Predicting the invasive trend of exotic plants in China based on the ensemble model under climate change: A case for three invasive plants of Asteraceae

Changes in the Range of Four Advantageous Grasshopper Habitats in the Hexi Corridor under Future Climate Conditions

Angaracris rhodopa (Fischer et Walheim), Calliptamus abbreviatus (Ikonnikov), Myrmeleotettix palpalis (Zubowsky), and Oedaleus decorus asiaticus (Bey-Bienko) are the main grasshoppers that harm the natural grassland in the Hexi Corridor in Gansu, northwest China. In this study, the MaxEnt model was employed to identify the key environmental factors affecting the distribution of the four grasshoppers' habitats and to assess their distribution under current and future climate conditions. The aim was to provide a basis for grasshopper monitoring, prediction, and precise control. In this study, distribution of suitable habitats for A. rhodopa, C. abbreviates, M. palpalis, O. decorus asiaticus were predicted under current and future climatic scenarios using the Maxent model. The average AUC (area under the ROC curve) and TSS (true skill statistic) values of the four grasshoppers were greater than 0.9, and the simulation results were excellent and highly reliable. The mean annual precipitation was the main factor limiting the current range of suitable areas for these four species. Under the current climate, A. rhodopa, C. abbreviatus, and O. decorus asiaticus were mainly distributed in the central and eastern parts of the Hexi Corridor, and M. palpalis was distributed throughout the Hexi Corridor, with a suitable area of 1.29 × 104, 1.43 × 104, 1.44 × 104, and 2.12 × 104 km2, accounting for 13.7%, 15.2%, 15.3%, and 22.5% of the total area of the grasslands in the Hexi Corridor, respectively. The highly suitable areas of A. rhodopa, C. abbreviatus, and O. decorus asiaticus were mainly distributed in the eastern-central part of Zhangye City, the western part of Wuwei City, and the western and southern parts of Jinchang City, with areas of 0.20 × 104, 0.29 × 104, and 0.35 × 104 km2, accounting for 2.2%, 3%, and 3.7% of the grassland area, respectively. The high habitat of M. palpalis was mainly distributed in the southeast of Jiuquan City, the west, middle, and east of Zhangye City, the west of Wuwei City, and the west and south of Jinchang City, with an area of 0.32 × 104 km2, accounting for 3.4% of the grassland area. In the 2030s, the range of A. rhodopa, C. abbreviatus, and O. decorus asiaticus was predicted to increase; the range of M. palpalis will decrease. The results of this study could provide a theoretical basis for the precise monitoring and control of key areas of grasshoppers in the Hexi Corridor.

Different sets of traits determine transition of alien species along the invasion continuum

Invasive alien species are currently considered as one of the dominant drivers of global environmental change. Till now, the majority of studies have focused on single or a few traits of alien species that facilitate their invasion. Also inclusion of all the traits which determine the transition of aliens along the different stages of invasion continuum (casual, naturalised and invasive) has remained largely overlooked. In this study, we collected a comprehensive trait dataset on 144 alien plant species of Kashmir Himalaya - a global biodiversity hotspot region. To test which traits of alien species, individually or in combination along with anthropogenic factors, determine their transition along the invasion continuum, we employed chi-square tests, boosted regression trees and phylogenetic methods. We found the perennial life span, longer residence time, greater number of introduced regions, and better seed dispersal mechanism were critical in determining the transition from casual to naturalised. The herbaceous growth form, therophyte Raunkiaer life-form, annual life span, achene fruit, longer residence time and broader introduced range were the species' traits determining transition from naturalised to invasive. Aliens introduced as ornamentals have more propensity to become naturalised; whereas aliens introduced unintentionally show overrepresentation at the invasive stage. Phylogeny alone showed mixed results indicating both clustering and dispersion; however, in combination with other traits, it plays a significant role in determining the stage of invasion. Overall, our study disentangles the individual and interactive roles of multiple traits that determine the transition of alien species' along the invasion continuum. Further, we foresee the potential applicability of our findings in designing robust invasion risk analysis protocols and stage-specific invasion management strategies in this Himalayan region, with learnings for elsewhere in the world.

Nitrogen Deposition Amplifies the Legacy Effects of Plant Invasion

The legacy effects of invasive plant species can hinder the recovery of native communities, especially under nitrogen deposition conditions, where invasive species show growth advantages and trigger secondary invasions in controlled areas. Therefore, it is crucial to thoroughly investigate the effects of nitrogen deposition on the legacy effects of plant invasions and their mechanisms. The hypotheses of this study are as follows: (1) Nitrogen deposition amplifies the legacy effects of plant invasion. This phenomenon was investigated by analysing four potential mechanisms covering community system structure, nitrogen metabolism, geochemical cycles, and microbial mechanisms. The results suggest that microorganisms drive plant-soil feedback processes, even regulating or limiting other factors. (2) The impact of nitrogen deposition on the legacy effects of plant invasions may be intensified primarily through enhanced nitrogen metabolism via microbial anaerobes bacteria. Essential insights into invasion ecology and ecological management have been provided by analysing how nitrogen-fixing bacteria improve nitrogen metabolism and establish sustainable methods for controlling invasive plant species. This in-depth study contributes to our better understanding of the lasting effects of plant invasions on ecosystems and provides valuable guidance for future ecological management.

Dynamics of the distribution of invasive alien plants (Asteraceae) in China under climate change

Climate change and biological invasions pose significant threats to the conservation of biodiversity and the provision of ecosystem services. With the rapid development of international trade and economy, China has become one of the countries most seriously affected by invasive alien plants (IAPs), especially the Asteraceae IAPs. For this end, we selected occurrence data of 31 Asteraceae IAPs and 33 predictor variables to explore the distribution pattern under current climate using MaxEnt model. Based on future climate data, the changes in distribution dynamics of Asteraceae IAPs were predicted under two time periods (2041-2060 and 2081-2100) and three climate change scenarios (SSP126, SSP245 and SSP585). The results indicated that the potential distribution of IAPs was mainly in the southeast of China under current climate. Climatic variables, including precipitation of coldest quarter (BIO19), temperature annual range (BIO07) and annual precipitation (BIO12) were the main factors affecting the potential distribution. Besides, human footprint (HFP), population (POP) and soil moisture (SM) also had a great contribution for shaping the distribution pattern. With climate change, the potential distribution of IAPs would shift to the northwest and expand. It would also accelerate the expansion of most Asteraceae IAPs in China. The results of our study can help to understand the dynamics change of distributions of Asteraceae IAPs under climate change in advance so that early strategies can be developed to reduce the risk and influence of biological invasions.

Integrating transcriptome and physiological analyses to elucidate the molecular responses of sorghum to fluxofenim and metolachlor herbicide

The extensive use of herbicides has raised concerns about crop damage, necessitating the development of effective herbicide safeners. Fluxofenim has emerged as a promising herbicide safener; however, it's underlying mechanism remains unclear. Here, we screened two inbred lines 407B and HYZ to investigate the detoxication of fluxofenim in mitigating metolachlor damage in sorghum. Metolachlor inhibited seedling growth in both 407B and HYZ, while, fluxofenim could significantly restore the growth of 407B, but not effectively complement the growth of HYZ. Fluxofenim significantly increased the activities of glutathione-S-transferase (GST) to decrease metolachlor residue in 407B, but not in HYZ. This implys that fluxofenim may reduce metolachlor toxicity by regulating its metabolism. Furthermore, metolachlor suppressed AUX-related and JA-related genes expression, while up-regulated the expression of SA-related genes. Fluxofenim also restored the expression of AUX-related and JA-related genes inhibited by metolachlor and further increased expression of SA-related genes. Moreover, we noted a significant increase in the content of trans-zeatin O-glucoside (tZOG) and Gibberellin1 (GA1) after the fluxofenim treatment. In conclusion, fluxofenim may reduce the injury of herbicide by affecting herbicide metabolism and regulating hormone signaling pathway.

Potentially suitable distribution areas of Populus euphratica and Tamarix chinensis by MaxEnt and random forest model in the lower reaches of the Heihe River, China

Populus euphratica and Tamarix chinensis play a vital role in windbreak and sand fixation, maintaining species diversity and ensuring community stability. Managing and protecting the P. euphratica and T. chinensis forests in the Heihe River's lower reaches is an urgent issue to maintain the desert region's ecological balance. In this study, based on the distribution points of P. euphratica and T. chinensis species and environmental data, MaxEnt and random forest (RF) models were used to characterize the potential distribution areas of P. euphratica and T. chinensis in the lower reaches of the Heihe River. The results showed that the accuracy of the RF model was much higher than that of the MaxEnt model. Both the RF and MaxEnt models showed that the distance to the river greatly influenced the distribution of P. euphratica and T. chinensis. Furthermore, the RF model predicted significantly larger highly suitable areas for both P. euphratica and T. chinensis than the MaxEnt model. Our study enhances the understanding of the species' spatial distribution, offering valuable insights for practical management and conservation strategies.

Constructing indicator species distribution models to study the potential invasion risk of invasive plants: A case of the invasion of Parthenium hysterophorus in China

Aim

As invasive plants are often in a non-equilibrium expansion state, traditional species distribution models (SDMs) are likely underestimating their suitable habitat. New methods are necessary to identify potential invasion risk areas.

Location

Tropical monsoon rainforest and subtropical evergreen broad-leaved forest regions in China.

Methods

We took Parthenium hysterophorus as a case study to predict its potential invasion risk using climate, terrain, and human activity variables. First, a generalized joint attribute model (GJAM) was constructed using the occurrence of P. hysterophorus and its 27 closely related species in Taiwan, given it is widely distributed in Taiwan. Based on the output correlation values, two positively correlated species (Cardiospermum halicacabum and Portulaca oleracea) and one negatively correlated species (Crassocephalum crepidioides) were selected as indicator species. Second, the distributions of P. hysterophorus and its indicator species in the study area were predicted separately using an ensemble model (EM). Third, when selecting indicator species to construct indicator SDMs, two treatments (indicator species with positive correlation only, or both positive and negative correlation) were considered. The indicator species' EM predictions were overlaid using a weighted average method, and a better indicator SDMs prediction result was selected by comparison. Finally, the EM prediction result of P. hysterophorus was used to optimize the indicator SDMs result by a maximum overlay.

Results

The optimized indicator SDMs prediction showed an expanded range beyond the current geographic range compared to EM and the thresholds for predicting key environmental variables were wider. It also reinforced the human activities' influence on the potential distribution of P. hysterophorus.

Main Conclusions

For invasive plants with expanding ranges, information about indicator species distribution can be borrowed as a barometer for areas not currently invaded. The optimized indicator SDMs allow for more efficient potential invasion risk prediction. On this basis, invasive plants can be prevented earlier.

Niche and Range Shifts of Aedes aegypti and Ae. albopictus Suggest That the Latecomer Shows a Greater Invasiveness

The yellow fever (Aedes aegypti) and Asian tiger (Ae. albopictus) mosquitos are major vectors of global mosquito-borne pathogens. However, their niche and range shifts, the underlying mechanisms, and related relative invasion rates remain scarcely known. We examined the niche and range shifts between the native and invasive Ae. aegypti and Ae. albopictus populations through dynamic niche and range models and the largest occurrence record datasets to date. We detected substantial niche and range expansions in both species, probably because the introduced populations have more opportunities to acclimate to diverse environmental conditions than their native counterparts. Mitigating climate change could effectively control their future invasions, given that future climate changes could promote their invasiveness. Additionally, compared to the introduced Ae. aegypti, the more recent invader Ae. albopictus had greater niche and range expansion over its shorter invasion history. In terms of the range shifts, Ae. albopictus had an invasion rate approximately 13.3 times faster than that of Ae. aegypti, making it a more invasive vector of global mosquito-borne pathogens. Therefore, considering its higher invasion rate, much more attention should be paid to Ae. albopictus in devising our strategies against prevailing global mosquito-borne pathogens than Ae. aegypti. Since small niche shifts could result in their large range shifts, niche shifts might be a more important indicator for biological invasion assessments.

Prediction of the potentially suitable areas of Ligularia virgaurea and Ligularia sagitta on the Qinghai-Tibet Plateau based on future climate change using the MaxEnt model

Ligularia virgaurea and Ligularia sagitta are two species of poisonous plants with strong invasiveness in natural grasslands in China that have caused considerable harm to animal husbandry and the ecological environment. However, little is known about their suitable habitats and the key environmental factors affecting their distribution. Although some studies have reported the distributions of poisonous plants on the Qinghai-Tibet Plateau (QTP) and predicted their potential distributions at local scales in some regions under climate change, there have been few studies on the widespread distributions of L. virgaurea and L. sagitta. In this study, we recorded 276 and 118 occurrence points of L. virgaurea and L. sagitta on the QTP using GPS, and then used the MaxEnt model to predict the distribution of suitable habitats. Results showed that (1) under current climate conditions, L. virgaurea and L. sagitta are mainly distributed in southern Gansu, eastern Qinghai, northwestern Sichuan, eastern Tibet, and southwestern Yunnan, accounting for approximately 34.9% and 39.8% of the total area of the QTP, respectively; (2) the main environmental variables affecting the distribution of suitable habitats for L. virgaurea and L. sagitta are the Human Footprint Index (52.8%, 42.2%), elevation (11%, 4.4%), soil total nitrogen (18.9%, 4.2%), and precipitation seasonality (5.1%, 7.3%); and (3) in the future, in the 2050s and 2070s, the area of habitat of intermediate suitability for L. virgaurea will spread considerably in northwest Sichuan, while that of high suitability for L. sagitta will spread to eastern Tibet and western Sichuan.

Invasive Trends of Spartina alterniflora in the Southeastern Coast of China and Potential Distributional Impacts on Mangrove Forests

Mangrove forests are one of the most productive and seriously threatened ecosystems in the world. The widespread invasion of Spartina alterniflora has seriously imperiled the security of mangroves as well as coastal mudflat ecosystems. Based on a model evaluation index, we selected RF, GBM, and GLM as a predictive model for building a high-precision ensemble model. We used the species occurrence records combined with bioclimate, sea-land topography, and marine environmental factors to predict the potentially suitable habitats of mangrove forests and the potentially suitable invasive habitats of S. alterniflora in the southeastern coast of China. We then applied the invasion risk index (IRI) to assess the risk that S. alterniflora would invade mangrove forests. The results show that the suitable habitats for mangrove forests are mainly distributed along the coastal provinces of Guangdong, Hainan, and the eastern coast of Guangxi. The suitable invasive habitats for S. alterniflora are mainly distributed along the coast of Zhejiang, Fujian, and relatively less in the southern provinces. The high-risk areas for S. alterniflora invasion of mangrove forests are concentrated in Zhejiang and Fujian. Bioclimate variables are the most important variables affecting the survival and distribution of mangrove forests and S. alterniflora. Among them, temperature is the most important environmental variable determining the large-scale distribution of mangrove forests. Meanwhile, S. alterniflora is more sensitive to precipitation than temperature. Our results can provide scientific insights and references for mangrove forest conservation and control of S. alterniflora.

Synergetic use of DEM derivatives, Sentinel-1 and Sentinel-2 data for mapping soil properties of a sloped cropland based on a two-step ensemble learning method

Understanding the spatial variability of soil organic matter (SOM), soil total nitrogen (STN), soil total phosphorus (STP), and soil total potassium (STK) is important to support site-specific agronomic management, food production, and climate change adaptation. High-resolution remote sensing imageries have emerged as an innovative solution to investigate the spatial variation in agricultural soils with machine learning (ML) algorithms. However, the predictive power of the individual and combined effects of Sentinel-1 (S1) synthetic aperture radar (SAR) and Sentinel-2 (S2) multispectral images for mapping soil properties, especially STN, STP, and STK, have rarely been investigated. Moreover, single ML model may achieve unstable performance for predicting multiple soil properties due to strong spatial heterogeneity. This study explored the combine use of S1, S2, and DEM derivatives to map SOM, STN, STP, and STK content of a sloped cropland of northeastern China. A two-step method with a weighted sum of four ML models was proposed to improve the accuracy and robustness in predicting multiple soil properties. Our results showed that single ML model has various performance in predicting the four soil properties. The optimal ML models could explain approximately 56 %, 53 %, 56 % and 37 % of the variability of SOM, STN, STP, and STK, respectively. Using the weights estimated through a 10-fold cross-validation procedure, the two-step ensemble learning model was retrained and showed more robust performance than the four ML models, in which the prediction accuracy was improved by 2.38 %, 1.40 %, 3.52 %, and 3.29 % for SOM, STN, STP, and STK, respectively. Our results also showed that the optical S2 derived features, especially the two S2 short-wave infrared bands, enhanced vegetation index, and soil adjusted vegetation index, were more important for soil property prediction than S1 data and DEM derivatives. Compared with individual sensor, a combination of S1 and S2 data yielded more accurate predictions of STN and STP but not for SOM and STK. The results of this study highlight the potential of high-resolution S1 and S2 data and the two-step method for soil property prediction at farmland scale.

Estimation of climate-induced increased risk of Centaurea solstitialis L. invasion in China: An integrated study based on biomod2

Introduction

Invasive alien plants (IAPs) are major hazards to biodiversity, human health, and the agricultural economy. As one of the most aggressive species of IAPs, the distribution area of Centaurea solstitialis L. has increased exponentially in the past two years since its invasion into Xinjiang, China, in July 2014. Predicting the potential geographic distributions (PGDs) of C. solstitialis in China can provide theoretical support for preventing the continued spread of this weed.

Methods

In this study, based on 5,969 valid occurrence records of C. solstitialis and 33 environmental variables, we constructed an ensemble model to predict suitable habitats for C. solstitialis under climate change scenarios.

Results

Our results showed that the mean true skill statistic (TSS) values, area under the receiver operating characteristic (ROC) curve (AUC), and Cohen’s Kappa (KAPPA) for the ensemble model were 0.954, 0.996, and 0.943, respectively. The ensemble model yielded more precise predictions than those of the single model. Temperature seasonality (Bio4), minimum temperature of the coldest month (Bio6), precipitation of the driest month (Bio14), and human influence index (HII) have significantly disrupted the PGDs of C. solstitialis in China. The total (high) suitability habitat area of C. solstitialis in China was 275.91 × 104 (67.78 × 104) km2, accounting for 71.26 (7.06)% of China. The PGDs of C. solstitialis in China under the current climate were mainly in East China (Shandong, Jiangsu, Shanghai, Zhejiang, and Anhui), Central China (Henan, southwestern Shanxi, southern Shaanxi, southern Gansu, Hubei, Hunan, Jiangxi, Chongqing, and Guizhou), and South China (southern Tibet, eastern Sichuan, Yunnan, Guangxi, Guangdong, Fujian, and Taiwan). Under future climate scenarios, the total suitability habitat area for C. solstitialis will expand, whereas the high suitability habitat area will decrease.

Discussion

The main manifestation is that the shift of southeast China into a moderate suitability habitat, and the total suitability habitats will be extended to northwest China. More focus needs to be placed on preventing further spread of C. solstitialis in northwest China.

Climate change has increased the global threats posed by three ragweeds (Ambrosia L.) in the Anthropocene

Invasive alien plants (IAPs) substantially affect the native biodiversity, agriculture, industry, and human health worldwide. Ambrosia (ragweed) species, which are major IAPs globally, produce a significant impact on human health and the natural environment. In particular, invasion of A. artemisiifolia, A. psilostachya, and A. trifida in non-native continents is more extensive and severe than that of other species. Here, we used biomod2 ensemble model based on environmental and species occurrence data to predict the potential geographical distribution, overlapping geographical distribution areas, and the ecological niche dynamics of these three ragweeds and further explored the environmental variables shaping the observed patterns to assess the impact of these IAPs on the natural environment and public health. The ecological niche has shifted in the invasive area compared with that in the native area, which increased the invasion risk of three Ambrosia species during the invasion process in the world. The potential geographical distribution and overlapping geographical distribution areas of the three Ambrosia species are primarily distributed in Asia, North America, and Europe, and are expected to increase under four representative concentration pathways in the 2050s. The centers of potential geographical distributions of the three Ambrosia species showed a tendency to shift poleward from the current time to the 2050s. Bioclimatic variables and the human influence index were more significant in shaping these patterns than other factors. In brief, climate change has facilitated the expansion of the geographical distribution and overlapping geographical distribution areas of the three Ambrosia species. Ecomanagement and cross-country management strategies are warranted to mitigate the future effects of the expansion of these ragweed species worldwide in the Anthropocene on the natural environment and public health.

Constructing an Ensemble Model and Niche Comparison for the Management Planning of Eucalyptus Longhorned Borer Phoracantha semipunctata under Climate Change

Phoracantha semipunctata is a destructive invasive alien forest pest worldwide. It primarily damages the eucalyptus via adults, affecting almost all parts of the eucalyptus. Its larvae develop in almost all major tissues of the plant. Phoracantha semipunctata spreads both via the migration of adults and global trade in intercontinental translocation. Currently, this pest has spread to six continents worldwide, except Antarctica, resulting in substantial economic losses. Based on global occurrence data and environmental variables, the potential global geographical distribution of P. semipunctata was predicted using an ensemble model. The centroid shift, overlap, unfilling, and expansion scheme were selected to assess niche dynamics during the global invasion process. Our results indicated that the AUC and TSS values of the ensemble model were 0.993 and 0.917, respectively, indicating the high prediction accuracy of the model. The distribution pattern of P. semipunctata is primarily attributed to the temperature seasonality (bio4), mean temperature of the warmest quarter (bio10), and human influence index variables. The potential geographical distribution of P. semipunctata is primarily in western and southwestern Asia, western Europe, western and southern North America, southern South America, southern Africa, and eastern and southern Oceania. The potential geographical distribution of P. semipunctata showed a downward trend in the 2030s and the 2050s. The distribution centroid showed a general tendency to shift southward from the near-current to future climate. Phoracantha semipunctata has largely conserved its niche during the global invasion process. More attention should be paid to the early warning, prevention, and control of P. semipunctata in the countries and regions where it has not yet become invasive.

Evidence of the niche expansion of crofton weed following invasion in China

Niche dynamics of invasive alien plants (IAPs) play pivotal roles in biological invasion. Ageratina adenophora-one of the most aggressive IAPs in China and some parts of the world-poses severe ecological and socioeconomic threats. However, the spatiotemporal niche dynamics of A. adenophora in China remain unknown, which we aimed to elucidate in the present study. China, Mexico; using a unifying framework, we reconstructed the climate niche dynamics of A. adenophora and applied the optimal MaxEnt model to predict its potential geographical distribution in China. Furthermore, we compared the heterogeneity of A. adenophora niche between Mexico (native) and China (invasive). We observed a low niche overlap between Mexico (native) and China (invasive). Specifically, the niche of A. adenophora in China has distinctly expanded compared to that in Mexico, enhancing the invasion risk of this IAP in the former country. In fact, the climatic niche of A. adenophora in Mexico is a subset of that in China. The potential geographical distribution of A. adenophora is concentrated in the tropical and subtropical zones of Southwest China, and its geographical distribution pattern in China is shaped by the combination of precipitation and temperature variables. The niche dynamics of A. adenophora follow the hypothesis of niche shift and conservatism. The present work provides a unifying framework for studies on the niche dynamics of other IAPs worldwide.

Spatial weed distribution models under climate change: a short review

Climate change is a concern worldwide that could trigger many changes with severe consequences. Since human demography is steadily increasing, agriculture has to be constantly investigated to aim at improving its efficiency. Weeds play a key role in this task, especially in the recent past and at present, when new introductions have been favoured by a rise in tourism and international trade. To obtain knowledge relating weeds and their behaviour to climate change, species distribution models (SDMs) have also increased recently. In this work, we have reviewed some articles published since 2017 on modelled weeds, aiming to give a response to, among other things, the species most studied, the scale and location of the studies, the algorithms used and validation parameters, global change scenarios, types of variables, and the sources from which the data were collected. Fifty-nine articles were selected to be reviewed, with maximum entropy (MaxEnt) and area under the curve (AUC) being the most popular software and validation processes. Environmental and topographic variables were considered above pedological and anthropogenic ones. Europe was the continent and China, the USA, and India the countries most studied. In this review, it was found that the number of published articles between developed and developing countries is unbalanced and comes out in favour of the former. The current knowledge on this topic can be considered to be good not enough, especially in developing countries with high population densities. The more knowledge we can obtain, the better our understanding is of how to deal with this issue, which is a worldwide preoccupation.

Potential distribution prediction of Amaranthus palmeri S. Watson in China under current and future climate scenarios

The vicious invasive alien plant Amaranthus palmeri poses a serious threat to ecological security and food security due to its strong adaptability, competitiveness, and herbicide resistance. Predicting its potential habitats under current and future climate change is critical for monitoring and early warning. In this study, we used two sets of climate data, namely, WorldClim1.4 and RCPs (the historical climate data of WorldClim version 1.4 and future climate data of RCPs), WorldClim2.1 and SSPs (the historical climate data of WorldClim version 2.1 and future climate data of SSPs), to analyze the dominant environmental variables affecting the habitat suitability and predict the potential distribution of A. palmeri to climate change in China based on the MaxEnt model. The results show that (i) Temperature has a greater impact on the distribution of A. palmeri. The relative contributions of temperature‐related variables count to 70% or more, and the annual mean temperature (bio1) reached more than 40%. (ii) At present, the potentially suitable area is widely distributed in the central‐east and parts of southwest China, and the high suitable area is focused on the North China Plain. The potential suitable area predicted by WorldClim1.4 and WorldClim2.1 both accounts for about 31% of China's total land area. (iii) Future climate change will expand the suitable habitats to high latitudes and altitudes. The overall suitable area maximum increased to 44.93% under SSPs and 38.91% under RCPs. We conclude that climate change would increase the risk of A. palmeri expanding to high latitudes and altitudes, the results have practical implications for the effective long‐term management in response to the global warming of A. palmeri.

Spatial Distribution Pattern and Risk Assessment of Invasive Alien Plants on Southern Side of the Daba Mountain Area

The southern side of the Daba Mountain area is a hotspot of global biodiversity and an essential barrier promoting ecological security. However, knowledge about the distribution status and transmission pathways of invasive alien species (IAS) in this area is limited. We counted the IAS on the southern side of the Daba Mountain area through sample transects and analyzed the factors affecting their spatial distribution. We also assessed IAS risk using the analytic hierarchy process (AHP), which found 64 IAS belonging to 23 families and 53 genera. Around rivers and roads, the results showed a vertical two-way dispersal pattern. Human and environmental factors, such as a very dense transportation network, can affect the distribution pattern of IAS. AHP assessed 43 IAS (67.19%), primarily distributed in villages and towns, as being of high or medium risk. High- and medium-risk IAS should be the focus of invasion prevention and control, and priority should be given to controlling the spread of IAS around rivers and roads.

Climatic Variability Caused by Topographic Barrier Prevents the Northward Spread of Invasive Ageratina adenophora

Ageratina adenophora (Spreng.) R.M.King & H.Rob. is one of the most threatening invasive alien plants in China. Since its initial invasion into Yunnan in the 1940s, it spread rapidly northward to southern Mount Nyba in Sichuan, which lies on the eastern edge of the Qinghai-Tibet Plateau. During fieldwork, we found an interesting phenomenon: A. adenophora failed to expand northward across Mount Nyba, even after the opening of the 10 km tunnel, which could have served as a potential corridor for its spread. In this work, to explore the key factors influencing its distribution and spread patterns, we used a combination of ensemble species distribution models with the MigClim model. We found that the temperature annual range (TAR), precipitation of driest month (PDM), highway density (HW), and wind speed (WS) were the most predominant factors affecting its distribution. The north of Mount Nyba is not suitable for A. adenophora survival due to higher TAR. The spatial-temporal dynamic invasion simulation using MigClim further illustrated that the northward invasion of A. adenophora was stopped by Mount Nyba. Overall, Mount Nyba may act as a topographic barrier that causes environmental differences between its south and north sides, preventing the northward invasion of A. adenophora. However, other suitable habitats on the northern side of the mountain still face challenges because A. adenophora is likely to invade via other routes. Therefore, long-term monitoring is needed to prevent human-induced long-distance spread events.

Mapping the Distribution and Dispersal Risks of the Alien Invasive Plant Ageratina adenophora in China

Identifying the distribution dynamics of invasive alien species can help in the early detection of and rapid response to these invasive species in newly invaded sites. Ageratina adenophora, a worldwide invasive plant, has spread rapidly since its invasion in China in the 1940s, causing serious damage to the local socioeconomic and ecological environment. To better control the spread of this invasive plant, we used the MaxEnt model and ArcGIS based on field survey data and online databases to simulate and predict the spatial and temporal distribution patterns and risk areas for the spread of this species in China, and thus examined the key factors responsible for this weed’s spread. The results showed that the risk areas for the invasion of A. adenophora in the current period were 18.394° N–33.653° N and 91.099° E–121.756° E, mainly in the tropical and subtropical regions of China, and densely distributed along rivers and well-developed roads. The high-risk areas are mainly located in the basins of the Lancang, Jinsha, Yalong, and Anning Rivers. With global climate change, the trend of continued invasion of A. adenophora is more evident, with further expansion of the dispersal zone towards the northeast and coastal areas in all climatic scenarios, and a slight contraction in the Yunnan–Guizhou plateau. Temperature, precipitation, altitude, and human activity are key factors in shaping the distribution pattern of A. adenophora. This weed prefers to grow in warm and precipitation-rich environments such as plains, hills, and mountains; in addition, increasing human activities provide more opportunities for its invasion, and well-developed water systems and roads can facilitate its spread. Measures should be taken to prevent its spread into these risk areas.

Predicting the potential geographical distribution of Ageratina adenophora in China using equilibrium occurrence data and ensemble model

Invasive alien plants (IAPs) pose a significant threat to the ecological environment and agricultural production in China. Ageratina adenophora is one of the most aggressive IAPs in China and poses serious ecological and socioeconomic threats. Estimating the distribution pattern of A. adenophora in China can provide baseline data for preventing damage by this weed. In the present study, based on the equilibrium occurrence data of A. adenophora in China and related environmental variables, we used an ensemble model to predict the distribution pattern of A. adenophora in China under climate change. Our findings indicated that true skill statistic (TSS), area under the receiver operating characteristic (ROC) curve (AUC), and Cohen’s Kappa (KAPPA) values for the ensemble model were 0.925, 0.993, and 0.936, respectively. The prediction results of the ensemble model were more accurate than those of the single models. Temperature variables had a significant impact on the potential geographical distribution (PGD) of A. adenophora in China. The total, high, and moderate suitability habitat areas of A. adenophora in China were 153.82 × 104, 92.13 × 104, and 21.04 × 104 km2, respectively, accounting for 16.02, 9.60, and 2.19% of the Chinese mainland area, respectively. The PGD of A. adenophora in China under the current climate is mainly located in southwestern and southeastern China, which are located in the tropical and subtropical zone. The high-suitability habitat areas of A. adenophora decreased under the future climate scenarios, mainly by changing to moderately suitable habitats in Southwest China. The geographical distribution of A. adenophora in southwestern China is currently saturated and will spread to southeastern China under climate change in the future. More attention should be paid to early warning and monitoring of A. adenophora in southeastern China to prevent its further spread.

Exploring the potential role of environmental and multi-source satellite data in crop yield prediction across Northeast China

Developing an accurate crop yield predicting system at a large scale is of paramount importance for agricultural resource management and global food security. Earth observation provides a unique source of information to monitor crops from a diversity of spectral ranges. However, the integrated use of these data and their values in crop yield prediction is still understudied. Here we proposed the combination of environmental data (climate, soil, geography, and topography) with multiple satellite data (optical-based vegetation indices, solar-induced fluorescence (SIF), land surface temperature (LST), and microwave vegetation optical depth (VOD)) into the framework to estimate crop yield for maize, rice, and soybean in northeast China, and their unique value and relative influence on yield prediction was assessed. Two linear regression methods, three machine learning (ML) methods, and one ML ensemble model were adopted to build yield prediction models. Results showed that the individual ML methods outperformed the linear regression methods, the ML ensemble model further improved the single ML models. Moreover, models with more inputs achieved better performance, the combination of satellite data with environmental data, which explained 72%, 69%, and 57% of maize, rice, and soybean yield variability, respectively, demonstrated higher yield prediction performance than individual inputs. While satellite data contributed to crop yield prediction mainly at the early-peak of the growing season, climate data offered extra information mainly at the peak-late season. We also found that the combined use of EVI, LST and SIF has improved the model accuracy compared to the benchmark EVI model. However, the optical-based vegetation indices shared similar information and did not provide much extra information beyond EVI. The within-season yield forecasting showed that crop yields can be satisfactorily forecasted at two to three months prior to harvest. Geography, topography, VOD, EVI, soil hydraulic and nutrient parameters are more important for crop yield prediction.

Composition, Distribution, and Factors Affecting Invasive Plants in Grasslands of Guizhou Province of Southwest China

Southwest China is an important route for invasive species. In this study, 49 invasive plants of 15 families and 41 genera were found within 373 grassland sampling sites of Guizhou Province, a typical karst mountainous region with a high invasion risk located in Southwest China. Invasive plants could be found within over 90% of the grassland sampling sites, and malignant invasive species were found in 60% of the sites. In about 30% of the sampling sites, more than one malignant species coexisted. The malignant invasive species were mainly distributed in the southwestern part of Guizhou Province. Their distribution patterns were affected by environmental and traffic factors; they preferred areas with low elevation, high temperature, high rainfall, high soil nutrient content, and traffic accessibility and could adversely affect plant cover and biomass. Conversely, seriously invasive species and other low-level invasive species had a positive or neutral effect on grassland communities. Therefore, the focus of invasive plant control measures should be on malignant invasive species. Specific control policies and practices, especially in areas with resource-rich environments and well-developed traffic networks, should be carried out to facilitate grassland ecosystem sustainability and to prevent the spread of invasive species to inland China.

Dam-induced difference of invasive plant species distribution along the riparian habitats

Riparian ecosystem is structurally unstable due to the frequent disturbances from water fluctuation. Moreover, dams on large rivers tend to trigger fundamental changes of the composition and structure of riparian plant communities, which provides high odds for invasive species to colonize. Yet, how the invasive species distribute along a dam-induced riparian habitat, and how the native species resist to plant invasion are still puzzles. In this study, we investigated spatial distribution of invasive floral species and its correlation with the distance from dam and the dam-triggered flooding stresses, as well as the resistance of native species to plant invasion in the water level fluctuation zone (WLFZ) of the Three Gorges Reservoir (TGR) along the Yangtze River. By our investigation, a total of 43 alien plant species belonging to 14 families and 34 genera were found, including 20 existed and 23 newly discovered alien species recorded. Most of the new invasive species are annual herbs of the Asteraceae family. At the current successional stage, the new invasive species had not yet fully occupied the habitats of the existed invasive species. Longitudinally, number and coverages of the new invasive species showed an opposite distribution pattern to the existed invasive species, but vertically they demonstrated similar pattern. Currently, the new dominant invasive species are mainly concentrated at the intermediate elevation of WLFZ in the middle section of the reservoir, whereas the existed dominant invasive species have proliferated across the whole WLFZ. Additionally, native species showed a weak resistance to plant invasion, and water fluctuation along the elevation exerted the most significant influence on plant invasion. The results indicated that, after a decade of riparian community succession, the invasiveness of alien species remain persisted. The potential penetration site of the invasion may locate at the intermediate section along the vertical and longitudinal dimension.

Investigating the Phenotypic Plasticity of the Invasive Weed Trianthema portulacastrum L

Phenotypic plasticity is frequently highlighted as a key factor in plant invasiveness, as it enables invasive species to adapt to diverse, complicated habitats. Trianthema portulacastrum is one of the most common aggressive species that threaten different crops around the world. Phenotypic plasticity in T. portulacastrum was investigated by comparing variation in germination, vegetative macromorphology, photosynthetic pigments, stomatal complexes, and seed micromorphological traits of 35 samples collected from 35 different localities. One-way cluster analysis and principal component analysis (PCA) were used to classify samples into homogeneous groups based on the measured traits. Pairwise statistical comparisons were conducted between the three resulting groups. The phenotypic plasticity index (PI) was calculated and compared among different groups of characters. Results showed that photosynthetic pigments and macromorphological characteristics had the highest PI, followed by seed micromorphology, and then stomatal complex traits, while germination parameters showed the lowest PI. We propose that soil moisture, salinity, and temperature are the most determinative and explanative variables of the variation between the three classified groups. We strongly believe that the phenotypic plasticity of T. portulacastrum will support species abundance and spread even under expected changes in climatic conditions, in contrast to the vulnerable traditional crops.

Engineering conversion of Asteraceae plants into biochars for exploring potential applications: A review

Asteraceae presents one of the most globally prevalent, cultivated, and fundamental plant families. However, a large amount of agricultural wastes has been yearly released from Asteraceae crops, causing adverse impacts on the environment. The objective of this work is to have insights into their biomass potentials and technical possibility of conversion into biochars. Physicochemical properties are systematically articulated to orientate environmental application, soil amendment, and other utilizations. Utilizations of Asteraceae biochars in wastewater treatment can be categorized by heavy metal ions, organic dyes, antibiotics, persistent organic pollutants (POPs), and explosive compounds. Some efforts were made to analyze the production cost, as well as the challenges and prospects of Asteraceae-based biochars.

Investigating the Invasion Pattern of the Alien Plant Solanum elaeagnifolium Cav. (Silverleaf Nightshade): Environmental and Human-Induced Drivers

Invasive alien plant species have impacts on nature conservation, ecosystem services and agricultural production. To identify environmental and human-related drivers of the invasion of Solanum elaeagnifolium (Solanaceae)—one of the worst alien invasive plants worldwide—we conducted an extensive drive-by survey across the Greek territory (presence/absence data; all national major multilane highways; 12–25% of the remaining road network; driven 3–5 times during 2000–2020). These data were linked in GIS with (i) physical environmental attributes (elevation, climate, soil properties) and (ii) type and intensity of human-related activities (land uses, settlements and road type). Compared to previous records, our survey showed that the range of S. elaeagnifolium increased by 1750% during the last decades, doubling its main distribution centers and reaching higher elevations. Our study revealed that the presence of S. elaeagnifolium is associated with (i) higher maximum temperatures and precipitation in summer and low precipitation in winter, as well as with (ii) soil disturbance related to agricultural activities, settlements and road networks, thus facilitating its spread mainly at low altitudes. Our study elucidates the current invasion pattern of S. elaeagnifolium and highlights the urgent need for its widespread monitoring, at least in the noninvaded areas in Greece that have been surveyed in this study. Preventative measures and integrative initiatives should be implemented quickly, and urgently incorporated into current agricultural, road network and conservation-management regimes.

Adaptation, restoration and collapse of anammox process to La(III) stress: Performance, microbial community, metabolic function and network analysis

During the mining of rare earth mineral, the use of lanthanum-containing fertilizers, and the disposal of lanthanum-containing electronic products, the content of lanthanum (La(III)) in typical ammonia wastewater with low carbon to nitrogen ratio is increasing day by day. Here, effects of La(III) on anammox process in performance, microbial community structure, metabolic function, and microbial co-occurrence network were investigated. The results shown that the nitrogen removal efficiency was declines briefly and then gradually recovers after low dosage (1-5 mg/L) La(III) treatment and the decrease to low level (24.25 ± 1.74%) under high La(III) dosage (10 mg/L). La(III) in the range of 1-5 mg/L significantly promoted the relative abundance of Anammoxoglobus (0.024% to 9.762%). The blocking of key metabolic pathways was confirmed to cause the breakdown of anammox by PICRUSt. Furthermore, network analysis revealed that lack of cooperation bacteria limits the activity of Anammoxoglobus.