Invasive alien species can pose a severe threat to biodiversity and stability of the ecosystems they invade. Predicting distribution
patterns of invasive species in regions outside their native range is a fundamental component of early warning systems. Crofton
weed (
Eupatorium adenophorum Spreng.) was first discovered in the Yunnan Province of China around the 1940s. The well-documented invasion history of this
plant species provided the opportunity for us to examine the spatiotemporal patterns of biological invasion by crofton weed.
Using the datasets documenting 441 known localities invaded by crofton weed in China over the past 50 years and 23 environmental
variables generated by the genetic algorithm for rule-set production (GARP) model, we tested the predictability of crofton
weed distribution with a high degree of accuracy. Both the Kappa statistics and the receiver–operator characteristic (ROC)
analysis indicated that it is possible to predict the geographical spread of crofton weed in China. Precipitation in the coldest
quarter of the year, extremely low air temperature, and maximum annual air temperature strongly influenced the predictions.
Our results indicate that crofton weed may break out in Yungui Plateau, Sichuan Basin, southeastern Coastlands, Hainan Island,
and Taiwan although currently it is either absent or has only recently been recorded in these regions. Redundancy analysis
(RDA) ordination results demonstrated that temperature and precipitation play an important role in confining the spread of
crofton weed. Over the past 20 years, crofton weed has spread from subtropical areas with higher annual mean temperature and
lower climatic fluctuations to much cooler and dryer areas at higher altitudes. The distribution of crofton weed was restricted
mainly to regions with mean annual air temperature ranging from 10 to 22°C and annual precipitation from 800 to 2000 mm. Our
results could help in developing and implementing early detection measures to minimize the ecological impacts of crofton weed
invasion in China.
Keywords Geographic potential - Ecological niche modeling -
Eupatorium adenophorum Spreng. - Spatiotemporal pattern - Biological invasions - China