Dataset of Iberian ibex population in Sierra Nevada (Spain)

José Enrique Granados Torres; José Enrique Granados Torres

doi:10.15470/3ucqfm

Dataset of Iberian ibex population in Sierra Nevada (Spain)

Citation

Granados Torres J E (2021). Dataset of Iberian ibex population in Sierra Nevada (Spain). Version 1.9. Sierra Nevada Global-Change Observatory (UGR-JA). Sampling event dataset https://doi.org/10.15470/3ucqfm accessed via GBIF.org on 2024-12-12.

Description

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.

Sampling Description

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.

Sampling

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.

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 steps

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.

Taxonomic Coverages

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.

Capra pyrenaica hispanica
common name: Iberian ibex rank: subspecies

Geographic Coverages

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.

Bibliographic Citations

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). -
Buckland, S. T. et al. Advanced distance sampling. Estimating abundance of biological populations. (Oxford University Press, 2004). -
Burnham, K. P., Anderson, D. R. & Laake, J. L. Estimation of density from line transect sampling of biological populations. Wildl. Monogr. 72, 202 (1980). -
Escós, J. & Alados, C. Estimating mountain ungulate density in Sierras de Cazorla y Segura. Mammalia 52, 425–428 (1988). -
ESRI Environmental Systems Research Institute. ArcGIS Desktop: Release 10.2. (2013). -
Fandos, P. La cabra montés (Capra pyrenaica) en el Parque Natural de Cazorla, Segura y Las Villas. (Colección Técnica - ICONA, 1991). -
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). -
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). -
Mahto, A. splitstackshape: Stack and Reshape Datasets After Splitting Concatenated Values. (2019). -
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). -
PostGIS Project Steering Committee. (2019). -
PostgreSQL Global Development Group. (2019). -
R Core Team. R: A language and environment for statistical computing. (R Foundation for Statistical Computing, 2019). -
(R-SIG-DB) R Special Interest Group on Databases, Wickham, H. & Müller, K. DBI: R Database Interface. (2018). -
Rivas-Martínez, S. Memoria del mapa de series de vegetación de España 1: 400.000. (ICONA. Ministerio de Agricultura, Pesca y Alimentación, 1987). -
Xie, Y. knitr: A General-Purpose Package for Dynamic Report Generation in R. (2019). -
Wickham, H., Ooms, J. & Müller, K. RPostgres: ‘Rcpp’ Interface to ‘PostgreSQL’. (2018). -
Wickham, H., François, R., Henry, L. & Müller, K. dplyr: A Grammar of Data Manipulation. (2019). -

Contacts

José Enrique Granados Torres
originator
position: 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.
Pinos Genil
18191
Granada
ES
Telephone: +0034 697956343
email: josee.granados@juntadeandalucia.es
userId: http://orcid.org/0000-0002-9787-9896

José Enrique Granados Torres
metadata author
position: 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.
Pinos Genil
18191
Granada
ES
Telephone: +0034 697956343
email: josee.granados@juntadeandalucia.es
userId: http://orcid.org/0000-0002-9787-9896

José Enrique Granados Torres
originator
position: 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.
Pinos Genil
18191
Granada
ES
Telephone: +0034 697956343
email: josee.granados@juntadeandalucia.es
userId: http://orcid.org/0000-0002-9787-9896

José Enrique Granados Torres
administrative point of contact
position: 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.
Pinos Genil
18191
Granada
ES
Telephone: +0034 697956343
email: josee.granados@juntadeandalucia.es
userId: http://orcid.org/0000-0002-9787-9896

Andrea Ros Candeira
administrative point of contact
position: Research Assistant
Laboratorio de Ecología (iEcolab), Instituto Interuniversitario de Investigación del Sistema Tierra en Andalucía (CEAMA), Universidad de Granada
Avenida del Mediterráneo s/n
Granada
18006
Granada
ES
Telephone: +34 958 249748
email: andrearos@ugr.es
userId: http://orcid.org/0000-0001-9535-6541