Gap Selection Index (GSI)

The Gap Index (GSI) allows identifying the areas in the country with missing information and therefore the sites in which additional sampling will improve knowledge on biodiversity. This analysis follows the proposal by García Márquez et al., 2012 to identify the spatial coverage of biological information in databases, the environmental representativeness of these records, as well as the complementarity of the species in the records. The GSI is quantified using values ​​that range between 0 and 1, with 0 being a well-represented sector, and 0 being the underrepresented areas or areas with higher values of information gaps.

Prerequisites

The index is calculated using the records of species present both in data portals (SiB Colombia, SpeciesLink, eBird) and the information that the Humboldt Institute has compiled in recent years (Ceiba). The GSI represents three dimensions as follows:: i) a quantification of the biological records per square kilometer, ii) the environmental representativeness of each occurrence following the methodology proposed by Aguiar et al., 2020 and iii) estimated complementary of species richness based on the first-order Jackknife non-parametric estimator..

For this reason you need the scripts 1_Record_dimension, 2_Ambiental_dimension and 3_Complementarity dimesion obtain the three GSI´s components and then, you must run the4_GSI script to obtain the GSI raster. Also it's necessary the GAPfunctions file, because it contains some of the functions used in the analysis.

Base Data

Dataframe with records of the species and geographical coordinates. The structure of the file requies the following names in the columns: ID, species, lat and lon.

Dependencies

To obtain the results you requires.

• R
• RStudio

Libraries

1. Record dimension

   • sf version 1.0-2
   • maptools version 1.1-1
   • spatstat version 2.2-0
   • raster version 3.4-13

2. Ambiental dimension

   • raster version 3.4-13
   • sf version 1.0-2
   • fmsb version 0.7.1
   • dismo version 1.3-3
   • rgdal version 1.5.23
   • MASS version 7.3.53
   • ROCR version 1.0-11
   • rgeos version 0.5-5

3. Complementarity dimension

   • raster version 3.4-13
   • rgdal version 1.5.23
   • janitor version 2.1.0
   • dplyr version 1.0.7

4. GSI

   • raster version 3.4-13
   • rgdal version 1.5.23
   • hyperSpec version 0.100.0

How to run

We suggest running the routines step by step, following the order of each script. Nevertheless, you can obtain the result for each dimenson independently.

The database must be stored in a root folder to be read throughout the process.

Authors and contact

• Cristian Alexander Cruz-Rodríguez - Investigador Asistente I.Humboldt - Contact
• Elkin Alexi Noguera Urbano - Investigador Adjunto I.Humboldt - Contact
• Iván gonzález
• Laura Carolina Bello
• Maria Cecilia Londoño - Investiadora Titular I.Humboldt

License

This project is licensed under the MIT License - see the LICENSE file for details.

Final considerations

This product contributes to the Annual Operational Plan to the Instituto Humboldt for the year 2021. Specifically to the activity associated with generating a repository with the codes used for the standardization of processes for raising baselines and monitoring biodiversity.