Dataset of Iberian ibex population in Sierra Nevada (Spain)

サンプリング イベント
最新バージョン Sierra Nevada Global Change Observatory. Andalusian Environmental Center, University of Granada, Regional Government of Andalusia により出版 12月 17, 2021 Sierra Nevada Global Change Observatory. Andalusian Environmental Center, University of Granada, Regional Government of Andalusia

DwC-A形式のリソース データまたは EML / RTF 形式のリソース メタデータの最新バージョンをダウンロード:

DwC ファイルとしてのデータ ダウンロード 3,091 レコード English で (48 MB) - 更新頻度: annually
EML ファイルとしてのメタデータ ダウンロード English で (25 KB)
RTF ファイルとしてのメタデータ ダウンロード English で (23 KB)

説明

This dataset provides long-term information about Iberian ibex (Capra pyrenaica hispanica Schimper, 1848) presence in Sierra Nevada (SE Iberian Peninsula), as a result of annual sampling from 1993 to 2018 done by the managers of the Sierra Nevada Natural and National Park. They carried out the transects collecting different variables such as the number of individuals observed, the perpendicular distance of each group of goats to the transect line and, at an individual level and sex as well as age of individuals in the case of males. These data enabled the calculation of population parameters such as density, sex ratio, birth rate and age structure. These parameters are key for Iberian ibex conservation and management, given that Sierra Nevada harbours the largest population of this species in the Iberian Peninsula. The data set we present is structured using the Darwin Core biological standard, which contains 3,091 events (582 transect walk events and 2,509 group sighting events), 5,396 occurrences, and 2,502 measurements. The occurrences include the sightings of 11,436 individuals (grouped by sex and age) from 1993 to 2018 in a total of 88 transects distributed along Sierra Nevada, of which 33 have been continuously sampled since 2008.

データ レコード

この sampling event 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、3,091 レコードが含まれています。

拡張データ テーブルは2 件存在しています。拡張レコードは、コアのレコードについての追加情報を提供するものです。 各拡張データ テーブル内のレコード数を以下に示します。

Event (コア)
3091
Occurrence 
5396
MeasurementOrFacts 
2502

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。:

Granados Torres J E (2021): Dataset of Iberian ibex population in Sierra Nevada (Spain). v1.9. Sierra Nevada Global Change Observatory. Andalusian Environmental Center, University of Granada, Regional Government of Andalusia. Dataset/Samplingevent. https://doi.org/10.15470/3ucqfm

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 Sierra Nevada Global Change Observatory. Andalusian Environmental Center, University of Granada, Regional Government of Andalusia。 To the extent possible under law, the publisher has waived all rights to these data and has dedicated them to the Public Domain (CC0 1.0). Users may copy, modify, distribute and use the work, including for commercial purposes, without restriction.

GBIF登録

このリソースをはGBIF と登録されており GBIF UUID: 5fe81b76-6d2f-4f09-a9e3-301e8e1eb918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Sierra Nevada Global Change Observatory. Andalusian Environmental Center, University of Granada, Regional Government of Andalusia が、このリソースをパブリッシュしました。

キーワード

Capra pyrenaica; Sierra Nevada; long term monitoring; population parameters; Iberian Peninsula; demographic time series; population trends; demographic structure; National Park; conservation and management; Capra pyrenaica; Sierra Nevada; Long term monitoring; Population parameters; Iberian Peninsula; Population trends; National Park; Conservation and management; Distance sampling; FAIR principles; Historical monitoring data; Southern Spain; Samplingevent

連絡先

José Enrique Granados Torres
  • メタデータ提供者
  • 最初のデータ採集者
  • 連絡先
Sierra Nevada National Park Technician
Board of Agriculture, Livestock, Fisheries and Sustainable Development of the Regional Government of Andalusia
Ctra. antigua de Sierra Nevada, Km 7.
18191 Pinos Genil
Granada
ES
+0034 697956343
Andrea Ros Candeira
  • 連絡先
Research Assistant
Laboratorio de Ecología (iEcolab), Instituto Interuniversitario de Investigación del Sistema Tierra en Andalucía (CEAMA), Universidad de Granada
Avenida del Mediterráneo s/n
18006 Granada
Granada
ES
+34 958 249748

地理的範囲

The geographical area where the dataset was obtained corresponds to Sierra Nevada: a mountainous region located in the south-east Iberian Peninsula (37°14'-36°54' N; 2°37'-3°39' W) within the Baetic System, in the called Penibaetic mountain ranges, near to the Mediterranean Sea. Sierra Nevada has the highest summits of the Iberian Peninsula, the peak Mulhacén reaching 3,479 m a.s.l., making this the second-highest mountain range in mainland Europe, after the Alps.

座標(緯度経度) 南 西 [36.901, -3.564], 北 東 [37.19, -2.63]

生物分類学的範囲

The Iberian ibex (Capra pyrenaica hispanica) is an endemic mountain and intermediate sized ungulate, widely distributed throughout much of the Mediterranean mountain ranges of the Iberian Peninsula.

Subspecies Capra pyrenaica hispanica (Iberian ibex)

時間的範囲

開始日 / 終了日 1993-07-08 / 2018-11-07

プロジェクトデータ

The main goal of these projects is to monitor ungulate populations in Sierra Nevada National Park.

タイトル Plan de Gestión de Ungulados Silvestres en el Parque Nacional de Sierra Nevada
識別子 30_00; 10050010; 10040016; 676/2006/A/00; 1571/2007/M/00; 173/2009/M/00; 861/11/M/00; 03/15/M/00; 2016 _00014_M; 2017-00189-M
Study Area Description The climate is Mediterranean; its mountainous condition gives it the characteristics of a continental climate. Biogeographically, five of the six thermotypes defined for the Mediterranean region appear in Sierra Nevada, from the thermomediterranean in the lowest and driest areas of the east to the cryoromediterranean in the highest peaks (Rivas-Martínez, 1987). The mean precipitation gives rise to a dry and subhumid ombrotype, although there are exceptions due to extreme drought (eastern part) and to areas with mean precipitation of more than 1,000 mm/year. Topographically is a heterogeneous area, with strong climatic contrasts between the sunny, dry south-facing slopes and the shaded, wetter north-facing slopes. Sierra Nevada is an important diversity hotspot in the Mediterranean region, with unique ecosystems and endemic species. Overall, Sierra Nevada comprises 27 habitats types from the habitat directive (Annex I of Directive 92/43/CEE). The mountain goat is distributed in Sierra Nevada from the summits to the bottom of the valleys, depending on the seasonality of the ecosystem.
研究の意図、目的、背景など(デザイン) Four different stages in the monitoring of the ibex population can be considered chronologically in Sierra Nevada, characterized by changes in environmental-protection categories and the methodology used to estimate the number of individuals. An initial stage (19th century to first half of the 20th century) includes ibex presence or absence data in particular sites of Sierra Nevada. The second stage (1960-1996) comprises the population inventories of the number of ibex present in the 35,000 hectares of the former National Hunting Reserve. The third stage began in 1989 with the declaration of Sierra Nevada as a Natural Park, with an area of ca. 172,000 hectares, where Distance Sampling has been undertaken since 1993 to estimate the size of this ibex population. The fourth stage began in 1999 with the declaration of part of Sierra Nevada mountain range as a National Park. This new category of protection has not entailed changes in the methodology used to estimate population size, although it has implied a new management model combining one territory where sport hunting is prohibited (National Park) with another where this activity is permitted (Natural Park). This sector has been favoured by improved management of the species as a whole.

プロジェクトに携わる要員:

José Enrique Granados Torres
  • 最初のデータ採集者

収集方法

Sampling based on linear transects has been used since the early 1930s. This method has proved practical, efficient, and relatively inexpensive (Anderson et al. 1979; Burnham et al. 1980). In addition, it has been recommended because it provides the ability to control the reliability of the results (Burnham et al. 1980), this being the main reason for using the Distance Sampling in the census of wild ungulates (Escós and Alados, 1988; Fandos, 1991). In Sierra Nevada, the linear transects method for estimating the size of the ibex population was first used in 1993 (Pérez et al. 1994). A more detailed explanation of the methodology can be found in the Plan específico de gestión de la población de cabra montés (Capra pyrenaica) en el Parque Nacional de Sierra Nevada (Granados et al. 2001) (Specific Management Plan for the Iberian ibex [Capra pyrenaica] population in Sierra Nevada National Park) and in the monitoring methodologies of the Sierra Nevada Global-Change Observatory (Granados et al. 2012). The sampling design (length and location of transects) was carried out following criteria of randomness and stratification. Although a total of 88 transects were sampled throughout the monitoring since 1993, not all of them were sampled every year: before 2008 due to methodological changes and after 2008 due only to weather conditions. This means that the transects designs were made uniform as of 2008, when 33 transects were fixed and were the only ones constantly sampled from 2008 onwards. Overall, one sampling was conducted annually, although in 1995 two samplings were undertaken (summer and autumn) but none in 1994, 1999, 2005, or 2006. The first years the surveys were conducted in summer so that snowfall would not prevent sampling. From 2008 onwards, the 33 fixed transects are sampled annually in autumn whenever the weather conditions allow. Transects are sampled in autumn (before the oestrous cycle), when animals are more active and more easily observed, offering greater probabilities of detecting animals.

Study Extent A total of 88 transects were sampled since 1993, of which 33 have been continuously sampled since 2008. They were classified by the most predominant habitats in the area covered by each transect. Type of habitats are forest, high mountain grasslands, high mountain shrubland, high mountain shrubland and forest, high mountain shrubland and high mountain grasslands, mountain crops, mid mountain scrubland and finally mid mountain scrubland and forest. The representation of the shape (multilinestring) can be found in the footprintWKT element of Darwing Core.
Quality Control Different validation processes were applied in the data cycle stages described below: (a) Field data collection in surveys. During the sampling, the observers fundamentally cross-checked the sightings in situ. (b) Digitalisation and storage in an Access database. In this second step, due to the large volume of data, we implement some controls and validation rules in the Access form in order to reduce human errors and facilitate the digitalisation: - Input masks to control data entry formats (especially date/time data type). - We defined required fields (e.g. transect number and sampling date). - We made lists of predefined values (e.g. group types: male alone, female alone, males, females, females with kids, and mixed groups). - We established some “control fields”, that is, variables that whoever digitalise the data calculated manually to facilitate the information identification. For instance: before introducing the observations, the person had to indicate the total number of groups identified in each survey; the size of each group; the type of group categorised by sex and age; etc. As for transects, a more accurate digitalisation was carried out at a scale of 1:1000 in ArcGIS 10.2 (ESRI, 2013), using as cartographic base the orthophotos from PNOA (Spanish National Program for Aerial Orthophoto). (c) Debugging and disaggregation. The data were processed through the PostgreSQL relational database management system (RDBMS) version 11.3 (PostgreSQL Global Development Group, 2013) together with R version 3.6.0 (R Core Team, 2019) using the package Rpostgres (Wickham et al. 2018) and the spatial extension PostGIS version 2.5.2 (PostGIS Project Steering Committee, 2019), in addition to other packages: DBI (R-SIG-DB, 2018), knitr (Xie, 2019), dplyr (Wickham et al. 2019) and splitstackshape (Mahto, 2019). In this way, we created a validation process in R and SQL code to check specific errors derived from digitalisation and corrected them. When it was necessary, the surveys were re-checked and we ran several validation rounds were run. Specific examples are given below: - We checked if all the information was associated: samplings without any observers assigned, groups that had no observations assigned, etc. - Regarding null values, we checked if all the essential variables were filled out, e.g. males without age variable, groups without size value, etc. - We identified if there was duplicated information. - We revised if there were incongruous data, e.g. the hour when a group was observed had to be between the start and end time of sampling. - We also checked the “control fields” because they were susceptible to contain errors, e.g. the automatic sum of individuals did not match the indicated group size; groups categorised as mixed should be males and females with kids, etc. (d) The standardisation to Darwin Core was done according to the practices recommended by the TDWG guidelines (https://dwc.tdwg.org/terms/).

Method step description:

  1. In each sampling, the observers walk the linear transects taking notes on the ibex groups sighted and collecting different variables such as: the number of individuals observed (group size); the contact hour; and perpendicular distance of each group of goats to the transect line. At the individual level, records are made of physical condition (mainly the presence of lesions caused by sarcoptidosis), the sex of each ibex, and the age in the case of the males. In addition, the date as well as the starting and ending times of the sampling are also recorded, as well as the identity of the observers. The transects are sampled by two or more observers, on foot or by vehicle, when terrain conditions allow, at a speed of no more than 15 km/h. The sampling time is adapted to the dates when the field work is carried out, recording the official time in the surveys. In summer time, the observers walk the transects mainly at dawn and dusk. In the other seasons, the sampling time is extended throughout the day. The optical materials used are binoculars (8 x 35) and a telescope (20 x 40). When circumstances prevent a satisfactory viewing (individuals far away or hidden by the surrounding vegetation, temporary brevity of contact, etc.) sightings are not taken into account. The probability of detecting an individual is related to spatial distribution of the sightings (Buckland et al. 2004) and visibility conditions, habitat coverage, land topography, animal and group size, as well as the density. The method assumes that, if the density is high, many individuals will be sighted up close. If the density is low, only a few individuals will be sighted, and far away. The following premises must be assumed: animals on the transect line are always observed; animals must be immobile when they are observed or located on the spot before they move; no animal should be counted twice; distances and sighting angles must be calculated accurately and sightings are independent events. With all these data collected, the parameters that define the population were: density (number of individuals/km²), sex ratio (number of females/number of males), birth rate (number of kids/number of adult females) and age pyramid mainly for males, in which the size of the horns and body morphology make it easier to determine the years of age or age class to which they belong.

書誌情報の引用

  1. Anderson, D. R., Laake, J. L., Crain, B. R. & Burnham, K. P. Guidelines for line transect sampling of biological populations. J. Wildl. Manag. 43, 70–78 (1979).
  2. Buckland, S. T. et al. Advanced distance sampling. Estimating abundance of biological populations. (Oxford University Press, 2004).
  3. Burnham, K. P., Anderson, D. R. & Laake, J. L. Estimation of density from line transect sampling of biological populations. Wildl. Monogr. 72, 202 (1980).
  4. Escós, J. & Alados, C. Estimating mountain ungulate density in Sierras de Cazorla y Segura. Mammalia 52, 425–428 (1988).
  5. ESRI Environmental Systems Research Institute. ArcGIS Desktop: Release 10.2. (2013).
  6. Fandos, P. La cabra montés (Capra pyrenaica) en el Parque Natural de Cazorla, Segura y Las Villas. (Colección Técnica - ICONA, 1991).
  7. Granados, J. E. et al. Plan de gestión de la cabra montés (Capra pyrenaica) en el Espacio Natural Protegido de Sierra Nevada. in III Congreso Forestal Español (2001).
  8. Granados, J. E., Cano-Manuel, F. J. & Fandos, P. Seguimiento de la población de cabra montés. in Observatorio de Cambio Global Sierra Nevada: metodologías de seguimiento (eds. Aspizua, R., Barea-Azcón, J. M., Bonet, F. J., Pérez-Luque, A. J. & Zamora, R. J.) 79 (Consejería de Medio Ambiente, Junta de Andalucía, 2012).
  9. Mahto, A. splitstackshape: Stack and Reshape Datasets After Splitting Concatenated Values. (2019).
  10. Pérez, J. M., Granados, J. E. & Soriguer, R. C. Population dynamic of the Spanish ibex Capra pyrenaica in Sierra Nevada Natural Park (southern Spain). Acta Theriol. (Warsz.) 39, 289–294 (1994).
  11. PostGIS Project Steering Committee. (2019).
  12. PostgreSQL Global Development Group. (2019).
  13. R Core Team. R: A language and environment for statistical computing. (R Foundation for Statistical Computing, 2019).
  14. (R-SIG-DB) R Special Interest Group on Databases, Wickham, H. & Müller, K. DBI: R Database Interface. (2018).
  15. Rivas-Martínez, S. Memoria del mapa de series de vegetación de España 1: 400.000. (ICONA. Ministerio de Agricultura, Pesca y Alimentación, 1987).
  16. Xie, Y. knitr: A General-Purpose Package for Dynamic Report Generation in R. (2019).
  17. Wickham, H., Ooms, J. & Müller, K. RPostgres: ‘Rcpp’ Interface to ‘PostgreSQL’. (2018).
  18. Wickham, H., François, R., Henry, L. & Müller, K. dplyr: A Grammar of Data Manipulation. (2019).

追加のメタデータ

代替識別子 10.15470/3ucqfm
5fe81b76-6d2f-4f09-a9e3-301e8e1eb918
https://ipt.gbif.es/resource?r=iberianibex