2.3 Ecology niche analysis

Using observations to compare the differences in environmental attributes of recorded sites between the native and exotic ranges in environmental space is a main approach for quantifying niche changes (Guisan et al., 2014). Environmental context similarity is a premise of ENM niche analysis, and a valid conclusion can only be drawn under the same or similar environmental conditions (Escobar et al., 2016; Petitpierre et al., 2012). To determine the analogy environments between the native and new distribution ranges, we adopted three metrics to test as Qiao et al, (2017). We used Mobility-Oriented Parity (MOP) (Owens et al., 2013) and multivariate environmental similarity surface (MESS) to measures environmental similarity (Elith et al., 2010). Both methods are implemented in the NicheToolbox (Osorio-Olvera et al., 2016). Then we employed ExDet to identify similar or novel environments between native and new distribution areas (Mesgaran et al., 2014). ExDet identifies areas with novel univariate (novelty Type 1) or combinations (novelty Type 2) of environmental parameters, and can identify the most influential environmental variables leading to non-analogous environments between the compared areas (Mesgaran et al., 2014).
To identify niche overlap and population utilization, Niche A and Ecospat were used. We used the first three components in Niche A software (Qiao et al., 2016) to display minimum volume ellipsoid (MVE) generated from observations of three study areas, analyze the overlap of three ellipsoids, and determine analogous and non-analogous environments, then projected these environments in geographical space to identify population utilization under analogous conditions according to a species distribution map (Elliott et al., 2020).
After determining the occupation of niche and similar environments, the first two PCA axes were selected at a resolution of 100×100 to compare species density differences between the native and new distribution areas. Meanwhile, we used the Schoener’s D metric to calculate the degree of overlap in the ecospat package (Di Cola et al., 2017) in R (R Core Team, 2013), including four indices overlap (D), unfilling, stability, and expansion (Guisan et al., 2014; Petitpierre et al., 2012). Overlap (D) measures niche overall match between two entities, from 0 (no Overlap) to 1 (complete Overlap) (Broennimann et al., 2012). When we overlapped the native and exotic niches, the proportion of exotic niche that did not overlap with the native niche was termed expansion, the exotic niche overlapping with the native niche was termed stability, and the native niche that did not overlap with the exotic niche was termed unfilling (Guisan et al., 2014). In addition, in order to test whether or not the niche is equivalent and similar, we used equivalency and similarity tests in ecospat (Broennimann et al., 2012; Warren et al., 2008). Niche equivalency tests were performed to determine whether the native and invaded niche generated by occurrences were identical, and sample data were randomly run 1000 times to calculate the overlap scores and actual overlap. When the actual overlap value was within 95% of the simulated value, the niche equivalency hypothesis could not be rejected. Niche similarity assesses whether the niches of two regions are higher or lower than the random expectation generated when the niche of one study area overlaps with the background of another study area after 1000 randomizations. If the actual overlap value was greater than 95% of the simulated value, the actual overlap was significantly greater than expected. According to the results of Niche A, we decided to compare the new southern and present niches to the original native population as niche conservatism (the alternative = ”greater”), and to test the new northern and original native population niches as niche divergence (the alternative = ”lower”). Finally, the ecospat package was used to identify response range differences of the 10 environmental variables between the new northern and original native populations.