Modelling spread of the invasive macrophyte Cabomba caroliniana

1. Predicting spread of non-indigenous species requires an understanding of where propagules are being transported, and whether these propagules can survive in the novel habitat and successfully integrate into the recipient community. In this study, we model potential spread of invading Cabomba caroliniana in Ontario, Canada, using a combination of passive and active dispersal models coupled with an environmental suitability model, thereby considering the first two stages of the invasion process.
2. Measures of propagule pressure incorporated both human-mediated dispersal via trailered boats, and advective flow from invaded to non-invaded systems, while habitat suitability was forecasted by combining native and global data sets and using boosted regression trees.
3. Risk of invasion differed depending on the combination of approaches used and the time period considered. Three lakes appear to be at greatest risk owing to a combination of high boater and water movement from invaded sources, and high environmental suitability. The best predictors of lake suitability were pH, mean lake temperature and dissolved calcium concentration. Hundreds of lakes in Ontario may be suitable for establishment of Cabomba , highlighting the need for vector management.     

Phenology predicts the native and invasive range limits of common ragweed

Accurate models for species' distributions are needed to forecast the progress and impacts of alien invasive species and assess potential range‐shifting driven by global change. Although this has traditionally been achieved through data‐driven correlative modelling, robustly extrapolating these models into novel climatic conditions is challenging. Recently, a small number of process‐based or mechanistic distribution models have been developed to complement the correlative approaches. However, tests of these models are lacking, and there are very few process‐based models for invasive species. We develop a method for estimating the range of a globally invasive species, common ragweed (Ambrosia artemisiifolia L.), from a temperature‐ and photoperiod‐driven phenology model. The model predicts the region in which ragweed can reach reproductive maturity before frost kills the adult plants in autumn. This aligns well with the poleward and high‐elevation range limits in its native North America and in invaded Europe, clearly showing that phenological constraints determine the cold range margins of the species. Importantly, this is a ‘forward’ prediction made entirely independently of the distribution data. Therefore, it allows a confident and biologically informed forecasting of further invasion and range shifting driven by climate change. For ragweed, such forecasts are extremely important as the species is a serious crop weed and its airborne pollen is a major cause of allergy and asthma in humans. Our results show that phenology can be a key determinant of species' range margins, so integrating phenology into species distribution models offers great potential for the mechanistic modelling of range dynamics.     

An integrated,spatio‐temporal modelling framework for analysing biological invasions

Aim

We develop a novel modelling framework for analysing the spatio‐temporal spread of biological invasions. The framework integrates different invasion drivers and disentangles their roles in determining observed invasion patterns by fitting models to historical distribution data. As a case study application, we analyse the spread of common ragweed (Ambrosia artemisiifolia).

Location

Central Europe.

Methods

A lattice system represents actual landscapes with environmental heterogeneity. Modelling covers the spatio‐temporal invasion sequence in this grid and integrates the effects of environmental conditions on local invasion suitability, the role of invaded cells and spatially implicit “background” introductions as propagule sources, within‐cell invasion level bulk‐up and multiple dispersal means. A modular framework design facilitates flexible numerical representation of the modelled invasion processes and customization of the model complexity. We used the framework to build and contrast increasingly complex models, and fitted them using a Bayesian inference approach with parameters estimated by Markov chain Monte Carlo (MCMC).

Results

All modelled invasion drivers codetermined the A. artemisiifolia invasion pattern. Inferences about individual drivers depended on which processes were modelled concurrently, and hence changed both quantitatively and qualitatively between models. Among others, the roles of environmental variables were assessed substantially differently subject to whether models included explicit source‐recipient cell relationships, spatio‐temporal variability in source cell strength and human‐mediated dispersal means. The largest fit improvements were found by integrating filtering effects of the environment and spatio‐temporal availability of propagule sources.

Main conclusions

Our modelling framework provides a straightforward means to build integrated invasion models and address hypotheses about the roles and mutual relationships of different putative invasion drivers. Its statistical nature and generic design make it suitable for studying many observed invasions. For efficient invasion modelling, it is important to represent changes in spatio‐temporal propagule supply by explicitly tracking the species’ colonization sequence and establishment of new populations.

     

Modeling habitat suitability and spread dynamics of two invasive rose species in protected areas of Mendoza,Argentina

Biological invasions are a main threat to biodiversity and natural resources, which calls for studies that identify the regions that present the greatest invasion risks. We assessed the potential distribution of two non-native rose species, Rosa canina and Rosa rubiginosa, in mountain environments in mid-western Argentina, using species distribution models and dynamic simulations. We first fitted the model for one protected area, Villavicencio Nature Reserve, and then we made predictions on the distribution of these species for other protected areas in the same region, where the presence of these species was observed but where there are no systematic surveys on their distribution. We also modeled the invasion dynamics of these species based on habitat suitability, considering the dispersal distance and the growth rate of the invaded area. High and very high suitability sites were detected in all the protected areas studied, suggesting high invasion risk in these protected areas. Our simulations of the spatio–temporal dynamics of the rose invasion in Villavicencio indicated that the spread depends strongly on the average seed dispersal distance, that the spread has been gradual since the rose introduction into the protected area, and that 150 years after the introduction even the areas identified as having low suitability are expected to have been invaded. This is the first study of this type for the region, where these invasive rose species are a serious problem. Taken together, our results may be useful to identify areas vulnerable to invasion and thus help generate effective preventive, monitoring, and control practices.     

Its all about connections: hubs and invasion in habitat networks

During the early stages of invasion, the interaction between the features of the invaded landscape, notably its spatial structure, and the internal dynamics of an introduced population has a crucial impact on establishment and spread. By approximating introduction areas as networks of patches linked by dispersal, we characterised their spatial structure with specific metrics and tested their impact on two essential steps of the invasion process: establishment and spread. By combining simulations with experimental introductions of Trichogramma chilonis (Hymenoptera: Trichogrammatidae) in artificial laboratory microcosms, we demonstrated that spread was hindered by clusters and accelerated by hubs but was also affected by small‐population mechanisms prevalent for invasions, such as Allee effects. Establishment was also affected by demographic mechanisms, in interaction with network metrics. These results highlight the importance of considering the demography of invaders as well as the structure of the invaded area to predict the outcome of invasions.     

Accounting for imperfect observation and estimating true species distributions in modelling biological invasions

The documentation of biological invasions is often incomplete with records lagging behind the species’ actual spread to a spatio‐temporally heterogeneous extent. Such imperfect observation bears the risk of underestimating the already realised distribution of the invading species, misguiding management efforts and misjudging potential future impacts. In this paper, we develop a hierarchical modelling framework which disentangles the determinants of the invasion and observation processes, models spatio‐temporal heterogeneity in detection patterns, and infers the actual, yet partly undocumented distribution of the species at any particular time. We illustrate the model with a case study application to the invasion of common ragweed Ambrosia artemisiifolia in Austria. The invasion part of the model reconstructs the historical spread of this species across a grid of ～ 6 × 6 km² cells as driven by spatio‐temporal variation in physical site conditions, propagule production, dispersal, and ‘background’ introductions from unknown sources. The observation part models the detection of the species’ occurrences based on heterogeneous sampling efforts, human population density, and estimated local invasion level. We fitted the hierarchical model using a Bayesian inference approach with parameters estimated by Markov chain Monte Carlo (MCMC). The actual spread of A. artemisiifolia concentrated on the climatically well‐suited lowlands and was mainly driven by spatio‐temporal propagule pressure from source cells with long‐distance dispersal occurring rather frequently. Annual detection probabilities were estimated to vary between about 1 and up to 28%, depending mainly on sampling intensity. The model suggested that by 2005 about half of the actual distribution of the species was not yet documented. Our hierarchical model offers a flexible means to account for imperfect observation and spatio‐temporal variability in detection efficiency. Inferences can be used to disentangle aspects of the invasion dynamics itself from patterns of data collection, develop improved future surveying schemes, and design more efficient invasion management strategies.     

Deciphering the worldwide invasion of the Asian long‐horned beetle: A recurrent invasion process from the native area together with a bridgehead effect

Retracing introduction routes is crucial for understanding the evolutionary processes involved in an invasion, as well as for highlighting the invasion history of a species at the global scale. The Asian long‐horned beetle (ALB) Anoplophora glabripennis is a xylophagous pest native to Asia and invasive in North America and Europe. It is responsible for severe losses of urban trees, in both its native and invaded ranges. Based on historical and genetic data, several hypotheses have been formulated concerning its invasion history, including the possibility of multiple introductions from the native zone and secondary dispersal within the invaded areas, but none have been formally tested. In this study, we characterized the genetic structure of ALB in both its native and invaded ranges using microsatellites. In order to test different invasion scenarios, we used an approximate Bayesian “random forest” algorithm together with traditional population genetics approaches. The strong population differentiation observed in the native area was not geographically structured, suggesting complex migration events that were probably human‐mediated. Both native and invasive populations had low genetic diversity, but this characteristic did not prevent the success of the ALB invasions. Our results highlight the complexity of invasion pathways for insect pests. Specifically, our findings indicate that invasive species might be repeatedly introduced from their native range, and they emphasize the importance of multiple, human‐mediated introductions in successful invasions. Finally, our results demonstrate that invasive species can spread across continents following a bridgehead path, in which an invasive population may have acted as a source for another invasion.     

北美刺龙葵在中国的适生区预测

【背景】北美刺龙葵是一种全球广泛分布的恶性杂草,已被列入我国进境检疫性有害生物名单。近年来北美刺龙葵不断随进口货物传入我国,明确其传入途径和适生区对控制其入侵具有重要意义。【方法】采用GIS、空间统计学、Maxent生态位模型等方法分析了北美刺龙葵的传入途径与潜在分布区,并通过ROC分析法对模型进行检验。【结果】跨区域农产品贸易是北美刺龙葵全球扩散的驱动力与传入我国的主要途径。生态模型预测结果表明,北美刺龙葵在我国具有广阔的适生区,除黑龙江、吉林、内蒙古、青海、甘肃、西藏、四川西北部以外的区域都是其在我国的适生区,其中高风险区主要集中在东部和南部沿海、西南边境和新疆的部分地区。AUC值为0.789,表明本研究建立的Maxent模型的预测能力较强,能够很好地拟合物种已知分布的环境生态位。【结论与意义】北美刺龙葵在我国的传入风险极高。基于北美刺龙葵在我国的主要传入途径与潜在扩散媒介的时空分布,划定了重点监测的区域,建议对适生区内极易传入的高风险区如港口、机场、物流中转站、加工厂等开展早期监测预警,以预防其再次入侵与进一步扩散蔓延。     

Evolutionarily labile species interactions and spatial spread of invasive species

Both exotic and native species have been shown to evolve in response to invasions, yet the impacts of rapidly evolving interactions between novel species pairs have been largely ignored in studies of invasive species spread. Here, I use a mathematical model of an interacting invasive predator and its native prey to determine when and how evolutionary lability in one or both species might impact the dynamics of the invader's spatial advance. The model shows that evolutionarily labile invaders continually evolve better adapted phenotypes along the moving invasion front, offering an explanation for accelerating spread and spatial phenotype clines following invasion. I then analytically derive a formula to estimate the relative change in spread rate due to evolution. Using parameter estimates from the literature, this formula shows that moderate heritabilities and selection strengths are sufficient to account for changes in spread rates observed in historical and ongoing invasions. Evolutionarily labile native species can slow invader spread when genes flow from native populations with exposure to the invader into native populations ahead of the invasion front. This outcome is more likely in systems with highly diffuse native dispersal, net directional movement of natives toward the invasion front, or human inoculation of uninvaded native populations.     

Local adaptation,dispersal evolution,and the spatial eco‐evolutionary dynamics of invasion

Local adaptation and dispersal evolution are key evolutionary processes shaping the invasion dynamics of populations colonizing new environments. Yet their interaction is largely unresolved. Using a single‐species population model along a one‐dimensional environmental gradient, we show how local competition and dispersal jointly shape the eco‐evolutionary dynamics and speed of invasion. From a focal introduction site, the generic pattern predicted by our model features a temporal transition from wave‐like to pulsed invasion. Each regime is driven primarily by local adaptation, while the transition is caused by eco‐evolutionary feedbacks mediated by dispersal. The interaction range and cost of dispersal arise as key factors of the duration and speed of each phase. Our results demonstrate that spatial eco‐evolutionary feedbacks along environmental gradients can drive strong temporal variation in the rate and structure of population spread, and must be considered to better understand and forecast invasion rates and range dynamics.     

Prediction and error in multi‐stage models for spread of aquatic non‐indigenous species

Aim Predictions of spread of non‐indigenous species allow for greater efficiency in managing invasions by targeting areas for preventative measures. The invasion sequence is a useful concept in predictions of spread, as it allows us to test hypotheses about the transport and establishment of propagules in novel habitats. Our aims are twofold: (1) to develop and validate multi‐stage invasion models for the introduced fishhook waterflea, Cercopagis pengoi, and (2) to assess how variability in the transport patterns of the propagules influences the accuracy and spatial extent for predictions of spread. Location New York State, USA. Methods We developed a two‐stage model for the spread of C. pengoi. First, we developed a stochastic gravity model for dispersal based on surveys of recreational boat traffic in New York State as a proxy for propagule pressure. We then modelled the probability of establishment based on predicted levels of propagule pressure and measures of lakes’ physicochemistry. In addition, we used Monte Carlo simulations based on the gravity model to propagate variability in boater traffic through the establishment model to assess how uncertainty in dispersal influenced predictions of spread. Results The amount recreationalists were willing to spend, lake area and population size of the city nearest to the destination lake were significant factors affecting boater traffic. In turn, boater traffic, lake area, specific conductance and turbidity were significant predictors of establishment. The inclusion of stochastic dispersal reduced the rate of false positives (i.e. incorrect prediction of an invasion) in detecting invasions at the upper 95% prediction interval for the probability of establishment. Main conclusions Combinations of measures of propagule pressure, habitat suitability and stochastic dispersal allow for the most accurate predictions of spread. Further, multi‐stage spread models may overestimate the extent of spread if stochasticity in early stages of the models is not considered.     

Forest edges and fire ants alter the seed shadow of an ant-dispersed plant

Exotic species invade fragmented, edge-rich habitats readily, yet the distinct impacts of habitat edges and invaders on native biota are rarely distinguished. Both appear detrimental to ant-dispersed plants such as bloodroot, Sanguinaria canadensis. Working in northeastern Georgia (USA), an area characterized by a rich ant-dispersed flora, fragmented forests, and invasions by the red imported fire ant, Solenopsis invicta , I monitored the interactions between ants and S. canadensis seeds in uninvaded forest interiors, uninvaded forest edges, invaded forest interiors, and invaded forest edges. I observed 95% of the seed dispersal events that occurred within the 60-min observation intervals. Seed collection rates were similar among all four (habitat × invasion) groups. The presence of invasive ants had a strong effect on seed dispersal distance: S. invicta collected most seeds in invaded sites, but was a poorer disperser than four of five native ant taxa. Habitat type (interior versus edge) had no effect on seed dispersal distance, but it had a strong effect on seed dispersal direction. Dispersal towards the edge was disproportionately rare in uninvaded forest edges, and ants in those habitats moved the average dispersed seed approximately 70 cm away from that edge. Dispersal direction was also skewed away from the edge in uninvaded forest interiors and invaded forest edges, albeit non-significantly. This biased dispersal may help explain the rarity of myrmecochorous plants in younger forests and edges, and their poor ability to disperse between fragments. This is the first demonstration that forest edges and S. invicta invasion influence seed dispersal destination and distance, respectively. These forces act independently.     

Uncovering the spatial pattern of invasion of the honeybee pest small hive beetle,Aethina tumida,in Italy

The fast tracking of invasion spatial patterns of alien species is crucial for the implementation of preventive and management strategies of those species. Recently, a honeybee pest, the small hive beetle Aethina tumida (hereafter SHB), has been reported in Italy, where it colonized more than 50 apiaries in an area of about 300 km². SHB is a nest parasite and scavenger of honeybee colonies native of Sub-Saharian Africa. Likely being helped by the globalization of apiculture, SHB underwent several invasions in the last twenty years, causing locally relevant economic impact. While many features of its biology have been addressed, an important knowledge gap concerns the spatial invasion dynamics in invaded areas. In this paper we coupled two spatial analysis techniques (geographic profiling and a density-based spatial clustering algorithm) to uncover the possible invasion pattern of SHB in Italy. We identified the port town of Gioia Tauro as the most likely point from which SHB may have spread and suggested the possible successive axes of diffusion. These putative diffusion paths suggest that the SHB spread in south Italy might have been due to a mix of natural dispersal between close apiaries and longer distance movement through faster, likely human-mediated, communication routes.     

The cane toad's (Chaunus [Bufo] marinus) increasing ability to invade Australia is revealed by a dynamically updated range model

Invasive species threaten biological diversity throughout the world. Understanding the dynamics of their spread is critical to mitigating this threat. In Australia, efforts are underway to control the invasive cane toad (Chaunus [Bufo] marinus). Range models based on their native bioclimatic envelope suggest that the cane toad is nearing the end of its invasion phase. However, such models assume a conserved niche between native and invaded regions and the absence of evolution to novel habitats. Here, we develop a dynamically updated statistical model to predict the growing extent of cane toad range based on their current distribution in Australia. Results demonstrate that Australian cane toads may already have the ability to spread across an area that almost doubles their current range and that triples projections based on their native distribution. Most of the expansion in suitable habitat area has occurred in the last decade and in regions characterized by high temperatures. Increasing use of extreme habitats may indicate that novel ecological conditions have facilitated a broader realized niche or that toad populations at the invasion front have evolved greater tolerance to extreme abiotic conditions. Rapid evolution to novel habitats combined with ecological release from native enemies may explain why some species become highly successful global invaders. Predicting species ranges following invasion or climate change may often require dynamically updated range models that incorporate a broader realization of niches in the absence of natural enemies and evolution in response to novel habitats.     

The intermediate distance hypothesis of biological invasions

Biological invasions are a worldwide phenomenon, but the global flows between native and alien regions have rarely been investigated in a cross‐taxonomic study. We therefore lack a thorough understanding of the global patterns of alien species spread. Using native and alien ranges of 1380 alien species, we show that the number of alien species follows a hump‐shaped function of geographic distance. We observe distinct variations in the relationship between alien species exchanges and distance among taxonomic groups, which relate to the taxa‐specific dispersal modes and their pathways of introduction. We formulate a simple statistical model, combining trade volume and biogeographic dissimilarity, which reproduces the observed pattern in good agreement with reported data and even captures variations among taxonomic groups. This study demonstrates the universality of the intermediate distance hypothesis of alien species spread across taxonomic groups, which will help to improve the predictability of new alien species arrivals.     

Predicting the current distribution and potential spread of the exotic grass Eragrostis plana Nees in South America and identifying a bioclimatic niche shift during invasion

Eragrostis plana (Poaceae) is a perennial grass introduced from South Africa to the state of Rio Grande do Sul in southern Brazil. Currently, it is considered an invasive grass in several regions of the world, including South America, where it has caused negative ecological and socio‐economic impacts. Ecological niche models, using bioclimatic variables, are often used to predict the potential distribution of invasive species. In this study we prepared two bioclimatic models for E. plana using the Genetic Algorithm for Rule‐set Production, the first based on data from its native region (South Africa) and the second on data from both the native and invaded (South America) regions. We then projected each model onto South America to identify regions vulnerable to invasion by the species, and compared our results with available records of the species in South America. Finally, we explored the model's predictions for the existence of a bioclimatic niche shift during the invasion process of E. plana in South America, using multivariate statistical analysis. The model created with native distribution data was only able to predict (with highly suitable habitat) the region of introduction of E. plana in South America. However, the current distribution, as well as the region of introduction of the species, was reliably predicted by the model created with data from both native and invaded regions. Our multivariate analysis supports a hypothesis of bioclimatic niche shift during the invasion process of E. plana in South America.     

Invasion phylogeography of the Ponto-Caspian crustacean Limnomysis benedeni dispersing across Europe

Aim  Limnomysis benedeni Czerniavsky, 1882 is a mysid crustacean native to the Ponto-Caspian (Black and Caspian Sea) rivers and estuaries, and has recently spread across Europe through intentional and unintentional introductions. We explored the structuring of genetic variation in native and non-native populations with an aim to trace the sources of the invasions, and to infer whether the spread has occurred through a single or multiple invasion waves.
Location  Native estuaries in the Ponto-Caspian basin (Volga, Don, Dnieper, Dniester, Danube) and the recently colonized range along the Danube–Rhine river systems and Lithuania.
Methods  A fragment of the mitochondrial COI gene was sequenced to assess genetic affinities and diversity in native and recently established populations.
Results  The genetic diversity in the native regions is organized into several strongly diverged haplotype groups or lineages, partly allopatric, partly sympatric. All these lineages have also spread beyond the native range. Even the recent rapid dispersal across Europe along the Danube–Rhine system towards the North Sea basin involved several lineages from the Danube delta sector. The structuring of genetic diversity among invaded sites suggests multiple invasion events to the Danube–Rhine drainage. This contrasts with data from some other Ponto-Caspian species, where a single haplotype seems to have occupied most invaded areas. There is no evidence that intentionally stocked reservoirs in the Baltic Sea basin would have contributed to further unintentional spread of L. benedeni.
Main conclusions  Limnomysis benedeni is spreading across Europe using the southern invasion corridor. The invasion most likely involved several waves from differentiated sources in the native Danube delta area.     

Niche shifts during the global invasion of the Asian tiger mosquito, Aedes albopictus Skuse (Culicidae), revealed by reciprocal distribution models

Aim Niche‐based distribution models are often used to predict the spread of invasive species. These models assume niche conservation during invasion, but invasive species can have different requirements from populations in their native range for many reasons, including niche evolution. I used distribution modelling to investigate niche conservatism for the Asian tiger mosquito (Aedes albopictus Skuse) during its invasion of three continents. I also used this approach to predict areas at risk of invasion from propagules originating from invasive populations. Location Models were created for Southeast Asia, North and South America, and Europe. Methods I used maximum entropy (Maxent ) to create distribution models using occurrence data and 18 environmental datasets. One native model was created for Southeast Asia; this model was projected onto North America, South America and Europe. Three models were created independently for the non‐native ranges and projected onto the native range. Niche overlap between native and non‐native predictions was evaluated by comparing probability surfaces between models using real data and random models generated using a permutation approach. Results The native model failed to predict an entire region of occurrences in South America, approximately 20% of occurrences in North America and nearly all Italian occurrences of A. albopictus. Non‐native models poorly predict the native range, but predict additional areas at risk for invasion globally. Niche overlap metrics indicate that non‐native distributions are more similar to the native niche than a random prediction, but they are not equivalent. Multivariate analyses support modelled differences in niche characteristics among continents, and reveal important variables explaining these differences. Main conclusions The niche of A. albopictus has shifted on invaded continents relative to its native range (Southeast Asia). Statistical comparisons reveal that the niche for introduced distributions is not equivalent to the native niche. Furthermore, reciprocal models highlight the importance of controlling bi‐directional dispersal between native and non‐native distributions.     

Species Invasiveness in Biological Invasions: A Modelling Approach

The study of invasiveness, the traits that enable a species to invade a habitat, and invasibility, the habitat characteristics that determine its susceptibility to the establishment and spread of an invasive species, provide a useful conceptual framework to formulate the biological invasion problem in a modelling context. Another important aspect is the complex interaction emerging among the invader species, the noninvader species already present in the habitat, and the habitat itself. Following a modelling approach to the biological invasion problem, we present a spatially explicit cellular automaton model (Interacting Multiple Cellular Automata (IMCA)). We use field parameters from the invader Gleditsia triacanthos and the native Lithraea ternifolia in montane forests of central Argentina as a case study to compare outputs and performance of different models. We use field parameters from another invader, Ligustrum lucidum, and the native Fagara coco from the same system to run the cellular automaton model. We compare model predictions with invasion values from aerial photographs. We discuss in detail the importance of factors affecting species invasiveness, and give some insights into habitat invasibility and the role of interactions between them. Finally, we discuss the relevance of mathematical modelling for studying and predicting biological invasions. The IMCA model provided a suitable context for integrating invasiveness, invasibility, and the interactions. In the invasion system studied, the presence of an invader's juvenile bank not only accelerated the rate of invasion but was essential to ensure invasion. Using the IMCA model, we were able to determine that not only adult survival but particularly longevity of the native species influenced the spread velocity of the invader, at least when a juvenile bank is present. Other factors determining velocity of invasion detected by the IMCA model were seed dispersal distance and age of reproductive maturity. We derived relationships between species' adult survival, fecundity and longevity of both theoretical and applied relevance for biological invasions. Invasion velocities calculated from the aerial photographs agreed well with predictions of the IMCA model.     

Landscape epidemiology and control of pathogens with cryptic and long-distance dispersal: sudden oak death in northern Californian forests

Exotic pathogens and pests threaten ecosystem service, biodiversity, and crop security globally. If an invasive agent can disperse asymptomatically over long distances, multiple spatial and temporal scales interplay, making identification of effective strategies to regulate, monitor, and control disease extremely difficult. The management of outbreaks is also challenged by limited data on the actual area infested and the dynamics of spatial spread, due to financial, technological, or social constraints. We examine principles of landscape epidemiology important in designing policy to prevent or slow invasion by such organisms, and use Phytophthora ramorum, the cause of sudden oak death, to illustrate how shortfalls in their understanding can render management applications inappropriate. This pathogen has invaded forests in coastal California, USA, and an isolated but fast-growing epidemic focus in northern California (Humboldt County) has the potential for extensive spread. The risk of spread is enhanced by the pathogen's generalist nature and survival. Additionally, the extent of cryptic infection is unknown due to limited surveying resources and access to private land. Here, we use an epidemiological model for transmission in heterogeneous landscapes and Bayesian Markov-chain-Monte-Carlo inference to estimate dispersal and life-cycle parameters of P. ramorum and forecast the distribution of infection and speed of the epidemic front in Humboldt County. We assess the viability of management options for containing the pathogen's northern spread and local impacts. Implementing a stand-alone host-free "barrier" had limited efficacy due to long-distance dispersal, but combining curative with preventive treatments ahead of the front reduced local damage and contained spread. While the large size of this focus makes effective control expensive, early synchronous treatment in newly-identified disease foci should be more cost-effective. We show how the successful management of forest ecosystems depends on estimating the spatial scales of invasion and treatment of pathogens and pests with cryptic long-distance dispersal.