Non-native species drive biotic homogenization, but it depends on the realm, beta diversity facet and study design: A meta-analytic systematic review
Data files
Dec 18, 2021 version files 654.85 KB
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Petsch_et_al_2021_Meta-Homog..xls
Abstract
While reducing the species richness of invaded communities is a well-known consequence of biological invasions, non-native species can also reduce variability between communities over time (i.e., beta diversity) in a process known as biotic homogenization. Although biotic homogenization due to non-native species is a common topic of theoretical reviews, we believe no global meta-analysis on the effect of non-native species on beta diversity has been carried out yet. Here, we systematically show that non-native species drive biotic homogenization, but it depends on the realm, beta diversity facet and study design. Biotic homogenization was more intense in marine and freshwater ecosystems than in terrestrial ecosystems. We also found that non-native species reduced both taxonomic and phylogenetic beta diversity, but not the functional beta diversity. Finally, we observed more intense effects using “before vs. after invasion” followed by “uninvaded vs. invaded sites” while the effect size of studies using “communities associated with native vs. non-native species” did not differ from zero. Our findings highlight that non-native species contribute to biotic homogenization as a prevalent pattern in communities worldwide, and that biodiversity conservation strategies should go beyond investigating the reduction in the number of species by also taking into account beta diversity in its multiple facets.
Methods
Data sampling
We performed a systematic search on the Web of Science (WoS) on March 2020 using the following combination of keywords and Boolean arguments: ("invas*" OR "biological invas*" OR "non-native" OR "exotic" OR "alien*") AND ("beta diversit*" OR "β diversit*" OR "dissimilar*" OR "bio* homog*"). We used this keyword combination because it is comprehensive enough regarding literature on biotic homogenization due to non-native species and it returned a viable number of studies for screening. The search was made on “Topic” and considering WoS main collection. We found a total of 1,468 studies in our WoS search. We excluded the non-primary studies (e.g., theoretical reviews or simulation-based studies), out of scope studies (those that did not assess the effect of non-native species on beta diversity or similarity) and duplicates. We retained only studies that planned to compare with and without non-native species effect. When evaluating the abstracts, 1,018 articles were excluded. Consequently, we evaluated 450 full-texts. Of these, 407 articles were excluded because they were out of scope, were not primary studies, did not present enough data (e.g., lack of dispersion measures, control and treatment mean beta diversity), the design was not appropriate (e.g., the effect of non-native species confused with other variables), or the control was not adequate (e.g., sampling native and non-native species in the same sampling units and then splitting the dataset in native and non-native species to estimate their respective beta diversities). Therefore, we included a total of 43 articles in our systematic review (see Figure 1 and Table S1).
From the selected studies, we extracted sample size, measures of central tendency (mean and median) and dispersion (standard deviation, standard error, confidence intervals and amplitude) for both control (without non-native species effect) and treatment (with non-native species effect) (Borenstein et al. 2009). For studies that did not provide mean and standard deviation, we estimated these values from medians and amplitudes according to Hozo et al. (2005) or from standard errors and confidence intervals according to Lajeunesse (2013). We also obtained information about the realm (terrestrial, freshwater or marine), taxa of the non-native species and from the resident community (algae, higher plants, fungi, invertebrates, or vertebrates), type of study (experimental, field sampling or species list), beta diversity facet (taxonomic, functional or phylogenetic), and study design. We also extracted spatial extent (largest distance between the farthest sample sites, in km) from maps, text or coordinates provided by each study.
Regarding studies design, we classified studies sampling the same sites before and after a non-native species invasion as “before vs. after invasion”. Comparisons “before vs. after invasion” assume that differences in beta diversity between the periods are due to the non-native species. We classified studies that conducted a spatial sampling with sites with and without non-native species as “uninvaded vs. invaded sites”. In those cases, researchers assume that invaded sites had comparable beta diversity to uninvaded sites in the same region, and everything being equal, changes in beta diversity were due to non-native species. We classified studies that sampled a set of sites with the presence of both a native and non-native species which were used as habitat for other communities as “communities associated with native vs. non-native species”. Examples of such experimental designs are aquatic fungi decomposing native or non-native vegetal material (Biasi et al. 2020) or arthropods exploring native or non-native trees (Buchholz et al. 2015). In those studies, differences in beta diversity of associated communities may arise due to the new features provided by the non-native species or because non-native species do not share evolutionary history with native communities. Finally, we classified studies that quantified beta diversity in communities from the native and non-native area of occurrence of a given non-native species as “native vs. invaded range”. These studies assume that beta diversity in both regions is comparable, and changes observed in the invaded range are due to unshared evolutionary history with the resident native community.