Lolium temulentum occurrence records were collected from the Global Biodiversity Information Facility (GBIF.org, 2022a), the Chinese Virtual Herbarium (CVH; https://www.cvh.ac.cn/, accessed May 2022), the Ministry of Agriculture and Rural Affairs of the People′s Republic of China (http://www.moa.gov.cn/, accessed May 2022), and China National Knowledge Infrastructure (CNKI; https://www.cnki.net/). Aegilops tauschii occurrence records were downloaded from GBIF (GBIF.org, 2022b), CVH in August 2022, and CNKI. For non-longitude and latitude records, Google Earth was used to obtain precise coordinates. To decrease the effect of duplicate coordinates and sampling bias, all occurrence records for both species were filtered using ENMTools to ensure that only one record was retained in per 5 km × 5 km grid square ( Figure 1 ). Ultimately, 4578 and 1966 occurrence records of L. temulentum and A. tauschii were retained worldwide, respectively.

Lolium temulentum and A. tauschii occurrence records were collected from CNKI and CVH. The year in which the earliest published articles or specimens were published was regarded as the invasive time in China. There were 217 for L. temulentum and 694 points for A. tauschii in China from 1950 to 2022. We used ArcGIS 10.5 was used with the GCS_Beijing_1954 geographic coordinate system, to map the invasive historical process of L. temulentum and A. tauschii over a 20-years interval in China.

Current climate data that comprised 19 bioclimatic variables at 2.5 arc-min resolution from 1979 to 2013 were downloaded from PaleoClim v1.2 (http://www.paleoclim.org/) (Brown et al., 2018). Future climate and elevation data with 2.5 arc-min resolution were obtained from WorldClim v. 2.0 (https://www.worldclim.org/), and these included two time periods (2021–2040 and 2041–2060) and three climate scenarios (SSP1-2.6, SSP2-4.5, and SSP5-8.5) based on the BCC-CSM2-MR model (Eyring et al., 2016; Fick and Hijmans, 2017). Slope and Aspect were extracted from elevation data using ArcGIS software. Soil data (AWC_CLASS, T_OC, T_PH_H₂O, and T_SAND) were downloaded from the Harmonized World Soil Database version 1.2 (https://www.fao.org/) (Fischer et al., 2008). The Global Human Influence Index (HII) from 1995 to 2004 was downloaded from the Socioeconomic Data and Applications Center (https://sedac.ciesin.columbia.edu/) (Wildlife Conservation Society and Center for International Earth Science Information Network, 2005). A total of 27 environmental variables are listed in Table S1 .

The collinearity of environmental variables can influence parameter optimization during MaxEnt model calibration (Dormann et al., 2013). To address this issue, the “band collection statistics” in ArcGIS was used to estimate the linear correlations and eliminate the highly linear correlations of 27 environmental variables ( Figure S1 ). All species occurrences of L. temulentum and A. tauschii and related environmental variables were entered into MaxEnt 3.4.4 to establish initial SDMs that provide percent contributions of each environmental variable. Comparing the correlation between two environmental variables (|r| > 0.8), the lower percent contribution was removed. Finally, 11 and 12 environmental variables screened for L. temulentum and A. tauschii are shown in Figure S2 .

SDMs, such as the MaxEnt model, face the challenge of balancing goodness-of-fit with model complexity because of their over-reliance on default settings (Warren and Seifert, 2011). Therefore, we used the R package (ENMeval) to calibrate the MaxEnt model to address these issues (Muscarella et al., 2014; Kass et al., 2021). Feature combinations (FCs) and regularization multipliers (RMs) are regarded as critical parameters for optimal settings in model calibration (Muscarella et al., 2014). RMs act synergistically in all FCs, which can adjust the level of regularization through each RM to protect against overfitting (Phillips, 2008). Based on the occurrence records and environmental variables of L. temulentum and A. tauschii, RM was set from 0.5 to 4, with a 0.5 interval, and six different FC combinations, including L, LQ, LQP, LQH, LQHP, and LQHPT (L = linear, H = hinge, Q = quadratic, P = product, and T= threshold) (Phillips and Dudík, 2008). The Akaike Information Criterion corrected (AICc) reflects the goodness-of-fit and model complexity, and the minimum AICc (i.e., Δ AICc = 0) was regarded as the best model parameter (Warren and Seifert, 2011). Therefore, for 48 combinations of FCs and RM values, FCs were set as LQHPT and RM was set to 0.5.

Optimized occurrence records and environmental variables of L. temulentum and A. tauschii were entered into MaxEnt 3.3.4; 25% of occurrence records were selected as training data, whereas the other 75% were considered testing data. The optimal MaxEnt model was set to replicate 10 times, and the replicated run type was set to “Bootstrap”. The maximum number of background points was set to 10000, and the output format was set to “Cloglog”, “Random seed” was chosen to improve the model’s randomness, and other parameters were left as default settings.

The area under the curve (AUC) of the receiver operator characteristic (ROC) is a metric for model performance (Roca et al., 2004). The AUC value is closely related to the rates of negative and positive values. The values range from 0 to 1, and those that are lower than 0.6 indicate that the model is unreliable. AUC values have been classified into four indices: poor (0.6 ≤ P < 0.7), moderate (0.7 ≤ P < 0.8), good (0.8 ≤ P < 0.9), and excellent (0.9 ≤ P < 1) (Swets, 1988).

The centroid of change trend in geographical distribution from the current climate to future scenarios was calculated using the ArcGIS software. In this study, we focused on the centroid transfer of L. temulentum and A. tauschii in the 2030s and 2050s, for example, SSP1-2.6, SSP2-4.5, and SSP5-8.5. The geographical distributions of L. temulentum and A. tauschii were reclassified and transferred to a vector file that dissolved a single central point to describe the direction (longitude and latitude) of the predicted change from the current climate to future scenarios in the 2030s and 2050s. This allows the model to depict shifts in habitat by tracking the centroid transfer and transfer distance.

The potential geographical distribution of L. temulentum and A. tauschii in a particular raster was based on MaxEnt model output. The maximum test sensitivity plus specificity was chosen as the threshold (Cantor et al., 1999; Manel et al., 2001). The potential geographical distribution of L. temulentum was classified into the following four categories under current and future climates: unsuitable (P < 0.35), poor (0.35 ≤ P < 0.5), moderate (0.5 ≤ P < 0.7), and high (0.7 ≤ P < 1). Similarly, A. tauschii was also classified into the following categories: unsuitable (P < 0.25), poor (0.25 ≤ P < 0.4), moderate (0.4 ≤ P < 0.6), and high (0.6 ≤ P < 1). Furthermore, ArcGIS was used to calculate the niche overlap of L. temulentum and A. tauschii under the current climate and three future scenarios in the 2030s and 2050s. The threshold of binary classification was based on the maximum test sensitivity plus specificity, for L. temulentum: unsuitable (P < 0.35) and suitable (0.35 ≤ P < 1), and for A. tauschii: unsuitable (P < 0.25) and suitable (0.25 ≤ P < 1).

Niche breadth is the range and variety of living conditions in a species’ niche, such as temperature range and food variety (Sexton et al., 2017). The value of niche breadth was calculated using ENMTools, Levins’ B1 and B2, that is, inverse concentration and uncertainty, respectively (Levins, 1968; Warren et al., 2010). The values of Levins’ B1 and B2 ranged from 0 to 1, indicating narrow to wide niche breadth (Levins, 1968). Furthermore, based on the ENMTools, there was value in evaluating the range of niche overlap in different species (Schoener’s D) (Schoener, 1968; Warren et al., 2008). The value of Schoener’s D ranged from 0 to 1, indicating that no niche overlapped to niche overlap identically (Warren et al., 2008). This could be directly compared to the traditional ecological assessment of niche overlap, including the overlap of microhabitat and diet.

For L. temulentum and A. tauschii, Δ AICc was calculated 400.24 and 254.95 in default MaxEnt model (FC = LQHPT and RM = 1). The optimal MaxEnt parameter settings for predicting the potential geographical distribution of L. temulentum and A. tauschii were when RM was set to 0.5, and FC was set as LQHPT via model calibration, Δ AICc was calculated 0. The mean AUC of L. temulentum and A. tauschii was 0.867 and 0.931, indicating the MaxEnt performance was “good” and “excellent”, respectively ( Figure S3 ).

The reconstruction of the historical expansion of L. temulentum and A. tauschii is shown in Figure 2 . The impact on the cereal trade from the spread of L. temulentum into China’s Heilongjiang province was first documented in 1956. Subsequently, L. temulentum gradually spread to most provinces, primarily in northwestern Xinjiang, the border of Gansu, Shaanxi, and Sichuan, and with a scattered distribution in Jilin, Shandong, Zhejiang, Anhui, Shanghai, Hubei, Jiangxi, Guangxi, Guangdong, and Tibet. Until 1990, the spread of L. temulentum increased in Qinghai, Jiangsu, Henan, Fujian, and Inner Mongolia, with the most notable increases in Hubei and Shaanxi. In the 2010s, the spread of L. temulentum increased in Hebei and Yunnan, with more increases in Yunnan and Jiangsu. To date, Liaoning, Tianjin, Beijing, Chongqing, Guizhou, and Ningxia are the most invaded regions of L. temulentum, which is primarily located in Gansu, Xinjiang, Yunnan, Hubei, Henan, Anhui, and Shandong. The historical spreading trend of L. temulentum began in Northwest China, spread to the Central China surrounding that region, then spread to North China, and sporadically throughout the Southwest and South China.

In 1950, it was reported that A. tauschii spread in Henan as the source of the D-gene in wheat, and spread sporadically in Shanxi and Shaanxi. Until 1990, A. tauschii had spread gradually in Xinjiang, Sichuan, and Beijing; however, by the 2010s, A. tauschii had spread to Jiangsu, Shaanxi, Guizhou, Hubei, Henan, Yunnan, Shandong, Shanxi, Guangdong, Anhui, and Gansu, primarily located on the border of Hubei, Henan, Shandong, and Shaanxi. Until now, Qinghai and Tianjin had become increasingly invaded regions, primarily in the Shaanxi, Shanxi, Hubei, Henan, Shandong, and Anhui regions. The historical trend shows the spread of A. tauschii originating in the southeast and northwest areas of Northwest China and spreading to the border of North China and down to Central and Eastern China. The spread continued constantly to the surrounding provinces but occurred more sporadically in areas in Southwest China.

The trends associated with species occurrence for L. temulentum and A. tauschii for the period from 1950 to 2022 are shown in Figure 2 . The number of L. temulentum increased rapidly from 1950 to 1990, but then declined until 2010 because of global control strategies. In 2010, the rate of increase for L. temulentum recovered, and ultimately exceeded the rate from the initial period. The number of A. tauschii increased slowly after the introduction of the species; however, in the 2000s, its occurrence increased significantly.

The potential geographical distribution of L. temulentum and A. tauschii for the current climate conditions in China is shown in Figure 3 , and under the 2030s and 2050s three climate scenarios, namely SSP1-2.6, SSP2-4.5, and SSP5-8.5, are presented in Figures 4 and 5 . The mainly suitable habitats under the current and future climate scenarios for L. temulentum were mainly located in northern Shanghai, southwestern and northeastern Sichuan, central Anhui, western Jiangsu, southern Gansu, central and southern Shaanxi, southwestern Shanxi, northern Henan, southern Hebei, and southern Beijing, Hubei, Tianjin, and Xinjiang.

The mainly suitable habitats under the current and future climate scenarios for A. tauschii were located primarily in northeastern Sichuan, central and southeastern Gansu, central Ningxia, central Shaanxi, northern and eastern Henan, northern Anhui, northern Shanghai, northern Jiangsu, Shandong, southern Hebei, southwestern Shanxi, southern Tianjin, central Beijing, northern and southern Liaoning, central Jilin, central Inner Mongolia, northwestern and southwestern Xinjiang, and Hubei.

In the current climate, the current total, highly, and moderately suitable habitat areas of L. temulentum were up to 125 × 10⁴, 2 × 10⁴, and 29 × 10⁴ km², accounting for 13.02, 0.21, and 3.02% of the total area of China, respectively. For A. tauschii, the current total, highly, and moderately suitable habitat areas were up to 235 × 10⁴, 47 × 10⁴, and 72 × 10⁴ km², accounting for 24.48, 4.90, and 7.50% of the total area of China, respectively.

Under SSP1-2.6, SSP2-4.5, and SSP5-8.5 in the 2030s, for L. temulentum, the overall trend in total, highly, and moderately suitable habitat areas of L. temulentum increased. The total and highly suitable habitat areas of L. temulentum reached the maximum under SSP2-4.5 and SSP5-8.5, up to 133 × 10⁴ and 5 × 10⁴ km², accounting for 13.85 and 0.52% of the total area of China, respectively. For A. tauschii, the overall trend in total and highly suitable habitat areas of A. tauschii decreased. The total and highly suitable habitat areas reached the maximum under SSP5-8.5, up to 168 × 10⁴ and 19 × 10⁴ km², accounting for 13.85 and 0.52% of the total area of China, respectively.

Under SSP1-2.6, SSP2-4.5, and SSP5-8.5 in the 2050s, for L. temulentum, the overall trend in total, highly, and moderately suitable habitat areas of L. temulentum increased. The total and highly suitable habitat areas of L. temulentum reached the maximum under SSP2-4.5, up to 144 × 10⁴ and 4 × 10⁴ km², accounting for 15.00 and 0.42% of the total area of China, respectively. For A. tauschii, the overall trend in total and highly suitable habitat areas of A. tauschii increased. The total and highly suitable habitat areas reached the maximum under SSP5-8.5 and SSP2-4.5, up to 239 × 10⁴ and 40 × 10⁴ km², accounting for 24.89 and 4.17% of the total area of China, respectively.

Changes in the future potential geographical distribution of L. temulentum and A. tauschii under SSP1-2.6, SSP2-4.5, and SSP5-8.5 in the 2030s and 2050s were shown in Figures 6 and 7 . Under the three scenarios in the 2030s, the increased habitat areas of L. temulentum in China were up to 32 × 10⁴, 17 × 10⁴, and 21 × 10⁴ km², mainly located in eastern Sichuan, northern and western Shandong, eastern Hebei, and northwestern Xinjiang, sporadically distributed in Southwest, Central, and Easter of China, and decreased habitat areas were up to 32 × 10⁴, 17 × 10⁴, and 21 × 10⁴ km², mainly located in northeastern and southeastern Guizhou, southern Shaanxi, southeastern Gansu, central Shanxi, and northern Shandong, sporadically distributed in Southwest and Central China. In the 2050s, the increased habitat areas of L. temulentum in China were up to 23 × 10⁴, 22 × 10⁴, and 28 × 10⁴ km², mainly distributed in northwestern and southeastern Yunnan, central Guizhou, eastern Sichuan, northern Anhui, southern Henan, central Jiangsu, and western Xinjiang, with decreased habitat areas of 23 × 10⁴, 26 × 10⁴, and 23 × 10⁴ km², sporadically distributed in eastern and western Southwest, Central, and southern North China.

Under the three scenarios in the 2030s, the increased habitat areas of A. tauschii in China were up to 1 × 10⁴, 0 × 10⁴, and 1 × 10⁴ km², sporadically located in eastern Southwest and southern North China, and decreased habitat areas were up to 74 × 10⁴, 73 × 10⁴, and 68 × 10⁴ km², mainly located in northeastern Yunnan, southern and eastern Sichuan, southeastern Qinghai, southern and central Gansu, northwestern Ningxia, southwestern Liaoning, eastern Jilin, central Inner Mongolia, and northwestern and southwestern Xinjiang. In the 2050s, the increased habitat areas of A. tauschii in China were up to 23 × 10⁴, 22 × 10⁴, and 28 × 10⁴ km², and sporadically located in Yunnan, Sichuan, Chongqing, Guizhou, Hunan, Hunan, Jiangxi, Zhejiang, Anhui, Hubei, Qinghai, Shanxi, and Xinjiang, and the decreased habitat areas were up to 23 × 10⁴, 26 × 10⁴, and 23 × 10⁴ km², mainly located in northeastern Yunnan, southern Sichuan, northern Gansu, northern Ningxia, and northwestern and southwestern Xinjiang, and sporadically distributed in Tibet, Qinghai, Inner Mongolia and Liaoning.

The trend of centroid transfer of L. temulentum and A. tauschii in China from the current climate to the three scenarios (SSP 2.6, SSP 4.5, and SSP 8.5) in the 2030s and 2050s is shown in Figure S4 . For L. temulentum, the centroid transferred to northeastern and northwestern in China from current to 2030s in the three scenarios, and moved to southeastern and southwestern under the 2050s in the three scenarios ( Figure 3B ). The longest transfer distance of L. temulentum centroid from the current climate to all future scenarios in the 2030s and 2050s was approximately 766.54 km and occurred under SSP5-8.5 in the 2030s. For A. tauschii, the centroid transferred to northeastern in China from current to 2030s in the three scenarios, and moved to southeastern and southern under the 2050s in the three scenarios ( Figure 3A ). The longest transfer distance of the centroid of A. tauschii from the current climate to the all future scenarios in the 2030s and 2050s was approximately 780.87 km under SSP1-2.6 in the 2050s.

Using ENMTools, the niche breadths of L. temulentum and A. tauschii were determined. The B2 niche breadth value of L. temulentum was 0.9308, which was similar to the value of A. tauschii (B2 = 0.9006). These values indicate that L. temulentum and A. tauschii are likely to fit a broad niche. However, the D value was 0.4742, suggesting only moderate niche overlap between L. temulentum and A. tauschii.

Under the current climate, there are four scenarios, namely unsuitable habitat, the geographical distribution of either L. temulentum or A. tauschii, and the overlap of the two ( Figure 8 ). The overlap area was 90 × 10⁴ km², and was primarily located in northern Yunnan, southern and northeastern Sichuan, northern Guizhou, southern Chongqing, Hunan, Jiangxi, northern Zhejiang, Shanghai, southeastern Hubei, central Anhui, southern Jiangsu, northern Shandong, northern and southern Henan, central and southwestern Shaanxi, southern and northeastern Gansu, southwestern and central Shanxi, southern Hebei, Beijing, southwestern Liaoning, and southern Xinjiang. The remaining areas of L. temulentum and A. tauschii were 35 × 10⁴ and 145 × 10⁴ km², respectively.

The future overlap between L. temulentum and A. tauschii is shown in Figure 8 . Compared with the current overlap area, the overlap area of both under the three scenarios in the 2030s declined, achieving a maximum area with approximately 82 × 10⁴ km² under SSP5-8.5-2030s, and increased in all scenarios in the 2050s, achieving a maximum of approximately 104 × 10⁴ km² under SSP1-2.6-2050s or SSP2-4.5-2050s. The overlap distribution of L. temulentum and A. tauschii in the 2030s and 2050s was similar to the current distribution, mainly distributed in East, Central, and eastern Southwest China. The remaining area of L. temulentum increased in the 2030s and 2050s in all scenarios except SSP5-8.5-2050s, achieving a maximum under SSP2-4.5-2030s (56 × 10⁴ km²) and SSP2-4.5-2050s (41 × 10⁴ km²), whereas A. tauschii decreased in the 2030s and 2050s in all scenarios except SSP 5-8.5-2050s, achieving a maximum under SSP1-2.6-2030s (92 × 10⁴ km²) and SSP5-8.5-2050s (149 × 10⁴ km²). The overlap change of L. temulentum and A. tauschii decreased by 21 × 10⁴, 14 × 10⁴,8 × 10⁴ km² in the 2030s under SSP1-2.6, SSP2-4.5, and SSP5-8.5, respectively, and increased in the 2050s by 14 × 10⁴, 14 × 10⁴,1 × 10⁴ km² for the same scenarios.

We screened most significant environmental variables of L. temulentum and A. tauschii, through percent contribution and “Jackknife method”. For L. temulentum, human influence index (HII, 43.6%), mean temperature of coldest quarter (bio11, 27.7%), and precipitation of coldest quarter (bio19, 19.8%) were screened ( Figure S2 and S5 ). For A. tauschii, human influence index (HII, 33.8%), temperature seasonality (standard deviation×100) (bio4, 30.8%) and annual mean temperature (bio1, 14.7%) were screened ( Figures S2 and S6 ).

The probability of presence of significant environmental factors in L. temulentum and A. tauschii is shown in the response curve ( Figure S7 ). This value is greater than 0.5, which indicates that the range of environmental variables is more suitable for the development of L. temulentum and A. tauschii. For L. temulentum, mean temperature for the coldest quarter was −8.52–16.53 °C, precipitation of coldest quarter was 72.64–914.52 mm, and the influence of human influence index on L. temulentum growth was increasing. For A. tauschii, the influence of human influence index was increasing, temperature seasonality was 7.68–10.57 °C, and annual mean temperature was 8.88–26.44 °C.

The most critical environmental variable for the distribution patterns of L. temulentum and A. tauschii was HII. Previous studies have confirmed that the established and spread of IAP populations in a new environment are closely linked to human activities, such as trade, tourism, transport, and human population density (McKinney, 2001; Pyšek et al., 2010). Another study indicated that the niche width of non-native plants increases with human activities (Irl et al., 2021). Non-native plants are carried by humans through travel and trade transportation, leaving their native region to novel environment (Boivin et al., 2016; Kueffer, 2017). Once, these invasive plants establish themselves and the populations spread, they integrate into ecosystems and ultimately have a negative influence on native species in the region (Kueffer, 2017). In our results, the value of HII increased concomitantly with increases in the probability of the species presence, revealing that HII played an important role and possibly influenced the geographical distribution of L. temulentum and A. tauschii.

In addition, for L. temulentum, bio11 and bio19 were the greatest contributions among 14 environmental variables. Low temperatures and high soil moisture are the conditions needed for the germination and growth of L. temulentum (Sagar et al., 1979). Vernalization can accelerate flowering, although L. temulentum seeds are dormant at 2 °C, but this did not reduce the seeds’ viability (Steiner and Ruckenbauer, 1995). When the temperature is higher than 5 °C, Lolium spp. develop a ‘stored growth’ potential that accelerate the extension of leaves (Peacock, 1975; Fournier et al., 2005). Our results showed that bio11 was −8.52–16.53 °C, which was consistent with the characteristic of low-temperature growth. Temperature, precipitation, and HII were vital environmental variables for L. temulentum growth. One study indicated that a mean annual precipitation of 400 to 1200 mm was an optimal development condition (CABI, 2022). Furthermore, we showed that approximately 900 mm of bio19, was optimum to establish populations for L. temulentum. For A. tauschii, and the greatest contributions among 17 environmental variables were bio4 and bio1, which were selected to predict the geographical distribution of A. tauschii in the optimal MaxEnt model. Previous studies have shown that the germination temperatures of A. tauschii range from 5 to 35 °C (Fang et al., 2015). Our results showed that the optimal range of temperature seasonality and annual mean temperature was consistent with this characteristic. The climatic characteristics of the living species were the dominant factors for population regeneration and establishment (Hansen et al., 2018).

Non-native plants that establish populations in novel environments undergo a two-stage process (Aikio et al., 2010). The first phase is the lag phase, when the occurrence of the invasive plants increase slowly or do not change at all, and the second is increase phase, species occurrence increase markedly (Crooks and Soulé, 1999). The lag phase is speculated to be closely linked to an adaption period invasive genotypes, abrupt invasion mechanisms, and environmental switches (Aikio et al., 2010). The invasive historical reconstruction of A. tauschii, showed that species occurrence increased slowly over 30 to 40 years after it invaded China, followed by population outbreak in 2000. This is exemplary of the two-stage process shown by the initial lag phase followed by a state of rapid growth. Alternatively, for L. temulentum, there was no obvious pattern, just a moderate increase. It has been suggested that this may have been influenced by sampling bias, such as incomplete survey techniques and monitoring (Delisle et al., 2003). All occurrences of L. temulentum and A. tauschii increase as awareness of IAPs increase and this is attributed to the progressive increases in the search and documentation of species occurrence (Cousens and Mortimer, 1995). Lolium temulentum and A. tauschii are critical IAPs in China, and their occurrence could continue to increase in the future.

The potential geographical distribution of some invasive plants will shrink, whereas others will expand with climate change (Tu et al., 2021; Zhang et al., 2021b). The suitable areas of Ageratina adenophora in China would decrease under the 2050s, whereas increased in the 2090s (Zhang et al., 2022). In this study, the total trend in suitable areas for L. temulentum increased from the current climate to future scenarios (SSP1-2.6, SSP2-4.5, and SSP5-8.5) in the 2030s and 2050s. This result is similar to other studies on the potential geographical distribution of non-invasive plants; for example, suitable areas of Cenchrus ciliaris increased under SSP1-2.6 and SSP2-4.5-2050s, and for Spartina anglica the suitable areas increase under SSP5-8.5-2100 in Northern Europe (Borges et al., 2021; Siller-Clavel et al., 2022). IPCC has indicated that global warming is likely to increase by 1.5 °C from 2030 to 2052 at the current rate (IPCC, 2021). The radiative forcing gradually increased in SSP1-2.6, SSP2-4.5, and SSP5-8.5, reaching 2.6, 4.5, and 8.5 W/m², respectively, indicating that global CO₂ concentrations are rising. Lolium temulentum is a C₃ plant that strengthens photosynthesis to advance nutrient absorption, facilitating the development of a rise in CO₂ concentrations, so the predicted suitable areas of L. temulentum will likely increase in future scenarios (Lush, 1976). Previous studies have shown that the suitable areas for some invasive plants shrank but still had a significant invasion risk, such as Xanthium italicum (Zhang et al., 2021b). This result is consistent similar with the predicted suitable areas for A. tauschii in the 2030s in this study, but it ultimately ended up increasing in the 2050s. Furthermore, the IPCC report indicated that the yield of some crops that grow at different latitudes, such as wheat, maize, and sugar beet, have been influenced by climate change in recent years (IPCC, 2021). We hypothesize that the change in the potential geographical distribution of L. temulentum and A. tauschii is related to this.

Plants can change their physiological characteristics to migrate to a new habitat or respond more suitably to climate change (Davis and Shaw, 2001).However, not all species have the ability to evolve adaptations that respond to rapid climate change; therefore, migration is considered a critical pathway to address this issue (Etterson and Shaw, 2001; Corlett and Westcott, 2013). some non-native plants, such as Alternanthera philoxeroides and Ambrosia artemisiifolia, are extremely adaptable and can migrate whereas others cannot with climate change (Tu et al., 2021). Previous studies have shown that climate change plays a critical role in range-shifting invasive plants, which may be geographically stable with climate warming, or shifting to different directions in future scenarios (Allen and Bradley, 2016; Rockwell-Postel et al., 2020). Our data show that the centroid of A. tauschii is primarily located in Henan from the current climate and in future scenarios, and it is unable to keep pace with climate change. However, L. temulentum transfers to the north and to different provinces under future scenarios, which indicates high adaptability to climate change.

Niche overlap is deemed to be ecological species that exhibit biological characteristics and ecological adaptability, including similarities in resource utilization and species competition (Jing et al., 2015). When the value of niche width is greater, it indicates greater adaptability to the environment and niche overlap (Wang et al., 2019). Our results demonstrate that L. temulentum and A. tauschii have a lot of similarities in resource utilization and geographical distribution, which may be due to the synergistic reduction in wheat quality. By calculating B1 and B2, it is evident that L. temulentum is more adaptable to the habitat of A. tauschii. The toxicity of L. temulentum threatens human and animal health, and the high reproduction rate and pesticide resistance of A. tauschii pose a significant threat of its spread. Therefore, some control measures have been considered and are proposed herein.

We demonstrated that the current overlap of L. temulentum and A. tauschii is primarily distributed in Yunnan, Sichuan, Guizhou, Chongqing, Hunan, Jiangxi, Zhejiang, Shanghai, Hubei, Anhui, Jiangsu, Shandong, Henan, Shaanxi, Gansu, Shanxi, Hebei, Beijing, Liaoning, and Xinjiang, and this is consistent with previous study (Fang et al., 2013; CABI, 2022). Yunnan, Zhejiang, and province regions were predicted to be novel environments that exist at high invasive risk for L. temulentum and A. tauschii. Spreading occurs primarily from seed dispersal during wheat trade transport to other provinces in China, therefore it is quintessential to secure wheat breeding bases without L. temulentum and A. tauschii seeds to increase wheat quality and purity, and these acceptance are considered effective control measures (Terreix, 1968; Fang et al., 2013; Gong, 2022).

Furthermore, other studies have suggested that cultural control and chemical control are effective means for controlling L. temulentum and A. tauschii. Cultural control includes establishing long rotations periods that disturb the soil environment or using wheat seed cleaning screens (Ferrari et al., 1984). Another study demonstrated that sowing wheat 30 and 60 days later and hand weeding twice was effective in controlling L. temulentum (Angiras and Rana, 1990). Strengthening seed quarantine, crop rotation that changes the environment of weed populations, and artificially pulling weeds are effective ways to control A. tauschii (Yu et al., 2018). However, pulling weeds can be difficult because of the similarities between L. temulentum and wheat. Therefore, individuals should take measures to control L. temulentum in combination with pesticides. The application of triallate and metoxuron to the soil can effectively control L. temulentum development before sowing wheat (Stevens and Meyes, 1976). In addition, the pre-emergence of wheat applications of metribuzin or pendimethalin show substantial governance (Cairns et al., 1979). As for A. tauschii, mesosulfuron-methyl is considered an effective herbicide, whereas excessive spraying could restrain wheat development such that seedlings become yellow or weak (Wu et al., 2022). Therefore, the dose, proportion of inert ingredients, and spraying time of mesosulfuron-methyl are the important issues to consider to avoid herbicide pollution. Recent studies have shown that mesosulfuron-methyl is not a permanent control of A. tauschii growth, which have developed resistance in parts of China, including the northwest plain, central mountains, and northern coastal areas in Shandong (Gao, 2021).