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Invasive plants are a prominent threat to ecosystems and economies worldwide. Knowing the identity of invasive plants is critical for preventing their introduction and spread. Yet several lines of evidence, including spatial and taxonomic biases in reporting and the ongoing emergence of new invasives, suggest that we are missing basic information about the identity of invasive plants. Using a database of invasive plants reported in the peer-reviewed literature between 1959 and 2020, we examined trends in the accumulation of new invasive plants over time and estimated the size of the current pool of invasive plants both continentally and globally. The number of new invasive plants continues to increase exponentially over time, showing no sign of saturation, even in the best studied regions. Moreover, a sample-size based rarefaction-extrapolation curve of reported taxa suggests that what is documented in the current literature (3008 taxa) only captures 64% of the likely number of invasive plants globally (4721 taxa ± 132 SE). These estimates varied continentally; less than half of invasive plant taxa have likely been identified in Oceania and Central and South Americas. Studies that included multiple invasive plants (e.g., floristic studies) were much more efficient at adding new taxa to our global understanding of what is invasive (identifying 4.2 times more new taxa than single-taxon studies). With more potential invaders arriving every day, this analysis highlights a critical gap in our knowledge of the current invasive plant pool. Expanding invasion science to better encompass understudied geographic areas and increasing the numbers of floristic surveys would greatly improve our ability to accurately and efficiently identify what taxa are invasive. Preventing invasive plant introductions is incumbent upon knowing the identity of invasive plants. Thus, large knowledge gaps remain in invasion ecology that hinder efforts to proactively prevent and manage invasive plants.

Effective natural resource management and policy is contingent on information generated by research. Conversely, the applicability of research depends on whether it is responsive to the needs and constraints of resource managers and policy makers. However, many scientific fields including invasion ecology suffer from a disconnect between research and practice. Despite strong socio-political imperatives, evidenced by extensive funding dedicated to addressing invasive species, the pairing of invasion ecology with stakeholder needs to support effective management and policy is lacking. As a potential solution, we propose translational invasion ecology (TIE). As an extension of translational ecology, as a framework to increase collaboration among scientists, practitioners, and policy makers to reduce negative impacts of invasive species. As an extension of translational ecology, TIE is an approach that embodies an intentional and inclusive process in which researchers, stakeholders, and decision makers collaborate to develop and implement ecological research via joint consideration of the ecological, sociological, economic, and/or political contexts in order to improve invasive species management. TIE ideally results in improved outcomes as well as shared benefits between researchers and managers. We delineate the steps of our proposed TIE approach and describe successful examples of ongoing TIE projects from the US and internationally. We suggest practical ways to begin incorporating TIE into research and management practices, including supporting boundary-spanning organizations and activities, expanding networks, sharing translational experiences, and measuring outcomes. We find that there is a need for strengthened boundary spanning, as well as funding and recognition for advancing translational approaches. As climate change and globalization exacerbate invasive species impacts, TIE provides a promising approach to generate actionable ecological research while improving outcomes of invasive species management and policy decisions.

Proactively addressing future impacts of invasive plants depends critically on modeling invasive plant abundance. Yet, the vast majority of spatial models of invasion risk focus on occurrence alone. Expanding spatial analyses to consider not only potential for establishment, but also potential for high abundance is an important next step in ecological modeling. We assembled spatial reports of occurrence and abundance across the coterminous United States for 70 terrestrial invasive plants. Using records of occurrence, we used maximum entropy to model suitable climate and land cover conditions for each species’ potential range (‘establishment range’). Combining abundance information into high, medium, and low ranks, we used ordinal regression to model suitable conditions for high potential abundance of each species (‘abundance range’). We compared establishment versus abundance ranges to assess overlap for individual species as well as geographic hotspots of invasion risk. Across all species, the abundance range encompassed a mean of only 16% of the establishment range. Hotspots where many species’ ranges overlapped were consistent for establishment and abundance ranges in 47% of land area. But, modeling establishment alone missed many abundance hotspots, particularly in western U.S. ecoregions. Expanding ecological modeling to focus on invasive plant abundance provides a considerably different view of geographic invasion risk. Our results suggest that spatial models using occurrence data alone are likely to overestimate areas of high impact in their assessment of ‘invasion risk’. Considering abundance in spatial models of invasion risk is a critical next step for more targeted monitoring and management.

Non-native, invasive Bromus tectorum (cheatgrass) is pervasive in sagebrush ecosystems in the Great Basin ecoregion of the western United States, competing with native plants and promoting more frequent fires. As a result, cheatgrass invasion likely alters carbon (C) storage in the region. Many studies have measured C pools in one or more common vegetation types: native sagebrush, invaded sagebrush and cheatgrass-dominated (often burned) sites, but these results have yet to be synthesized. We performed a literature review to identify studies assessing the consequences of invasion on C storage in above-ground biomass (AGB), below-ground biomass (BGB), litter, organic soil and total soil. We identified 41 articles containing 386 unique studies and estimated C storage across pools and vegetation types. We used linear mixed models to identify the main predictors of C storage. We found consistent declines in biomass C with invasion: AGB C was 55% lower in cheatgrass (40 ± 4 g C/m2) than native sagebrush (89 ± 27 g C/m2) and BGB C was 62% lower in cheatgrass (90 ± 17 g C/m2) than native sagebrush (238 ± 60 g C/m2). In contrast, litter C was >4× higher in cheatgrass (154 ± 12 g C/m2) than native sagebrush (32 ± 12 g C/m2). Soil organic C (SOC) in the top 10 cm was significantly higher in cheatgrass than in native or invaded sagebrush. SOC below 20 cm was significantly related to the time since most recent fire and losses were observed in deep SOC in cheatgrass >5 years after a fire. There were no significant changes in total soil C across vegetation types. Synthesis and applications. Cheatgrass invasion decreases biodiversity and rangeland productivity and alters fire regimes. Our findings indicate cheatgrass invasion also results in persistent biomass carbon (C) losses that occur with sagebrush replacement. We estimate that conversion from native sagebrush to cheatgrass leads to a net reduction of C storage in biomass and litter of 76 g C/m2, or 16 Tg C across the Great Basin without management practices like native sagebrush restoration or cheatgrass removal.

As Earth’s climate rapidly changes, species range shifts are considered key to species persistence. However, some range-shifting species will alter community structure and ecosystem processes. By adapting existing invasion risk assessment frameworks, we can identify characteristics shared with high-impact introductions and thus predict potential impacts. There are fundamental differences between introduced and range-shifting species, primarily shared evolutionary histories between range shifters and their new community. Nevertheless, impacts can occur via analogous mechanisms, such as wide dispersal, community disturbance and low biotic resistance. As ranges shift in response to climate change, we have an opportunity to develop plans to facilitate advantageous movements and limit those that are problematic. Climate change will cause species to shift their ranges to persist. This Review uses invasion ecology theory to consider the impacts of shifting species and how to manage these shifts to protect the recipient communities as well as the survival of the shifters.

Non-native, invasive plants are projected to shift their ranges with climate change, creating hotspots of risk where a multitude of novel species may soon establish and spread. The Northeast U.S. is one such hotspot. However, because monitoring for novel species is costly, these range-shifting invasive plants need to be prioritized. Preventing negative impacts is a key goal of management, thus, comparing the potential impacts of range-shifting invasive species could inform this prioritization. Here, we adapted the environmental impacts classification for alien taxa protocol to evaluate potential impacts of 100 invasive plants that could establish either currently or by 2050 in the states of New York, Massachusetts, Connecticut, or Rhode Island. We searched Web of Science for each species and identified papers reporting ecological, economic, human health, or agricultural impacts. We scored ecological impacts from 1 (‘minimal concern’) to 4 (‘major’) and socio-ecological impacts as present or absent. We evaluated 865 impact studies and categorized 20 species as high-impact, 36 as medium-impact, and 26 as low-impact. We further refined high-impact invasive species based on whether major impacts affect ecosystems found in Northeast U.S. and identified five high-priority species: Anthriscus caucalis, Arundo donax, Avena barbata, Ludwigia grandiflora, and Rubus ulmifolius. Additional research is needed for 18 data-deficient species, which had no studies reporting impacts. Identifying and prioritizing range-shifting invasive plants provides a unique opportunity for early detection and rapid response that targets future problem species before they can establish and spread. This research illustrates the feasibility of using impacts assessments on range-shifting invasive species in order to inform proactive policy and management.

When analyzing biotic resistance/diversity-invasibility, including predictors of species richness may result in a false negative correlation between native and non-native richness. However, reanalysis of vegetation surveys shows that the negative effect of native richness is statistically significant whether or not predictors of species richness are included.

Cheatgrass (Bromus tectorum) has increased the extent and frequency of fire and negatively affected native plant and animal species across the Intermountain West (USA). However, the strengths of association between cheatgrass occurrence or abundance and fire, livestock grazing, and precipitation are not well understood. We used 14 years of data from 417 sites across 10,000 km2 in the central Great Basin to assess the effects of the foregoing predictors on cheatgrass occurrence and prevalence (i.e., given occurrence, the proportion of measurements in which the species was detected). We implemented hierarchical Bayesian models and considered covariates for which > 0.90 or

Fire-prone invasive grasses create novel ecosystem threats by increasing fine-fuel loads and continuity, which can alter fire regimes. While the existence of an invasive grass-fire cycle is well known, evidence of altered fire regimes is typically based on local-scale studies or expert knowledge. Here, we quantify the effects of 12 nonnative, invasive grasses on fire occurrence, size, and frequency across 29 US ecoregions encompassing more than one third of the conterminous United States. These 12 grass species promote fire locally and have extensive spatial records of abundant infestations. We combined agency and satellite fire data with records of abundant grass invasion to test for differences in fire regimes between invaded and nearby “uninvaded” habitat. Additionally, we assessed whether invasive grass presence is a significant predictor of altered fire by modeling fire occurrence, size, and frequency as a function of grass invasion, in addition to anthropogenic and ecological covariates relevant to fire. Eight species showed significantly higher fire-occurrence rates, which more than tripled for Schismus barbatus and Pennisetum ciliare. Six species demonstrated significantly higher mean fire frequency, which more than doubled for Neyraudia reynaudiana and Pennisetum ciliare . Grass invasion was significant in fire occurrence and frequency models, but not in fire-size models. The significant differences in fire regimes, coupled with the importance of grass invasion in modeling these differences, suggest that invasive grasses alter US fire regimes at regional scales. As concern about US wildfires grows, accounting for fire-promoting invasive grasses will be imperative for effectively managing ecosystems.

Invasive Alien Species (IAS) are amongst the most significant drivers of species extinction and ecosystem degradation, causing negative impacts on ecosystem services and human well-being. InvasiBES, a project funded by BiodivERsA-Belmont Forum for 2019–2021, will use data and models across scales, habitats and species to understand and anticipate the multi-faceted impacts of IAS and to provide tools for their management. Using Alien Species Narratives as reference, we will design future intervention scenarios focused on prevention, control and eradication of IAS in Europe and the United States, through a participatory process bringing together the expertise of scientists and stakeholders. We will also adapt current impact assessment protocols to assess both the detrimental and beneficial impacts of IAS on biodiversity and ecosystem services. This information will then be combined with maps of the potential distribution of Invasive Species of Interest in Europe under current and future climate-change scenarios. Likewise, we will anticipate areas under risk of invasion by range-shifting plants of concern in the US. Finally, focusing on three local-scale studies that cover a range of habitats (freshwater, terrestrial and marine), invasive species (plants and animals) and ecosystem services (supporting, provisioning, regulating and cultural), we will use empirical field data to quantify the real-world impacts of IAS on biodiversity and ecosystem services and calculate indicators of ecosystem recovery after the invader is removed. Spatial planning tools (InVEST) will be used to evaluate the costs and benefits of species-specific intervention scenarios at the regional scale. Data, models and maps, developed throughout the project, will serve to build scenarios and models of biodiversity and ecosystem services that are relevant to underpin management of IAS at multiple scales.

Invasive alien species are likely to interact with climate change, thus necessitating management that proactively addresses both global changes. However, invasive species managers’ concerns about the effects of climate change, the degree to which they incorporate climate change into their management, and what stops them from doing so remain unknown. Therefore, we surveyed natural resource managers addressing invasive species across the U.S. about their priorities, concerns, and management strategies in a changing climate. Of the 211 managers we surveyed, most were very concerned about the influence of climate change on invasive species management, but their organizations were significantly less so. Managers reported that lack of funding and personnel limited their ability to effectively manage invasive species, while lack of information limited their consideration of climate change in decision-making. Additionally, managers prioritized research that identifies range-shifting invasive species and native communities resilient to invasions and climate change. Managers also reported that this information would be most effectively communicated through conversations, research summaries, and meetings/symposia. Despite the need for more information, 65% of managers incorporate climate change into their invasive species management through strategic planning, preventative management, changing treatment and control, and increasing education and outreach. These results show the potential for incorporating climate change into management, but also highlight a clear and pressing need for more targeted research, accessible science communication, and two-way dialogue between researchers and managers focused on invasive species and climate change.

International audience; To predict the threat of biological invasions to native species, it is critical that we understand how increasing abundance of invasive alien species (IAS) affects native populations and communities. The form of this relationship across taxa and ecosystems is unknown, but is expected to depend strongly on the trophic position of the IAS relative to the native species. Using a global metaanalysis based on 1,258 empirical studies presented in 201 scientific publications, we assessed the shape, direction, and strength of native responses to increasing invader abundance. We also tested how native responses varied with relative trophic position and for responses at the population vs. community levels. As IAS abundance increased, native populations declined nonlinearly by 20%, on average, and community metrics declined linearly by 25%. When at higher trophic levels, invaders tended to cause a strong, nonlinear decline in native populations and communities, with the greatest impacts occurring at low invader abundance. In contrast, invaders at the same trophic level tended to cause a linear decline in native populations and communities, while invaders at lower trophic levels had no consistent impacts. At the community level, increasing invader abundance had significantly larger effects on species evenness and diversity than on species richness. Our results show that native responses to invasion depend critically on invasive species’ abundance and trophic position. Further, these general abundance–impact relationships reveal how IAS impacts are likely to develop during the invasion process and when to best manage them.

Global change experiments are often spatially and temporally limited because they are time‐ and labor‐intensive, and expensive to carry out. We describe how the incorporation of remote‐sensing techniques into global change experiments can complement traditional methods and provide additional information about system processes. We describe five emerging near‐surface remote‐sensing techniques: spectroscopy, thermal and fluorescence imaging, terrestrial laser scanning, digital repeat photography, and unmanned aerial systems. The addition of such techniques can reduce cost and effort, provide novel information, and expand existing observations by improving their context, accuracy, and completeness. In addition, we contend that use of airborne and satellite remote‐sensing data during site selection can improve the ecological representativeness of future experiments. We conclude by recommending a high level of communication and collaboration between remote‐sensing scientists and ecologists at all stages of global change experimentation.

Stopping invasive species early, before they are introduced or before they have a chance to spread, is essential for effective invasive species management. With new plants introduced constantly through global trade and shifting their ranges due to climate change, proactive action to prevent invasions is more important than ever. But, before we can prevent invasions through policy, monitoring, and management, we need to know the identity of which species are invasive. Existing lists of invasive plants vary across political and jurisdictional boundaries, often rely on inconsistent knowledge of local experts, and may conflate nonnative with invasive. Here, we reviewed papers published from 1959 to 2020 to create a single consistently derived list of known invasive plants. We searched the Web of Science core collection for "articles" containing the keywords "invasi*" and "plant" within the categories "Ecology," "Environmental Sciences," "Biodiversity Conservation," and "Plant Sciences." We also reviewed papers cited in reviews of invasive plants (see Metadata S1, Class II, Section B). We read titles and abstracts to identify papers that focused on nonnative and invasive vascular plants and included in the database any nonnative plant taxon either explicitly termed invasive in the paper or implicitly defined as invasive through a description of abundance, spread and/or impact. For 2017-2020, we included only papers that described multiple invasive plants, which are much more likely to uncover novel taxa. For each paper, we retained the reported invasive taxon name, text defining invasiveness, bibliographic information, and the country or countries in the invaded range where the study took place. We used Catalogue of Life and the Plant Taxonomic Name Resolution Source to resolve the taxonomy of the invasive taxa and compiled a list of unique invasive plants described in one or more scientific papers. We extracted data from 5,893 papers and identified 3,008 unique taxa, including 2,842 species, 96 subspecies, 29 varieties, and 41 hybrids. Of these, 2,981 taxa were resolved, while 27 were unresolved. 42% of the total unique taxa were studied once in the database. This database provides a consistent, global assessment of nonnative, invasive plant taxa. We release these data into the public domain under a Creative Commons Zero license waiver (https://creativecommons.org/share-your-work/public-domain/cc0/). Individuals who use these data for publication may cite this data paper.

Southern New England is currently experiencing the first major gypsy moth (Lymantria dispar) defoliation event in nearly 30 years. Using a novel approach based on time series of Landsat satellite observations, we generated consistent maps of gypsy moth defoliation for 2015 (first year of the outbreak), 2016 (second year of outbreak), and 2017 (third year of outbreak). Our mapped results demonstrate that the defoliation event continued through the 2017 growing season. Moreover, the affected area more than doubled in extent each year and expanded radially to encompass 4386 km2 of forested area in Rhode Island, eastern Connecticut, and central Massachusetts. The current gypsy moth outbreak is believed to be the result of a series of unusually dry springs in 2014, 2015, and 2016, which suppressed Entomophaga maimaiga, a fungal mortality agent that has historically reduced gypsy moth impacts in this region. The continuation and marked expansion of the outbreak in 2017 despite average spring rainfall suggests that caterpillars were active early in the growing season, and mortality from the fungus likely peaked after significant defoliation had already occurred. Our Landsat time series approach represents an important new source of data on spatial and temporal patterns in gypsy moth defoliation, and continued satellite-based monitoring will be essential for tracking the progress of this and other gypsy moth outbreaks.

Cheatgrass (Bromus tectorum L.) presence in the Great Basin is associated with an increase in fire frequency and size, likely due to increased spatial continuity of fine fuel biomass. Measurements of the extent and cover of cheatgrass are steadily improving, but the strength of the relationship between cover and aboveground biomass (AGB) is unclear. An allometric equation that can reliably convert cover to AGB of cheatgrass would allow for improved incorporation of regional estimates of cover into models of fire activity, carbon storage, and net primary productivity, all of which rely on biomass. We measured cover and AGB of cheatgrass at 60 locations in the north-central Great Basin and used these measurements to model the relationship. We found a strong, linear relationship between the percent cover and AGB, which was improved after square root transformation of both cover and AGB, and after incorporating the number of days after peak NDVI that the biomass and cover were measured. These results show that AGB of cheatgrass can be reliably estimated from cover. It is likely that allometric equations based on cover will be effective for other grass species, but care must be taken to account for phenology (e.g., peak NDVI) in the estimation.

Cheatgrass (Bromus tectorum) is an invasive grass pervasive across the Intermountain Western US and linked to major increases in fire frequency. Despite widespread ecological impacts associated with cheatgrass, we lack a spatially extensive model of cheatgrass invasion in the Intermountain West. Here, we leverage satellite phenology predictors and thousands of field surveys of cheatgrass abundance to create regional models of cheatgrass distribution and percent cover. We compare cheatgrass presence to fire probability, fire seasonality and ignition source. Regional models of percent cover had low predictive power (34% of variance explained), but distribution models based on a threshold of 15% cover to differentiate high abundance from low abundance had an overall accuracy of 74%. Cheatgrass achieves ≥ 15% cover over 210,000 km2 (31%) of the Intermountain West. These lands were twice as likely to burn as those with low abundance, and four times more likely to burn multiple times between 2000 and 2015. Fire probability increased rapidly at low cheatgrass cover (1–5%) but remained similar at higher cover, suggesting that even small amounts of cheatgrass in an ecosystem can increase fire risk. Abundant cheatgrass was also associated with a 10 days earlier fire seasonality and interacted strongly with anthropogenic ignitions. Fire in cheatgrass was particularly associated with human activity, suggesting that increased awareness of fire danger in invaded areas could reduce risk. This study suggests that cheatgrass is much more spatially extensive and abundant than previously documented and that invasion greatly increases fire frequency, even at low percent cover.

The biotic resistance hypothesis predicts that diverse native communities are more resistant to invasion. However, past studies vary in their support for this hypothesis due to an apparent contradiction between experimental studies, which support biotic resistance, and observational studies, which find that native and non-native species richness are positively related at broad scales (small-scale studies are more variable). Here, we present a novel analysis of the biotic resistance hypothesis using 24 456 observations of plant richness spanning four community types and seven ecoregions of the United States. Non-native plant occurrence was negatively related to native plant richness across all community types and ecoregions, although the strength of biotic resistance varied across different ecological, anthropogenic and climatic contexts. Our results strongly support the biotic resistance hypothesis, thus reconciling differences between experimental and observational studies and providing evidence for the shared benefits between invasive species management and native biodiversity conservation.

Identifying invasion risk is critical for regional prioritization of management and monitoring, however, we currently lack a comprehensive assessment of the invasion risk posed by plants for the United States. We aim to quantify geographic invasion risk for currently established terrestrial invasive plants in the continental U.S. under current and future climate. We assembled a comprehensive occurrence database for 896 terrestrial invasive plant species from 33 regional collections of field and museum data and projected species ranges using MaxEnt species distribution models based on current (1950–2000 average) and future (2040–2060 average) climate. We quantified geographic invasion risk as differences in species richness, invasion debt, range infilling, and identification of hotspots. Potential invasive plant richness was higher than observed richness, particularly in eastern temperate forests, where as many as 83% of species with suitable climate have not yet established. A small percentage (median = 0.22%) of species' potential ranges are currently occupied by them. With climate change, potential invasive plant richness declined by a median of 7.3% by 2050. About 80% of invasive plant hotspots were geographically stable with climate change, with the remaining 20% shifting northward. Invasion hotspots and current invasion debt reveal extensive, ongoing risk from existing invasive plants across the U.S., particularly in the Southeast. Climate change alters the spatial distributions of focal species for monitoring and is likely to reduce overall invasion risk in many areas. Early detection and rapid response programs could be most effective in stemming the spread of invasive plant species in areas with increased risk under climate change, while areas with persistent high risk are candidates for containment and control. The areas with reduced risk are prime locations for invasion of new imports from tropical and subtropical climates, highlighting the simultaneous need for prevention strategies.

Aim A surprising finding of genetic studies of Phragmites australis is that native populations, whether in Europe or North America, are characterized by lower genetic diversity than non-native populations. What is not clear is whether higher diversity within invasive stands results from disturbance facilitating sexual reproduction or whether individuals with higher diversity have greater invasion potential. Location Upper Midwest, United States, North America. Methods To answer this question, we investigated genetic structure of native and non-native P. australis stands at multiple spatial scales and under differing levels of anthropogenic disturbance. Our goals were to assess the influence of habitat disturbance on genetic structure and determine whether patterns differed in native versus non-native stands. We also screened for hybrid genotypes, which have not been reported from this region. Results When controlling for disturbance, native and non-native P. australis exhibited relatively similar within-site genetic diversity and degrees of clonal growth, suggesting that their spread is comparably reliant on clonal versus sexual dispersal. In all cases, discrete clumps of P. australis were composed of multiple, closely related genotypes, indicating seed heads as the key dispersal units. The genetic structure of P. australis stands did not differ with disturbance; however, only non-native P. australis was found in highly disturbed anthropogenic habitats. Native P. australis stands exhibited lower genetic diversity overall, lower sexual reproduction in less disturbed sites and greater isolation by distance and differentiation among sites, which is consistent with its longer residence time in this region. We found no evidence of hybrid genotypes, despite native and non-native stands sometimes co-occurring. Main conclusions Our results suggest that invasion by non-native P. australis is sporadic, associated with disturbance and involves closely related individuals, likely derived from a single seed head. The ability of the non-native lineage to exploit a variety of anthropogenic habitats helps to explain its invasiveness.

Aim Biogeographers have long known that plant species do not fully encompass their fundamental niche. Nonetheless, in practice, species distribution modelling assumes that plant distributions represent a reasonable approximation of their environmental tolerance. For ecological forecasting, projections of habitat loss due to climate change assume that many species will be unable to tolerate climate conditions outside of those found within their current distributional ranges. We aim to test how well occurrences in the native range approximate the climatic conditions in which plant species can survive. Location Continental USA. Methods We compared the climatic conditions between occurrences in the US native versus US non-native ranges using 144 non-invasive plant species. We quantified differences in January minimum temperature, July maximum temperature and annual precipitation as indicators of climatic tolerance. We also compared modelled potential distributions throughout the US based on native and total ranges to test how expanded climatic tolerance translates into predicted geographical range. Results Most species (86%) had non-native occurrences in climates outside those described by their native distributions. For the 80 species with lower minimum temperatures at non-native occurrences, the median expansion of minimum temperature tolerance was −2.9 °C. Similarly, for the 90 species with lower precipitation at non-native occurrences, the median expansion of minimum annual precipitation was −23 cm. Broader climatic conditions at non-native occurrences expanded the modelled potential geographical range by a median of 35%, with smaller range species showing larger expansions of potential geographical range. Main conclusions Our results show that plants' native ranges strongly underestimate climatic tolerance, leading species distribution models to underpredict potential range. The climatic tolerance of species with narrow native ranges appears most prone to underestimation. These findings suggest that many plants will be able to persist in situ with climate change for far longer than projected by species distribution models.

Nonnative, invasive plants are becoming increasingly widespread and abundant throughout the southwestern United States, leading to altered fire regimes and negative effects on native plant communities. Models of potential invasion are pertinent tools for informing regional management. However, most modeling studies have relied on occurrence data, which predict the potential for nonnative establishment only and can overestimate potential risk. We compiled locations of presence and high abundance for two problematic, invasive plants across the southwestern United States: red brome (Bromus rubens L.) and African mustard (Brassica tournefortii Gouan). Using an ensemble of five climate projections and two types of distribution model (MaxEnt and Bioclim), we modeled current and future climatic suitability for establishment of both species. We also used point locations of abundant infestations to model current and future climatic suitability for abundance (i.e., impact niche) of both species. Because interpretations of future ensemble models depend on the threshold used to delineate climatically suitable from unsuitable areas, we applied a low threshold (1 model of 10) and a high threshold (6 or more models of 10). Using the more-conservative high threshold, suitability for Bromus rubens presence expands by 12%, but high abundance contracts by 42%, whereas suitability for Brassica tournefortii presence and high abundance contract by 34% and 56%, respectively. Based on the low threshold (worst-case scenario), suitability for Bromus rubens presence and high abundance are projected to expand by 65% and 64%, respectively, whereas suitability for Brassica tournefortii presence and high abundance expand by 29% and 28%, respectively. The difference between results obtained from the high and low thresholds is indicative of the variability in climate models for this region but can serve as indicators of best- and worst-case scenarios.

A number of modeling approaches have been developed to predict the impacts of climate change on species distributions, performance, and abundance. The stronger the agreement from models that represent different processes and are based on distinct and independent sources of information, the greater the confidence we can have in their predictions. Evaluating the level of confidence is particularly important when predictions are used to guide conservation or restoration decisions. We used a multi-model approach to predict climate change impacts on big sagebrush (Artemisia tridentata), the dominant plant species on roughly 43 million hectares in the western United States and a key resource for many endemic wildlife species. To evaluate the climate sensitivity of A. tridentata, we developed four predictive models, two based on empirically derived spatial and temporal relationships, and two that applied mechanistic approaches to simulate sagebrush recruitment and growth. This approach enabled us to produce an aggregate index of climate change vulnerability and uncertainty based on the level of agreement between models. Despite large differences in model structure, predictions of sagebrush response to climate change were largely consistent. Performance, as measured by change in cover, growth, or recruitment, was predicted to decrease at the warmest sites, but increase throughout the cooler portions of sagebrush's range. A sensitivity analysis indicated that sagebrush performance responds more strongly to changes in temperature than precipitation. Most of the uncertainty in model predictions reflected variation among the ecological models, raising questions about the reliability of forecasts based on a single modeling approach. Our results highlight the value of a multi-model approach in forecasting climate change impacts and uncertainties and should help land managers to maximize the value of conservation investments.

Measuring and predicting invasive plant abundance is critical for understanding impacts on ecosystems and economies. Although spatial abundance datasets remain rare, occurrence datasets are increasingly available across broad regional scales. We asked whether the frequency of these point occurrences can be used as a proxy for abundance of invasive plants. We compiled both occurrence and abundance data for 13 regionally important invasive plants in the northeast United States from herbarium records and several contributed distribution datasets. We integrated all available abundance information based on infested area, stem count, percent cover, or qualitative descriptions into abundance rankings ranging from 0 (absent) to 4 (highly abundant). Within equal-area grid cells of 800 m, we counted numbers of occurrence points and used ordinal regression to test whether higher densities of occurrence points increased the odds of a higher abundance ranking. We compiled a total of 86,854 occurrence points in 34,596 grid cells, of which 26,114 points (30%) within 11,976 cells (35%) had some form of abundance information. Eleven of the 13 species had a slight but significantly positive odds ratio; that is, more occurrence points of a species increased the odds that the species was abundant within the grid cell. However, the predictive ability of the models was poor (κ

B.A.B. was supported by the Department of Defense through the Strategic Environmental Research and Development Program (SERDP) project RC-1722. R.E. was supported by FCT grant SFRH/BPD/63195/2009.

Aim Trophic cascades are a common consequence of herbivore outbreak and in the absence of hunting can cause the local extinction of native plant species and communities. We compared plant communities at 66 island and mainland sites to test the hypothesis that deer (Cervidae) determine species cover, richness and diversity and that palatable species become rare at high deer density. We validate a region-wide index of deer density and impact on plant communities in a region where culturally significant food plants maintained by aboriginal people prior to European contact helped to define baseline plant communities. Location Gulf and San Juan Island archipelagos and North American mainland. Methods We conducted surveys of 49 native, 10 exotic and 15 culturally significant plant species and deer sign at 66 sites on 35 islands and mainland to determine deer abundance and plant species cover, richness and diversity. We identified culturally significant food plants facilitated by aboriginal people using ethnobotanical knowledge, quantified plant palatability via cafeteria trials and characterized shrub architecture. Results Native and culturally significant shrub cover, richness and diversity were 52–85% lower at sites with abundant deer (0.9–2.8 ha−1) versus no deer. However, these values were also 38–82% lower at sites in the lowest deer density class (

The spatial distribution of non-native, invasive plants on the landscape is strongly influenced by human action. People introduce non-native species to new landscapes and regions (propagule pressure) as well as increase ecosystem invasibility through disturbance of native ecosystems. However, the relative importance of different landscape drivers of invasion may vary with landscape context (i.e., the types and amounts of surrounding land cover and land use). If so, data collected in one context may not be appropriate for predicting invasion risk across a broader landscape. To test whether independent occurrence datasets suggest similar landscape drivers of invasion, we compared landscape models based on data compiled by the Invasive Plant Atlas of New England (IPANE), which are contributed opportunistically by trained citizen scientists, to models based on Forest Stewardship plans (FSPs), which are located in privately owned and relatively undisturbed forests. We evaluated 16 landscape variables related to propagule pressure and/or disturbance for significant predictors of invasive plant presence based on presence/absence and count regression models. Presence and richness of invasive plants within FSPs was most influenced by proportion of open land and proximity to residential areas, which are both sources of propagules in forest interiors. In contrast, IPANE invasive plant presence and richness for the same area was influenced by distance to roads and streams. These results suggest that landscape drivers of invasion vary considerably depending on landscape context, and the choice of occurrence dataset will strongly influence model results.

The article Incorporating climate change into invasive species management: insights from managers, written by Evelyn M. Beaury

Much of the biodiversity-related climate change impacts research has focused on the direct effects to species and ecosystems. Far less attention has been paid to the potential ecological consequences of human efforts to address the effects of climate change, which may equal or exceed the direct effects of climate change on biodiversity. One of the most significant human responses is likely to be mediated through changes in the agricultural utility of land. As farmers adapt their practices to changing climates, they may increase pressure on some areas that are important to conserve (conservation lands) whereas lessening it on others. We quantified how the agricultural utility of South African conservation lands may be altered by climate change. We assumed that the probability of an area being farmed is linked to the economic benefits of doing so, using land productivity values to represent production benefit and topographic ruggedness as a proxy for costs associated with mechanical workability. We computed current and future values of maize and wheat production in key conservation lands using the DSSAT4.5 model and 36 crop-climate response scenarios. Most conservation lands had, and were predicted to continue to have, low agricultural utility because of their location in rugged terrain. However, several areas were predicted to maintain or gain high agricultural utility and may therefore be at risk of near-term or future conversion to cropland. Conversely, some areas were predicted to decrease in agricultural utility and may therefore prove easier to protect from conversion. Our study provides an approximate but readily transferable method for incorporating potential human responses to climate change into conservation planning.

Alien grass invasions in arid and semi-arid ecosystems are resulting in grass–fire cycles and ecosystem-level transformations that severely diminish ecosystem services. Our capacity to address the rapid and complex changes occurring in these ecosystems can be enhanced by developing an understanding of the environmental factors and ecosystem attributes that determine resilience of native ecosystems to stress and disturbance, and resistance to invasion. Cold desert shrublands occur over strong environmental gradients and exhibit significant differences in resilience and resistance. They provide an excellent opportunity to increase our understanding of these concepts. Herein, we examine a series of linked questions about (a) ecosystem attributes that determine resilience and resistance along environmental gradients, (b) effects of disturbances like livestock grazing and altered fire regimes and of stressors like rapid climate change, rising CO2, and N deposition on resilience and resistance, and (c) interacting effects of resilience and resistance on ecosystems with different environmental conditions. We conclude by providing strategies for the use of resilience and resistance concepts in a management context. At ecological site scales, state and transition models are used to illustrate how differences in resilience and resistance influence potential alternative vegetation states, transitions among states, and thresholds. At landscape scales management strategies based on resilience and resistance—protection, prevention, restoration, and monitoring and adaptive management—are used to determine priority management areas and appropriate actions.

Remote sensing image analysis is increasingly being used as a tool for mapping invasive plant species. Resulting distribution maps can be used to target management of early infestations and to model future invasion risk. Remote identification of invasive plants based on differences in spectral signatures is the most common approach, typically using hyperspectral data. But several studies have found that textural and phenological differences are also effective approaches for identifying invasive plants. I review examples of remote detection of invasive plants based on spectral, textural and phenological analysis and highlight circumstances where the different approaches are likely to be most effective. I also review sources and availability of remotely sensed data that could be used for mapping and suggest field data collection approaches that would support the analysis of remotely sensed data. Remote mapping of biological invasions remains a relatively specialized research topic, but the distinct cover, morphology and/or seasonality of many invaded versus native ecosystems suggests that more species could be detected remotely. Remote sensing can sometimes support early detection and rapid response directly, however, accurately detecting small, nascent populations is a challenge. However, even maps of heavily infested areas can provide a valuable tool for risk assessment by increasing knowledge about temporal and spatial patterns and predictors of invasion.

Crop model-specific biases are a key uncertainty affecting our understanding of climate change impacts to agriculture. There is increasing research focus on intermodel variation, but comparisons between mechanistic (MMs) and empirical models (EMs) are rare despite both being used widely in this field. We combined MMs and EMs to project future (2055) changes in the potential distribution (suitability) and productivity of maize and spring wheat in South Africa under 18 downscaled climate scenarios (9 models run under 2 emissions scenarios). EMs projected larger yield losses or smaller gains than MMs. The EMs' median-projected maize and wheat yield changes were -3.6% and 6.2%, respectively, compared to 6.5% and 15.2% for the MM. The EM projected a 10% reduction in the potential maize growing area, where the MM projected a 9% gain. Both models showed increases in the potential spring wheat production region (EM = 48%, MM = 20%), but these results were more equivocal because both models (particularly the EM) substantially overestimated the extent of current suitability. The substantial water-use efficiency gains simulated by the MMs under elevated CO2 accounted for much of the EM-MM difference, but EMs may have more accurately represented crop temperature sensitivities. Our results align with earlier studies showing that EMs may show larger climate change losses than MMs. Crop forecasting efforts should expand to include EM-MM comparisons to provide a fuller picture of crop-climate response uncertainties.

Aim Intercomparison of mechanistic and empirical models is an important step towards improving projections of potential species distribution and abundance. We aim to compare suitability and productivity estimates for a well-understood crop species to evaluate the strengths and weaknesses of mechanistic versus empirical modelling. Location South Africa. Methods We compared four habitat suitability models for dryland maize based on climate and soil predictors. Two were created using maximum entropy (MAXENT), the first based on national crop distribution points and the second based only on locations with high productivity. The third approach used a generalized additive model (GAM) trained with continuous productivity data derived from the satellite normalized difference vegetation index (NDVI). The fourth model was a mechanistic crop growth model (DSSAT) made spatially explicit. We tested model accuracy by comparing the results with observed productivity derived from MODIS NDVI and with observed suitability based on the current spatial distribution of maize crop fields. Results The GAM and DSSAT results were linearly correlated to NDVI-measured yield (R 2 = 0.75 and 0.37, respectively). MAXENT suitability values were not lin

A prominent goal of invasive plant management is to prevent or reduce the spread of invasive species into uninvaded landscapes and regions. Monitoring and control efforts often rely on scientific knowledge of suitable habitat for the invasive species. However, rising temperatures and altered precipitation projected with climate change are likely to shift the geographic range of that suitable habitat. Here, we review experimental and modeling studies of climatic limits to exotic annual Bromus (Bromus hereafter) distribution in the Intermountain West in the context of projections of future climate change. We update empirical models of range shifts to test whether Bromus rubens L. (red brome) is likely to expand into ranges that become less suitable for Bromus tectorum L. (cheatgrass or downy brome). Warming temperatures are likely to create an advantage for Bromus species throughout much of the Intermountain West, potentially enhancing invasion into formerly resistant ecosystems if native species mortality increases with warming and drought. Bromus rubens is likely to expand into areas of the Southern Great Basin and Colorado Plateau as warmer winters reduce range constraints caused by cold intolerance. However, a primary limitation to exotic annual Bromus invasion and expansion is growing season precipitation. Projections for precipitation change are uncertain, but increased precipitation during periods critical for exotic annual Bromus germination and growth is forecast for the Northern Great Basin. Increased Bromus reproduction and biomass may exacerbate B. tectorum invasion and associated fire risk, especially if coupled with longer fire seasons and more extreme fire weather. Managers should anticipate both shifts in the overall distribution of Bromus species, as well as changes in relative abundance within its existing range.

Habitat suitability models developed for non-native, invasive species often implicitly assume that projected invasion risk equates to risk of impact. I aim to test to what extent this assumption is true by comparing commonly-used invasive plant distribution datasets to abundance records. I compared herbarium occurrence records (downloaded from an online database) and regional occurrence records (compiled from individual states) to abundance estimates collected from over 300 invasive plant experts for 9 invasive species in the western U.S. I also created habitat suitability models (HSMs) using these datasets and compared the areas of predicted suitability. Sixty percent of the time, herbarium occurrences were located in regions where the species was rare enough to be undetected by experts, while only 26 % coincided with locations identified as having high abundance. Regional occurrences were located in areas where the species was not detected 32 % of the time, and on high abundance 42 % of the time. HSMs based on herbarium records encompassed 89 % of land area at risk of abundance, but overestimated the area of estimated risk (27–46 % false positive rate). HSMs based on regional occurrences had a smaller false positive rate (22–31 %), but encompassed only 67–68 % of area suitable for abundance. Herbarium records are strongly skewed towards locations with low invasive plant abundance, leading to invasion risk models that vastly overestimate abundance risk. Models based on occurrence points should be interpreted as risk of establishment only, not risk of abundance or impact. If HSMs aim to be more management relevant, invasion risk models should include abundance as well as occurrence.

Non-native, invasive grasses have been linked to altered grass-fire cycles worldwide. Although a few studies have quantified resulting changes in fire activity at local scales, and many have speculated about larger scales, regional alterations to fire regimes remain poorly documented. We assessed the influence of large-scale Bromus tectorum (hereafter cheatgrass) invasion on fire size, duration, spread rate, and interannual variability in comparison to other prominent land cover classes across the Great Basin, USA. We compared regional land cover maps to burned area measured using the Moderate Resolution Imaging Spectroradiometer (MODIS) for 2000-2009 and to fire extents recorded by the USGS registry of fires from 1980 to 2009. Cheatgrass dominates at least 6% of the central Great Basin (650 000 km(2) ). MODIS records show that 13% of these cheatgrass-dominated lands burned, resulting in a fire return interval of 78 years for any given location within cheatgrass. This proportion was more than double the amount burned across all other vegetation types (range: 0.5-6% burned). During the 1990s, this difference was even more extreme, with cheatgrass burning nearly four times more frequently than any native vegetation type (16% of cheatgrass burned compared to 1-5% of native vegetation). Cheatgrass was also disproportionately represented in the largest fires, comprising 24% of the land area of the 50 largest fires recorded by MODIS during the 2000s. Furthermore, multi-date fires that burned across multiple vegetation types were significantly more likely to have started in cheatgrass. Finally, cheatgrass fires showed a strong interannual response to wet years, a trend only weakly observed in native vegetation types. These results demonstrate that cheatgrass invasion has substantially altered the regional fire regime. Although this result has been suspected by managers for decades, this study is the first to document recent cheatgrass-driven fire regimes at a regional scale.

a b s t r a c t Remotely sensed datasets are increasingly being used to model habitat suitability for a variety of taxa. We review habitat suitability models (HSMs) developed for both plants and animals that include remote sensing predictor variables to determine how these variables could affect model projections. For models focused on plant species habitat, we find several instances of unintentional bias in HSMs of vegetation due to the inclusion of remote sensing variables. Notably, studies that include continuous remote sensing variables could be inadvertently mapping actual species distribution instead of potential habitat due to unique spectral or temporal characteristics of the target species. Additionally, HSMs including categorical classifications are rarely explicit about assumptions of habitat suitability related to land cover, which could lead to unintended exclusion of potential habitat due to current land use. Although we support the broader application of remote sensing in general, we caution developers of HSMs to be aware of introduced model bias. These biases are more likely to arise when remote sensing variables are added to models simply because they improve accuracy, rather than considering how they affect the model results and interpretation. When including land cover classifications as predictors, we recommend that modellers provide more explicit descriptions of how habitat is defined (e.g., is deforested land considered suitable for trees?). Further, we suggest that continuous remote sensing variables should only be included in habitat models if authors can demonstrate that their inclusion characterizes potential habitat rather than actual species distribution. Use of the term 'habitat suitability model' rather than 'species distribution model' could reduce confusion about modelling goals and improve communication between the remote sensing and ecological modelling communities.

Extreme climatic events (ECEs) – such as unusual heat waves, hurricanes, floods, and droughts – can dramatically affect ecological and evolutionary processes, and these events are projected to become more frequent and more intense with ongoing climate change. However, the implications of ECEs for biological invasions remain poorly understood. Using concepts and empirical evidence from invasion ecology, we identify mechanisms by which ECEs may influence the invasion process, from initial introduction through establishment and spread. We summarize how ECEs can enhance invasions by promoting the transport of propagules into new regions, by decreasing the resistance of native communities to establishment, and also sometimes by putting existing non-native species at a competitive disadvantage. Finally, we outline priority research areas and management approaches for anticipating future risks of unwanted invasions following ECEs. Given predicted increases in both ECE occurrence and rates of species introductions around the globe during the coming decades, there is an urgent need to understand how these two processes interact to affect ecosystem composition and functioning.

Habitat Conservation Plans (HCPs) under the Endangered Species Act (ESA) are an important mechanism for the acquisition of land and the management of terrestrial and aquatic ecosystems. HCPs have become a vital means of protecting endangered and threatened species and their habitats throughout the United States, particularly on private land. The scientific consensus that climate is changing and that these changes will impact the viability of species has not been incorporated into the conservation strategies of recent HCPs, rendering plans vulnerable biologically. In this paper we review the regulatory context for incorporating climate change into HCPs and analyze the extent to which climate change is linked to management actions in a subset of large HCPs. We conclude that most current plans do not incorporate climate change into conservation actions, and so we provide recommendations for integrating climate change into the process of HCP development and implementation. These recommendations are distilled from the published literature as well as the practice of conservation planning and are structured to the specific needs of HCP development and implementation. We offer nine recommendations for integrating climate change into the HCP process: (1) identify species at-risk from climate change, (2) explore new strategies for reserve design, (3) increase emphasis on corridors, linkages, and connectivity, (4) develop anticipatory adaptation measures, (5) manage for diversity, (6) consider assisted migration, (7) include climate change in scenarios of water management, (8) develop future-oriented management actions, and (9) increase linkages between the conservation strategy and adaptive management/monitoring programs.

Many non-native plants in the US have become problematic invaders of native and managed ecosystems, but a new generation of invasive species may be at our doorstep. Here, we review trends in the horticultural trade and invasion patterns of previously introduced species and show that novel species introductions from emerging horticultural trade partners are likely to rapidly increase invasion risk. At the same time, climate change and water restrictions are increasing demand for new types of species adapted to warm and dry environments. This confluence of forces could expose the US to a range of new invasive species, including many from tropical and semiarid Africa as well as the Middle East. Risk assessment strategies have proven successful elsewhere at identifying and preventing invasions, although some modifications are needed to address emerging threats. Now is the time to implement horticulture import screening measures to prevent this new wave of plant invasions.