DOI: 10.5061/dryad.q573n5tm1
title: Data from: Climate matching and anthropogenic factors contribute to the colonisation and extinction of local populations during avian invasions

description: Concern about the impacts of biological invasions has generated a great
 deal of interest in understanding factors that determine invasion success.
 Most of our current knowledge comes from static approaches that use
 spatial patterns as a proxy of temporal processes. These approaches assume
 that species are present in areas where environmental conditions are the
 most favourable. However, this assumption is problematic when applied to
 dynamic processes such as species expansions when equilibrium has not been
 reached. In our work, we analyse the roles played by human activities,
 climatic matching, and spatial connectivity on the two main underlying
 processes shaping the spread of invasive species (i.e., colonisation and
 extinction) using a dynamic modelling approach. For this, we used a large
 dataset that has recorded the occurrence of two invasive bird species -the
 ring-necked and the monk parakeets-  in the Iberian Peninsula
 from 1991 to 2016. 
description: Temporal occurrence data for the monk and ring-necked parakeets
 were obtained from a comprehensive database of exotic birds in mainland
 Spain and Portugal, which compiled records of exotic species observed in
 the wild in both countries from 1912 to 2012 through a systematic review
 of scientific and grey literature and observations from local experts [1].
 This dataset was updated until 2016 using the same methodology and
 complemented with ‘human observation’ data from the Global Biodiversity
 Information Facility [2,3]. Locations were incorporated
 to a Geographic Information System (GIS) using a cylindrical equal-area
 projection at 10 km resolution to fit the maximum daily distances covered
 by the species. We used as sampling sites for analyses the 10-km grid
 cells in the Iberian Peninsula. The occurrence data in each sampling sites
 was classified in surveys seasons and replicate observation periods within
 seasons using the date of the records. To account for potential variation
 related to the criteria used to classified the data, we considered three
 alternative sampling schemes: (1) survey seasons of one calendar year with
 two replicate observation periods (Jan-Jun and Jul-Dec), (2) survey
 seasons of two calendar years with two replicate observation periods (each
 of 1 calendar year) and (3) survey seasons of three calendar years with
 two replicate observation periods (each of 1.5 years). To account for
 potential detection biases related to an uneven sampling effort across
 time and space, we included an estimate of sampling effort as a
 survey-specific covariate of detection probability in models. This
 variable was computed as the cumulative value of observation records of
 both native and alien bird individuals retrieved from GBIF (‘human
 observation’ category [4]) in a particular sampling site and observation
 period considered.  As sampling site covariates, we
 calculated the climatic similarity between each of the sites in the study
 area and the species native ranges using multivariate environmental
 similarity surfaces (MESS) and compiled information on three variables
 describing human-transformed environments: (i) the Global Human Influence
 Index [5] and two more specific descriptors of anthropogenic habitats
 known to affect invasions, the percentage of ii) urban environments
 (including urban and built-up areas) and iii) farmland. These two land-use
 variables were derived from data provided by the USGS Land Cover Institute
 (LCI) (https://landcover.usgs.gov/) at 500m resolution using ArcMap
 10.5. More detailed description of methods can be found
 in the manuscript. References: [1]
 Abellán, P., Carrete, M., Anadón, J. D., Cardador, L., & Tella, J.
 L. (2016). Non-random patterns and temporal trends (1912-2012) in the
 transport, introduction and establishment of exotic birds in Spain and
 Portugal. Diversity and Distributions, 22(3), 263–273.
 https://doi.org/10.1111/ddi.12403 [2] GBIF.org (03 June
 2020) GBIF Occurrence Download
 https://doi.org/10.15468/dl.mwj59n [3] GBIF.org (11 May
 2020) GBIF Occurrence Download
 https://doi.org/10.15468/dl.5a4ax6 [4] GBIF.org (03
 June 2020) GBIF Occurrence Download
 https://doi.org/10.15468/dl.mudmhx [5] Sanderson, E.
 W., Malanding, J., Levy, M. A., Redford, K. H., Wannebo, A. V., &
 Woolmer, G. (2002). The human footprint and the last of the wild.
 BioScience, 52, 891–904.
 https://doi.org//10.1641/0006-3568(2002)052[0891:THFATL]2.0.CO;2
description: Description of the files: File
 "README.txt": Description and metadata associated with data
 files and scripts uploaded File
 "input_data_myimon.csv": Temporal occurrence data for
 <em>Myiopsitta monachus</em> in the Iberian Peninsula from
 1975 to 2016. File "input_data_psikra.csv":
 Temporal occurrence data for <em>Psittacula krameri</em> in
 the Iberian Peninsula from 1970 to 2016. File
 "myimon_1y2sampl_data_with_vars.csv": Detection history,
 sampling effort, site covariates and testing data for <em>Myiopsitta
 monachus</em> according to survey seasons of 1 year with two
 replicate observation periods. File
 "myimon_2y2sampl_data_with_vars.csv": Detection history,
 sampling effort, site covariates and testing data for <em>Myiopsitta
 monachus</em> according to survey seasons of 2 years with two
 replicate observation periods. File
 "myimon_3y2sampl_data_with_vars.csv": Detection history,
 sampling effort, site covariates and testing data for <em>Myiopsitta
 monachus </em>according to survey seasons of 3 years with two
 replicate observation periods. File
 "psikra_1y2sampl_data_with_vars.csv": Detection history,
 sampling effort, site covariates and testing data for <em>Psittacula
 krameri </em>according to survey seasons of 1 year with two
 replicate observation periods. File
 "psikra_2y2sampl_data_with_vars.csv": Detection history,
 sampling effort, site covariates and testing data for <em>Psittacula
 krameri</em> according to survey seasons of 2 years with two
 replicate observation periods. File
 "psikra_3y2sampl_data_with_vars.csv": Detection history,
 sampling effort, site covariates and testing data for <em>Psittacula
 krameri</em> in the period 1991-2013 according to survey seasons of
 3 years with two replicate observation periods. File
 "Prepare_datasets_for_PRESENCE.R": Code from R to set the data
 in the format for software PRESENCE. File
 "Run_multiseason_occupancy_models.R": Code from R to conduct
 multiseason occupancy models using the package RPresence in R.