Dataset used for analyzing the critical area thresholds for undergoing rapid increases of established non-native terrestrial vertebrates in global islands
Data files
Apr 25, 2024 version files 478.94 KB
Abstract
Biological invasions are among the threats to global biodiversity and social sustainability, especially on islands. Identifying the threshold of area at which non-native species begin to increase abruptly is crucial for the early prevention strategies. The small-island effect (SIE) was proposed to quantify the nonlinear relationship between native species richness and area but has not yet been applied to non-native species and thus to predict the key breakpoints at which established non-native species start to increase rapidly. Here, based on the extensive global dataset including 769 non-native bird, mammal, amphibian, and reptile species established on 4,277 islands across 54 archipelagos, we detected a high prevalence of SIEs across 66.7% of archipelagos, and approximately 50% of islands have reached the threshold area and thus may be undergoing a rapid increase of biological invasions. SIEs were more likely to occur in those archipelagos with more non-native species introduction events, more established historical non-native species, lower habitat diversity and larger archipelago area range. Our findings may have important implications not only for targeted surveillance of biological invasions on global islands but also for predicting the responses of both non-native and native species to ongoing habitat fragmentation under sustained land-use modification and climate change.
README: Dataset used for analyzing the critical area thresholds for undergoing rapid increases of established non-native terrestrial vertebrates in global islands
https://doi.org/10.5061/dryad.2280gb61f
The dataset includes the data used to conduct the generalized linear mixed models for the presence of the small-island effect (SIE) analyses. And the dataset of the species-area relationship models for the established non-native terrestrial vertebrates in global islands analyses.
Description of the data and file structure
The dataset includes the number of established non-native terrestrial vertebrates per taxon and global islands; the number of established non-native terrestrial vertebrates per taxon and archipelago. And the data was used to analyse the effect of different variables in predicting the presence of SIE based on generalized linear mixed models when using the number of non-native species established earlier on the islands and all the other recorded established non-native species.
This dataset consists of 3 data files:
Number of established non-native terrestrial vertebrates per taxon and global islands.xlsx. Established non-native mammals and birds only recorded the species richness on islands larger than 1square kilometre due to the large sample size, while amphibians and reptiles had no area limit due to the small sample size
IslandArea: Used the USGS Global Islands Database to obtain island areas, standard length in square kilometres measured
Established non-native species richness:The richness of different establishednon-nativetaxon on each island
Number of established non-native terrestrial vertebrates per taxon and archipelago.xlsx. We combined amphibians and reptiles to increase the sample size.
Archipelago: An archipelago name to which the island belongs
IslandArea: Used the USGS Global Islands Database to obtain island areas, standard length in square kilometres measured
Established non-native species richness:The richness of different establishednon-nativetaxon on each island
GLMM_analysis.xlsx. The Cook islands were excluded from the analysis due to lack of data. All predictor variables were log-transformed to increase normality and normalization to dimensional and order of magnitude effects. The sheet of GLMM_analysis was used to analyse the effect of different variables in predicting the presence of SIE based on generalized linear mixed models when using the number of non-native species established earlier on the islands. The sheet of Sensitive_GLMM_analysis was used to analyse the effect of different variables in predicting the presence of SIE based on generalized linear mixed models when using all the other recorded established non-native species.
Arcship: An archipelago name to which the island belongs
Human_population: Obtained the data of human population density at a resolution of 30s from the Gridded Population of the World (GPW, v4) database of the Socioeconomic Data and Applications Center in NASA’s Earth Observing System Data and Information System (EOSDIS) hosted by CIESIN at Columbia University and averaged the data to represent the archipelago.
Average_annual_temperature: Obtained the data for each island from the WorldClim database with a resolution of 30s (i.e., approximately 1 km).
Average_annual_precipitation: Obtained the data for each island from the WorldClim database with a resolution of 30s (i.e., approximately 1 km).
Isolation: The degree to which an island is isolated from the mainland, standard length in kilometres measured
Number_of_Intros: The number of introduction events and averaged the data to represent the archipelago.
GDP: 20 years of GDP per capita data for the countries where the islands were located from the World Bank Open Dataset
Number_of_Port: The number of ports on each island and averaged the data to represent the archipelago.
Habitat_type: The number of habitat types for each island and averaged the data to represent the archipelago.
Archipelago_area_range: the range in island area within an archipelago and is calculated as “areamax – areamin”, standard length in square kilometres measured
Number_of_established_species_earlier: Using the published dates of first records for different taxonomic groups based on the First Record Database. We determined the number of families that existed at least one year before the introduction of our study species. We selected the median of the prior presence of other alien species to represent the data to remove the impact of the imbalance between earlier and later arrival species.
Number_of_established_species: Using the published dates of first records for different taxonomic groups based on the First Record Database. We determined the number of families that all the other recorded established non-native species in the archipelag.