Invasive alien species (IAS) are a major global challenge requiring urgent action, and the Strategic Plan for Biodiversity (2011)(2012)(2013)(2014)(2015)(2016)(2017)(2018)(2019)(2020) of the Convention on Biological Diversity (CBD) includes a target on the issue. Meeting the target requires an understanding of invasion patterns. However, national or regional analyses of invasions are limited to developed countries. We identified 488 IAS in China's terrestrial habitats, inland waters and marine ecosystems based on available literature and field work, including 171 animals, 265 plants, 26 fungi, 3 protists, 11 procaryots, and 12 viruses. Terrestrial plants account for 51.6% of the total number of IAS, and terrestrial invertebrates (104 species) for 21.3%. Of the total numbers, 67.9% of plant IAS and 34.8% of animal IAS were introduced intentionally. All other taxa were introduced unintentionally despite very few animal and plant species that invaded naturally. In terms of habitats, 64.3% of IAS occur on farmlands, 13.9% in forests, 8.4% in marine ecosystems, 7.3% in inland waters, and 6.1% in residential areas. Half of all IAS (51.1%) originate from North and South America, 18.3% from Europe, 17.3% from Asia not including China, 7.2% from Africa, 1.8% from Oceania, and the origin of the remaining 4.3% IAS is unknown. The distribution of IAS can be divided into three zones. Most IAS are distributed in coastal
Understanding the spatial patterns in species richness gets new implication for biodiversity conservation in the context of climate change and intensified human intervention. Here, we created a database of the geographical distribution of 30,519 vascular plant species and 565 mammal species from 2,376 counties across China and disentangled the determinants that explain species richness patterns both at national and regional scales using spatial linear models. We found that the determinants of species richness patterns varied among regions: elevational range was the most powerful predictor for the species richness of plants and mammals across China. However, species richness patterns in the Qinghai-Tibetan Plateau Region (QTR) are quite unique, where net primary productivity was the most important predictor. We also detected that elevational range was positively related to plant species richness when it is less than 1,900 m, whereas the relationship was not significant when elevational range is larger than 1,900 m. It indicated that elevational range often emerges as the predominant controlling factor within the regions where energy is sufficient. The effects of land use on mammal species richness should attract special attention. Our study suggests that region-specific conservation policies should be developed based on the regional features of species richness.
Understanding the spatial patterns in species richness is a central issue in macroecology and biogeography. Analyses that have traditionally focused on overall species richness limit the generality and depth of inference. Spatial patterns of species richness and the mechanisms that underpin them in China remain poorly documented. We created a database of the distribution of 580 mammal species and 849 resident bird species from 2376 counties in China and established spatial linear models to identify the determinants of species richness and test the roles of five hypotheses for overall mammals and resident birds and the 11 habitat groups among the two taxa. Our result showed that elevation variability was the most important determinant of species richness of overall mammal and bird species. It is indicated that the most prominent predictors of species richness varied among different habitat groups: elevation variability for forest and shrub mammals and birds, temperature annual range for grassland and desert mammals and wetland birds, net primary productivity for farmland mammals, maximum temperature of the warmest month for cave mammals, and precipitation of the driest quarter for grassland and desert birds. Noteworthily, main land cover type was also found to obviously influence mammal and bird species richness in forests, shrubs and wetlands under the disturbance of intensified human activities. Our findings revealed a substantial divergence in the species richness patterns among different habitat groups and highlighted the group-specific and disparate environmental associations that underpin them. As we demonstrate, a focus on overall species richness alone might lead to incomplete or misguided understanding of spatial patterns. Conservation priorities that consider a broad spectrum of habitat groups will be more successful in safeguarding the multiple services of biodiversity.
The golden apple snail, Pomacea canaliculata, is one of the world's 100 most notorious invasive alien species. Knowledge about the critical climate variables that limit the global distribution range of the snail, as well as predictions of future species distributions under climate change, is very helpful for management of snail. In this study, the climatically suitable habitats for this kind of snail under current climate conditions were modeled by biomod2 and projected to eight future climate scenarios (2 time periods [2050s, 2080s] × 2 Representative Concentration Pathways [RCPs; RCP2.6, RCP8.5] × 2 atmospheric General Circulation Models [GCMs; Canadian Centre for Climate Modelling and Analysis (CCCMA), Commonwealth Scientific and Industrial Research Organisation (CSIRO)]). The results suggest that the lowest temperature of coldest month is the critical climate variable to restrict the global distribution range of P. canaliculata. It is predicted that the climatically suitable habitats for P. canaliculata will increase by an average of 3.3% in 2050s and 3.8% in 2080s for the RCP2.6 scenario, while they increase by an average of 8.7% in 2050s and 10.3% in 2080s for the RCP8.5 scenario. In general, climate change in the future may promote the global invasion of the invasive species. Therefore, it is necessary to take proactive measures to monitor and preclude the invasion of this species.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
customersupport@researchsolutions.com
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.