Emergent spatial structure and pathogen epidemics: the influence of management and stochasticity in agroecosystems

Organisms susceptible to disease, from humans to crops, inevitably have spatial geometry that influence disease dynamics. Understanding how spatial structure emerges through time in ecological systems and how that structure influences disease dynamics is of practical importance for natural and human management systems. Here we use the perennial crop, coffee, Coffea arabica, along with its pathogen, the coffee leaf rust, Hemileia vastatrix, as a model system to understand how spatial structure is created in agroecosystems and its subsequent influence on the dynamics of the system. Here, we create a simple null model of the socio-ecological process of death and stochastic replanting of coffee plants on a plot. We then use spatial networks to quantify the spatial structures and make comparisons of our stochastic null model to empirically observed spatial distributions of coffee. We then present a simple model of pathogen spread on spatial networks across a range of spatial geometries emerging from our null model and show how both local and regional management of agroecosystems interact with space and time to alter disease dynamics. Our results suggest that our null model of evolving spatial structure can capture many critical features of how the spatial arrangement of plants changes through time in coffee agroecosystems. Additionally, we find small changes in management factors that can influence the scale of pathogen transmission, such as shade tree removal, and result in a rapid transition to epidemics with lattice-like spatial arrangements but not with irregular planting geometries. The results presented here may have practical implications for farmers in Latin America who are in the process of replanting and overhauling management of their coffee farms in response to a coffee leaf rust epidemic in 2013. We suggest that shade reduction in conjunction with more lattice-like planting schemes may result in coffee being more prone to epidemic-like dynamics of the coffee leaf rust in the future.     

On the spatial spread of rabies among foxes

We present a simple model for the spatial spread of rabies among foxes and use it to quantify its progress in England if rabies were introduced. The model is based on the known ecology of fox behaviour and on the assumption that the main vector for the spread of the disease is the rabid fox. Known data and facts are used to determine real parameter values involved in the model. We calculate the speed of propagation of the epizootic front, the threshold for the existence of an epidemic, the period and distance apart of the subsequent cyclical epidemics which follow the main front, and finally we quantify a means for control of the spatial spread of the disease. By way of illustration we use the model to determine the progress of rabies up through the southern part of England if it were introduced near Southampton. Estimates for the current fox density in England were used in the simulations. These suggest that the disease would reach Manchester within about 3.5 years, moving at speeds as high as 100 km per year in the central region. The model further indicates that although it might seem that the disease had disappeared after the wave had passed it would reappear in the south of England after just over 6 years and at periodic times after that. We consider the possibility of stopping the spread of the disease by creating a rabies 'break' ahead of the front through vaccination to reduce the population to a level below the threshold for an epidemic to exist. Based on parameter values relevant to England, we estimate its minimum width to be about 15 km. The model suggests that vaccination has considerable advantages over severe culling.     

The Integrated Aerobiology Modeling System applied to the spread of soybean rust into the Ohio River valley during September 2006

Soybean rust (Phakopsora pachyrhizi) has recently invaded North America and has the potential to be the most destructive foliar disease of soybean. As part of the response to this threat, the Integrated Aerobiology Modeling System (IAMS) was constructed to forecast the aerial movement of this pathogen from subtropical to middle latitude portions of the continent. IAMS simulations have been conducted daily for the past two growing seasons and integrated with information from a nationwide observation network into a decision support system for soybean farmers. After the 2005 season, the United States Department of Agriculture reported that many millions of United States (U.S.) soybean hectares that would have been treated for soybean rust in 2005 were not due to this decision support system. In 2006, soybean rust appeared for the first time in the major U.S. soybean production region over 1000 km from known areas of inoculum production. IAMS predictions of the geographical extent and timing of disease symptom expression were well matched with subsequent observations of the disease in the field.     

Modelling the initial spread of foot-and-mouth disease through animal movements

Livestock movements in Great Britain (GB) are well recorded and are a unique record of the network of connections among livestock-holding locations. These connections can be critical for disease spread, as in the 2001 epidemic of foot-and-mouth disease (FMD) in the UK. Here, the movement data are used to construct an individual-farm-based model of the initial spread of FMD in GB and determine the susceptibility of the GB livestock industry to future outbreaks under the current legislative requirements. Transmission through movements is modelled, with additional local spread unrelated to the known movements. Simulations show that movements can result in a large nationwide epidemic, but only if cattle are heavily involved, or the epidemic occurs in late summer or early autumn. Inclusion of random local spread can considerably increase epidemic size, but has only a small impact on the spatial extent of the disease. There is a geographical bias in the epidemic size reached, with larger epidemics originating in Scotland and the north of England than elsewhere.     

Spatio-temporal patterns of ptarmigan occupancy relative to shrub cover in the Arctic

Rock and willow ptarmigan are abundant herbivores that require shrub habitats in arctic and alpine areas. Shrub expansion is likely to increase winter habitat availability for ptarmigan, which in turn influence shrub architecture and growth through browsing. Despite their ecological role in the Arctic, the distribution and movement patterns of ptarmigan are not well known, particularly in northern Alaska where shrub expansion is occurring. We used multi-season occupancy models to test whether ptarmigan occupancy varied within and among years, and the degree to which colonization and extinction probabilities were related to shrub cover and latitude. Aerial surveys were conducted from March to May in 2011 and April to May 2012 in a 21,230 km² area in northeastern Alaska. In areas with at least 30 % shrub cover, the probability of colonization by ptarmigan was >0.90, indicating that moderate to extensive patches of shrubs (typically associated with riparian areas) had a high probability of becoming occupied by ptarmigan. Occupancy increased throughout the spring in both years, providing evidence that ptarmigan migrated from southern wintering areas to breeding areas north of the Brooks Range. Occupancy was higher in the moderate snow year than the high snow year, and this was likely due to higher shrub cover in the moderate snow year. Ptarmigan distribution and migration in the Arctic are linked to expanding shrub communities on a wide geographic scale, and these relationships may be shaping ptarmigan population dynamics, as well as rates and patterns of shrub expansion.     

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.     

Aerial Dispersal and Multiple-Scale Spread of Epidemic Disease

Disease spread has traditionally been described as a traveling wave of constant velocity. However, aerially dispersed pathogens capable of long-distance dispersal often have dispersal gradients with extended tails that could result in acceleration of the epidemic front. We evaluated empirical data with a simple model of disease spread that incorporates logistic growth in time with an inverse power function for dispersal. The scale invariance of the power law dispersal function implies its applicability at any spatial scale; indeed, the model successfully described epidemics ranging over six orders of magnitude, from experimental field plots to continental-scale epidemics of both plant and animal diseases. The distance traveled by epidemic fronts approximately doubled per unit time, velocity increased linearly with distance (slope ~½), and the exponent of the inverse power law was approximately 2. We found that it also may be possible to scale epidemics to account for initial outbreak focus size and the frequency of susceptible hosts. These relationships improve understanding of the geographic spread of emerging diseases, and facilitate the development of methods for predicting and preventing epidemics of plants, animals, and humans caused by pathogens that are capable of long-distance dispersal.     

Patterns of grassland invasions by trees: insights from demographic and genetic spatial analyses

Aims Woody invasions into grasslands have increased globally due to changing land use, climate and introduced woody species, but spatial processes generating and sustaining these invasions are not well understood. To gain insight into the patterns of spread of tree populations within grasslands, and to propose a full spatial analytical toolbox for studying native and non-native woody species spread when long-term data are not available, we tested if 50 years of grassland invasion in Western Carpathians by Norway spruce (Picea abies Karst.) proceeded by one of the two traditionally competing hypotheses of species spread: (i) by frontier expansion, or (ii) by advanced groups established ahead of the population frontier. We also tested whether the pattern of invasion changed over time.Methods We analyzed the spatial demographic and genetic patterns of a Norway spruce population invading a Western Carpathian grassland using Ripley's L (t) and genetic kinship coefficients (F ij). We mapped and genotyped spruce trees across the invasion front (from the invasion leading edge to fully colonized grassland near the source population) using three demographic classes (adults, juveniles and seedlings) to approximate the temporal aspects of the invasion. We studied how the spatial patterns of invasion by individual demographic classes and their genetic kinship varied among adjacent plots established at different distances from the source population (ranging from 0 to 160 m, in 40-m distance increments).Important findings Juveniles were positively genetically related to adults on fine scales (<4 m), suggesting that adults within the grassland acted as a seed source and accelerated early invasion. However, adults did not act as nucleation centers for the formation of advanced juvenile groups. Instead, genetically unrelated juveniles formed groups independently of adults. These groups were small and separate at the leading edge but they increased in size and graded into a continuous zone near the source population. Thus, juvenile recruitment occurred as a frontier expansion near the source population and as advanced groups controlled by environmental variation at the leading edge. Unlike juveniles, seedlings were clustered on all scales across the invasion front and formed groups around adult crowns at the invasion leading edge. The bulk of seedling establishment occurred at intermediate distances from the source population, independently from the adults, suggesting that the invasion front continued to expand as a frontier, gradually coalescing with the advanced groups at the leading edge. Thus, the grassland invasion was driven by a gradual frontier expansion of the original population during the first 50 years, with advanced groups enhancing but not driving the invasion process. Frontier expansion appeared more important as a mechanism of woody species spread early in the invasion process in this study, while advanced groups may play a larger role over longer temporal scales.     

Invasion spread of Operophtera brumata in northeastern United States and hybridization with O. bruceata

We used five methods to estimate the rate of spread of the winter moth, Operophtera brumata L., a European Lepidoptera, invading the northeastern USA and occasionally hybridizing with the closely related O. bruceata. These two species utilize the same sex attractant and pheromone traps capture both species. We estimated spread based on the ratio of the two species captured in pheromone-baited traps. Population boundaries were derived from captures in a grid of traps and spread was estimated as 6.6 km/year based on displacement of population boundaries between 2005 and 2008. Radial spread rate was also estimated as 6.9 km/year from the displacement of boundaries using logistic regression of trap captures along a single east–west transect of traps deployed yearly from 2007 to 2011. We also estimated the rate of spread from the expansion of defoliation mapped during aerial surveys. Based on the displacement of defoliation boundaries from 2005 to 2008, spread rate was estimated as 6.0 km/year. Based on the year of first defoliation, spread was estimated as 4.8 km/year and regression of the square-root of the cumulative area/π versus time yielded an estimate of 4.7 km/year. All five estimates were similar, and differences reflect the nuances of the data from which they were derived. We discuss here how the occasional hybridization with O. bruceata may be either retarding or enhancing O. brumata spread.     

A spatially explicit analysis of <Emphasis Type="Italic">Paysandisia archon</Emphasis> attack on the endemic Mediterranean dwarf palm

Autochthonous plant species are heavily threatened by the increasing spread of invasive insects. The spatial distribution of invasive species’ hosts is likely to play a pivotal role in the establishment and further expansion of the invading species; more specifically, distance and density dependent (DDD) processes linked to plant spatial arrangement are crucial in determining susceptibility to attack, but they have usually been overlooked in invasive research. We take a spatially explicit approach to evaluate potential DDD processes in the interaction between Paysandisia archon, a tropical lepidopteran recently introduced in Spain, and the endemic Mediterranean dwarf palm (Chamaerops humilis) in Mallorca (Balearic Islands). Specifically, we used spatial marked point pattern analyses, which allowed testing whether DDD processes affect attack probability and intensity on three dwarf palm populations corresponding to three different invasion phases (i.e., infestation core, early expansion, and expansion front). Our approach also allowed evaluation of whether and how intrinsic palm traits (size, sex) alter the proneness to P. archon attack over a range of spatial scales. The occurrence and nature of DDD effects on C. humilis performance varied largely among localities. At the infestation core, our analyses revealed positive density dependence, i.e., reduced damage at high densities or proximity to conspecific neighbors. By contrast, the early expansion locality showed negative density dependence of C. humilis performance, whereas at the expansion front, there was no evidence of DDD effects. Larger palms were consistently more prone to P. archon attack than small ones up to scales of 50 m. We found no evidence that palm sex altered the probability of attack by P. archon. Our results highlight the importance of spatially explicit analyses for assessing invasive events and point to the need of early interventions and prioritizing management efforts on larger palms in order to guarantee the conservation of autochthonous dwarf palm populations.     

Disentangling the genetic origins of a plant pathogen during disease spread using an original molecular epidemiology approach

The advent of molecular epidemiology has greatly improved our ability to identify the population sources and track the pathogen movement. Yet the wide spatial and temporal scales usually considered are useful only to infer historical migration pathways. In this study, Bayesian genetic assignments and a landscape epidemiology approach were combined to unravel genetic origin and annual spread during a single epidemic of a plant pathogen: the poplar rust fungus Melampsora larici-populina. The study focused on a particular area-the Durance River valley-which enabled inoculum sources to be identified and channelled spread of the epidemic along a one-dimensional corridor. Spatio-temporal monitoring of disease showed that the epidemic began in the upstream part of the valley and spread out downstream. Using genetic assignment tests, individuals collected at the end of the epidemic were sorted into two genetic groups; very few hybrids were detected, although individuals from both groups coexisted locally downstream in the valley. The epidemic originated from two genetically distinct inoculum sources. Individuals of each group then dispersed southwards along the Durance River and became mixed in poplar riparian stands. These two genetic groups were found previously at a wider spatial scale and proved to result from distinct evolutionary histories on either wild or cultivated poplars. This study showed that the two groups can mix during an epidemic but do not hybridize because they then reproduce asexually. In general, the methods employed here could be useful for elucidating the genetic origin and retracing the colonization history and migration pathways of recent epidemics.     

Reconstructing the invasion history of a spreading,non-native,tropical tree through a snapshot of current distribution,sizes, and growth rates

Elucidating the invasion history of non-native species has been dependent on coarse-grain and expensive methods or long-term monitoring during which the spread may have proceeded beyond feasible control. We used the case of a relatively recent introduction and spread of the neotropical Cecropia pachystachya in Singapore to develop a method for reconstructing spatio-temporal patterns of spread through a low-cost, cross-sectional study. Size and growth rates were measured for C. pachystachya trees as well as the native Macaranga gigantea. A power-expansion exponential-decline function was a better fit than the probability density function of the log-normal distribution in describing the growth-rate to size relationship for both species. C. pachystachya trees generally grew faster (up to 5.4 ± 0.1 cm per year at 12.2 ± 0.2 cm DBH) than M. gigantea trees (up to 3.8 ± 0.2 cm per year at 11.5 ± 0.3 cm DBH). We demonstrated that the integral of the reciprocal of these growth equations provides an estimate of the age of the individuals from their size. Using the size and geographic coordinates of C. pachystachya trees from an island-wide search, we estimate that the invasion front of reproductive trees (>5 cm DBH) showed at least a 20-year lag phase from the time of initial establishment to the year 2005, before advancing exponentially at median rates between 5 and 466 m year^?1 with maximum rates of several km year^?1. The extent of occurrence expanded by nearly tenfold from 2004 to 2012. Consequently, the spatial dynamics of trees can be reproduced using ontogenetic growth functions.     

Predictive spatial dynamics and strategic planning for raccoon rabies emergence in Ohio

Rabies is an important public health concern in North America because of recent epidemics of a rabies virus variant associated with raccoons. The costs associated with surveillance, diagnostic testing, and post-exposure treatment of humans exposed to rabies have fostered coordinated efforts to control rabies spread by distributing an oral rabies vaccine to wild raccoons. Authorities have tried to contain westward expansion of the epidemic front of raccoon-associated rabies via a vaccine corridor established in counties of eastern Ohio, western Pennsylvania, and West Virginia. Although sporadic cases of rabies have been identified in Ohio since oral rabies vaccine distribution in 1998, the first evidence of a significant breach in this vaccine corridor was not detected until 2004 in Lake County, Ohio. Herein, we forecast the spatial spread of rabies in Ohio from this breach using a stochastic spatial model that was first developed for exploratory data analysis in Connecticut and next used to successfully hind-cast wave-front dynamics of rabies spread across New York. The projections, based on expansion from the Lake County breach, are strongly affected by the spread of rabies by rare, but unpredictable long-distance translocation of rabid raccoons; rabies may traverse central Ohio at a rate 2.5-fold greater than previously analyzed wildlife epidemics. Using prior estimates of the impact of local heterogeneities on wave-front propagation and of the time lag between surveillance-based detection of an initial rabies case to full-blown epidemic, specific regions within the state are identified for vaccine delivery and expanded surveillance effort.     

Anisotropic spread of hemlock woolly adelgid in the eastern United States

Simple population models predict that the spread of an invading species through a homogenous habitat should be equal in all directions, but geographic variation in the habitat that affects either reproduction or movement could result in variable rates of spread. We analyse records of the historical range expansion of the hemlock woolly adelgid (HWA) (Adelges tsugae Annand) in the eastern United States from 1951 to 2006 to document that this species has spread in an anisotropic fashion. Furthermore, the magnitude and direction of this anisotropy has varied through time. We explore the extent to which this spatial and temporal variation in spread can be explained by geographical variation in climate and by the abundance of hosts, eastern hemlock (Tsuga canadensis L.) and Carolina hemlock (Tsuga caroliniana Engelm.). We found that a significant component of the spatial anisotropy in HWA spread rate can be explained by the geographical distribution of host trees. January temperatures were negatively associated with spread rates but this may be an artifact of the association between hemlock and cold climates. The current distribution of the adelgid in eastern N. America may be approaching the extent of its potential range to the south and west determined by availability of host hemlock and to the north determined by lethal cold winter temperatures.     

Geographical Analysis of the Distribution and Spread of Human Rabies in China from 2005 to 2011

Background

Rabies is a significant public health problem in China in that it records the second highest case incidence globally. Surveillance data on canine rabies in China is lacking and human rabies notifications can be a useful indicator of areas where animal and human rabies control could be integrated. Previous spatial epidemiological studies lacked adequate spatial resolution to inform targeted rabies control decisions. We aimed to describe the spatiotemporal distribution of human rabies and model its geographical spread to provide an evidence base to inform future integrated rabies control strategies in China.

Methods

We geo-referenced a total of 17,760 human rabies cases of China from 2005 to 2011. In our spatial analyses we used Gaussian kernel density analysis, average nearest neighbor distance, Spatial Temporal Density-Based Spatial Clustering of Applications with Noise and developed a model of rabies spatiotemporal spread.

Findings

Human rabies cases increased from 2005 to 2007 and decreased during 2008 to 2011 companying change of the spatial distribution. The ANN distance among human rabies cases increased between 2005 and 2011, and the degree of clustering of human rabies cases decreased during that period. A total 480 clusters were detected by ST-DBSCAN, 89.4% clusters initiated before 2007. Most of clusters were mainly found in South of China. The number and duration of cluster decreased significantly after 2008. Areas with the highest density of human rabies cases varied spatially each year and in some areas remained with high outbreak density for several years. Though few places have recovered from human rabies, most of affected places are still suffering from the disease.

Conclusion

Human rabies in mainland China is geographically clustered and its spatial extent changed during 2005 to 2011. The results provide a scientific basis for public health authorities in China to improve human rabies control and prevention program.     

Identification and mapping in spring wheat of genetic factors controlling stem rust resistance and the study of their epistatic interactions across multiple environments

Stem rust (Puccinia graminis f. sp. tritici) is responsible for major production losses in hexaploid wheat (Triticum aestivum L.) around the world. The spread of stem rust race Ug99 and variants is a threat to worldwide wheat production and efforts are ongoing to identify and incorporate resistance. The objectives of this research were to identify quantitative trait loci (QTL) and to study their epistatic interactions for stem rust resistance in a population derived from the Canadian wheat cultivars AC Cadillac and Carberry. A doubled haploid (DH) population was developed and genotyped with DArT^® and SSR markers. The parents and DH lines were phenotyped for stem rust severity and infection response to Ug99 and variant races in 2009, 2010 and 2011 in field rust nurseries near Njoro, Kenya, and to North American races in 2011 and 2012 near Swift Current, SK, Canada. Seedling infection type to race TTKSK was assessed in a bio-containment facility in 2009 and 2012 near Morden, MB. Eight QTL for stem rust resistance and three QTL for pseudo-black chaff on nine wheat chromosomes were identified. The phenotypic variance (PV) explained by the stem rust resistance QTL ranged from 2.4 to 48.8 %. AC Cadillac contributed stem rust resistance QTL on chromosomes 2B, 3B, 5B, 6D, 7B and 7D. Carberry contributed resistance QTL on 4B and 5A. Epistatic interactions were observed between loci on 4B and 5B, 4B and 7B, 6D and 3B, 6D and 5B, and 6D and 7B. The stem rust resistance locus on 6D interacted synergistically with 5B to improve the disease resistance through both crossover and non-crossover interactions depending on the environment. Results from this study will assist in planning breeding for stem rust resistance by maximizing QTL main effects and epistatic interactions.     

Aggressiveness and Genetic Diversity of Hemileia vastatrix During an Epidemic in Colombia

Since 2008, Colombia has been experiencing an epidemic of the coffee rust Hemileia vastatrix. The altitude range of the disease has expanded, and nursery and young plants that were usually not attacked by the disease are now significantly affected. To determine whether this new epidemic has been caused by a new pathogenic isolate, the molecular diversity of the pathogen causing the epidemic in different regions of the country was assessed, using AFLP molecular markers on isolates collected from coffee fields prior and after the year 2008. We also evaluated the aggressiveness of isolates collected from diverse coffee‐producing areas and from different coffee genotypes. Isolates collected before and during the present epidemic were quite similar both genetically and with regard to their aggressiveness. Out of a total of 349 fragments amplified from 6 AFLP primer combinations, 48 (13.2%) were polymorphic and only 18 were unique among H. vastatrix isolates representative of pre‐2008 and post‐2008 epidemic populations. We conclude that the epidemic was caused by the excessive rainfall that has occurred in Colombia since 2006 and that extended to 2011 and not by the arrival of a new isolate of the pathogen or a change in virulence of the species present in the country.     

An outbreak vector-host epidemic model with spatial structure: the 2015–2016 Zika outbreak in Rio De Janeiro

Background

A deterministic model is developed for the spatial spread of an epidemic disease in a geographical setting. The disease is borne by vectors tosusceptible hosts through criss-cross dynamics. The model is focused on an outbreak that arises from a small number of infected hosts imported into a subregion of the geographical setting. The goal is to understand how spatial heterogeneity of the vector and host populations influences the dynamics of the outbreak, in both the geographical spread and the final size of the epidemic.

Methods

Partial differential equations are formulated to describe the spatial interaction of the hosts and vectors. The partial differential equations have reaction-diffusion terms to describe the criss-cross interactions of hosts and vectors. The partial differential equations of the model are analyzed and proven to be well-posed. A local basic reproduction number for the epidemic is analyzed.

Results

The epidemic outcomes of the model are correlated to the spatially dependent parameters and initial conditions of the model. The partial differential equations of the model are adapted to seasonality of the vector population, and applied to the 2015–2016 Zika seasonal outbreak in Rio de Janeiro Municipality in Brazil.

Conclusions

The results for the model simulations of the 2015–2016 Zika seasonal outbreak in Rio de Janeiro Municipality indicate that the spatial distribution and final size of the epidemic at the end of the season are strongly dependent on the location and magnitude of local outbreaks at the beginning of the season. The application of the model to the Rio de Janeiro Municipality Zika 2015–2016 outbreak is limited by incompleteness of the epidemic data and by uncertainties in the parametric assumptions of the model.

     

Life on the edge: reproductive mode and rate of invasive <Emphasis Type="Italic">Phragmites australis</Emphasis> patch expansion

The dynamics of plant invasions from initial colonization through patch expansion are driven in part by mode of reproduction, i.e., sexual (seed) and asexual (clonal fragments and expansion) means. Expansion of existing patches—both rate and mode of spread into a matrix of varying conditions—is important for predicting potential invader impacts. In this study, we used fine-scale genetic assessments and remote sensing to describe both the rate and mode of expansion for 20 Phragmites australis patches in flooded and unflooded wetland units on the Great Salt Lake, UT. We found that the majority of Phragmites patch expansion occurred via clonal spread but we also documented instances of (potentially episodic) seedling recruitment. The mode of patch expansion, inferred from patch edge genet richness, was unrelated to flooding in the wetland unit in the preceding growing season. The rate of Phragmites patch expansion varied from 0.09 to 0.35 year^?1 and was unrelated to the mode of spread. In six patches monitored across two years, monoclonal patches stayed monoclonal, whereas patches with higher genet richness had a marked increase in diversity in the second year. The findings of the present study suggest how this partially clonal species can exploit the benefits of both sexual (i.e., genetic recombination, widespread dispersal, colonization of new areas) and asexual reproduction (i.e., stability of established clones suited to local environmental conditions) to become one of the most successful wetland plant invaders. To control this species, both forms of reproduction need to be fully addressed through targeted management actions.