Rates Of Spatial Spread Research Articles

Transient population dynamics drive the spread of invasive wild pigs and reveal impacts of management in North America

Invasion of nonindigenous species is considered one of the most urgent problems affecting native ecosystems and agricultural systems. Mechanistic models that account for short-term population dynamics can improve prediction because they incorporate differing demographic processes that link the environmental conditions of a spatial location explicitly with the invasion process. Yet short-term population dynamics are rarely accounted for in spatial models of invasive species spread.Accounting for transient (short-term) population dynamics that arise from the interaction of age structure and vital rates, we predict the stochastic population growth rate and establishment probability of wild pigs following introduction into any location in North America. Established ecological theory suggests that the rate of spatial spread is proportional to population growth rate. Using observed geographic distribution data for wild pigs we calculated geographic spread rates (watersheds/year) from 1982 to 2021. We investigated if observed spread rates increased in watersheds with higher stochastic population growth rates. Stochastic population growth rate and establishment probability of wild pigs increased with increasing initial population (propagule) size and length of establishment time. Areas along the Mississippi, Ohio, and lower portions of the Missouri river drainages had the highest probability of wild pig establishment with many regions having probabilities close to 1. Spread rates demonstrated strong spatial heterogeneity with the greatest rates of spread (5.8 watersheds/year) occurring from 2008 to 2013 prior to the establishment of a National wild pig control program in 2013. Spread rates declined 82% (0.57 watersheds/year) in the period from 2013 to 2021 compared to the period from 1982 to 2013. We found significant positive associations among stochastic population growth rate and observed geographic rates of spread. Stochastic population growth rate explained a large amount of variation (79.3–92.1%) in annual rate of watershed spread of wild pigs. Our predicted probabilities of establishment and population growth can be used to inform surveillance and control efforts to reduce the potential for establishment and spread of wild pigs.

Individual variation in dispersal and fecundity increases rates of spatial spread.

Dispersal and fecundity are two fundamental traits underlying the spread of populations. Using integral difference equation models, we examine how individual variation in these fundamental traits and the heritability of these traits influence rates of spatial spread of populations along a one-dimensional transect. Using a mixture of analytic and numerical methods, we show that individual variation in dispersal rates increases spread rates and the more heritable this variation, the greater the increase. In contrast, individual variation in lifetime fecundity only increases spread rates when some of this variation is heritable. The highest increases in spread rates occur when variation in dispersal positively co-varies with fecundity. Our results highlight the importance of estimating individual variation in dispersal rates, dispersal syndromes in which fecundity and dispersal co-vary positively and heritability of these traits to predict population rates of spatial spread.

Variation in host home range size decreases rabies vaccination effectiveness by increasing the spatial spread of rabies virus.

Animal movement influences the spatial spread of directly transmitted wildlife disease through host–host contact structure. Wildlife disease hosts vary in home range‐associated foraging and social behaviours, which may increase the spread and intensity of disease outbreaks. The consequences of variation in host home range movement and space use on wildlife disease dynamics are poorly understood, but could help to predict disease spread and determine more effective disease management strategies.We developed a spatially explicit individual‐based model to examine the effect of spatiotemporal variation in host home range size on the spatial spread rate, persistence and incidence of rabies virus (RABV) in raccoons (Procyon lotor). We tested the hypothesis that variation in home range size increases RABV spread and decreases vaccination effectiveness in host populations following pathogen invasion into a vaccination zone.We simulated raccoon demography and RABV dynamics across a range of magnitudes and variances in weekly home range size for raccoons. We examined how variable home range size influenced the relative effectiveness of three components of oral rabies vaccination (ORV) programmes targeting raccoons—timing and frequency of bait delivery, width of the ORV zone and proportion of hosts immunized.Variability in weekly home range size increased RABV spread rates by 1.2‐fold to 5.2‐fold compared to simulations that assumed a fixed home range size. More variable host home range sizes decreased relative vaccination effectiveness by 71% compared to less variable host home range sizes under conventional vaccination conditions. We found that vaccination timing was more influential for vaccination effectiveness than vaccination frequency or vaccination zone width.Our results suggest that variation in wildlife home range movement behaviour increases the spatial spread and incidence of RABV. Our vaccination results underscore the importance of prioritizing individual‐level space use and movement data collection to understand wildlife disease dynamics and plan their effective control and elimination.

Spatio-temporal trend in heat waves over India and its impact assessment on wheat crop

This study presents two aspects of heat waves over India. Firstly, we have analysed the gridded daily temperature data (1° × 1°) for six decades (1951–2015) to understand the changes in heat waves using the heat wave magnitude index daily (HWMId). Secondly, we have post-facto assessed the impact of the March 2010 heat wave on the growth and yield of wheat crop over north India. The study clearly showed the effectiveness of HWMId to capture the heat waves over India. The most-intense heat waves have significantly increased over 56% area of the country, and over the past three decades, it also started occurring in non-conventional heat wave regions of the southern peninsula and northeastern India. Among different categories of HWMId, the rate of spatial spread was highest for the very extreme category. The auto-regressive integrated moving average (ARIMA) intervention technique showed negative impact of the March 2010 extreme heat on yield of wheat over north India. The yield decreased by 4.9%, 4.1% and 3.5% over Punjab, Haryana and Uttar Pradesh, respectively, which were statistically significant (p < 0.1). Though the total production decreased, it was non-significant due to the slight increase in harvested area. Satellite-derived crop phenology parameters also captured the event. The rate of browning increased significantly over the study area. There were inter-district variations in the heat-wave impacts. The results may be used for identification of potential heat wave zones. It may also be used for devising zone-specific adaptation strategies for shielding wheat crop from such events.

Predicting the spatial dynamics of Wolbachia infections in Aedes aegypti arbovirus vector populations in heterogeneous landscapes

Abstract A promising strategy for reducing the transmission of dengue and other arboviral human diseases by Aedes aegypti mosquito vector populations involves field introductions of the endosymbiotic bacteria Wolbachia. Wolbachia infections inhibit viral transmission by the mosquito, and can spread between mosquito hosts to reach high frequencies in the vector population. Wolbachia spreads by maternal transmission, and spread dynamics can be variable and highly dependent on natural mosquito population dynamics, population structure and fitness components. We develop a mathematical model of an A. aegypti metapopulation that incorporates empirically validated relationships describing density‐dependent mosquito fitness components. We assume that density dependent relationships differ across subpopulations, and construct heterogeneous landscapes for which model‐predicted patterns of variation in mosquito abundance and demography approximate those observed in field populations. We then simulate Wolbachia release strategies similar to that used in field trials. We show that our model can produce rates of spatial spread of Wolbachia similar to those observed following field releases. We then investigate how different types of spatio‐temporal variation in mosquito habitat, as well as different fitness costs incurred by Wolbachia on the mosquito host, influence predicted spread rates. We find that fitness costs reduce spread rates more strongly when the habitat landscape varies temporally due to stochastic and seasonal processes. Synthesis and applications: Our empirically based modelling approach represents effects of environmental heterogeneity on the spatial spread of Wolbachia. The models can assist in interpreting observed spread patterns following field releases and in designing suitable release strategies for targeting spatially heterogeneous vector populations.

Accounting for heterogeneous invasion rates reveals management impacts on the spatial expansion of an invasive species

AbstractSuccess of large‐scale control programs for established invasive species is challenging to evaluate because of spatial variability in expansion rates, management techniques, and the strength of management intensity. For a well‐established invasive species in the spreading phase of invasion, a useful metric of impact is the magnitude by which control slows the rate of spatial spread. The prevention of spatial spreading likely results in substantial benefits in terms of ecosystem or economic damage that is prevented by an expanding invasive species. To understand how local management actions could impact the spatial spread of an established invasive species, we analyzed distribution and management data for feral swine across contiguous United States using occupancy analysis. We quantified changes in the rate of spatial expansion of feral swine and its relationship to local management actions. We found that after 4 yr of enhanced control, invasion probability decreased by 8% on average relative to pre‐program rates. This decrease was as high as 15% on average in states with low‐density populations of feral swine. The amount of decrease in invasion rate was attributed to removal intensity in neighboring counties and depended on the extent of neighboring counties with feral swine (spatial heterogeneity in local invasion pressure). Although we did not find a significant overall increase in the probability of elimination, increased elimination probability tended to occur in regions with low invasion pressure. Accounting for spatial heterogeneity in invasion pressure was important for quantifying management impacts (i.e., the relationship between management intensity and spatial spreading processes) because management impacts changed depending on the strength of invasion pressure from neighboring counties. Predicting reduction in spatial spread of an invasive species is an important first step in valuation of overall damage reduction for invasive species control programs by providing estimates of where a species may be, and thus which natural and agricultural resources would be affected, if the control program had not been operating. For minimizing losses from spatial expansion of an invasive species, our framework can be used for adaptive resource prioritization to areas where spatial expansion and underlying damage potential are concurrently highest.

Stability of travelling waves in a &lt;i&gt;Wolbachia&lt;/i&gt; invasion

Numerous studies have examined the growth dynamics of Wolbachia within populations and the resultant rate of spatial spread. This spread is typically characterised as a travelling wave with bistable local growth dynamics due to a strong Allee effect generated from cytoplasmic incompatibility. While this rate of spread has been calculated from numerical solutions of reaction-diffusion models, none have examined the spectral stability of such travelling wave solutions. In this study we analyse the stability of a travelling wave solution generated by the reaction-diffusion model of Chan & Kim [ 4 ] by computing the essential and point spectrum of the linearised operator arising in the model. The point spectrum is computed via an Evans function using the compound matrix method, whereby we find that it has no roots with positive real part. Moreover, the essential spectrum lies strictly in the left half plane. Thus, we find that the travelling wave solution found by Chan & Kim [ 4 ] corresponding to competition between Wolbachia-infected and -uninfected mosquitoes is linearly stable. We employ a dimension counting argument to suggest that, under realistic conditions, the wavespeed corresponding to such a solution is unique.

Predicting spatial spread of rabies in skunk populations using surveillance data reported by the public

BackgroundPrevention and control of wildlife disease invasions relies on the ability to predict spatio-temporal dynamics and understand the role of factors driving spread rates, such as seasonality and transmission distance. Passive disease surveillance (i.e., case reports by public) is a common method of monitoring emergence of wildlife diseases, but can be challenging to interpret due to spatial biases and limitations in data quantity and quality.Methodology/Principal findingsWe obtained passive rabies surveillance data from dead striped skunks (Mephitis mephitis) in an epizootic in northern Colorado, USA. We developed a dynamic patch-occupancy model which predicts spatio-temporal spreading while accounting for heterogeneous sampling. We estimated the distance travelled per transmission event, direction of invasion, rate of spatial spread, and effects of infection density and season. We also estimated mean transmission distance and rates of spatial spread using a phylogeographic approach on a subsample of viral sequences from the same epizootic. Both the occupancy and phylogeographic approaches predicted similar rates of spatio-temporal spread. Estimated mean transmission distances were 2.3 km (95% Highest Posterior Density (HPD95): 0.02, 11.9; phylogeographic) and 3.9 km (95% credible intervals (CI95): 1.4, 11.3; occupancy). Estimated rates of spatial spread in km/year were: 29.8 (HPD95: 20.8, 39.8; phylogeographic, branch velocity, homogenous model), 22.6 (HPD95: 15.3, 29.7; phylogeographic, diffusion rate, homogenous model) and 21.1 (CI95: 16.7, 25.5; occupancy). Initial colonization probability was twice as high in spring relative to fall.Conclusions/SignificanceSkunk-to-skunk transmission was primarily local (< 4 km) suggesting that if interventions were needed, they could be applied at the wave front. Slower viral invasions of skunk rabies in western USA compared to a similar epizootic in raccoons in the eastern USA implies host species or landscape factors underlie the dynamics of rabies invasions. Our framework provides a straightforward method for estimating rates of spatial spread of wildlife diseases.

Deploying dengue-suppressing Wolbachia : Robust models predict slow but effective spatial spread in Aedes aegypti

A novel strategy for controlling the spread of arboviral diseases such as dengue, Zika and chikungunya is to transform mosquito populations with virus-suppressing Wolbachia. In general, Wolbachia transinfected into mosquitoes induce fitness costs through lower viability or fecundity. These maternally inherited bacteria also produce a frequency-dependent advantage for infected females by inducing cytoplasmic incompatibility (CI), which kills the embryos produced by uninfected females mated to infected males. These competing effects, a frequency-dependent advantage and frequency-independent costs, produce bistable Wolbachia frequency dynamics. Above a threshold frequency, denoted pˆ, CI drives fitness-decreasing Wolbachia transinfections through local populations; but below pˆ, infection frequencies tend to decline to zero. If pˆ is not too high, CI also drives spatial spread once infections become established over sufficiently large areas. We illustrate how simple models provide testable predictions concerning the spatial and temporal dynamics of Wolbachia introductions, focusing on rate of spatial spread, the shape of spreading waves, and the conditions for initiating spread from local introductions. First, we consider the robustness of diffusion-based predictions to incorporating two important features of wMel-Aedes aegypti biology that may be inconsistent with the diffusion approximations, namely fast local dynamics induced by complete CI (i.e., all embryos produced from incompatible crosses die) and long-tailed, non-Gaussian dispersal. With complete CI, our numerical analyses show that long-tailed dispersal changes wave-width predictions only slightly; but it can significantly reduce wave speed relative to the diffusion prediction; it also allows smaller local introductions to initiate spatial spread. Second, we use approximations for pˆ and dispersal distances to predict the outcome of 2013 releases of wMel-infected Aedes aegypti in Cairns, Australia, Third, we describe new data from Ae. aegypti populations near Cairns, Australia that demonstrate long-distance dispersal and provide an approximate lower bound on pˆ for wMel in northeastern Australia. Finally, we apply our analyses to produce operational guidelines for efficient transformation of vector populations over large areas. We demonstrate that even very slow spatial spread, on the order of 10–20 m/month (as predicted), can produce area-wide population transformation within a few years following initial releases covering about 20–30% of the target area.

Host and pathogen ecology drive the seasonal dynamics of a fungal disease, white-nose syndrome.

Seasonal patterns in pathogen transmission can influence the impact of disease on populations and the speed of spatial spread. Increases in host contact rates or births drive seasonal epidemics in some systems, but other factors may occasionally override these influences. White-nose syndrome, caused by the emerging fungal pathogen Pseudogymnoascus destructans, is spreading across North America and threatens several bat species with extinction. We examined patterns and drivers of seasonal transmission of P. destructans by measuring infection prevalence and pathogen loads in six bat species at 30 sites across the eastern United States. Bats became transiently infected in autumn, and transmission spiked in early winter when bats began hibernating. Nearly all bats in six species became infected by late winter when infection intensity peaked. In summer, despite high contact rates and a birth pulse, most bats cleared infections and prevalence dropped to zero. These data suggest the dominant driver of seasonal transmission dynamics was a change in host physiology, specifically hibernation. Our study is the first, to the best of our knowledge, to describe the seasonality of transmission in this emerging wildlife disease. The timing of infection and fungal growth resulted in maximal population impacts, but only moderate rates of spatial spread.

Allee effects and population spread in patchy landscapes

Invasion of alien species is one of the major threats for natural community structures, potentially leading to high economic and environmental costs. In this work, we study through a reaction–diffusion model the dynamics of an invasion in a heterogeneous environment and in the presence of a strong Allee effect. We model space as an infinite landscape consisting of periodically alternating favourable and unfavourable patches. In addition, we consider that at the interface between patch types individuals may show preference for more favourable regions. Using homogenization techniques and a classical result for spread with Allee effect in homogeneous landscapes, we derive approximate expressions for the spread speed. When compared with numerical simulations, these expressions prove to be very accurate even beyond the expected small-scale heterogeneity limit of homogenization. We demonstrate how rates of spatial spread depend on demographic and movement parameters as well as on the landscape properties.

Quantifying Dispersal of European Culicoides (Diptera: Ceratopogonidae) Vectors between Farms Using a Novel Mark-Release-Recapture Technique

Studying the dispersal of small flying insects such as Culicoides constitutes a great challenge due to huge population sizes and lack of a method to efficiently mark and objectively detect many specimens at a time. We here describe a novel mark-release-recapture method for Culicoides in the field using fluorescein isothiocyanate (FITC) as marking agent without anaesthesia. Using a plate scanner, this detection technique can be used to analyse thousands of individual Culicoides specimens per day at a reasonable cost. We marked and released an estimated 853 specimens of the Pulicaris group and 607 specimens of the Obsoletus group on a cattle farm in Denmark. An estimated 9,090 (8,918–9,260) Obsoletus group specimens and 14,272 (14,194–14,448) Pulicaris group specimens were captured in the surroundings and subsequently analysed. Two (0.3%) Obsoletus group specimens and 28 (4.6%) Pulicaris group specimens were recaptured. The two recaptured Obsoletus group specimens were caught at the release point on the night following release. Eight (29%) of the recaptured Pulicaris group specimens were caught at a pig farm 1,750 m upwind from the release point. Five of these were recaptured on the night following release and the three other were recaptured on the second night after release. This is the first time that movement of Culicoides vectors between farms in Europe has been directly quantified. The findings suggest an extensive and rapid exchange of disease vectors between farms. Rapid movement of vectors between neighboring farms may explain the the high rate of spatial spread of Schmallenberg and bluetongue virus (BTV) in northern Europe.

Prey‐processing by avian predators enhances virus transmission in the gypsy moth

The Lymantria dispar nucleopolyhedrovirus (LdNPV) is one of the most important regulators of gypsy moth populations, but some aspects of its transmission remain poorly understood, particularly its high rate of spatial spread and ability to persist in low‐density populations. We tested the role of predatory birds in the transmission of this virus using experimental gypsy moth populations in an aviary. Predatory birds captured virus‐infected caterpillars and facilitated viral dispersal via two processes: 1) by ingesting infected caterpillars and passing viral occlusion bodies (OBs) through their guts, and 2) by scattering OBs during predator‐specific processing behaviors, a mechanism documented here for the first time. The relative importance of both pathways differed by predator species. After eating virus‐infected gypsy moth larvae, red‐eyed vireos and black‐capped chickadees passed more gypsy moth nucleopolyhedrovirus in feces than did gray catbirds. During prey‐processing, the repetitive beating of caterpillars by red‐eyed vireos, a behavior that was rarely utilized by chickadees and catbirds, resulted in the scattering of infectious virus. Due to the combination of efficient gut passage and virus spread from prey beating, higher rates of transmission occurred in experimental gypsy moth populations exposed to red‐eyed vireos than those exposed to catbirds or chickadees. Our results show that effective virus transmission was achieved when virus was vectored by predatory birds through a combination of both behavioral and physiological traits.

Spatiotemporal Spread of Cucurbit Downy Mildew in the Eastern United States

The dynamics of cucurbit downy mildew, caused by Pseudoperonospora cubensis, in the eastern United States in 2008 and 2009 were investigated based on disease records collected in 24 states as part of the Cucurbit downy mildew ipmPIPE monitoring program. The mean season-long rate of temporal disease progress across the 2 years was 1.4 new cases per day. Although cucurbit downy mildew was detected in mid-February and early March in southern Florida, the disease progressed slowly during the spring and early summer and did not enter its exponential phase until mid-June. The median nearest-neighbor distance of spread of new disease cases was ≈110 km in both years, with ≈15% of the distances being >240 km. Considering disease epidemics on all cucurbits, the epidemic expanded at a rate of 9.2 and 10.5 km per day in 2008 and 2009, respectively. These rates of spatial spread are at the lower range of those reported for the annual spread of tobacco blue mold in the southeastern United States, a disease that is also aerially dispersed over long distances. These results suggest that regional spread of cucurbit downy mildew may be limited by opportunities for establishment in the first half of the year, when fewer cucurbit hosts are available for infection. The O-ring statistic was used to determine the spatial pattern of cucurbit downy mildew outbreaks using complete spatial randomness as the null model for hypothesis testing. Disease outbreaks in both years were spatially aggregated and the extent of spatial dependence was up to 1,000 km. Results from the spatial analysis suggests that disease outbreaks in the Great Lakes and mid-Atlantic regions may be due to the spread of P. cubensis sporangia from outbreaks of the disease near the Georgia/South Carolina/North Carolina border rather than from overwintering sites in southern Florida. Space-time point pattern analysis indicated strong (P < 0.001) evidence for a space-time interaction and a space-time risk window of ≈3 to 5 months after first disease outbreak and 300 to 600 km was detected in both years. Results of this study support the hypothesis that infection of cucurbits by P. cubensis appears to be an outcome of a contagion process, and the relative large space-time window suggests that factors occurring on a large spatial scale (≈1,000 km) facilitate the spread of cucurbit downy mildew in the eastern United States.

Hierarchical modeling of an invasive spread: the Eurasian Collared-Dove Streptopelia decaocto in the United States

Invasive species are regularly claimed as the second threat to biodiversity. To apply a relevant response to the potential consequences associated with invasions (e.g., emphasize management efforts to prevent new colonization or to eradicate the species in places where it has already settled), it is essential to understand invasion mechanisms and dynamics. Quantifying and understanding what influences rates of spatial spread is a key research area for invasion theory. In this paper, we develop a model to account for occupancy dynamics of an invasive species. Our model extends existing models to accommodate several elements of invasive processes; we chose the framework of hierarchical modeling to assess site occupancy status during an invasion. First, we explicitly accounted for spatial structure and how distance among sites and position relative to one another affect the invasion spread. In particular, we accounted for the possibility of directional propagation and provided a way of estimating the direction of this possible spread. Second, we considered the influence of local density on site occupancy. Third, we decided to split the colonization process into two subprocesses, initial colonization and recolonization, which may be ground-breaking because these subprocesses may exhibit different relationships with environmental variations (such as density variation) or colonization history (e.g., initial colonization might facilitate further colonization events). Finally, our model incorporates imperfection in detection, which might be a source of substantial bias in estimating population parameters. We focused on the case of the Eurasian Collared-Dove (Streptopelia decaocto) and its invasion of the United States since its introduction in the early 1980s, using data from the North American BBS (Breeding Bird Survey). The Eurasian Collared-Dove is one of the most successful invasive species, at least among terrestrial vertebrates. Our model provided estimation of the spread direction consistent with empirical observations. Site persistence probability exhibits a quadratic response to density. We also succeeded at detecting differences in the relationship between density and initial colonization vs. recolonization probabilities. We provide a map of sites that may be colonized in the future as an example of possible practical application of our work.

Efficient Simulation of the Spatial Transmission Dynamics of Influenza

Early data from the 2009 H1N1 pandemic (H1N1pdm) suggest that previous studies over-estimated the within-country rate of spatial spread of pandemic influenza. As large spatially resolved data sets are constructed, the need for efficient simulation code with which to investigate the spatial patterns of the pandemic becomes clear. Here, we present a significant improvement to the efficiency of an individual-based stochastic disease simulation framework commonly used in multiple previous studies. We quantify the efficiency of the revised algorithm and present an alternative parameterization of the model in terms of the basic reproductive number. We apply the model to the population of Taiwan and demonstrate how the location of the initial seed can influence spatial incidence profiles and the overall spread of the epidemic. Differences in incidence are driven by the relative connectivity of alternate seed locations. The ability to perform efficient simulation allows us to run a batch of simulations and take account of their average in real time. The averaged data are stable and can be used to differentiate spreading patterns that are not readily seen by only conducting a few runs.

Invasion speeds for structured populations in fluctuating environments

We live in a time where climate models predict future increases in environmental variability and biological invasions are becoming increasingly frequent. A key to developing effective responses to biological invasions in increasingly variable environments will be estimates of their rates of spatial spread and the associated uncertainty of these estimates. Using stochastic, stage-structured, integro-difference equation models, we show analytically that invasion speeds are asymptotically normally distributed with a variance that decreases in time. We apply our methods to a simple juvenile-adult model with stochastic variation in reproduction and an illustrative example with published data for the perennial herb, \emph{Calathea ovandensis}. These examples buttressed by additional analysis reveal that increased variability in vital rates simultaneously slow down invasions yet generate greater uncertainty about rates of spatial spread. Moreover, while temporal autocorrelations in vital rates inflate variability in invasion speeds, the effect of these autocorrelations on the average invasion speed can be positive or negative depending on life history traits and how well vital rates ``remember'' the past.

The effect of habitat on the range expansion of a native and an introduced bird species

Aim Range expansion across a heterogeneous landscape may depend on the habitat selected and used by the expanding species. If habitat selection influences range expansion then localities colonized by a species should contain a greater proportion of favoured habitat (and less non-habitat) than other nearby localities not colonized. White-winged doves (Zenaida asiatica) and Eurasian collared doves (Streptopelia decaocto) are two bird species that provide an excellent opportunity to test this hypothesis, because the geographic ranges of both species have been expanding in North America for more than two decades. Location Continental USA. Methods We used distribution data from the North American Breeding Bird Survey to test whether the landscapes occupied by each species contained a greater proportion of favoured habitat (urban land, grassland/pasture, shrub land and cropland) and a lower proportion of non-habitat (forest land) than landscapes where doves were not found. We tested each species separately in each of three broad expansion areas, namely East, Central and West. We also compared rates of spatial spread between expansion areas and between the two species. Results As predicted, both species tended to occupy landscapes with greater proportions of urban land, shrub land and cropland but with less forest land compared with landscapes without doves, in all three expansion areas. Contrary to prediction, occupied landscapes tended to have slightly less grassland/pasture than unoccupied landscapes. Rates of spread differed between the two species and among expansion areas. Main conclusions Range expansion and the extent to which a species fills or saturates its range are influenced by the habitat ecology of the expanding species. Species colonize localities based on the availability of suitable habitat. However, the role of habitat in a species’ range expansion does depend somewhat on the greater geographical setting. Over large regional and geographical scales, range expansion (rate of spread and saturation) may proceed unevenly, suggesting that range expansion is a very dynamic and context-specific process.

Contributions of demography and dispersal parameters to the spatial spread of a stage‐structured insect invasion

Stage-structured models that integrate demography and dispersal can be used to identify points in the life cycle with large effects on rates of population spatial spread, information that is vital in the development of containment strategies for invasive species. Current challenges in the application of these tools include: (1) accounting for large uncertainty in model parameters, which may violate assumptions of "local" perturbation metrics such as sensitivities and elasticities, and (2) forecasting not only asymptotic rates of spatial spread, as is usually done, but also transient spatial dynamics in the early stages of invasion. We developed an invasion model for the Diaprepes root weevil (DRW; Diaprepes abbreviatus [Coleoptera: Curculionidae]), a generalist herbivore that has invaded citrus-growing regions of the United States. We synthesized data on DRW demography and dispersal and generated predictions for asymptotic and transient peak invasion speeds, accounting for parameter uncertainty. We quantified the contributions of each parameter toward invasion speed using a "global" perturbation analysis, and we contrasted parameter contributions during the transient and asymptotic phases. We found that the asymptotic invasion speed was 0.02-0.028 km/week, although the transient peak invasion speed (0.03-0.045 km/week) was significantly greater. Both asymptotic and transient invasions speeds were most responsive to weevil dispersal distances. However, demographic parameters that had large effects on asymptotic speed (e.g., survival of early-instar larvae) had little effect on transient speed. Comparison of the global analysis with lower-level elasticities indicated that local perturbation analysis would have generated unreliable predictions for the responsiveness of invasion speed to underlying parameters. Observed range expansion in southern Florida (1992-2006) was significantly lower than the invasion speed predicted by the model. Possible causes of this mismatch include overestimation of dispersal distances, demographic rates, and spatiotemporal variation in parameter values. This study demonstrates that, when parameter uncertainty is large, as is often the case, global perturbation analyses are needed to identify which points in the life cycle should be targets of management. Our results also suggest that effective strategies for reducing spread during the asymptotic phase may have little effect during the transient phase.

Radiocarbon dates as data: quantitative strategies for estimating colonization front speeds and event densities

Archaeological analysis of large-scale prehistoric population history requires us to estimate rates of spatial spread during dispersals, and rates and magnitudes of temporal contraction during crashes. Using OxCal’s MCMC sampling routine, I introduce and demonstrate a simple and easily implemented method of estimating front speeds that takes due account of the uncertainty in the archaeological data (in both dates and distances), and argue that this method is more appropriate than those most often used in front speed estimation at present. I also propose a simple and easily implemented method of estimating event densities as a demographic proxy, as an alternative to summed calibrated probability distributions. I argue that this alternative is a significantly better technique, and show that its use also enables us to identify individual archaeological dates that are exerting particularly strong influence on the results, so that we can efficiently allocate our attention when assessing the possible effects of exogenous sampling uncertainty. To illustrate these methods I re-analyse two published datasets relating to the early Paleoindian colonization of North America. My results with the new technique indicate that even with a very noisy dataset, there was clear evidence in the framework of the INTCAL04 calibration curve for a drastic reduction in archaeological event densities following the Younger Dryas onset, followed by a prolonged period of reduced human activity, and a possible renewed phase of rapid growth after the Younger Dryas termination and onset of the Holocene. However, the revised estimate of the Younger Dryas marine reservoir offset in the INTCAL09 calibration curve for ∼12,550–12,900 cal BP changes the picture significantly, by flattening the peak in Clovis-age events and pushing it forward in time into the early Younger Dryas itself.