Current and projected future risks of freshwater fish invasions in China

Abstract

Biological invasions are a primary threat to global biodiversity, supporting mounting calls for the development of early‐warning systems to manage existing and emerging invaders. Here, we evaluated the geographical pattern of invasion risks of currently established and potentially emerging nonnative freshwater fishes in China by jointly considering the threats of introduction and establishment under climate change. Introduction threats were estimated according to proxies of human activities and propagule pressure for two primary pathways (aquaculture or ornamental). Establishment threats for 51 current and 64 potential invaders (based on whether having established or not self‐sustaining populations) were assessed using an ensemble of species distribution models under current (1960–1990) and future [2041–2060 (2050s) and 2061–2080 (2070s)] climate scenarios. Geographical patterns of invasion risk were then assessed by overlaying the threats of introduction and establishment for each species group both in present‐day and in the future. We found that eastern China displayed the highest threat of introduction. By contrast, southeastern and northwestern regions were identified as the most suitable for the establishment of both current and potential invaders. Under a changing climate, 83 out of 115 species displayed an increase in habitat suitability, resulting in an overall increase of 4.8% by 2050s and 7.1% by 2070s in the extent of suitable habitat for nonnative freshwater fishes. Taken together, invasion risk was found to be highest in southeastern China and lowest in the Tibet Plateau. Our research highlights the importance of assessing invasion risk by integrating the threats associated with the introduction and establishment stages. In particular, our findings revealed convergent patterns of invasion risk between current and potential nonnative freshwater fishes under climate change. Geographic patterns in hotspots of existing and emerging invasions provide critical insights to guide the allocation of resources to monitor and control existing and emerging invasions in China.

Identifying potential emerging invasive non‐native species from the freshwater pet trade

“…Studies have shown that species' range size is a good predictor of invasiveness (Ricciardi & Rasmussen, 1998), which has led to the 'niche breadth-invasion success hypothesis', with generalist species with broad niches more likely to successfully invade than specialist species with narrow niches (Vázquez, 2006). Niche analysis also allows us to predict how a specific system could be at risk based on the niche overlap between source and recipient regions for NNS (Liu et al, 2019). This is because the niche of a species changes very slowly through space and time (i.e.…”

“…Crucially, previously banned species may still be available in stores or on online marketplaces. Preventative measures are deemed the most effective NNS management options (Leung et al, 2002; Ricciardi & MacIsaac, 2022; Roy et al, 2014), but they require the identification of risky traded species with high likelihoods of introduction, establishment and spread (Liu et al, 2019). There is therefore a pressing need for a quantitative method that allows this.…”

Introduction of non‐native fish for aquaculture in China: A systematic review

“…43 Every day, it is likely that enormous numbers of individuals move across biogeographic barriers at a global scale. 44,45 Though only a small fraction of the translocated species survive, 46 the expansion of NAS has greatly altered fish biogeography, especially in freshwater ecosystems, reducing the uniqueness of fish fauna 47 and leading to biotic homogenization by reducing beta diversity. 48,49 China is a vast country with diverse environments which allows NAS to spread far and wide.…”

Predicting aquatic invasions in a megadiverse region: Maximum‐entropy‐based modelling of six alien fish species in Malaysia

“…Species distribution models, which identify relationships between observed occurrences and environmental predictors by using statistical models, or theoretically derived response curves (Elith & Leathwick, 2009; Srivastava, Lafond & Griess, 2019), have now emerged as a promising early warning tool in alien species management. In addition to quantifying geographical patterns of risks from alien species (Yates et al, 2018; Liu et al, 2019) and helping optimize control strategies (Giljohann et al, 2011), species distribution models are also particularly useful for predicting the suitability of new areas for alien species invasions under future climate scenarios (Li et al, 2016).…”