Modelling species distributions and environmental suitability highlights risk of plant invasions in western United States

Modeling current and future distributions of invasive Asteraceae species in Northeast China

The ecological balance and agricultural productivity of northeastern China are seriously threatened by the long-term invasion and spread of Asteraceae plants, which have severely disrupted the region's biodiversity and ecosystem stability. Ambrosia artemisiifolia L., Ambrosia trifida L., and Erigeron canadensis L. are Class 1 malignant invasive species widely distributed across northeastern China. In this context, we selected 36 predictor variables and utilized the MaxEnt model to investigate the influence of current climate on their distribution patterns. Using future climate data, we projected shifts in the distribution dynamics of these three Asteraceae species for two time periods (2041-2060 and 2061-2080) under three climate change scenarios (SSP126, SSP245, and SSP585). The MaxEnt model demonstrated a good predictive impact, with an average area under the curve (AUC) of 0.918. Currently, the three Asteraceae species are primarily found in the southern part of northeastern China. However, due to future climatic changes, their distribution centroids are gradually shifting southwest, leading to an increase in the area of highly suitable zones for these species. Moreover, trend analysis revealed that the potential distribution changes of highly suitable zones for the three Asteraceae species in the southwestern northeastern China are likely to experience an increasing invasive trend under various future climate models. This study provides initial insights into the distribution dynamics of Asteraceae species in northeastern China under climate change, enabling the formulation of plans for managing and preventing the risks and impacts of invasive species.

Projected Impacts of Climate Change on the Range Expansion of the Invasive Straggler Daisy (Calyptocarpus vialis) in the Northwestern Indian Himalayan Region

Human-induced climate change modifies plant species distribution, reorganizing ecologically suitable habitats for invasive species. In this study, we identified the environmental factors that are important for the spread of Calyptocarpus vialis, an emerging invasive weed in the northwestern Indian Himalayan Region (IHR), along with possible habitats of the weed under current climatic scenarios and potential range expansion under several representative concentration pathways (RCPs) using MaxEnt niche modeling. The prediction had a high AUC (area under the curve) value of 0.894 ± 0.010 and a remarkable correlation between the test and expected omission rates. BIO15 (precipitation seasonality; 38.8%) and BIO1 (annual mean temperature; 35.7%) had the greatest impact on the probable distribution of C. vialis, followed by elevation (11.7%) and landcover (6.3%). The findings show that, unlike the current situation, "high" and "very high" suitability areas would rise while less-suited habitats would disappear. All RCPs (2.6, 4.5, 6.0, and 8.5) indicate the expansion of C. vialis in "high" suitability areas, but RCP 4.5 predicts contraction, and RCPs 2.6, 6.0, and 8.5 predict expansion in "very high" probability areas. The current distribution of C. vialis is 21.59% of the total area of the state, with "medium" to "high" invasion suitability, but under the RCP 8.5 scenario, it might grow by 10% by 2070. The study also reveals that C. vialis may expand its niche at both lower and higher elevations. This study clarifies how bioclimatic and topographic factors affect the dispersion of invasive species in the biodiverse IHR. Policymakers and land-use managers can utilize the data to monitor C. vialis hotspots and develop scientifically sound management methods.

Impacts of climate change on climatically suitable regions of two invasive Erigeron weeds in China

Introduction

Erigeron philadelphicus and Erigeron annuus are two ecologically destructive invasive plants from the Asteraceae family. Predicting the potential distribution pattern of two invasive alien Erigeron weeds can provide a scientific basis for prevent the further spread of these two weeds in China under climate change.

Methods

Based on historical occurrence datasets and environmental variables, we optimized a MaxEnt model to predict the potential suitable habitats of E. philadelphicus and E. annuus. We also analyzed the shifts of distribution centroids and patterns under climate change scenarios.

Results

The key variables that affect the potential geographical distribution of E. annuus and E. philadelphicus, respectively, are temperature seasonality and precipitation of the driest month. Moreover, topsoil sodicity and topsoil salinity also influence the distribution of E. philadelphicus. Under climate change, the overall suitable habitats for both invasive alien Erigeron weeds are expected to expand. The potential geographical distribution of E. annuus exhibited the highest expansion under the SSP245 climate scenario (medium forcing scenarios), whereas E. philadelphicus had the highest expansion under the SSP126 climate scenario (lower forcing scenarios) globally. The future centroid of E. annuus is projected to shift to higher latitudes specifically from Hubei to Hebei, whereas E. philadelphicus remains concentrated primarily in Hubei Province. The overlapping suitable areas of the two invasive alien Erigeron plants mainly occur in Jiangsu, Zhejiang, Fujian, Jiangxi, Hunan, Guizhou, and Chongqing, within China.

Discussion

Climate change will enable E. annuus to expand into northeastern region and invade Yunnan Province whereas E. philadelphicus was historically the only suitable species. E. annuus demonstrates a greater potential for invasion and expansion under climate change, as it exhibits higher environmental tolerance. The predictive results obtained in this study can serve as a valuable reference for early warning systems and management strategies aimed at controlling the spread of these two invasive plants.

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 and the potential distribution of the glassy-winged sharpshooter (Homalodisca vitripennis), an insect vector of Xylella fastidiosa

Biological invasions represent a major threat for biodiversity and agriculture. Despite efforts to restrict the spread of alien species, preventing their introduction remains the best strategy for an efficient control. In that context preparedness of phytosanitary authorities is very important and estimating the geographical range of alien species becomes a key information. The present study investigates the potential geographical range of the glassy-winged sharpshooter (Homalodisca vitripennis), a very efficient insect vector of Xylella fastidiosa, one of the most dangerous plant-pathogenic bacteria worldwide. We use species distribution modeling (SDM) to analyse the climate factors driving the insect distribution and we evaluate its potential distribution in its native range (USA) and in Europe according to current climate and different scenarios of climate change: 6 General Circulation Models (GCM), 4 shared socioeconomic pathways of gas emission and 4 time periods (2030, 2050, 2070, 2090). The first result is that the climate conditions of the European continent are suitable to the glassy-winged sharpshooter, in particular around the Mediterranean basin where X. fastidiosa is present. Projections according to future climate conditions indicate displacement of climatically suitable areas towards the north in both North America and Europe. Globally, suitable areas will decrease in North America and increase in Europe in the coming decades. SDM outputs vary according to the GCM considered and this variability indicated areas of uncertainty in the species potential range. Both potential distribution and its uncertainty associated to future climate projections are important information for improved preparedness of phytosanitary authorities.

New indicators of ecological resilience and invasion resistance to support prioritization and management in the sagebrush biome, United States

Ecosystem transformations to altered or novel ecological states are accelerating across the globe. Indicators of ecological resilience to disturbance and resistance to invasion can aid in assessing risks and prioritizing areas for conservation and restoration. The sagebrush biome encompasses parts of 11 western states and is experiencing rapid transformations due to human population growth, invasive species, altered disturbance regimes, and climate change. We built on prior use of static soil moisture and temperature regimes to develop new, ecologically relevant and climate responsive indicators of both resilience and resistance. Our new indicators were based on climate and soil water availability variables derived from process-based ecohydrological models that allow predictions of future conditions. We asked: (1) Which variables best indicate resilience and resistance? (2) What are the relationships among the indicator variables and resilience and resistance categories? (3) How do patterns of resilience and resistance vary across the area? We assembled a large database (n = 24,045) of vegetation sample plots from regional monitoring programs and derived multiple climate and soil water availability variables for each plot from ecohydrological simulations. We used USDA Natural Resources Conservation Service National Soils Survey Information, Ecological Site Descriptions, and expert knowledge to develop and assign ecological types and resilience and resistance categories to each plot. We used random forest models to derive a set of 19 climate and water availability variables that best predicted resilience and resistance categories. Our models had relatively high multiclass accuracy (80% for resilience; 75% for resistance). Top indicator variables for both resilience and resistance included mean temperature, coldest month temperature, climatic water deficit, and summer and driest month precipitation. Variable relationships and patterns differed among ecoregions but reflected environmental gradients; low resilience and resistance were indicated by warm and dry conditions with high climatic water deficits, and moderately high to high resilience and resistance were characterized by cooler and moister conditions with low climatic water deficits. The new, ecologically-relevant indicators provide information on the vulnerability of resources and likely success of management actions, and can be used to develop new approaches and tools for prioritizing areas for conservation and restoration actions.

Atlantic rainforest natural regeneration in fragmented formations affected by increasing human disturbance

Forests provides major ecosystem services worldwide. The Brazilian Atlantic Forest (BAF) has been dramatically devastated, with fragmentation processes jeopardizing its long-term sustainability. This study investigated the structure and successional dynamics in BAF natural regeneration along an anthroposequence characterized by increasing human disturbance histories as: secondary (SF) > disturbed (DF) > late forest (LF). We aimed to understand how and the degree to which BAF fragmentation and human disturbance affected plants, soils, and the whole soil-plant relationships and feedbacks. We investigated the natural regeneration conditions of plants (using plant classification and quali-quantitative analyses) and soil chemistry (including pH-CaCl₂, H + Al, C, N, Pt, cation-exchange capacity (CEC), exchangeable cations, Al, B, Cu, Fe, K, Mn, and Zn) at twelve permanent, 2000 m² plots, distributed across LF, DF, and SF forests. Significant differences were determined by ANOVA. Correlation matrix (CM) and factor analysis (FA) were used for understanding correlations and feedbacks/variability among investigated parameters, respectively. Most of investigated plant and soil parameters showed significant differences (p < 0.05) between more developed plant formations (LF) vs less developed ones (SF), with differences mainly due to soil's development stage. All investigated forest formations are featured by a great influence of the soil-plant relationships and feedbacks, with a decreasing magnitude as LF → DF → SF. Thus, there is a direct, statistically recognizable impact of both "recent" as well as "ancient" human disturbance on investigated soil-plant formations. The anthropogenic influence clearly affected not only plant and soil as "separate" systems but the whole complex of interactions and feedbacks among ecosystem components. A decreasing quality in soil and plant parameters was observed as human disturbance increased. We demonstrated that BAF plant and soil require decades for their recovery after human disturbances, with complex mechanisms and behaviors in the relationships among ecosystem components. The results can be useful for managing future recovery in an ecosystem of worldwide strategic importance.

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.

Multi-Species Inference of Exotic Annual and Native Perennial Grasses in Rangelands of the Western United States Using Harmonized Landsat and Sentinel-2 Data

The invasion of exotic annual grass (EAG), e.g., cheatgrass (Bromus tectorum) and medusahead (Taeniatherum caput-medusae), into rangeland ecosystems of the western United States is a broad-scale problem that affects wildlife habitats, increases wildfire frequency, and adds to land management costs. However, identifying individual species of EAG abundance from remote sensing, particularly at early stages of invasion or growth, can be problematic because of overlapping controls and similar phenological characteristics among native and other exotic vegetation. Subsequently, refining and developing tools capable of quantifying the abundance and phenology of annual and perennial grass species would be beneficial to help inform conservation and management efforts at local to regional scales. Here, we deploy an enhanced version of the U.S. Geological Survey Rangeland Exotic Plant Monitoring System to develop timely and accurate maps of annual (2016–2020) and intra-annual (May 2021 and July 2021) abundances of exotic annual and perennial grass species throughout the rangelands of the western United States. This monitoring system leverages field observations and remote-sensing data with artificial intelligence/machine learning to rapidly produce annual and early season estimates of species abundances at a 30-m spatial resolution. We introduce a fully automated and multi-task deep-learning framework to simultaneously predict and generate weekly, near-seamless composites of Harmonized Landsat Sentinel-2 spectral data. These data, along with auxiliary datasets and time series metrics, are incorporated into an ensemble of independent XGBoost models. This study demonstrates that inclusion of the Normalized Difference Vegetation Index and Normalized Difference Wetness Index time-series data generated from our deep-learning framework enables near real-time and accurate mapping of EAG (Median Absolute Error (MdAE): 3.22, 2.72, and 0.02; and correlation coefficient (r): 0.82, 0.81, and 0.73; respectively for EAG, cheatgrass, and medusahead) and native perennial grass abundance (MdAE: 2.51, r:0.72 for Sandberg bluegrass (Poa secunda)). Our approach and the resulting data provide insights into rangeland grass dynamics, which will be useful for applications, such as fire and drought monitoring, habitat suitability mapping, as well as land-cover and land-change modelling. Spatially explicit, timely, and accurate species-specific abundance datasets provide invaluable information to land managers.

Interannual climate variability mediates changes in carbon and nitrogen pools caused by annual grass invasion in a semiarid shrubland

Exotic plant invasions alter ecosystem properties and threaten ecosystem functions globally. Interannual climate variability (ICV) influences both plant community composition (PCC) and soil properties, and interactions between ICV and PCC may influence nitrogen (N) and carbon (C) pools. We asked how ICV and non-native annual grass invasion covary to influence soil and plant N and C in a semiarid shrubland undergoing widespread ecosystem transformation due to invasions and altered fire regimes. We sampled four progressive stages of annual grass invasion at 20 sites across a large (25,000 km² ) landscape for plant community composition, plant tissue N and C, and soil total N and C in 2013 and 2016, which followed 2 years of dry and wet conditions, respectively. Multivariate analyses and ANOVAs showed that in invasion stages where native shrub and perennial grass and forb communities were replaced by annual grass-dominated communities, the ecosystem lost more soil N and C in wet years. Path analysis showed that high water availability led to higher herbaceous cover in all invasion stages. In stages with native shrubs and perennial grasses, higher perennial grass cover was associated with increased soil C and N, while in annual-dominated stages, higher annual grass cover was associated with losses of soil C and N. Also, soil total C and C:N ratios were more homogeneous in annual-dominated invasion stages as indicated by within-site standard deviations. Loss of native shrubs and perennial grasses and forbs coupled with annual grass invasion may lead to long-term declines in soil N and C and hamper restoration efforts. Restoration strategies that use innovative techniques and novel species to address increasing temperatures and ICV and emphasize maintaining plant community structure-shrubs, grasses, and forbs-will allow sagebrush ecosystems to maintain C sequestration, soil fertility, and soil heterogeneity.