Aranzadi Ringing Scheme (bird ring-recovery data)

データ レコード

この オカレンス（観察データと標本) リソース内のデータは、1 つまたは複数のデータ テーブルとして生物多様性データを共有するための標準化された形式であるダーウィン コア アーカイブ (DwC-A) として公開されています。 コア データ テーブルには、476,743 レコードが含まれています。

この IPT はデータをアーカイブし、データ リポジトリとして機能します。データとリソースのメタデータは、 ダウンロード セクションからダウンロードできます。 バージョン テーブルから公開可能な他のバージョンを閲覧でき、リソースに加えられた変更を知ることができます。

バージョン

次の表は、公にアクセス可能な公開バージョンのリソースのみ表示しています。

引用方法

研究者はこの研究内容を以下のように引用する必要があります。:

Arizaga Martínez J (2024). Aranzadi Ringing Scheme (bird ring-recovery data). Version 2.28. Aranzadi Science Society. Occurrence dataset. https://doi.org/10.15470/gprffz

権利

研究者は権利に関する下記ステートメントを尊重する必要があります。:

パブリッシャーとライセンス保持者権利者は Aranzadi Science Society。 This work is licensed under a Creative Commons Attribution (CC-BY 4.0) License.

GBIF登録

このリソースをはGBIF と登録されており GBIF UUID: 52f2051b-c47e-403a-8e32-04b2f2273c20が割り当てられています。   GBIF Spain によって承認されたデータ パブリッシャーとして GBIF に登録されているAranzadi Science Society が、このリソースをパブリッシュしました。

キーワード

Birds; Europe; Ringing; Ring-recovery data; Aranzadi Sciences Society; Banding; Aves;; Observation; Occurrence

連絡先

地理的範囲

Europe, Africa, Asia and America

生物分類学的範囲

説明がありません

時間的範囲

収集方法

説明がありません

Method step description:

1. Data collection is carried out using the EURING code standards, i.e., controlled vocabularies as stated by EURING (Speek et al. 2001). There are more than 60 fields that, overall, fix the criteria to register data on the ringing scheme, ring code and the use of other marks, species, catching method, sex and age, date, time, geographical position (coordinates), several fields related with individual biological traits (morphology, moult, brood size, etc.), and the condition and circumstance of the encounter (e.g., ringed, shot, etc.). Specific comments to be highlighted regarding methodological questions: (1) Species. Currently, both EURING and the ARS use the IOC (International Ornithological Congress) taxonomy. (2) For the specific case of the ARS databank, we must notice that the data in the field are collected through different methods, depending on the nature and aims of each ringing project. Such methods include, among many other techniques (Bub et al. 1996), mist nets at constant effort sites working under standardized protocols (e.g., Arizaga et al. 2022), chicks captured by hand in their nests (e.g., in colonies of seabirds, raptors breeding either in cliffs or trees, etc.), spring traps baited with insects to capture some territorial small passerine birds, clap nets, etc. Overall, the data can belong to one of the following two main project type categories: (1) projects coordinated directly from the ARS, most of which are based on constant effort sites using standardized mist-netting (Ralph and Dunn 2004), or (2) specific projects, normally created and managed by individual ringers or groups of ringers, e.g. designed to monitor given species (e.g., long-term population dynamics survey protocols), to promote and enhance training capacities, to environmental education and formation, etc. (3) Currently, the coordinates are taken with great accuracy, but in the past the accuracy of a locality was normally of ±5 km. Since birds are very mobile beings, this low accuracy poses no major impact on quality of the data bank. Before inserting new data into the system, a series of filters are applied to guarantee a minimum quality of the data: (1) in all the fields having categorical nature (that is, values are chosen from a closed list of possible values), such as the species and catching method, the system automatically checks for the consistency of values; (2) the coordinates are examined to detect impossible values (e.g., offshore or at an impossible latitude or longitude); (3) in recoveries, it is checked whether recovery date was not before ringing date and whether the species identified when the bird was ringed was the same of that reported for the recovery. The ARS Databank contain a record for each ring set or recovered, that is, each record corresponds to an individual bird. The ARS Databank contains 1773910 records (December 2023) and it is continually updated with new ones. Up to the decade of 1990, the mean number of ringings per decade was around 20,000 (but note that many ringings for the period 1950-1970 remain to be digitalized; Fig. 3A). This pattern started to change in 2000, and definitively in 2010, with almost 1,000,000 ringings, due to the incorporation of many ringers that until then had been using the ‘Ministry of Environment’ rings from the Government of Spain. A similar pattern can be seen for recoveries (Fig 3B). Up to 1990, the mean number of recoveries per decade was around 500 recoveries. Note also that, in older times, ringers were obliged to register only long-distance (>10 km), long-temporal (>1 year) or foreign recoveries, so many within-site recoveries were simply non-recorded within the ARS databank. The summarised bird ring-recovery data set here described (i.e., the data set published in GBIF) derives from the ARS Databank through a data aggregation process. The ARS Databank records are combined in one record in the published dataset when they have the same values for the following parameters: 1. Date. Recorded under "day", "month", "year , and "verbatimEventDate" 2. Species. Recorded using the DwC terms for taxon. 3. Sampling protocol. Recorded under "samplingProtocol", following the EURING controlled vocabulary (Speek et al. 2001). 4. Whether the records correspond to a new ringing or to a recovery, provided under "dynamicProperties" 5. Condition (bird found alive, dead or sick or wounded), according to the EURING controlled vocabulary (Speek et al. 2001), provided under "dynamicProperties" 6. Circumstance of the encounter, according to the EURING controlled vocabulary (Speek et al. 2001), provided under "dynamicProperties". The number of records combined in each case is shown under "individualCount".

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