Antarctic Penguin Biogeography Project: Database of abundance and distribution for the Adélie, chinstrap, gentoo, emperor, macaroni, and king penguin south of 60 S

資料紀錄

此資源sampling event的資料已發佈為達爾文核心集檔案（DwC-A），其以一或多組資料表構成分享生物多樣性資料的標準格式。 核心資料表包含 4,055 筆紀錄。

亦存在 2 筆延伸集的資料表。延伸集中的紀錄補充核心集中紀錄的額外資訊。 每個延伸集資料表中資料筆數顯示如下。

此 IPT 存放資料以提供資料儲存庫服務。資料與資源的詮釋資料可由「下載」單元下載。「版本」表格列出此資源的其它公開版本，以便利追蹤其隨時間的變更。

版本

以下的表格只顯示可公開存取資源的已發布版本。

如何引用

研究者應依照以下指示引用此資源。:

Che-Castaldo C, Humphries G, Lynch H, Van de Putte A (2023). Antarctic Penguin Biogeography Project: Database of abundance and distribution for the Adélie, chinstrap, gentoo, emperor, macaroni, and king penguin south of 60 S. Version 2.3. SCAR - AntOBIS. Samplingevent dataset. https://doi.org/10.48361/zftxkr

權利

研究者應尊重以下權利聲明。:

此資料的發布者及權利單位為 SCAR - AntOBIS。 This work is licensed under a Creative Commons Attribution (CC-BY 4.0) License.

GBIF 註冊

此資源已向GBIF註冊，並指定以下之GBIF UUID: f7c30fac-cf80-471f-8343-4ec5d8594661。  SCAR - AntOBIS 發佈此資源，並經由Ocean Biodiversity Information System同意向GBIF註冊成為資料發佈者。

關鍵字

Samplingevent; OCEAN; SOUTHERN OCEAN; ANTARCTICA; BIRDS; PENGUINS; POPULATION ABUNDANCE; BIOGEOGRAPHY

聯絡資訊

地理涵蓋範圍

Penguin breeding colonies located at or very near sea level distributed around the Antarctic continent and along the Antarctic Peninsula as well as on outlying islands in the Southern Ocean.

分類群涵蓋範圍

無相關描述

時間涵蓋範圍

計畫資料

The objective of this project is to compile all available data on the distribution and abundance of Antarctic penguins, and to make that data available for the scientific and management communities.

參與計畫的人員:

取樣方法

This database includes all known records of penguin breeding abundance and distribution south of 60 S. Data sources include peer reviewed scientific manuscripts, expedition reports and other public datasets outside the scientific literature, management and policy documents, and private communications. Abundance estimates are derived primarily from direct ground counting, imagery collected by remotely-piloted aircraft systems, and satellite imagery. Additional data types include counts from aerial, ground, or vessel-based photographs.

方法步驟描述:

1. Data contained within the core database include information collated from peer reviewed scientific manuscripts, expedition reports and other public data outside the scientific literature, management and policy documents, and private communications. These data contain information on breeding pairs of penguins only, and does not contain information on non-breeding distributions or sightings-at-sea. The fundamental unit of this database is the breeding “site”, which represents a population breeding on a single island or, in some cases, a discrete area of a larger landmass. In some cases, a geographically distributed population may be divided into multiple “sites” depending on the logistics of ground surveys, where each “site” can be accessed from a single landing location along the coastline. Rarely, several smaller nesting areas will be aggregated into a single “site” following historical precedent. Each site is associated with a unique four digit alphanumeric code, a name, and a specific geographic location. Note that several species may inhabit a single “site”. Data are ingested into the database manually and extensively checked against existing maps and records to ensure consistency. Because of the complexity of the geography and the different naming systems, site names may be changed between a published record and the database.
2. The database includes data on the number of nests (equivalently, breeding pairs), the number of chicks, or the number of total adults. If multiple measures are available (a count of nests and also a count of chicks), the database will include all data points as separate entries. Each data point is associated with information on the survey date, the survey method, an estimate of the accuracy of each data point, and a reference. In this database, we follow the five-point scale initially used by Croxall and Kirkwood (1979) and described in detail in Supplementary Materials 1 to Che-Castaldo et al. (2017). If the original data source followed the Croxall and Kirkwood scale or reported an uncertainty that could be translated into that scale, our database includes that precision value. Where no information on uncertainty is provided, we estimate the precision based on information provided in the original account.
3. Some data are not eligible to be included in this database. Data that are collected at a spatial scale other than the “site” cannot be included. All data must be “site-wide” census estimates. In keeping with our commitment to open-source data, data that are not in the public domain or remain in private collections unavailable to the public are also not included in this database. Data that cannot be verified and/or cannot be unambiguously assigned to a “site” are not included. Data on the presence of breeding pairs absent a population estimate are included only when no survey data exist.
4. While traditional methods of surveying penguin colonies rely on the direct enumeration of penguin nests by ground-based researchers, more recent surveys have relied on various remote sensing methods. Remotely-piloted aircraft systems (RPAS; also known as drones, quadcopters, or unmanned aerial vehicles) take photographs from a low-altitude flight over the colony and yield photographs sufficient for the individual enumeration of nests, chicks, or adults. While the precision of such counts depends on the timing of the survey and the quality of the imagery, RPAS are capable of providing exceptionally precise counts and are often in the high accuracy category of N1. Satellite imagery can identify the areal extent of breeding colonies through the spectral properties of penguin guano and these estimates can be used to estimate the number of breeding pairs at a “site”. Because the precision of such estimates remains an active research question, all such estimates are assigned the lowest accuracy category of N5 (broadly defined as “order-of-magnitude”).
5. In some cases, data from a single location in a given year is published in multiple venues. However, it is difficult to know whether these multiple outlets represent one actual sampling event because the same event may be associated with different occurrence or abundance records between sources, either because earlier mistakes were corrected or because data were re-analyzed. It also can happen that a single site is surveyed multiple times by separate parties on the same day, arriving at different counts due to observation error. Our approach is to classify an event as a survey conducted at a specific site and time, using a specific sampling protocol, and reported in a specific publication (peer-reviewed article, policy document, thesis, or other type of report), dataset, or personal communication. From each event, there can be one or more occurrence or measurement records, depending on the number of species or life stages reported. In cases where we have information that data from a unique sampling event is published in multiple venues, we retain all records reported in publications and datasets, and drop duplicate records if the duplicate event is based on personal communication. We allow this potential duplication because 1) it is not clear which source is ultimately correct if counts differ between sources and 2) withholding records creates confusion with our end-users as to whether we have overlooked sources of data.

引用文獻

1. Che-Castaldo, C., S. Jenouvrier, C. Youngflesh, K.T. Shoemaker, G. Humphries, P. McDowall, L. Landrum, M.M. Holland, Y. Li, R. Ji, and H.J. Lynch, “Pan-Antarctic analysis aggregating spatial estimates of Adélie penguin abundance reveals robust dynamics despite stochastic noise,” Nature Communications 8:832 (2017). https://doi.org/10.1038/s41467-017-00890-0
2. Croxall, J.P., and E. D. Kirkwood. The distribution of penguins on the Antarctic Peninsula and islands of the Scotia Sea. Cambridge: British Antarctic Survey, 1979.
3. Humphries, G., R. Naveen, M. Schwaller, C. Che-Castaldo, P. McDowall, M. Schrimpf, and H.J. Lynch, “Mapping Application for Penguin Populations and Projected Dynamics (MAPPPD): Data and tools for dynamic management and decision support,” Polar Record 53, 2 (2017): 160–166. https://doi.org/10.1017/S0032247417000055
4. The Scientific Committee on Antarctic Research. (2023). SCAR Report 42 - September 2022 - SCAR Data Policy (2022). Zenodo. https://doi.org/10.5281/zenodo.7825314

額外的詮釋資料