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International audience; Ambrosia trifida L. (giant ragweed, Asteraceae) is native to the North American continent and was introduced into Europe and Asia at the end of the 19th century. In its native range, this tall annual species is common in riparian and ruderal habitats and is also a major weed in annual cropping systems. For nearly a century, A. trifida has also been of great concern in the U.S. for its highly allergenic pollen, necessitating targeted control measures to reduce its impact on human populations. Based on the distribution of A. trifida in North America and in its introduced range, riparian systems in the rest of the world may be particularly at risk to invasion, with potential negative consequences for their biodiversity. Currently, A. trifida has invaded Asia more widely than Europe, likely due to the more favourable local conditions in Asia. Throughout its introduced range, A. trifida is host to a limited number of invertebrates and pathogens and only a few biological agents are available for its control. The main impacts of A. trifida at a global level are on crop yield and human health, resulting in significant socio-economic impacts. The success of A. trifida invasion in areas in which it has been introduced is still unclear, but climate change may increase climate suitability, increasing the potential for A. trifida to spread. While effective management in cultivated fields seems potentially possible, the development and control of A. trifida in natural riparian habitats is of great concern due to the difficulty of management in these areas.

1. Plant pathogens are introduced to new geographical regions ever more frequently as global connectivity increases. Predicting the threat they pose to plant health can be difficult without in‐depth knowledge of behaviour, distribution and spread. Here, we evaluate the potential for using biological traits and phylogeny to predict global threats from emerging pathogens. 2. We use a species‐level trait database and phylogeny for 179 Phytophthora species: oomycete pathogens impacting natural, agricultural, horticultural and forestry settings. We compile host and distribution reports for Phytophthora species across 178 countries and evaluate the power of traits, phylogeny and time since description (reflecting species‐level knowledge) to explain and predict their international transport, maximum latitude and host breadth using Bayesian phylogenetic generalised linear mixed models. 3. In the best‐performing models, traits, phylogeny and time since description together explained up to 90%, 97% and 87% of variance in number of countries reached, latitudinal limits and host range, respectively. Traits and phylogeny together explained up to 26%, 41% and 34% of variance in the number of countries reached, maximum latitude and host plant families affected, respectively, but time since description had the strongest effect. 4. Root‐attacking species were reported in more countries, and on more host plant families than foliar‐attacking species. Host generalist pathogens had thicker‐walled resting structures (stress‐tolerant oospores) and faster growth rates at their optima. Cold‐tolerant species are reported in more countries and at higher latitudes, though more accurate interspecific empirical data are needed to confirm this finding. 5. Policy implications. We evaluate the potential of an evolutionary trait‐based framework to support horizon‐scanning approaches for identifying pathogens with greater potential for global‐scale impacts. Potential future threats from Phytophthora include Phytophthora x heterohybrida, P. lactucae, P. glovera, P. x incrassata, P. amnicola and P. aquimorbida, which are recently described, possibly under‐reported species, with similar traits and/or phylogenetic proximity to other high‐impact species. Priority traits to measure for emerging species may be thermal minima, oospore wall index and growth rate at optimum temperature. Trait‐based horizon‐scanning approaches would benefit from the development of international and cross‐sectoral collaborations to deliver centralised databases incorporating pathogen distributions, traits and phylogeny.

Context Intact tropical rainforests are considered robust to plant invasions. However, land-use change alters the structure and species composition of native forest, opening up tropical landscapes to invasion. Yet, the relative roles of key drivers on tropical forest invasions remain little investigated. Objectives We examine factors affecting plant invasion of rainforest remnants in oil-palm dominated landscapes in Sabah, Malaysian Borneo. We hypothesized that invasion is greater in highly fragmented landscapes, and in disturbed forests with lower native plant diversity (cf. old-growth rainforests). Methods Native and exotic plants were surveyed in 47 plots at 17 forest sites, spanning gradients in landscape-scale fragmentation and local forest disturbance. Using partial least squares path-modelling, we examined correlations between invasion, fragmentation, forest disturbance, propagule pressure, soil characteristics and native plant community. Results We recorded 6999 individuals from 329 genera in total, including eight exotic species (0–51% of individuals/plot, median = 1.4%) representing shrubs, forbs, graminoids and climbers. The best model (R2 = 0.343) revealed that invasion was correlated with disturbance and propagule pressure (high prevalence of exotic species in plantation matrix), the latter being driven by greater fragmentation of the landscape. Our models revealed a significant negative correlation between invasion and native tree seedlings and sapling community diversity. Conclusions Increasing landscape fragmentation promotes exotic plant invasion in remnant tropical forests, especially if local disturbance is high. The association between exotic species invasion and young native tree community may have impacts for regeneration given that fragmentation is predicted to increase and so plant invasion may become more prevalent.

Humans fundamentally affect dispersal, directly by transporting individuals and indirectly by altering landscapes and natural vectors. This human-mediated dispersal (HMD) modifies long-distance dispersal, changes dispersal paths, and overall benefits certain species or genotypes while disadvantaging others. HMD is leading to radical changes in the structure and functioning of spatial networks, which are likely to intensify as human activities increase in scope and extent. Here, we provide an overview to guide research into HMD and the resulting rewiring of spatial networks, making predictions about the ecological and evolutionary consequences and how these vary according to spatial scale and the traits of species. Future research should consider HMD holistically, assessing the range of direct and indirect processes to understand the complex impacts on eco-evolutionary dynamics.

Selective logging has affected large areas of tropical forests and there is increasing interest in how to manage selectively logged forests to enhance recovery. However, the impacts of logging and active restoration, by liberation cutting and enrichment planting, on tree community composition are poorly understood compared to trajectories of biomass recovery. Here, we assess the long-term impacts of selective logging and active restoration for biomass recovery on tree species diversity, community composition, and forest structure. We censused all stems ≥2 cm diameter at breast height (DBH) on 46 permanent plots in unlogged, primary forest in the Danum Valley Conservation Area (DVCA; 12 plots, totalling 0.6 ha) and in sites logged 23–35 years prior to the census in the Ulu Segama Forest Reserve adjacent to DVCA (34 plots, totalling 1.7 ha) in Sabah, Malaysian Borneo. Active restoration treatments, including enrichment planting and climber cutting, were implemented on 17 of the logged forest plots 12–24 years prior to the census. Total plot-level basal area and pole (5–10 cm DBH) stem density were lower in logged than unlogged forests, however no difference was found in stem density amongst saplings (2–5 cm DBH) or established trees (≥10 cm DBH). Neither basal area, nor plot-level stem density varied with time since logging at any size class, although sapling and pole stem densities were lower in actively restored than naturally regenerating logged forest. Sapling species diversity was lower in logged than unlogged forest, however there were no other significant effects of logging on tree species richness or diversity indices. Tree species composition, however, differed between logged and unlogged forests across all stem size classes (PERMANOVA), reflected by 23 significant indicator species that were only present in unlogged forest. PERMANOVA tests revealed no evidence that overall species composition changed with time since logging or with active restoration treatments at any size class. However, when naturally regenerating and actively restored communities were compared, two indicator species were identified in naturally regenerating forest and three in actively restored forests. Together our results suggest that selective logging has a lasting effect on tree community composition regardless of active restoration treatments and, even when species richness and diversity are stable, species composition remains distinct from unlogged forest for more than two decades post-harvest. Active restoration efforts should be targeted, monitored, and refined to try to ensure positive outcomes for multiple metrics of forest recovery. © 2021 Elsevier, Forest Ecology and Management, 488, ISSN:0378-1127, ISSN:1872-7042

International audience; Ecosystems face multiple, potentially interacting, anthropogenic pressures that can modify biodiversity and ecosystem functioning. Using a bryophyte–microarthropod microecosystem we tested the combined effects of habitat loss, episodic heat-shocks and an introduced non-native apex predator on ecosystem function (chlorophyll fluorescence as an indicatorof photosystem II function) and microarthropod communities (abundance and body size). The photosynthetic function was degraded by the sequence of heat-shock episodes, but unaffected by microecosystem patch size or top-down pressure from the introduced predator. In small microecosystem patches without the non-native predator, Acari abundance decreased with heat-shock frequency, while Collembola abundance increased. These trends disappeared in larger microecosystem patches or when predators were introduced, although Acari abundance was lower in large patchesthat underwent heat-shocks and were exposed to the predator. Mean assemblage body length (Collembola) was reduced independently in small microecosystem patches and with greater heat-shock frequency. Our experimental simulation of episodic heatwaves, habitat loss and nonnative predation pressure in microecosystems produced evidence of individual and potentially synergistic and antagonistic effects on ecosystem function and microarthropod communities. Such complex outcomes of interactions between multiple stressors need to be considered when assessing anthropogenic risks for biota and ecosystem functioning.

Maintaining forest conservation set-asides is a key criterion of sustainability certification of many crops that drive tropical deforestation, but their value for carbon storage and associated biodiversity is unclear. We conducted vegetation measurements to examine the benefits of set-asides for aboveground carbon stocks (AGC) in certified oil palm plantations on Borneo, and whether their AGC is positively associated with plant diversity. The mean estimated AGC of live trees and palms ≥10 cm diameter in set-asides in certified oil palm plantations (52.8 Mg ha−1) was >1.5-times that of oil palm (30.3 Mg ha−1), with some plots supporting similar AGC to primary forest. For lowland Borneo, we estimate that the average AGC of oil palm plantations with 10% coverage of set-asides is up to 20% greater than the average AGC of oil palm plantations without set-asides, newly demonstrating carbon storage as a benefit of conservation set-asides. We found positive relationships between AGC and plant diversity, highlighting the carbon–biodiversity co-benefits of set-asides. However, set-asides had a lower density of tree seedlings than continuous primary forest, indicating potential suppression of future tree regeneration and AGC. Our findings support the application of zero-deforestation during agricultural development, to conserve areas of remaining forest with high AGC and high biodiversity. We recommend management practices that boost regeneration in existing set-asides (e.g. enrichment planting), which would be most effective in larger set-asides, and could substantially increase the AGC of agricultural landscapes without removing land from production, and help conserve forest-dependent biodiversity.

Aim: Hotspots of human activity are focal points for ecosystem disturbance and non‐native introduction, from which invading populations disperse and spread. As such, connectivity to locations used by humans may influence the likelihood of invasion. Moreover, connectivity in freshwater ecosystems may follow the hydrological network. Here we tested whether multiple forms of connectivity to human recreational activities promotes biological invasion of freshwater ecosystems. Location: England, UK. Time period: 1990–2018. Major taxa studied: One hundred and twenty‐six non‐native freshwater birds, crustaceans, fish, molluscs and plants. Methods: Machine learning was used to predict spatial gradients in human recreation and two high risk activities for invasion (fishing and water sports). Connectivity indices were developed for each activity, in which human influence decayed from activity hotspots according to Euclidean distance (spatial connectivity) or hydrological network distance (downstream, upstream and along‐channel connectivity). Generalized linear mixed models identified the connectivity type most associated to invasive species richness of each group, while controlling for other anthropogenic and environmental drivers. Results: Connectivity to humans generally had stronger positive effects on invasion than all other drivers except recording effort. Recreation had stronger influence than urban land cover, and for most groups high risk activities had stronger effects than general recreation. Downstream human connectivity was most important for invasion by most of the groups, potentially reflecting predominantly hydrological dispersal. An exception was birds, for which spatial connectivity was most important, possibly because of overland dispersal capacity. Main conclusions: These findings support the hypothesis that freshwater invasion is partly determined by an interaction between human activity and species dispersal in the hydrological network. By comparing alternative connectivity types for different human activities, our approach could enable robust inference of specific pathways and spread mechanisms associated with particular taxa. This would provide evidence to support better prioritization of surveillance and management for invasive non‐native species.

The present study aimed to investigate the role of propagule pressure (P), abiotic (A), and biotic (B) factors (collectively indicated as PAB) on the suitability of the Mediterranean island of Sardinia (Italy) to be invaded by the tree Acacia saligna, recently included in the list of invasive alien species of European Union concern. To this aim, a binomial Generalized Linear Model was applied for disentangling the relationship between 432 A. saligna occurrence records and 10 thematic layers, at high-resolution (10 x10 m), used as proxies for the 3 categories of PAB variables. The 432 occurrence records of A. saligna were periodically monitored (period 2000–2018) to check the persistence of the populations and their invasive status. The predictive power of the model was evaluated by computing the mean of the AUC scores, through cross-fold validation. The model adequately described how the PAB factors influence the presence of A. saligna which is mainly shaped by abiotic factors such as topography, and biotic factors such as the presence of woody dune vegetation, and to a lesser extent by other predictors. The projection of the model to the whole island clearly shows that suitability varies at the landscape level due to the variation of the PAB across the territory. The probability of A. saligna occurrence near the coast is higher in sand dunes. In the internal areas of the island it occurs close to the roads and urban areas. This study and the tested methodology could represent a suitable tool to prioritize areas for the monitoring of A. saligna to meet the requirements of the Regulation (EU) No. 1143/2014 on Invasive Alien Species (the IAS Regulation).

Aim: Although global trade is implicated in biological invasions, the assumption that trade networks explain the large-scale distributions of non-native species remains largely untested. We addressed this by analysing relationships between global trade networks and plant pest invasion. Location: Forty-eight countries in Europe and the Mediterranean. Time period: Current. Major taxa studied: Four hundred and twenty-two non-native plant pests (173 invertebrates, 166 pathogens, 83 plants). Methods: Ten types of connectivity index were developed, representing potential roles of trade networks, air transport links, geographical proximity, climatic similarity and source country wealth in facilitating invasion. Generalized linear mixed models (GLMMs) identified the connectivity index that best explained both historical and recent invasion. Then, more complex GLMMs were developed including connectivity through trade networks for multiple commodities relevant for pests (live plants, forest products, fruit and vegetables and seeds) and species’ transport associations with those commodities. Results: Total import volumes, species’ global prevalence and connectivity measures based on air transport, geographical distance or climate did not explain invasion as well as connectivity through global trade networks. Invasion was strongly promoted by agricultural imports from countries in which the focal species was present and that were climatically similar to the importing country. However, live plant imports from nearby countries provided a better explanation of the most recent invasions. Connectivity through multiple trade networks predicted invasion better than total agricultural trade, and there was support for our hypothesis that species known to be transported with a particular network had greater sensitivity to its connectivity. Main conclusions: Our findings show that patterns of invasion are governed to a large extent by global trade networks connecting source areas for non-native species and the dispersal of those species through multiple trade networks. This enhances potential for developing a predictive framework to improve risk assessment, biosecurity and surveillance for invasions.

Aim: We present a novel strategy for species distribution models (SDMs) aimed at predicting the potential distributions of range‐expanding invasive non‐native species (INNS). The strategy combines two established perspectives on defining the background region for sampling “pseudo‐absences” that have hitherto only been applied separately. These are the accessible area, which accounts for dispersal constraints, and the area outside the environmental range of the species and therefore assumed to be unsuitable for the species. We tested an approach to combine these by fitting SDMs using background samples (pseudo‐absences) from both types of background. Location: Global. Taxon: Invasive non‐native plants: Humulus scandens, Lygodium japonicum, Lespedeza cuneata, Triadica sebifera, Cinnamomum camphora. Methods: Presence‐background (or presence‐only) SDMs were developed for the potential global distributions of five plant species native to Asia, invasive elsewhere and prioritised for risk assessment as emerging INNS in Europe. We compared models where the pseudo‐absences were selected from the accessible background, the unsuitable background (defined using biological knowledge of the species’ key limiting factors) or from both types of background. Results: Combining the unsuitable and accessible backgrounds expanded the range of environments available for model fitting and caused biological knowledge about ecological unsuitability to influence the fitted species‐environment relationships. This improved the realism and accuracy of distribution projections globally and, generally, within the species’ ranges. Main conclusions: Correlative SDMs remain valuable for INNS risk mapping and management, but are often criticised for a lack of biological underpinning. Our approach partly addresses this concern by using prior knowledge of species’ requirements or tolerances to define the unsuitable background for modelling, while also accommodating dispersal constraints through considerations of accessibility. It can be implemented with current SDM software and results in more accurate and realistic distribution projections. As such, wider adoption has potential to improve SDMs that support INNS risk assessment.

When faced with a large species pool of invasive or potentially invasive alien plants, prioritization is an essential prerequisite for focusing limited resources on species which inflict high impacts, have a high rate of spread and can be cost-effectively managed. The prioritization process as detailed within this paper is the first tool to assess species for priority for risk assessment (RA) in the European Union (EU) specifically designed to incorporate the requirements of EU Regulation no. 1143/2014. The prioritization process can be used for any plant species alien to the EU, whether currently present within the territory or absent. The purpose of the prioritization is to act as a preliminarily evaluation to determine which species have the highest priority for RA at the EU level and may eventually be proposed for inclusion in the list of invasive alien species of EU concern. The preliminary risk assessment stage (Stage 1), prioritizes species into one of four lists (EU List of Invasive Alien Plants, EU Observation List of Invasive Alien Plants, EU List of Minor Concern and the Residual List) based on their potential for spread coupled with impacts. The impacts on native species and ecosystem functions and related ecosystem services are emphasized in line with Article 4.3(c) of the Regulation. Only those species included in the EU List of Invasive Alien Plants proceed to Stage 2 where potential for further spread and establishment coupled with evaluating preventative and management actions is evaluated. The output of Stage 2 is to prioritize those species which have the highest priority for a RA at the EU level or should be considered under national measures which may involve a trade ban, cessation of cultivation, monitoring, control, containment or eradication. When considering alien plant species for the whole of the EPPO region, or for species under the Plant Health Regulation, the original EPPO prioritization process for invasive alien plants remains the optimum tool.

Indicators of large-scale ecological change are typically derived from long-term monitoring networks. As such, it is important to assess how well monitoring networks provide evidence for ecological trends in the regions they are monitoring. In part, this depends on the network’s representativeness of the full range of environmental conditions occurring in the monitored region. In addition, the statistical power to detect trends and ecological changes using the network depends on its structure, size and the intensity and accuracy of monitoring. This paper addresses the optimisation of representativeness and statistical power when re-designing existing large-scale ecological monitoring networks, for example due to financial constraints on monitoring programmes. It uses a real world example of a well-established river monitoring network of 254 sites distributed across Scotland. We first present a novel approach for assessing a monitoring network’s representativeness of national habitat and pressure gradients using the multivariate two-sample Cramer’s T statistic. This compares multivariate gradient distributions among sites inside and outside of the network. Using this test, the existing network was found to over-represent larger and more heavily polluted sites, reflecting earlier research priorities when it was originally designed. Network re-design was addressed through stepwise selection of individual sites to remove from or add to the network to maximise multivariate representativeness. This showed that combinations of selective site retention and addition can be used to modify existing monitoring networks, changing the number of sites and improving representativeness. We then investigated the effect of network re-design on the statistical power to detect long-term trends across the whole network. The power analysis was based on linear mixed effects models for long-term trends in three ecological indicators (ecological quality ratios for diatoms, invertebrates and macrophytes) over a ten-year period. This revealed a clear loss of power in smaller networks with less accurate sampling, but sampling schedule had a smaller effect on power. Interestingly, more representative networks had slightly lower trend detection power than the current unrepresentative network, though they should give a less biased estimate of national trends. Our analyses of representativeness and statistical power provide a general framework for designing and adapting large-scale ecological monitoring networks. Wider use of such methods would improve the quality of indicators derived from them and improve the evidence base for detecting and managing ecological change.

The Global Biodiversity Information Facility (GBIF) is at the moment one of the largest and most widely used biodiversity databases. Nevertheless, there are still some limitations, e.g. in terms of plant species status (native vs. non-native) and geographic resolution of records. At the same time, it is well known that alien plant invasions in inland freshwaters can alter community structure, ecosystem functions and services with significant negative impacts on biodiversity and human activities. We assessed if the GBIF database has a geospatial homogeneous information for native and non-native aquatic plant species for South America and whether or not literature resources not yet digitalized (floras, checklists and other papers) could provide additional information. We selected a set of 40 native and 40 non-native aquatic species. These 80 species included a sub-set of 40 alien species previously evaluated with the USAqWRA scheme (US Aquatic Weed Risk Assessment). Species with non-reliable identification, duplicates of the same collection, records poorly georeferenced were removed from the dataset. New records were manually compiled through classical literature research. All the georeferenced records (GBIF + literature) were used for the mapping and the comparative analysis. As a result, we can conclude that the two datasets provide quite significantly different information and the combination of the two offers new information that would not exist in a single data source. Nevertheless, a careful quality evaluation of the primary information, both in the case of literature and GBIF should be conducted, before the data is used for further analyses.

1.Riparian invertebrate communities occupy a dynamic ecotone where hydrogeomorphological (e.g. river flows) and ecological (e.g. succession) processes may govern assemblage structure by filtering species according to their traits (e.g. dispersal capacity, niche).2.We surveyed terrestrial invertebrate assemblages (millipedes, carabid beetles, spiders) in 28 river islands across four river catchments over 2 years. We predicted that distinct ecological niches would produce taxon-specific responses of abundance and species richness to: (i) disturbance from episodic floods, (ii) island area, (iii) island vegetation structure, and (iv) landscape structure. We also predicted that responses would differ according to species’ dispersal ability (aerial vs. terrestrial only), indicating migration was sustaining community structure.3.Invertebrate abundance and richness was affected by different combinations of vegetation structure, island area, and flood disturbance according to species’ dispersal capacity. Carabid abundance related negatively to episodic floods, particularly for flightless species, but the other taxa were insensitive to this disturbance. Larger islands supported greater abundance of carabids and all invertebrates able to disperse aerially. Vegetation structure, particularly tree canopy density and plant richness, related positively to invertebrate abundance across all taxa and aerial dispersers, whereas terrestrial disperser richness related positively to tree cover. Landscape structure did not influence richness or abundance.4.Multiple ecological processes govern riparian invertebrate assemblages. Overall insensitivity to flood disturbance and responses contingent on dispersal mode imply that spatial dynamics subsidise the communities through immigration. Particular habitat features (e.g. trees, speciose vegetation) may provide refuges from disturbance and concentration of niches and food resources.

Thirty-seven alien plant species, pre-identified by horizon scanning exercises were prioritised for pest risk analysis (PRA) using a modified version of the EPPO Prioritisation Process designed to be compliant with the EU Regulation 1143/2014. In Stage 1, species were categorised into one of four lists – a Residual List, EU List of Minor Concern, EU Observation List and the EU List of Invasive Alien Plants. Only those species included in the latter proceeded to the risk management stage where their priority for PRA was assessed. Due to medium or high spread potential coupled with high impacts twenty-two species were included in the EU List of Invasive Alien Plants and proceeded to Stage 2. Four species (Ambrosia trifida, Egeria densa, Fallopia baldschuanica and Oxalis pes-caprae) were assigned to the EU Observation List due to moderate or low impacts. Albizia lebbeck, Clematis terniflora, Euonymus japonicus, Lonicera morrowii, Prunus campanulata and Rubus rosifolius were assigned to the residual list due to a current lack of information on impacts. Similarly, Cornus sericea and Hydrilla verticillata were assigned to the Residual List due to unclear taxonomy and uncertainty in native status, respectively. Chromolaena odorata, Cryptostegia grandiflora and Sphagneticola trilobata were assigned to the Residual List as it is unlikely they will establish in the Union under current climatic conditions. In the risk management stage, Euonymus fortunei, Ligustrum sinense and Lonicera maackii were considered a low priority for PRA as they do not exhibit invasive tendencies despite being widely cultivated in the EU over several decades. Nineteen species were identified as having a high priority for a PRA (Acacia dealbata, Ambrosia confertiflora, Andropogon virginicus, Cardiospermum grandiflorum, Celastrus orbiculatus, Cinnamomum camphora, Cortaderia jubata, Ehrharta calycina, Gymnocoronis spilanthoides, Hakea sericea, Humulus scandens, Hygrophila polysperma, Lespedeza cuneata, Lygodium japonicum, Pennisetum setaceum, Prosopis juliflora, Sapium sebiferum, Pistia stratiotes and Salvinia molesta).

1. Pollinator network structure arising from the extent and strength of interspecific mutualistic interactions can promote species persistence and community robustness. However, environmental change may re-organise network structure limiting capacity to absorb or resist shocks and increasing species extinctions. 2. We investigated if habitat disturbance and the level of mutualism dependence between species affected the robustness of insect–flower visitation networks Following a recently developed Stochastic Co-extinction Model (SCM), we ran simulations to produce the number of extinction episodes (cascade degree), which we correlated with network structure in undisturbed and disturbed habitat. We also explicitly modelled whether a species’ intrinsic dependence on mutualism affected the propensity for extinction cascades in the network. 3. Habitat disturbance generated a gradient in network structure with those from disturbed sites being less connected, but more speciose and so larger. Controlling for network size (z-score standardisation against the null model) revealed that disturbed networks had disproportionately low linkage density, high specialisation, fewer insect visitors per plant species (vulnerability) and lower nestedness (NODF). 4. This network structure gradient driven by disturbance increased and decreased different aspects of robustness to simulated plant extinction. Disturbance decreased the risk that an initial insect extinction would follow a plant species loss. Although, this effect disappeared when network size and connectance were standardised, suggesting the lower connectance of disturbed networks increased robustness to an initial secondary extinction. 5. However, if a secondary extinction occurred then networks from disturbed habitat were more prone to large co-extinction cascades, likely resulting from a greater chance of extinction in these larger, speciose networks. Conversely, when species mutualism dependency was explicit in the SCM simulations the disturbed networks were disproportionately more robust to very large co-extinction cascades, potentially caused by non-random patterns of interaction between species differing in dependence on mutualism. 6. Our results showed disturbance altered the size and the distribution of interspecific interactions in the networks to affect their robustness to co-extinction cascades. Controlling for effects due to network size and the interspecific variation in demographic dependence on mutualism can improve insight into properties conferring the structural robustness of networks to environmental changes.

Niche shifts of nonnative plants can occur when they colonize novel climatic conditions. However, the mechanistic basis for niche shifts during invasion is poorly understood and has rarely been captured within species distribution models. We quantified the consequence of between-population variation in phenology for invasion of common ragweed (Ambrosia artemisiifolia L.) across Europe. Ragweed is of serious concern because of its harmful effects as a crop weed and because of its impact on public health as a major aeroallergen. We developed a forward mechanistic species distribution model based on responses of ragweed development rates to temperature and photoperiod. The model was parameterized and validated from the literature and by reanalyzing data from a reciprocal common garden experiment in which native and invasive populations were grown within and beyond the current invaded range. It could therefore accommodate between-population variation in the physiological requirements for flowering, and predict the potentially invaded ranges of individual populations. Northern- origin populations that were established outside the generally accepted climate envelope of the species had lower thermal requirements for bud development, suggesting local adaptation of phenology had occurred during the invasion. The model predicts that this will extend the potentially invaded range northward and increase the average suitability across Europe by 90% in the current climate and 20% in the future climate. Therefore, trait variation observed at the population scale can trigger a climatic niche shift at the biogeographic scale. For ragweed, earlier flowering phenology in established northern populations could allow the species to spread beyond its current invasive range, substantially increasing its risk to agriculture and public health. Mechanistic species distribution models offer the possibility to represent niche shifts by varying the traits and niche responses of individual populations. Ignoring such effects could substantially underestimate the extent and impact of invasions.

Biological invasions are a major driver of global change, for which models can attribute causes, assess impacts and guide management. However, invasion models typically focus on spread from known introduction points or non-native distributions and ignore the transport processes by which species arrive. Here, we developed a simulation model to understand and describe plant invasion at a continental scale, integrating repeated transport through trade pathways, unintentional release events and the population dynamics and local anthropogenic dispersal that drive subsequent spread. We used the model to simulate the invasion of Europe by common ragweed (Ambrosia artemisiifolia), a globally invasive plant that causes serious harm as an aeroallergen and crop weed. Simulations starting in 1950 accurately reproduced ragweed's current distribution, including the presence of records in climatically unsuitable areas as a result of repeated introduction. Furthermore, the model outputs were strongly correlated with spatial and temporal patterns of ragweed pollen concentrations, which are fully independent of the calibration data. The model suggests that recent trends for warmer summers and increased volumes of international trade have accelerated the ragweed invasion. For the latter, long distance dispersal because of trade within the invaded continent is highlighted as a key invasion process, in addition to import from the native range. Biosecurity simulations, whereby transport through trade pathways is halted, showed that effective control is only achieved by early action targeting all relevant pathways. We conclude that invasion models would benefit from integrating introduction processes (transport and release) with spread dynamics, to better represent propagule pressure from native sources as well as mechanisms for long-distance dispersal within invaded continents. Ultimately, such integration may facilitate better prediction of spatial and temporal variation in invasion risk and provide useful guidance for management strategies to reduce the impacts of invasion.

Biotic interactions have been considered as an important factor to be included in species distribution modelling, but little is known about how different types of interaction or different strategies for modelling affect model performance. This study compares different methods for including interspecific interactions in distribution models for bees, their brood parasites, and the plants they pollinate. Host–parasite interactions among bumble bees (genus Bombus: generalist pollinators and brood parasites) and specialist plant–pollinator interactions between Centris bees and Krameria flowers were used as case studies. We used 7 different modelling algorithms available in the BIOMOD R package. For Bombus, the inclusion of interacting species distributions generally increased model predictive accuracy. The improvement was better when the interacting species was included with its raw distribution rather than with its modeled suitability. However, incorporating the distributions of non-interacting species sometimes resulted in similarly increased model accuracy despite their being no significance of any interaction for the distribution. For the Centris-Krameria system the best strategy for modelling biotic interactions was to include the interacting species model-predicted values. However, the results were less consistent than those for Bombus species, and most models including biotic interactions showed no significant improvement over abiotic models. Our results are consistent with previous studies showing that biotic interactions can be important in structuring species distributions at regional scales. However, correlations between species distributions are not necessarily indicative of interactions. Therefore, choosing the correct biotic information, based on biological and ecological knowledge, is critical to improve the accuracy of species distribution models and forecast distribution change.