Palmer Penguins

The Palmer penguins dataset by Allison Horst, Alison Hill, and Kristen Gorman was first made publicly available as an R package. The goal of the Palmer Penguins dataset is to replace the highly overused Iris dataset for data exploration & visualization. However, now you can use Palmer penguins on huggingface!

  License

Data are available by CC-0 license in accordance with the Palmer Station LTER Data Policy and the LTER Data Access Policy for Type I data.… See the full description on the dataset page: https://huggingface.co/datasets/SIH/palmer-penguins.

Context

The palmer penguins data contains size measurements for three penguin species observed on three islands in the Palmer Archipelago, Antarctica.

Content

These data were collected from 2007 - 2009 by Dr. Kristen Gorman with the Palmer Station Long Term Ecological Research Program, part of the US Long Term Ecological Research Network. The data were imported directly from the Environmental Data Initiative (EDI) Data Portal, and are available for use by CC0 license (“No Rights Reserved”) in accordance with the Palmer Station Data Policy.

The Antarctic Penguin Biogeography Project is an effort to collate all known information about the distribution and abundance of Antarctic penguins through time and to make such data available to the scientific and management community. The core data product involves a series of structured tables with information on known breeding sites and surveys conducted at those sites from the earliest days of Antarctic exploration through to the present. This database, which is continuously updated as new information becomes available, provides a unified and comprehensive repository of information on Antarctic penguin biogeography that contributes to a growing suite of applications of value to the Antarctic community. One such application is the Mapping Application for Antarctic Penguins and Projected Dynamics (MAPPPD; www.penguinmap.com) - a browser-based search and visualization tool designed primarily for policymakers and other non-specialists (Humphries et al., 2017), and ‘mapppdr’, an R package developed to assist the Antarctic science community. The Antarctic Penguin Biogeography Project has been funded by the National Aeronautics and Space Administration (NASA), the Pew Fellowship for Marine Conservation, and the Institute for Advanced Computational Sciences at Stony Brook University. Antarctic Penguin Biogeography Project: Database of abundance and distribution for the Adélie, chinstrap, gentoo, emperor, macaroni, and king penguin south of 60 S is an occurrence and sampling event type dataset published by SCAR-AntBIOS. This dataset contains records of Pygoscelis adeliae, Pygoscelis antarctica, Pygoscelis papua, Eudyptes chrysolophus, Aptenodytes patagonicus, and Aptenodytes forsteri annual nest, adult, and/or chick counts conducted during field expeditions or collected using remote sensing imagery, that were subsequently gathered by the Antarctic Penguin Biogeography Project from published and unpublished sources, at all known Antarctic penguin breeding colonies south of 60 S from 1892-11-01 to 2022-02-12. The data is published as a standardized Darwin Core Archive and includes an event core and occurrence and eMoF extensions. This dataset is published by SCAR-AntOBIS under the license CC-BY 4.0. Please follow the guidelines from the SCAR Data Policy (SCAR, 2023) when using the data. If you have any questions regarding this dataset, please contact us via the contact information provided in the metadata or via data-biodiversity-aq@naturalsciences.be. Issues with dataset can be reported at https://github.com/biodiversity-aq/data-publication/ This dataset is part of the Antarctic Penguin Biogeography Project project funded by National Aeronautics and Space Administration (NASA), the Pew Fellowship for Marine Conservation, and the Institute for Advanced Computational Sciences at Stony Brook University.

This dataset includes Adelie penguin colonies and coastline digitised from Eric J. Woehler, G.W. Johnstone and Harry R. Burton, 'ANARE Research Notes 71, The distribution and abundance of Adelie penguins, Pygoscelis adeliae, in the Mawson area and at the Rookery Islands (Specially Protected Area 2), 1981 and 1988'. Copies of the maps as PDF and TIFF downloads are available through the SCAR Map Catalogue (see the links in the related links section). Map 1 [Mawson area, including the Rookery Islands SPA] Map 2 [Rookery Islands SPA] Map 3 [Islands near Mawson Station] Map 4 [Rookery Island 1] Map 5 [Rookery Island 2] Map 6 [Rookery Island 3] Map 7 [Rookery Island 3A] Map 8 [Rookery Island 4] Map 9 [Rookery Island 5] Map 10 [Rookery Island 6] Map 11 [Rookery Island 7] Map 13 [Rookery Island 9] Map 14 [Rookery Island 10 and 11] Map 15 [Giganteus Island] Map 16 [Rookery Island] Map 17 [Bechervaise Island] Map 18 [Verner Island] Map 19 [Petersen Island] Map 20 [Welch Island Sheet 1 of 2] Map 20 [Welch Island Sheet 2 of 2] Map 21 [Klung Island] Map 22 [Un-named island west of Klung Island] Map 23 [Gibbney Island] Map 24 [Un-named island west of Forbes Glacier] Map 25 [Islands surveyed in 1981-82 where Adelie penguin colonies were located]

On February 8, 2021, Deception Island Chinstrap penguin colonies were photographed during the PiMetAn Project XXXIV Spanish Antarctic campaign using unmanned aerial vehicles (UAV) at a height of 30m. From the obtained imagery, a training dataset for penguin detection from aerial perspective was generated. The penguin species is the Chinstrap penguin (Pygoscelis antarcticus). The dataset consists of three folders: "train", containing 531 images, intended for model training; "valid", containing 50 images, intended for model validation; and "test", containing 25 images, intended for model testing. In each of the three folders, an additional .csv file is located, containing labels (x,y positions and class names for every penguin in the images), annotated in Tensorflow Object Detection format. There is only one annotation class: Penguin. All 606 images are 224x224 px in size, and 96 dpi. The following augmentation was applied to create 3 versions of each source image: * Random shear of between -18° to +18° horizontally and -11° to +11° vertically This dataset was annotated and exported via www.roboflow.com The model Faster R-CNN64 with ResNet-101 backbone was used to perform object detection tasks. Training and evaluation tasks were performed using the TensorFlow 2.0 machine learning platform by Google.

Population reference: CHI (Chiloé), PUP (Pupuya), ALG (Algarrobo), CAC (Cachagua), TIL (Tilgo), PAJ (Pajaros), CHO (Choros), CHA (Chañaral), GRA (Isla Grande), AZU (Pan de Azucar), and PSJ (Punta San Juan).

Study system This study was conducted on Cape Crozier, Ross Island, Antarctica (77°27’15.00”S, 169°13’45.00”E) during the summers of 2012–13 and 2013–14 (hereafter 2012 and 2013, respectively). Cape Crozier is the largest Adélie Penguin colony in the southern Ross Sea and one of the largest for the species (Lynch and LaRue 2014). It is surrounded by hundreds of nesting South Polar Skuas (S. maccormicki), with most of the colony within skua foraging territories (Wilson et al. 2016). Our study included 43 chicks in 2012 and 69 in 2013 (112 total). Across both years, 84 chicks survived to the crèche stage and could be used to model crèching size and age and survival during that period. The mean crèching age was 21.3 days (SE = 0.46, range 15-26, n = 33) in 2012, and 18.9 days (SE = 0.41, range 10-25, n = 51) in 2013. Across the entire colony, not just study chicks, we observed that substantially more chicks died from apparent starvation in 2013 than in 2012. Although the average amount of...

This dataset contains information on the distribution of Penguins and their breeding colonies in the Australian Antarctic sector, as of 1983. It forms Australia's contribution to the International Survey of Antarctic Seabirds (ISAS). The results are listed in the documentation. These include counts of chicks, adults and nests, as well as colony distribution maps. The survey includes Emperor Penguins, Adelie Penguins, King Penguins, Gentoo Penguins, Macaroni Penguins, Rockhopper Penguins, Chinstrap Penguins and Royal Penguins.

Original data were taken from ANARE Research Notes 9.

Only data from the Australian Antarctic Territory is described in this metadata record.

Images of rough maps detailing the locations of each of the colonies are available for download from the url given below. Observation and count data have been incorporated into the Australian Antarctic Data Centre's Biodiversity Database.

The data are presented in the format of Croxall and Kirkwood (1979) as recommended by the Report of the Subcommittee on Bird Biology held in Pretoria. In the tables all counts are estimates of the number of breeding pairs except where otherwise indicated. The numerical estimates and counts are of three kinds, indicated by the coded N, C or A:

NESTS (N = count of NESTS or breeding/incubating pairs) The most accurate count of breeding pairs is that derived from a count of nests. This is usually carried out during incubation, but may also be made while chicks are still in the nest, before creches are formed. Such counts are only underestimates of breeding pairs by the number of breeding failures sustained between egg laying and the date of the count.

CHICKS (C = count of CHICKS) Late in the breeding season the only counts possible are those of chicks. In general most pygosceild penguins raise one chick per pair per season, so a count of chicks gives a reasonable approximation of the original number of breeding pairs. However, season to season variation in breeding success can often be considerable. For example Yeates (1968) reports breeding success in Adelie Penguins at Cape Royds of twenty-six per cent, forty-seven per cent and sixty-eight per cent ever three seasons. Also, Macaroni Penguins only raise approximately 0.5 chicks per pair per season, so that chick counts of this species may be a considerable underestimate of the true breeding population.

ADULTS (A = count of ADULTS) Many colony counts and estimates were expressed as total number of birds or adults. These figures are difficult to interpret as they depend on the time during the breeding season at which they were made. For some days prior to and until laying is finished, both birds of a pair will be present at the nest site while during incubation it is more likely that only one bird will be present. A further problem with counts of 'birds' is that they may include individuals who are not breeding and this gives an overestimate of the true breeding population. The counts of 'birds' or 'adults' which appear unqualified in log books have been divided by two to give an estimate of the number of breeding pairs. It must be stressed therefore that these counts are the least accurate.

The degree of accuracy of these counts is inevitably highly variable and it is often difficult to ascertain on what basis a figure was arrived at. For the present survey counts have been allocated to one of five degrees of accuracy.

1. Pairs/nests essentially individually counted. The count is probably accurate to better than + 5 per cent.

2. Numbers of pairs in a known area counted individually and knowing the total area of the colony, the overall total calculated. This technique is useful for very large colonies.

3. Accurate estimates; + 10-15 per cent accuracy.

4. Rough estimate; accurate to 25-50 per cent.

5. Guesstimate; to nearest order of magnitude.

Many references are in the form ANARE (Johnstone) or simply ANARE. These refer to unpublished reports extracted from ANARE station biology logs. Those in the form Budd (1961) refer to published records and are listed in the references at the end of this publication.

The locations of some colonies are indicated on maps. Place names that (as of 1983) have not yet been approved are shown in the tables and on the maps in parentheses, for example: (ROCKERY ISLAND).

Three skeletons collected from the late Oligocene Kokoamu Greensand of New Zealand are among the most complete Paleogene penguins known. These specimens, described here as Kairuku waitaki gen. et sp. nov. and Kairuku grebneffi sp. nov., reveal for the first time the unique proportions of a giant fossil penguin and the morphology of many key elements of the stem penguin skeleton associated with underwater flight, including the first reasonably complete sternum, one of only two complete forelimbs and the first described pygostyle. Relative proportions of the trunk, flippers and hindlimbs can now be determined from a single individual, offering insight into the body plan of stem penguins and improved constraints on size estimates for 'giant' taxa. Kairuku is characterized by an elongate, narrow sternum, a short and flared coracoid, an elongate narrow flipper and a robust hindlimb. The pygostyle of Kairuku lacks the derived triangular cross-section seen in extant Spheniscidae, suggesting the rectrices attached in a more typical avian pattern and the tail may have lacked the propping function utilized by living penguins. New materials described here, along with restudy of previously described specimens, resolves several long-standing phylogenetic, biogeographic and taxonomic issues stemming from the inadequate comparative material of several of the first-named fossil penguin species. An array of partial associated skeletons from the Eocene-Oligocene of New Zealand historically referred to Palaeeudyptes antarcticus or Palaeeudyptes sp. are recognized as at least five distinct species: Palaeeudyptes antarcticus, Palaeeudyptes marplesi, Kairuku waitaki, Kairuku grebneffi and an unnamed Burnside Formation species

Population reference: CHI (Chiloé), PUP (Pupuya), ALG (Algarrobo), CAC (Cachagua), TIL (Tilgo), PAJ (Pajaros), CHO (Choros), CHA (Chañaral), GRA (Isla Grande), AZU (Pan de Azucar), and PSJ (Punta San Juan).

Code and data for a multispecies IPM (integrated population model) on South polar skua and Adélie penguin. Please contact me for any questionMail: lise.viollat@protonmail.comTwitter: @LiseViollat Code files : - multispeIPM_skua_adelie_CODE.txt: Code of the multispecies IPM (Bugs language) - Parameter_init.txt : initialisation of the parameters used for the model Bayesian posterior distributions of the multispecies IPM were approximated with Markov chain Monte Carlo (MCMC) algorithms. Two independent chains MCMC of 30 000 iterations were used, with a burn-in period of 10 000 iterations. Gelman-Rubin convergence diagnostics (Brooks and Gelman, 1998) were below 1.1 for each parameter and the mixing of the chains was satisfactory. The analyses were performed using JAGS (Plummer, 2003; version 4.3.0) and program R (R version 4.0.5). Data files : From 1988 to 2018 - Count_adelie.csv: Number of breeding pairs of Adelie Penguins and Chicks by year - Count_skua.csv : Number of occupied sites, breeder, non breeder and chicks of South polar Skua by year - Skua_matrix.txt: CMR data on South polar skua CMR code: 0 = non-observed 1 = seen as non-breeder 2 = seen as failed breeder 3 = seen as successful breeder with one fledged chick 4 = seen as successful breeder with two chicks fledged chicks 5 = seen in a uncertain state The last column is if the individual as been seen dead (-1) or not (1) - Climat_cova.txt: climatic covariables (Air temperature (AT), sea ice concentration (SIC), sea surface temperature anomalies (ssta), and number of emperor penguin dead chicks - N_immigrant: number of new individuals seen for the first time at the colony by year

The NSF-supported research icebreaker Laurence M. Gould operates year-round in support of the U.S. Antarctic Program, carrying out global change studies in biological, chemical, physical, and oceanographic disciplines. This data set consists of underway data from leg LMG0009 on the R/V Laurence M. Gould. This leg started at Punta Arenas, Chile and ended at Punta Arenas, Chile.

These represent the speed filtered GPS dataset and associated CRAWL models (R package crawl, v2.2.1) for 83 individual Chinstrap penguins instrumented between November 2018 and February 2019 at Deception Island at Bailey Head and Macaroni Point. Each individual penguin has a unique identifier (D_Rxx_Pxx) The data is tidy (one row = 1 observation = 1 location) and clean (no NAs; no duplicated lines, tracks cut off by deployment date + 24h and recovery date; points less than 2 min apart were removed for D_R4_P10). Each track is matched to the individual penguin metadata (ID, instrument type, deployment, recovery dates, original file, breeding status) The data is stored as a tibble in a R environment, contains 84,550 GPS locations and 24 columns. The GPS locations are available unprojected (lat lon " +proj=lonlat +ellps=WGS84 +datum=WGS84"; EPGS 4326) and projected in Polar stereographic (+proj=stere +lat_0=-90 +lat_ts=-71 +lon_0=0 +x_0=0 +y_0=0 +datum=WGS84 +units=m +no_defs; EPSG:3031). Also included are pdf images of individual tracks, and the shapefile (polygon) of Deception Island used as a mask.

Collection of code and dataframes used to calculate ice support vector-based metrics and run ice support models in R for Ecology submission.

Dataframes:

IceSupportDF_envinddatana.RData - Data frame used to run both distance and support models.

Code:

Final_Distance_Model_Ecology.R - Code used to run and evaluate distance model

Final_Support_Model_Ecology.R - Code used to run and evaluate support model

ice_vector_metrics_Ecology.R - Code showing mathematical functions listed in manuscript for vector based ice support metrics were calculated

This dataset includes:\r \r (i) a 2 metre resolution digital elevation model (DEM) of Shirley Island, Windmill Islands, Antarctica;\r \r (ii) reliability data for the DEM;\r \r (iii) contours interpolated from the DEM; and \r \r (iv) an orthophoto created using the DEM.\r \r The data are stored in the UTM zone 49 map projection. \r \r The horizontal datum is WGS84. \r \r The data were created by Robert Anders, Centre for Spatial Information Science, University of Tasmania, Australia to support the postgraduate research of Phillipa Bricher into the nesting sites of Adelie Penguins.\r \r See a related URL below for a map showing Shirley island.

Distribution, abundance and dates of relict Adelie Penguin colonies in the Australian Antarctic Territory (AAT).

Current mapping efforts have focused on the Windmill Islands in preparation for a PhD study to commence in 2004/05 with the two investigators.

The planned PhD study will work at either the Windmill Islands or the Vestfold Hills.

This project integrates ASAC projects 1219 and 1322 (ASAC_1219, ASAC_1322).

The fields in the excel spreadsheet are:

Radiocarbon Samples Isotope Samples Site - list of precise locations provided in the downloadable paper Level - horizontal stratum (depth), given in 5cm blocks Species Material Weight (g) Notes Lab no. Uncorrected Date (BP) - (day) Standard Deviation Delta R - range of corrected date for sample, 2 standard deviations either side of the mean Mean - estimated mean of sample date

See the paper included in the download file for further information.

Vortex project input file for PVA of Humboldt penguins, completed by workshop participants in Lima, Peru, 2019. Report of the full PHVA and PVA workshop is provided in:

McGill, P., A. Baker, R. Lacy, R. Paredes, J. Reyes, J. Rodriguez, A. Tieber, & R. Wallace, (eds.) 2021. Humboldt penguin (Spheniscus humboldti) Population and Habitat Viability Assessment Workshop Final Report. IUCN SSC Conservation Planning Specialist Group, Apple Valley, MN, USA. A PDF of this workshop report can be downloaded at: www.cpsg.org.

Breeding distribution of the Adelie penguin, Pygoscelis adeliae, was surveyed with Landsat-7 Enhanced Thematic Mapper Plus (ETM+) data along the coastline of Antarctica, an area covering approximately 330° of longitude. An algorithm was designed to minimize the radiometric contribution from exogenous sources and to retrieve Adelie penguin colony location and spatial extent from the ETM+ data. In all, 9143 individual pixels were classified as belonging to an Adelie penguin colony class out of the entire dataset of 195 ETM+ scenes, where the dimension of each pixel is 30 m by 30 m, and each scene is approximately 180 km by 180 km. Pixel clustering identified a total of 187 individual Adelie penguin colonies, ranging in size from a single pixel (900 m**2) to a maximum of 875 pixels (0.788 km**2). Colony retrievals have a very low error of commission, on the order of 1 percent or less, and the error of omission was estimated to be 2.9 percent by population based on comparisons with direct observations from surveys across east Antarctica. Thus, the Landsat retrievals can successfully locate Adelie penguin colonies that account for ~97 percent of a regional population. Geographic coordinates and the spatial extent of each colony retrieved from the Landsat data are available publically. Regional analysis found several areas where the Landsat retrievals suggest populations that are significantly larger than published estimates. Six Adelie penguin colonies were found that are believed to be unreported in the literature.

This data set contains raw, annotated, and synthesized data used in the analysis by Hinke et al. (2021) titled "Serendipitous observations from animal-borne video loggers reveal synchronous diving and equivalent prey capture rates in chinstrap penguins" (DOI:10.1007/s00227-021-03937-5). The data derive from field work to monitor the diving and predation behaviors of two chinstrap penguins (Pygo...

The NSF-supported research icebreaker Laurence M. Gould operates year-round in support of the U.S. Antarctic Program, carrying out global change studies in biological, chemical, physical, and oceanographic disciplines. This data set consists of underway data from leg LMG0207 on the R/V Laurence M. Gould. This leg started at Punta Arenas, Chile and ended at Punta Arenas, Chile.