Spatially mixed crops to control the stratified dispersal of airborne fungal diseases

Intraspecific crop diversification is thought to be a possible solution to the disease susceptibility of monocultured crops. We modelled the stratified dispersal of an airborne pathogen population in order to identify the spatial patterns of cultivar mixtures that could slow epidemic spread driven by dual dispersal mechanisms acting over both short and long distances. We developed a model to simulate the propagation of a fungal disease in a 2D field, including a reaction-diffusion model for short-distance disease dispersal, and a stochastic model for long-distance dispersal. The model was fitted to data for the spatio-temporal spread of faba bean rust (caused by Uromyces viciae-fabae) through a discontinuous field. The model was used to compare the effectiveness of eight different planting patterns of cultivar mixtures against a disease spread by short-distance and stratified dispersal. Our combined modelling approach provides a reasonably good fit with the observed data for the spread of faba bean rust. Similar predictive power could be expected for the management of resource-mediated invasions by other airborne fungi. If a disease spreads by short-distance dispersal, random mixtures can be used to slow the epidemic spread, since their spatial irregularity creates a natural barrier to the progression of a smooth epidemic wave. In the context of stratified dispersal, heterogeneous patterns should be used that include a minimum distance between susceptible units, which decreases the probability of infection by long-distance spore dispersal. We provide a simple framework for modelling the stratified dispersal of disease in a diversified crop. The model suggests that the spatial arrangement of components in cultivar mixtures has to accord with the dispersal characteristics of the pathogen in order to increase the efficiency of diversification strategies in agro-ecosystems and forestry. It can be applied in low input agriculture to manage pathogen invasion by intercropping and cultivar mixtures, and to design sustainable systems of land use.     

Microgeographic genetic differentiation in a colonial ascidian (Botryllus schlosseri) population

Limited gene flow via the restricted dispersal of larvae and gametes is expected to result in the genetic differentiation of populations of clonal invertebrates on small spatial scales. However, occasional dispersal events over greater distances may generate sufficient gene flow to maintain genetic homogeneity. We applied a spatial autocorrelation approach that does not require a priori definitions of subdivision boundaries to examine genetic differentiation within a continuous population of the colonial ascidian Botryllus schlosseri (Pallas) at two allozyme and five polychromatism loci. Colonies were sampled in July 1992, on a 12 by 18 m grid superimposed on a shallow subtidal (1 to 3 m) population in the Damariscotta River estuary in Maine, USA. Low but significant levels of positive autocorrelation were detected over very small spatial scales (<5 m), with negative autocorrelation occurring on larger scales (>8 m). This pattern indicates significant genetic differentiation over distances of 8 to 21 m, and is consistent with genetic drift and inbreeding creating small scale genetic structure. Received: 18 October 1999 / Accepted: 11 July 2000     

Stepping-stone gene flow in the solitary coral Balanophyllia elegans: equilibrium and nonequilibrium at different spatial scales

Limited dispersal should result in genetic differences between populations proportional to geographic distances of separation. This association between gene flow and distance can be disrupted by (1) continuing genetic exchange among distant populations, (2) historical changes in gene flow, and (3) physical barriers or corridors to dispersal. The movements of larvae are thought to determine dispersal capability in benthic marine invertebrates. The solitary scleractinian Balanophyllia elegans Verrill possesses crawling larvae capable of only limited dispersal. Paradoxically, however, inferred levels of gene flow between pairs of localities spread over much of the 4000 km range of B. elegans exhibited a weaker relationship with geographical separation than that expected for a linear array of populations in which all genetic exchange takes place between adjacent populations. In this paper, I examined the pattern of gene flow (inferred from the frequencies of eight polymorphic allozyme loci) in B. elegans at a smaller (1 to 50 km) spatial scale to determine (1) whether gene flow at this spatial scale conformed to the expectations of the stepping-stone model, and (2) whether continuing long-distance gene flow or historical changes in gene flow were responsible for the weak relationship between gene flow and distance observed previously at the rangewide spatial scale. Between May and August 1992, I collected 75 adults from each of 18 localities along the coast of Sonoma County, California, USA. These populations of B. elegans were significantly subdivided both among localities separated by 1 to 50 km (F _LT =0.053, Se=0.0075) and among patches separated by 4 to 8 m (F PL=0.026, SE=0.0023). The observed slope and correlation (r ²=0.54) between inferred levels of gene flow and the geographic distance at the 1 to 50 km spatial scale conformed to equilibrium expectations (obtained by simulation) for a linear stepping-stone model, although those from the rangewide spatial scale did not. This implies that the mechanisms conferring patterns of inferred genetic differentiation between localities in B. elegans differ fundamentally with spatial scale. At a scale of 1 to 50 km, continuing gene flow and drift have equilibrated and the process of isolation-bydistance may facilitate local adaptive change. At a broader spatial scale, historical changes in gene flow, perhaps affected by late Pleistocene climatic fluctuations, disrupt the equilibration of gene flow and genetic drift, so that genetic differentiation may not increase continuously with separation between populations.     

Spatial autocorrelation analysis of small-scale genetic structure in a clonal soft coral with limited larval dispersal

The philopatric larval dispesal and small effective population sizes characteristic of many clonal species should promote the development of significant small-scale genetic structure within populations as a result of isolation-by-distance. We used spatial autocorrelation statistics to detect genetic structure, arising from both clonal reproduction and philopatric dispersal of sexual propagules, for five allozyme loci within populations of the soft coral Alcyonium sp. In a population on Tatoosh Island, Washington, USA, sampled in 1991/1992, we found significant positive spatial autocorrelation at all loci among individuals separated by <40 cm, reflecting the presence of significant smallscale genetic structure due to associations among clonemates. For 4 of 5 loci, however, we detected no significant spatial autocorrelation among the different clones within this population over distances of 1 to 40 m. Analysis of soft-coral populations from six additional, topographically diverse sites in the north-east Pacific also did not reveal significant spatial autocorrelation among clones at any loci. This general lack of spatial autocorrelation of genotypes among clones suggests that significant small-scale genetic structure has not arisen in populations of Alcyonium sp. as a consequence of isolation-by-distance.     

Assessing biodegradation benefits from dispersal networks

The performance of biodegradation of organic pollutants in soil often depends on abiotic conditions and the bioavailability of these pollutants to degrading bacteria. In this context, bacterial dispersal is an essential aspect. Recent studies on the potential promotion of bacterial dispersal by fungal hyphae raised the idea of specifically applying fungal networks to accelerate bacterial degradation processes in situ. Our objective is to investigate these processes and their performance via simulation modelling and address the following questions: (1) Under what abiotic conditions can dispersal networks significantly improve bacterial degradation? and (2) To what extent does the spatial configuration of the networks influence the degradation performance? To answer these questions, we developed a spatially explicit bacterial colony model, which is applied to controlled laboratory experiments with Pseudomonas putida G7 organisms as a case study. Using this model, we analyzed degradation performance in response to different environmental scenarios and showed that conditions of limited bacterial dispersal also limit degradation performance. Under such conditions, dispersal networks have the highest potential for improving the bioavailability of pollutants to bacteria. We also found that degradation performance significantly varies with the spatial configuration of the dispersal networks applied and the time horizon over which performance is assessed. Regarding future practical applications, our results suggest that (1) fungal networks may dramatically improve initially adverse conditions for biodegradation of pollutants in soil, and (2) the network's spatial structure and accessibility are decisive for the success of such tasks.     

Modelling the effect of in-stream and overland dispersal on gene flow in river networks

Modelling gene flow across natural landscapes is a current challenge of population genetics. Models are essential to make clear predictions about conditions that cause genetic differentiation or maintain connectivity between populations. River networks are a special case of landscape matrix. They represent stretches of habitat connected according to a branching pattern where dispersal is usually limited to upstream or downstream movements. Because of their peculiar topology, and the increasing concern about conservation issues in hydrosystems, there has been a recent revival of interest in modelling dispersal in river networks. Network complexity has been shown to influence global population differentiation. However, geometric characteristics are likely to interact with the way individuals move across space. Studies have focused on in-stream movements. None of the work published so far took into consideration the ability of many species to disperse overland between branches of the same network though. We predicted that the relative contribution of these two dispersal modalities (in-stream and overland) would affect the overall genetic structure. We simulated dispersal in synthetic river networks using an individual-based model. We tested the effect of dispersal modalities, i.e. the ratio of overland/in-stream dispersal, and two geometric parameters, bifurcation angle between branches and network complexity. Data revealed that if geometrical parameters affected population differentiation, dispersal parameters had the strongest effect. Interestingly, we observed a quadratic relationship between p the proportion of overland dispersers and population differentiation. We interpret this U-shape pattern as a balance between isolation by distance caused by in-stream movements at low values of p and intense migrant exchanges within the same branching unit at high values of p. Our study is the first attempt to model out-of-network movements. It clearly shows that both geometric and dispersal parameters interact. Both should be taken into consideration in order to refine predictions about dispersal and gene flow in river network.     

Effects of habitat fragmentation on the genetic structure and connectivity of the black-lipped pearl oyster Pinctada margaritifera populations in French Polynesia

Habitat destruction leading to increased fragmentation is detrimental to species by reducing population size and genetic diversity and by restraining population connectivity. However, little is known about the effects of naturally fragmented habitats on wild populations, especially when it comes to marine benthic invertebrates with long pelagic larval duration. In this framework, we investigated the connectivity and genetic diversity variation among nine wild populations of the black-lipped pearl oyster, Pinctada margaritifera, throughout French Polynesia using ten microsatellite DNA markers. Despite the naturally fragmented habitat (South Pacific oceanic islands), we found high values of genetic diversity and population admixture, indicating connectivity at small and large spatial scales within sampled sites of the Tuamotu, and between the Society and Tuamotu Archipelagos. In the meantime, habitat geomorphology increased genetic drift in populations occurring in small, closed lagoons. Significant genetic structure not correlated to geographic distance was detected mainly between closed and open lagoons. The Marquesas Islands hosted the most divergent populations, likely a result of vicariance. Our results also highlight that migration patterns among lagoons are not symmetrical. Altogether, the general pattern of gene flow, nonsymmetrical migration rates among populations, absence of isolation by distance and absence of recent extinction events found in our study strongly suggest that P. margaritifera populations of French Polynesia follow an asymmetrical island model of dispersal.     

A method for building spatial model of annual weed seed dispersal from experimental data and its application to simulating Bromus sterilis population dispersal

Spatial model of annual weed seed dispersal, in this article, was theoretically derived. According to the requirements of building the spatial model, we designed and done an indoor experiment of weed seed dispersal by wind. In the experiment, the seeds of Bromus sterilis were released at 100 cm height under different wind velocity conditions. Based on the experimental data, the spatial models of seed dispersal of the weed species were built, which were divided into three types according to the coefficient β < 0, β = 0, β > 0. The results showed that dispersal of annual weed seed in any direction obeyed an approximate Gaussian distribution; under the experimental conditions, spatial distribution type of weed seed dispersal changed with variation of wind velocity. Well-known Howard et al.'s model (Howard et al., 1991) of Bromus sterilis seed dispersal is an especial example of the model built in this article. The result of model analysis indicated that the distribution type described by Howard's model was similar to that of seed dispersal of the weed species at the height of 100 cm under the condition of lower wind velocity (about 2.18 m/s). Using CA simulation analysis we found that mean control agent applying to a cell with weed should have a decrease with an increase of wind velocity to prevent weed with the initial configuration from spreading, which implicated less herbicide needs spraying in every cell with weed on average when wind velocity increases.     

Hydrology influences population genetic structure and connectivity of the intertidal amphipod Corophium volutator in the northwest Atlantic

The mechanisms driving genetic structure in marine systems are elusive due to the difficulty of identifying temporal and spatial barriers to dispersal. By studying marine invertebrate species with limited dispersal potential, genetic structure can be directly related to physical and biological factors restricting connectivity. In the northwest Atlantic, the benthic brood-rearing amphipod Corophium volutator is distributed across basins with distinct circulation patterns and has the potential to disperse passively during its adult stage. We analyzed spatial genetic variation and migration rates across C. volutator’s North American range with sequence data for mitochondrial DNA and three novel nuclear markers using frequency and coalescent-based methods. We found low genetic differentiation within basins, but strong subdivision within the Bay of Fundy and a striking biogeographic break between the Bay of Fundy and Gulf of Maine, suggesting that genetic drift may act on populations in which connectivity is restricted due to the limitation of passive dispersal by hydrological patterns.     

Modeling species-habitat relationships with spatially autocorrelated observation data.

Spatial autocorrelation in wildlife observation data arises when extrinsic environmental processes and patterns that influence the spatial distribution of wildlife are themselves spatially structured, or when species are subject to intrinsic population processes, causing contagion or dispersion effects. Territoriality, Allee effects, dispersal limitations, and social clustering are examples of intrinsic processes. Both forms of autocorrelation can violate the assumptions of generalized linear regression models, resulting in biased estimation of model coefficients and diminished predictive performance. Such consequences may be avoided for extrinsic autocorrelation when autocorrelated environmental variables are available for use as model covariates, whereas intrinsic spatial autocorrelation requires an alternative modeling approach. The autologistic model provides an approach suited to the binary observations often obtained in wildlife surveys, but its performance has not been tested across widely varying sampling intensities or strengths of intrinsic spatial structure. Here we use simulated data to test the autologistic model under a range of sampling conditions. The autologistic model obtains better fits and substantially better predictive performance than the standard logistic regression model over the full range of sampling designs and intensities tested. We provide a simple Bayesian implementation of the autologistic model, which until now has not been achieved with standard statistical software alone. A step-by-step procedure is given for characterizing and modeling spatial autocorrelation in binary observation data, along with computer code for fitting autologistic models in WinBUGS, a freeware Bayesian analysis package. This approach avoids normal approximations to the pseudo-likelihood, in contrast to previous Bayesian applications of the autologistic model. We provide a sample application of the autologistic model, fitted to survey data for a gliding marsupial in southeastern Australia.     

Connectivity in solitary ascidians: Is a 24-h propagule duration sufficient to maintain large-scale genetic homogeneity?

Ascidians are considered to have lower dispersal potential than most other sessile marine invertebrates with planktonic propagules by virtue of a very brief propagule duration. The larvae of colonial forms remain in the water column for only a few minutes, whereas most solitary forms settle in less than 24 h. This difference in propagule duration has been used to explain why allozyme data from colonial ascidians on the Australian east coast were genetically distinct at different sampling sites, whereas a solitary species exhibited no genetic structure. Spatial homogeneity in solitary species is surprising because genetic structure of species with much higher dispersal potential can be characterised by isolation by geographic distance, suggesting that these disperse by means of a stepping-stone pattern of dispersal. I reassessed the dispersal potential of solitary ascidians using DNA sequence data from the mitochondrial cytochrome oxidase subunit 1 gene and the intron of the nuclear adenine nucleotide transporter gene of a common south-eastern Australian solitary ascidian, Pyura praeputialis, using samples that span the species’ distribution range. Congruent with earlier findings, there was no evidence for stepping-stone dispersal, but it must be conceded that these results could be strongly affected by frequent adult dispersal, particularly by means of anthropogenic vectors, as well as insufficient marker resolution.     

Social structures,genetic structures and dispersal strategies in Australian rabbit (<Emphasis Type="Italic">Oryctolagus cuniculus</Emphasis>) populations

In this study, the pattern of movement of young male and female rabbits and the genetic structures present in adult male and female populations in four habitats was examined. The level of philopatry in young animals was found to vary between 18-90% for males and 32-95% for females in different populations. It was skewed, with more males dispersing than females in some but not all populations. Analysis of allozyme data using spatial autocorrelation showed that adult females from the same social group, unlike males, were significantly related in four of the five populations studied. Changes in genetic structure and rate of dispersal were measured before and during the recovery of a population that was artificially reduced in size. There were changes in the rate and distance of dispersal with density and sex. Subadults of both sexes moved further in the first year post crash (low density) than in the following years. While the level of dispersal for females was lower than that of the males for the first 3 years, thereafter (high density) both sexes showed similar, low levels of dispersal (20%). The density at which young animals switch behaviour between dispersal and philopatry differed for males and females. The level of genetic structuring in adult females was high in the precrash population, reduced in the first year post crash and undetectable in the second year. Dispersal behaviour of rabbits both affects the genetic structure of the population and changes with conditions. Over a wide range of levels of philopatry, genetic structuring is present in the adult female , but not the male population. Consequently, though genetic structuring is present, it does not lead to inbreeding. More long-distance movements are found in low-density populations, even though vacant warrens are available near birth warrens. The distances moved decreased as density increased. Calculation of the effective population size (N_e) shows that changes in dispersal distance offset changes in density, so that N_e remains constant.     

Spatiotemporal dynamics in variable population interactions with density-dependent interaction coefficients

In this article, I present a two-patch metapopulation model with locally explicit dynamics to study the effect of spatial heterogeneity and dispersal upon population interactions with variable or conditional outcomes. These are interactions that may be either detrimental or beneficial for each species depending on the balance of the density-dependent costs and benefits involved. The local dynamics respond to density-dependent α-interaction functions that may change sign, thus yielding a diversity of possible local outcomes for the association in terms of type of interaction and in the number of stable solutions. The spatiotemporal model predicts that the fragmentation of space and dispersal between patches may cause further variation in these outcomes. First, the demographic performance of a species in the association is enhanced if migrations cause a proportional increase of individuals of its own species; being so, a victim may become a mutualist or an exploiter, an excluded species may invade, and a good competitor may overcome its own carrying capacity: the ‘enhancement effect of dispersal’; a sort of rescue effect in source-sink dynamics. The underlying mechanisms involve an interplay between density-dependent effects of dispersal per se and the relative local and global average α-interaction functions, which involve costs and benefits at both the local and regional level that may either counteract or reinforce each other; thus, localities and/or populations may change dynamically their sink or source role in the spatial dynamics. A significant insight arises herewith: in the context of variable or conditional interactions the concept of the role of a species does not make strict sense; it becomes a spatiotemporal dynamic quality. Second, regardless of which species disperses, bifurcation of equilibria may occur in those patches that receive the migrating individuals, and annihilation of equilibria in those from where migration leaves; thus, the number of equilibria increases or decreases accordingly.     

Predictability of marine nematode biodiversity

In this paper, we investigated: (1) the predictability of different aspects of biodiversity, (2) the effect of spatial autocorrelation on the predictability and (3) the environmental variables affecting the biodiversity of free-living marine nematodes on the Belgian Continental Shelf. An extensive historical database of free-living marine nematodes was employed to model different aspects of biodiversity: species richness, evenness, and taxonomic diversity. Artificial neural networks (ANNs), often considered as “black boxes”, were applied as a modeling tool. Three methods were used to reveal these “black boxes” and to identify the contributions of each environmental variable to the diversity indices. Since spatial autocorrelation is known to introduce bias in spatial analyses, Moran's I was used to test the spatial dependency of the diversity indices and the residuals of the model. The best predictions were made for evenness. Although species richness was quite accurately predicted as well, the residuals indicated a lack of performance of the model. Pure taxonomic diversity shows high spatial variability and is difficult to model. The biodiversity indices show a strong spatial dependency, opposed to the residuals of the models, indicating that the environmental variables explain the spatial variability of the diversity indices adequately. The most important environmental variables structuring evenness are clay and sand fraction, and the minimum annual total suspended matter. Species richness is also affected by the intensity of sand extraction and the amount of gravel of the sea bed.     

Male's return rate, rather than territory fidelity and breeding dispersal, explains geographic variation in song sharing in two populations of an oscine passerine (Oreothlypis celata)

Males of some oscine passerines learn and share songs of neighboring males. This process can lead to the formation of song pattern neighborhoods or microhabitat song dialects. The degree to which song sharing occurs between populations and the spatial scale over which neighboring males share songs, however, can vary widely, and interpopulation comparisons have suggested that song sharing is more common in residents than in migrants. Here, we examine two populations of the orange-crowned warbler (Oreothlypis celata) to quantify patterns of song sharing at the northern (long-distance migrant) and southern (short-distance migrant) edges of the breeding distribution and to test if return rate, territory fidelity, and breeding dispersal explain the patterns found in the two populations. The southern population (O. celata sordida breeding on Santa Catalina Island, California; 33°N) had a higher annual return rate to their territories and exhibited higher song sharing in neighborhoods than their counterparts (O. celata celata breeding in Fairbanks, Alaska; 64°N). Year-to-year patterns of territory fidelity and breeding dispersal distances were similar between populations. Our results suggest that if migratory distance generally covaries with the proportion of returning males, this could explain different levels of song sharing between the short- and long-distance migrants.     

沤肥浸渍液对3种黄瓜病害的防治作用

从１９９２ 年开始连续８ 年研究马、牛和猪厩肥沤制并浸泡提取物对黄瓜病害的防治作用．盆栽试验表明,沤肥浸渍液对黄瓜霜霉病、黄瓜枯萎病、黄瓜白粉病具有良好的防治效果,对黄瓜霜霉病的防治效果可达４６ ．５ ％６７ ．３ ％ ,对黄瓜枯萎病的防治效果可达７２ ．１ ％９２ ．５ ％ ,对黄瓜白粉病的防治效果可达７２ ．３ ％７９ ．７ ％ ．对沤肥浸渍液的防病机理的研究表明,微生物代谢产物对病原菌孢子的抑制作用、沤肥中微生物对病原菌的拮抗作用和沤肥诱导的生理生化和组织形态方面的抗病性起着重要的作用     

Increasing accuracy of dispersal kernels in grid-based population models

Dispersal kernels in grid-based population models specify the proportion, distance and direction of movements within the model landscape. Spatial errors in dispersal kernels can have large compounding effects on model accuracy. Circular Gaussian and Laplacian dispersal kernels at a range of spatial resolutions were investigated, and methods for minimizing errors caused by the discretizing process were explored. Kernels of progressively smaller sizes relative to the landscape grid size were calculated using cell-integration and cell-center methods. These kernels were convolved repeatedly, and the final distribution was compared with a reference analytical solution. For large Gaussian kernels (σ > 10 cells), the total kernel error was <10⁻¹¹ compared to analytical results. Using an invasion model that tracked the time a population took to reach a defined goal, the discrete model results were comparable to the analytical reference. With Gaussian kernels that had σ ≤ 0.12 using the cell integration method, or σ ≤ 0.22 using the cell center method, the kernel error was greater than 10%, which resulted in invasion times that were orders of magnitude different than theoretical results. A goal-seeking routine was developed to adjust the kernels to minimize overall error. With this, corrections for small kernels were found that decreased overall kernel error to <10⁻¹¹ and invasion time error to <5%.     

Predation-affected spatial pattern changes in a prey population

Predation-affected spatial pattern changes in a prey population were studied. The spatial pattern of a population of Galleria mellonella is changed by its predator, Podisus maculiventris. The pattern is affected by the frequency of attack by the predator (attack ability), the homogeneity of the attack ability within a predator population and the mobility of the predator. A mathematical model incorporating these three factors was constructed, and several computer simulations were conducted by changing the parameter values. A natural enemy population having high and homogeneous attack ability and high mobility effectively kills prey individuals.     

Modelling dispersal with diffusion and habitat selection: Analytical results for highly fragmented landscapes

Quantifying dispersal is crucial both for understanding ecological population dynamics, and for gaining insight into factors that affect the genetic structure of populations. The role of dispersal becomes pronounced in highly fragmented landscapes inhabited by spatially structured populations. We consider a landscape consisting of a set of habitat patches surrounded by unsuitable matrix, and model dispersal by assuming that the individuals follow a random walk with parameters that may be specific to the habitat type. We allow for spatial variation in patch quality, and account for edge-mediated behavior, the latter meaning that the individuals bias their movement towards the patches when close to an edge between a patch and the matrix. We employ a diffusion approximation of the random walk model to derive analytical expressions for various characteristics of the dispersal process. For example, we derive formulae for the time that an individual is expected to spend in its current patch i, and for the time that it will spend in the matrix, both conditional on the individual hitting next a given patch j before hitting any of the other patches or dying. The analytical formulae are based on the assumptions that the landscape is infinitely large, that the patches are circularly shaped, and that the patches are small compared to interpatch distances. We evaluate the effect of these assumptions by comparing the analytical results to numerical results in a real patch network that violates all of the three assumptions. We then consider a landscape that fulfills the assumptions, and show that in this case the analytical results are in a very good agreement with the numerical results. The results obtained here allow the construction of computationally efficient dispersal models that can be used as components of metapopulation models.