How does temporal variation in habitat connectivity influence metapopulation dynamics?

Metapopulation persistence depends on connectivity between habitat patches. While emphasis has been placed on the spatial dynamics of connectivity, much less has been placed on its short‐term temporal dynamics. In many terrestrial and aquatic ecosystems, however, transient (short‐term) changes in connectivity occur as habitat patches are connected and disconnected due, for example, to climatic or hydrological variability. We evaluated the implications of transient connectivity using a network‐based metapopulation model and a series of scenarios representing temporal changes in connectivity. The transient loss of connectivity can influence metapopulation persistence, and more strongly autocorrelated temporal dynamics affect metapopulation persistence more severely. Given that many ecosystems experience short‐term and temporary loss of habitat connectivity, it is important that these dynamics are adequately represented in metapopulation models; failing to do so may yield overly optimistic‐estimates of metapopulation persistence in fragmented landscapes.     

Landscape diversity slows the spread of an invasive forest pest species

According to the associational resistance hypothesis, diverse habitats provide better resistance to biological invasions than monocultures. Host‐plant abundance has been shown to affect the range expansion of invasive pests, but the effect of landscape diversity (i.e. density of host/non‐host patches and diversity of forest habitat patches) on invasions remains largely untested. We used boundary displacement models and boosted regression tree analyses to investigate the effects of landscape diversity on the invasion of Corsica by the maritime pine bast scale Matsucoccus feytaudi over an 18‐yr period. Taking the passive wind dispersal of the scale into account, we showed that open habitats and connectivity between host patches accelerated spread by up to 13%, whereas landscapes with high tree diversity and a high density of non‐host trees decreased scale spread by up to 14%. We suggest a new mechanism for such associational resistance to pest invasion at the landscape level, which we term ‘the pitfall effect’.     

Invasive spread in meta-food-webs depends on landscape structure,fertilization and species characteristics

Land use change and biological invasions collectively threaten biodiversity. Yet, few studies have addressed how altering the landscape structure and nutrient supply can promote biological invasions and particularly invasive spread (the spread of an invader from the place of introduction), or asked whether and how these factors interact with biotic interactions and invader properties. We here bridge this knowledge gap by providing a holistic network-based approach. Our approach combines a trophic network model with a spatial network model allowing us to test which combinations of abiotic and biotic factors can facilitate invasions and in particular invasive spread in food webs. We numerically simulated 6300 single-species invasions in clustered and random landscapes at different levels of nutrient supply. In total, our simulation experiment yielded 69% successful invasions – 71% in clustered landscapes and 66% in random landscapes, with the proportion of successful invasions increasing with nutrient supply. However, invasive spread was generally higher in random than in clustered landscapes. The latter can facilitate invasive spread within a habitat cluster, but prevent invasive spread between clusters. Low nutrient levels generally prevented the establishment of invasive species and their subsequent spread. However, successful invaders could have more severe impacts as they contribute more to total biomass density and species richness under such conditions. Good dispersal abilities drive the broad-scale spread of invasive species in fragmented landscapes. Our approach makes an important contribution towards a better understanding of what combination of landscape and invader properties can facilitate or prevent invasive spread in natural ecosystems. This should allow ecologists to more effectively predict and manage biological invasions.     

Predicted range expansion of Chinese tallow tree (Triadica sebifera) in forestlands of the southern United States

Aim We present an integrated approach for predicting future range expansion of an invasive species (Chinese tallow tree) that incorporates statistical forecasting and analytical techniques within a spatially explicit, agent‐based, simulation framework. Location East Texas and Louisiana, USA. Methods We drew upon extensive field data from the US Forest Service and the US Geological Survey to calculate spread rate from 2003 to 2008 and to parameterize logistic regression models estimating habitat quality for Chinese tallow within individual habitat cells. We applied the regression analyses to represent population spread rate as a function of habitat quality, integrated this function into a logistic model representing local spread, and coupled this model with a dispersal model based on a lognormal kernel within the simulation framework. We simulated invasions beginning in 2003 based on several different dispersal velocities and compared the resulting spatial patterns to those observed in 2008 using cross Mantel’s tests. We then used the best dispersal velocity to predict range expansion to the year 2023. Results Chinese tallow invasion is more likely in low and flat areas adjacent to water bodies and roads, and less likely in mature forest stands and in pine plantations where artificial regeneration by planting seedlings is used. Forecasted invasions resulted in a distribution that extended from the Gulf Coast of Texas and Louisiana northward and westward as much as 300 km, representing approximately 1.58 million ha. Main conclusions Our new approach of calculating time series projections of annual range expansion should assist land managers and restoration practitioners plan proactive management strategies and treatments. Also, as field sampling continues on the national array of FIA plots, these new data can be incorporated easily into the present model, as well as being used to develop and/or improve models of other invasive plant species.     

Initial conditions and their effect on invasion velocity across heterogeneous landscapes

Accurate, time dependent control options are required to halt biological invasions prior to equilibrium establishment, beyond which control efforts are often impractical. Although invasions have been successfully modeled using diffusion theory, diffusion models are typically confined to providing simple range expansion estimates. In this work, we use a Susceptible/Infected cellular automaton (CA) to simulate diffusion. The CA model is coupled with a network model to track the speed and direction of simulated invasions across heterogeneous landscapes, allowing for identification of locations for targeted control in both time and space. We evaluated the role of the location of initial establishment insofar as it affected the pattern and rate of spread and how these are influenced by patch attributes such as size. Our results show that the location of initial establishment can significantly affect the temporal dynamics of an invasion. Traditional network metrics such as degree and measures of topological distance were insufficient for predicting the direction and speed of the invasion. Our coupled models allow the dynamic tracking of invasions across fragmented landscapes for both theoretical and practical applications.     

Excluding access to invasion hubs can contain the spread of an invasive vertebrate

Many biological invasions do not occur as a gradual expansion along a continuous front, but result from the expansion of satellite populations that become established at 'invasion hubs'. Although theoretical studies indicate that targeting control efforts at invasion hubs can effectively contain the spread of invasions, few studies have demonstrated this in practice. In arid landscapes worldwide, humans have increased the availability of surface water by creating artificial water points (AWPs) such as troughs and dams for livestock. By experimentally excluding invasive cane toads (Bufo marinus) from AWP, we show that AWP provide a resource subsidy for non-arid-adapted toads and serve as dry season refuges and thus invasion hubs for cane toads in arid Australia. Using data on the distribution of permanent water in arid Australia and the dispersal potential of toads, we predict that systematically excluding toads from AWP would reduce the area of arid Australia across which toads are predicted to disperse and colonize under average climatic conditions by 38 per cent from 2,242,000 to 1,385,000 km(2). Our study shows how human modification of hydrological regimes can create a network of invasion hubs that facilitates a biological invasion, and confirms that targeted control at invasion hubs can reduce landscape connectivity to contain the spread of an invasive vertebrate.     

网络理论在入侵生物学中的应用研究现状

生物入侵是一个动态有序的过程,其发生和危害存在异质性,通常由来源地、入侵地和它们之间的连接构成的系统中的自然、生物、社会等因素所决定。网络理论是研究复杂系统的一种新方法,本质是从复杂的信息中抽象出规律、揭示系统的结构特征共性。近20年,网络理论已被应用于生物入侵研究。本研究综述了网络理论在生物入侵研究中的应用进展,明确了主要的研究方向和前沿热点,认为:2000年以来国际上已开展的研究集中在评估外来物种入侵风险和入侵后对生态系统影响2个方面;外来物种随运输网络入侵的风险评估和景观连接性对入侵物种扩散的影响、外来物种入侵对本地物种间互作网络的影响及生态群落可入侵性是网络理论应用的热点;研究热点具有明显的时间发展特征,2013年以前多是对生态系统的影响,近10年来主要是风险评估。我国利用网络理论研究外来物种入侵较少且集中于对生态系统的危害,未来应加强对外来物种的时空定量传入和扩散风险评估,为我国制定和提升外来入侵物种早期监测预警、阻止新的入侵、抑制进一步扩散的管理措施提供依据。     

The effect of landscape heterogeneity on host–parasite dynamics

Environmental heterogeneity has been shown to have a profound effect on population dynamics and biological invasions, yet the effect of its spatial structure on the dynamics of disease invasion in a spatial host–parasite system has received little attention. Here we explore the effect of environment heterogeneity using the pair approximation and the stochastic spatially explicit simulation in which the lost patches are clustered in a fragmented landscape. The intensity of fragmentation is defined by the amount and spatial autocorrelation of the lost habitat. More fragmented landscape (high amount of habitat loss, low clustering of lost patches) was shown to be detrimental to the parasitic disease invasion and transmission, which implies that the potential of using artificial disturbances as a disease-control agency in biological conservation and management. Two components of the spatial heterogeneity (the amount and spatial autocorrelation of the lost habitat) formed a trade-off in determining the host–parasite dynamics. An extremely high degree of habitat loss was, counter-intuitively, harmful to the host. These results enrich our understanding of eco-epidemiological, host–parasite systems, and suggest the possibility of using the spatial arrangement of habitat patches as a conservation tool for guarding focal species against parasitic infection and transmission.     

Invasion theory and biological control

Recent advances in the mathematical theory of invasion dynamics have much to offer to biological control. Here we synthesize several results concerning the spatiotemporal dynamics that occur when a biocontrol agent spreads into a population of an invading pest species. We outline conditions under which specialist and generalist predators can influence the density and rate of spatial spread of the pest, including the rather stringent conditions under which a specialist predator can successfully reverse a pest invasion. We next discuss the connections between long distance dispersal and invasive spread, emphasizing the different consequences of fast spreading pests and predators. Recent theory has considered the effects of population stage-structure on invasion dynamics, and we discuss how population demography affects the biological control of invading pests. Because low population densities generally characterize early stages of an invasion, we discuss the lessons invasion theory teaches concerning the detectability of invasions. Stochasticity and density-dependent dynamics are common features of many real invasions, influencing both the spatial character (e.g. patchiness) of pest invasions and the success of biocontrol agents. We conclude by outlining theoretical results delineating how stochastic effects and complex dynamics generated by density dependence can facilitate or impede biological pest control.     

Offense and defense in landscape-level invasion control

Biological invasions are multi-stage processes comprising chance demographic events, species interactions, and dispersal. Despite this complexity, simple models can increase understanding of the invasion process. We model the spread of aquatic invasive species through a network of lakes to evaluate the effectiveness of two intervention strategies. The first, which we call offense, contains the invader at sources; the second, which we call defense, protects uninvaded destinations. Deterministic models reveal the effects of these intervention strategies on spread rates. Practical applications involve finite collections of uninvaded lakes, however, and we therefore also present a stochastic model to describe how these strategies affect expected times to important invasion milestones. When the goal is to reduce overall spread rates, both approaches agree that offense is better early in invasions, but that defense is better after 1/2 the lakes are invaded. When the goal is to protect areas of high conservation value, however, defensive site protection always provides lower per site introduction rates. Although we focus on lakes, our results are quite general, and could be applied to any discrete habitat patches including, for example, fragmented terrestrial habitats.     

Invasion dynamics of an introduced squirrel in Argentina

Biological invasions are one of the major threats to both ecosystem and economic functioning. Their management typically involves culling of the pest or removal of its habitat. The Asiatic red-bellied beautiful squirrel Callosciurus erythraeus is the first known introduction of a squirrel into South America. It established from five releases in 1973, using exotic trees to spread through Argentinean Pampas. It now causes substantial economic damage in agricultural and urban areas across >680 km², and its continued spread threatens indigenous species. We developed a spatially explicit model of the invasion for the likely range of life-history parameters, matched against empirical data on patch occupancy in 2004. The two best-fitting models suggest the current population to be on the cusp of an explosive expansion. These models were used to predict future trends under alternative scenarios of strategic culling or habitat removal aimed at slowing the spread. The predictions for 18 yr into the future were that 1) the present lack of systematic management will lead to a 5-fold increase in area of occupancy, 2) removal of habitat down to half carrying capacity will thin the population but accelerate its spread, 3) 10 yr of culling above the maximum sustainable yield (MSY) will precipitate declines in abundance and patch occupancy towards extinction, but with immediate recovery upon cessation of the cull. We recommend continuous culling above the MSY in priority patches, aimed at slowing arrival to valuable conservation areas. This study demonstrates the need for prompt action to terminate invasions before they establish. The squirrel invasion is now irreversible after 30 yr of slow spread across fragmented habitat. Although culling requires public awareness campaigns and sustained governmental commitment, it is now the best feasible strategy for managing this invasion.     

Comparing short and long‐distance dispersal: modelling and field case studies

Dispersal is a factor of great importance in determining a species spatial distribution. Short distance dispersal (SDD) and long distance dispersal (LDD) strategies yield very different spatial distributions. In this paper we compare spatial spread patterns from SDD and LDD simulations, contrast them with patterns from field data, and assess the significance of biological and population traits. Simulated SDD spread using an exponential function generates a single circular patch with a well‐defined invasion front showing a travelling‐wave structure. The invasive spread is relatively slow as it is restricted to reproductive individuals occupying the outer zone of the circular patch. As a consequence of this dispersal dynamics, spread is slower than spread generated by LDD. In contrast, the early and fast invasion of the entire habitat mediated by power law LDD not only involves a significantly greater invasion velocity, but also an entirely different habitat occupation. As newly dispersed individuals soon reach very distant portions of the habitat as well as the vicinity of the original dispersal focus, new growing patches are generated while the main patch increases its own growth absorbing the closest patches. As a consequence of both dispersal and lower density dependence, growth of the occupied area is much faster than with SDD. SDD and LDD also differ regarding pattern generation. With SDD, fractal patterns appear only in the border of the invasion front in SDD when competitive interaction with residents is included. In contrast, LDD patterns show fractality both in the spatial arrangements of patches as well as in patch borders. Moreover, values of border fractal dimension inform on the dispersal process in relation with habitat heterogeneity. The distribution of patch size is also scale‐free, showing two power laws characteristic of small and large patch sizes directly arising from the dispersal and reproductive dynamics. Ecological factors like habitat heterogeneity are relevant for dispersal, although its importance is greater for SDD, lowering the invasion velocity. Among the life history traits considered, adult mortality, the juvenile bank and mean dispersal distance are the most relevant for SDD. For LDD, habitat heterogeneity and changes in life history traits are not so relevant, causing minor changes in the values of the scale‐free parameters. Our work on short and long distance dispersal shows novel theoretical differences between SDD and LDD in invasive systems (mechanisms of pattern formation, fractal and scaling properties, relevance of different life history traits and habitat variables) that correspond closely with field examples and were not analyzed, at least in this degree of detail, by the previously existing models.     

Accounting for multi‐scale spatial autocorrelation improves performance of invasive species distribution modelling (iSDM)

Aim Analyses of species distributions are complicated by various origins of spatial autocorrelation (SAC) in biogeographical data. SAC may be particularly important for invasive species distribution models (iSDMs) because biological invasions are strongly influenced by dispersal and colonization processes that typically create highly structured distribution patterns. We examined the efficacy of using a multi‐scale framework to account for different origins of SAC, and compared non‐spatial models with models that accounted for SAC at multiple levels. Location We modelled the spatial distribution of an invasive forest pathogen, Phytophthora ramorum, in western USA. Methods We applied one conventional statistical method (generalized linear model, GLM) and one nonparametric technique (maximum entropy, Maxent) to a large dataset on P. ramorum occurrence (n = 3787) to develop four types of model that included environmental variables and that either ignored spatial context or incorporated it at a broad scale using trend surface analysis, a local scale using autocovariates, or multiple scales using spatial eigenvector mapping. We evaluated model accuracies and amounts of explained spatial structure, and examined the changes in predictive power of the environmental and spatial variables. Results Accounting for different scales of SAC significantly enhanced the predictive capability of iSDMs. Dramatic improvements were observed when fine‐scale SAC was included, suggesting that local range‐confining processes are important in P. ramorum spread. The importance of environmental variables was relatively consistent across all models, but the explanatory power decreased in spatial models for factors with strong spatial structure. While accounting for SAC reduced the amount of residual autocorrelation for GLM but not for Maxent, it still improved the performance of both approaches, supporting our hypothesis that dispersal and colonization processes are important factors to consider in distribution models of biological invasions. Main conclusions Spatial autocorrelation has become a paradigm in biogeography and ecological modelling. In addition to avoiding the violation of statistical assumptions, accounting for spatial patterns at multiple scales can enhance our understanding of dynamic processes that explain ecological mechanisms of invasion and improve the predictive performance of static iSDMs.     

洲际入侵植物生态位稳定性研究进展

人类活动引起的大规模洲际物种交换与生物入侵, 改变了当地生态系统结构与功能, 使生物多样性受到日益严重的威胁。本文通过综合分析主要国家和地区入侵植物的地理起源, 发现洲际入侵主要包括东亚—北美、东亚—南美、欧洲—南非、欧洲—北美、欧洲—东亚、北美—大洋洲等, 这些洲际入侵造成的后果往往比陆内入侵更为严重。利用物种分布模型(SDMs)预测入侵物种潜在分布范围是有效管理和提早预防生物入侵的重要依据, 但这些模型的一个关键假定是: 入侵物种的生态位在空间和时间上是保守的、稳定的。然而, 对于远离原产地种群并能快速适应新生境的洲际入侵植物来说, 生态位可能发生显著的变化。入侵种能否在入侵地保持原有的生态位, 取决于制约其生态分布的限制因素和生态过程在不同地区间是否发生变化。本文中作者总结了洲际入侵与陆内入侵的生态与进化过程的异同点, 认为这些限制物种原产地分布的因素如扩散限制、种间互作、适应性进化、生态可塑性和种群遗传特性等均可能导致入侵物种生态位的改变。建议下一步的研究应该重视: (1)对生态位属性进行多尺度的研究, 包括时间、空间、环境或系统发育等几个方面; (2)对比生态位稳定与发生偏移的物种特性, 确定什么样的入侵物种更容易改变原有的生态位; (3)进行生态位时间动态格局研究, 探讨生态位变化的倾向、历史速率和偏移程度, 以便判定生态位变化趋势。这些研究结果将会进一步提高物种分布模型的预测能力, 有助于更为准确地揭示气候变化和物种入侵对生物多样性的影响。     

Developing dynamic mechanistic species distribution models: predicting bird-mediated spread of invasive plants across northeastern North America

Species distribution models are a fundamental tool in ecology, conservation biology, and biogeography and typically identify potential species distributions using static phenomenological models. We demonstrate the importance of complementing these popular models with spatially explicit, dynamic mechanistic models that link potential and realized distributions. We develop general grid-based, pattern-oriented spread models incorporating three mechanisms--plant population growth, local dispersal, and long-distance dispersal--to predict broadscale spread patterns in heterogeneous landscapes. We use the model to examine the spread of the invasive Celastrus orbiculatus (Oriental bittersweet) by Sturnus vulgaris (European starling) across northeastern North America. We find excellent quantitative agreement with historical spread records over the last century that are critically linked to the geometry of heterogeneous landscapes and each of the explanatory mechanisms considered. Spread of bittersweet before 1960 was primarily driven by high growth rates in developed and agricultural landscapes, while subsequent spread was mediated by expansion into deciduous and coniferous forests. Large, continuous patches of coniferous forests may substantially impede invasion. The success of C. orbiculatus and its potential mutualism with S. vulgaris suggest troubling predictions for the spread of other invasive, fleshy-fruited plant species across northeastern North America.     

Stabilization through spatial pattern formation in metapopulations with long-range dispersal

Many studies of metapopulation models assume that spatially extended populations occupy a network of identical habitat patches, each coupled to its nearest neighbouring patches by density-independent dispersal. Much previous work has focused on the temporal stability of spatially homogeneous equilibrium states of the metapopulation, and one of the main predictions of such models is that the stability of equilibrium states in the local patches in the absence of migration determines the stability of spatially homogeneous equilibrium states of the whole metapopulation when migration is added. Here, we present classes of examples in which deviations from the usual assumptions lead to different predictions. In particular, heterogeneity in local habitat quality in combination with long-range dispersal can induce a stable equilibrium for the metapopulation dynamics, even when within-patch processes would produce very complex behaviour in each patch in the absence of migration. Thus, when spatially homogeneous equilibria become unstable, the system can often shift to a different, spatially inhomogeneous steady state. This new global equilibrium is characterized by a standing spatial wave of population abundances. Such standing spatial waves can also be observed in metapopulations consisting of identical habitat patches, i.e. without heterogeneity in patch quality, provided that dispersal is density dependent. Spatial pattern formation after destabilization of spatially homogeneous equilibrium states is well known in reaction–diffusion systems and has been observed in various ecological models. However, these models typically require the presence of at least two species, e.g. a predator and a prey. Our results imply that stabilization through spatial pattern formation can also occur in single-species models. However, the opposite effect of destabilization can also occur: if dispersal is short range, and if there is heterogeneity in patch quality, then the metapopulation dynamics can be chaotic despite the patches having stable equilibrium dynamics when isolated. We conclude that more general metapopulation models than those commonly studied are necessary to fully understand how spatial structure can affect spatial and temporal variation in population abundance.     

The shape of the spatial kernel and its implications for biological invasions in patchy environments

Ecological and epidemiological invasions occur in a spatial context. We investigated how these processes correlate to the distance dependence of spread or dispersal between spatial entities such as habitat patches or epidemiological units. Distance dependence is described by a spatial kernel, characterized by its shape (kurtosis) and width (variance). We also developed a novel method to analyse and generate point-pattern landscapes based on spectral representation. This involves two measures: continuity, which is related to autocorrelation and contrast, which refers to variation in patch density. We also analysed some empirical data where our results are expected to have implications, namely distributions of trees (Quercus and Ulmus) and farms in Sweden. Through a simulation study, we found that kernel shape was not important for predicting the invasion speed in randomly distributed patches. However, the shape may be essential when the distribution of patches deviates from randomness, particularly when the contrast is high. We conclude that the speed of invasions depends on the spatial context and the effect of the spatial kernel is intertwined with the spatial structure. This implies substantial demands on the empirical data, because it requires knowledge of shape and width of the spatial kernel, and spatial structure.     

The role of Allee effects in gypsy moth, <Emphasis Type="Italic">Lymantria dispar</Emphasis> (L.), invasions

Allee effects have been applied historically in efforts to understand the low-density population dynamics of rare and endangered species. Many biological invasions likewise experience the phenomenon of decreasing population growth rates at low population densities because most founding populations of introduced nonnative species occur at low densities. In range expansion of established species, the initial colonizers of habitat beyond the organism’s current range are usually at low density, and thus could be subject to Allee dynamics. There has been consistent empirical and theoretical evidence demonstrating, and in some cases quantifying, the role of Allee dynamics in the gypsy moth, Lymantria dispar (L.), invasion of North America. In this review, we examine the potential causes of the Allee effect in the gypsy moth and highlight the importance of mate-finding failure as a primary mechanism behind an Allee effect, while the degree to which generalist predators induce an Allee effect remains unclear. We then explore the role of Allee effects in the establishment and spread dynamics of the gypsy moth system, which conceptually could serve as a model system for understanding how Allee effects manifest themselves in the dynamics of biological invasions.     

Revealing historic invasion patterns and potential invasion sites for two non-native plant species

The historical spatio-temporal distribution of invasive species is rarely documented, hampering efforts to understand invasion dynamics, especially at regional scales. Reconstructing historical invasions through use of herbarium records combined with spatial trend analysis and modeling can elucidate spreading patterns and identify susceptible habitats before invasion occurs. Two perennial species were chosen to contrast historic and potential phytogeographies: Japanese knotweed (Polygonum cuspidatum), introduced intentionally across the US; and mugwort (Artemisia vulgaris), introduced largely accidentally to coastal areas. Spatial analysis revealed that early in the invasion, both species have a stochastic distribution across the contiguous US, but east of the 90(th) meridian, which approximates the Mississippi River, quickly spread to adjacent counties in subsequent decades. In contrast, in locations west of the 90(th) meridian, many populations never spread outside the founding county, probably a result of encountering unfavorable environmental conditions. Regression analysis using variables categorized as environmental or anthropogenic accounted for 24% (Japanese knotweed) and 30% (mugwort) of the variation in the current distribution of each species. Results show very few counties with high habitat suitability (>/=80%) remain un-invaded (5 for Japanese knotweed and 6 for mugwort), suggesting these perennials are reaching the limits of large-scale expansion. Despite differences in initial introduction loci and pathways, Japanese knotweed and mugwort demonstrate similar historic patterns of spread and show declining rates of regional expansion. Invasion mitigation efforts should be concentrated on areas identified as highly susceptible that border invaded regions, as both species demonstrate secondary expansion from introduction loci.