recently supported by the Interreg Med Programme (Grant number Pr MPA-Adapt 1MED15_3.2_M2_337) 85% co-funded by the European Regional Development Fund, which implemented the use of standard LEK protocols for Marine Protected areas and partially supported the writing of this publication.</p> <p>Data refers to self-reported trends of various fish species, which were regarded as increaseing by a sample of fishermen from various Mediterranean countries. Interviews were elicited from fishermen through semi-structured protocols (see Azzurro et al., 2011).</p>
H2020 Prime Fish Firm level competitiveness data Iceland Norway Newfoundland
<p>The data set contains survey data from three Norwegian, one Icelandic, one Newfoundland fish processing firm. Data are collected as part of the EU H2020 project PrimeFish (grant no 635761). The survey asks several questions concerning the firm’s evaluation of several aspects of competitiveness, following a Porter framework. The questions posed to the respondents are stated along with scoring help. All data are numeric, and on a 1-7 scale. Data were collected from the World Economic Forum 2017 competitiveness report and surveys and hard data collected in 2017.</p>
Historical contingency shapes adaptive radiation in Antarctic fishes [Data set]
<p>Assembled reference contigs for protein-coding exons and conserved non-coding regions from targeted sequence enrichment of notothenioid fishes and outgroups. </p> <p>Published in : Daane, JM, Dornburg, A, Smits, P, MacGuigan, D, Hawkins, B, Near, TJ, Detrich, HW III*, Harris MP*. (2019). Historical contingency shapes adaptive radiation in Antarctic fishes. <em>Nature Ecology & Evolution.</em></p> <p> </p> <p>-contigs.zip contains the assembled contigs for each species. Each contig represents a targeted region with the addition of flanking DNA sequence</p> <p>-cnes.zip contains the targeted conserved non-coding regions isolated from the larger contigs in contigs.zip</p> <p>-exons.zip contains the targeted protein coding exons isolated from the larger contigs in contigs.zip</p> <p>-protein.zip contains the translated protein coding exons from exons.zip</p>
"Effects of forestry on summertime low flows and physical fish habitat in snowmelt-dominant headwater catchments of the Pacific Northwest" -- data sets
<p>These files contain the data used in the analysis and production of graphs reported in a manuscript titled "Effects of forestry on summertime low flows and physical fish habitat in snowmelt-dominant headwater catchments of the Pacific Northwest," by Stefan Gronsdahl, R. Dan Moore, Jordan Rosenfeld, Rich McCleary, Rita Winkler. The paper will be published in the journal Hydrological Processes. The file named "readme.txt" explains the contents of the files.</p>
EOL Fossil Fishes Patch: EOL Fossil Fishes Patch
<p>Taxonomy of fossil fishes compiled from multiple sources:</p> <p>Bardack, D. & Richardson, E. S., Jr. 1977. New agnathous fishes from the Pennsylvanian of Illinois. Fieldiana, Geology 33(26):489-510. <a href="http://doi.org/10.5962/bhl.title.5167">http://doi.org/10.5962/bhl.title.5167</a></p> <p>Bardack, D. and Zangerl, R., 1968. First fossil lamprey: a record from the Pennsylvanian of Illinois. Science, 162(3859), pp.1265-1267. <a href="http://doi.org/10.1126/science.162.3859.1265">http://doi.org/10.1126/science.162.3859.1265</a></p> <p>Denison, R.H., 1967. Ordovician vertebrates from western United States. Fieldiana, Geology 16(6):131-192. <a href="http://doi.org/10.5962/bhl.title.5321">http://doi.org/10.5962/bhl.title.5321</a></p> <p>Denison, R.H., 1970. Revised classification of Pteraspididae with description of new forms from Wyoming. Fieldiana, Geology 20(1):1-41. <a href="https://doi.org/10.5962/bhl.title.3330">https://doi.org/10.5962/bhl.title.3330</a></p> <p>Dineley, D.L., 1964. New specimens of Traquairaspis from Canada. Palaeontology 7:210–219. Dineley, D. L. and Loeffler, E. J. 1976. Osctracoderm faunas of the Delorme and associated Siluro-Devonian formations, North West Territories, Canada. Spec. Pap. Paleont. 18:1-214. Dzik, J. and Moskalenko, T.A., 2016. Problematic scale-like fossils from the Ordovician of Siberia with possible affinities to vertebrates. Neues Jahrbuch für Geologie und Paläontologie-Abhandlungen, pp.251-260. <a href="http://doi.org/10.1127/njgpa/2016/0553">http://doi.org/10.1127/njgpa/2016/0553</a> </p> <p>Janvier, P. and Lund, R., 1983. Hardistiella montanensis n. gen. et sp.(Petromyzontida) from the Lower Carboniferous of Montana, with remarks on the affinities of the lampreys. Journal of vertebrate Paleontology, 2(4), pp.407-413. <a href="http://doi.org/10.1080/02724634.1983.10011943">http://doi.org/10.1080/02724634.1983.10011943</a> </p> <p>Märss, T., 2019. Silurian cyathaspidid heterostracans of Northern Eurasia. Estonian Journal of Earth Sciences, 68(3), pp.113-146. <a href="https://doi.org/10.3176/earth.2019.11">https://doi.org/10.3176/earth.2019.11</a> </p> <p>Märss, T. and Karatajūte-Talimaa, V., 2009. Late Silurian-Early Devonian tessellated heterostraean Oniscolepis Pander, 1856 from the East Baltic and North Timan. Estonian Journal of Earth Sciences, 58(1). <a href="http://doi.org/10.3176/EARTH.2009.1.05">http://doi.org/10.3176/EARTH.2009.1.05</a> </p> <p>Paleobiology Database, PBDB, accessed at h<a>ttps://paleobiodb.org</a> </p> <p>Shu, D.G., Luo, H.L., Conway Morris, S., Zhang, X.L., Hu, S.X., Chen, L., Han, J.I.A.N., Zhu, M., Li, Y. and Chen, L.Z., 1999. Lower Cambrian vertebrates from south China. Nature, 402(6757), pp.42-46. <a href="http://doi.org/10.1038/46965">http://doi.org/10.1038/46965</a> </p> <p>Tarlo, L. B. H. 1964. Psammosteiformes (Agnatha). 1 General part. Palaeontologia Polonica 13:1-135. Tarrant, P.R., 1991. The ostracoderm Phialaspis from the Lower Devonian of the Welsh Borderland and South Wales. Palaeontology 34:399–438. Van der Laan, R., 2018. Family-group names of fossil fishes. European Journal of Taxonomy, (466). <a href="http://doi.org/10.5852/ejt.2018.466">http://doi.org/10.5852/ejt.2018.466</a> </p> <p>WoRMS Editorial Board (2020). World Register of Marine Species. Available from <a href="http://www.marinespecies.org">http://www.marinespecies.org</a> at VLIZ. <a href="https://doi.org/10.14284/170">https://doi.org/10.14284/170</a> </p> <p>Zarling, A., 2017. Phenotypic trajectories during the evolution of hybrid lineages: the case of Oophaga histrionica and Oophaga lehmanni. Thesis, Universidad de los Andes, Colombia. <a href="http://doi.org/10.1038/nature0473">http://doi.org/10.1038/nature0473</a></p>
Fish Traits: Fish Trait Data
Data about fish mined from EOL text objects. Most of the data are body size and age. Rights belong with the source of the text from which the datum was mined.<p></p>Data about fish mined from EOL text objects. Most of the data are body size and age. Rights belong with the source of the text from which the datum was mined.
Çiçek et al: Freshwater Turkey Fish
Çiçek, Erdoğan, Sevil Sungur Birecikligil, and Ronald Fricke. "Freshwater fishes of Turkey; a revised and updated annotated checklist." Biharean Biologists 9, no. 2 (2015): 141-157.<p></p>
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