938 resultados para Population Dynamics Spatial Correlation


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1. We analysed time-series data from populations of red kangaroos (Macropus rufus, Desmarest) inhabiting four areas in the pastoral zone of South Australia. We formulated a set of a priori models to disentangle the relative effects of the covariates: rainfall, harvesting, intraspecific competition, and domestic herbivores, on kangaroo population-growth rate. 2. The statistical framework allowed for spatial variation in the growth-rate parameters, response to covariates, and environmental variability, as well as spatially correlated error terms due to shared environment. 3. The most parsimonious model included all covariates but no area-specific parameter values, suggesting that kangaroo densities respond in the same way to the covariates across the areas. 4. The temporal dynamics were spatially correlated, even after taking into account the potentially synchronizing effect of rainfall, harvesting and domestic herbivores. 5. Counter-intuitively, we found a positive rather than negative effect of domestic herbivore density on the population-growth rate of kangaroos. We hypothesize that this effect is caused by sheep and cattle acting as a surrogate for resource availability beyond rainfall. 6. Even though our system is well studied, we must conclude that approximating resources by surrogates such as rainfall is more difficult than previously thought. This is an important message for studies of consumer-resource systems and highlights the need to be explicit about population processes when analysing population patterns.

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The onset of measles vaccination in England and Wales in 1968 coincided with a marked drop in the temporal correlation of epidemic patterns between major cities. We analyze a variety of hypotheses for the mechanisms driving this change. Straightforward stochastic models suggest that the interaction between a lowered susceptible population (and hence increased demographic noise) and nonlinear dynamics is sufficient to cause the observed drop in correlation. The decorrelation of epidemics could potentially lessen the chance of global extinction and so inhibit attempts at measles eradication.

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Background: Variation in carrying capacity and population return rates is generally ignored in traditional studies of population dynamics. Variation is hard to study in the field because of difficulties controlling the environment in order to obtain statistical replicates, and because of the scale and expense of experimenting on populations. There may also be ethical issues. To circumvent these problems we used detailed simulations of the simultaneous behaviours of interacting animals in an accurate facsimile of a real Danish landscape. The models incorporate as much as possible of the behaviour and ecology of skylarks Alauda arvensis, voles Microtus agrestis, a ground beetle Bembidion lampros and a linyphiid spider Erigone atra. This allows us to quantify and evaluate the importance of spatial and temporal heterogeneity on the population dynamics of the four species. Results: Both spatial and temporal heterogeneity affected the relationship between population growth rate and population density in all four species. Spatial heterogeneity accounted for 23–30% of the variance in population growth rate after accounting for the effects of density, reflecting big differences in local carrying capacity associated with the landscape features important to individual species. Temporal heterogeneity accounted for 3–13% of the variance in vole, skylark and spider, but 43% in beetles. The associated temporal variation in carrying capacity would be problematic in traditional analyses of density dependence. Return rates were less than one in all species and essentially invariant in skylarks, spiders and beetles. Return rates varied over the landscape in voles, being slower where there were larger fluctuations in local population sizes. Conclusion: Our analyses estimated the traditional parameters of carrying capacities and return rates, but these are now seen as varying continuously over the landscape depending on habitat quality and the mechanisms of density dependence. The importance of our results lies in our demonstration that the effects of spatial and temporal heterogeneity must be accounted for if we are to have accurate predictive models for use in management and conservation. This is an area which until now has lacked an adequate theoretical framework and methodology.

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Noise is an intrinsic feature of population dynamics and plays a crucial role in oscillations called phase-forgetting quasicycles by converting damped into sustained oscillations. This function of noise becomes evident when considering Langevin equations whose deterministic part yields only damped oscillations. We formulate here a consistent and systematic approach to population dynamics, leading to a Fokker-Planck equation and the associate Langevin equations in accordance with this conceptual framework, founded on stochastic lattice-gas models that describe spatially structured predator-prey systems. Langevin equations in the population densities and predator-prey pair density are derived in two stages. First, a birth-and-death stochastic process in the space of prey and predator numbers and predator-prey pair number is obtained by a contraction method that reduces the degrees of freedom. Second, a van Kampen expansion in the inverse of system size is then performed to get the Fokker-Planck equation. We also study the time correlation function, the asymptotic behavior of which is used to characterize the transition from the cyclic coexistence of species to the ordinary coexistence.

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The recruitment of 0-group plaice to sandy beach nursery grounds in Galway Bay was examined, using a Riley push-net, from February to June in 2005 and 2006. Sampling was carried out every two weeks on spring tides. Three beaches were sampled, Ballyloughan, Silverstrand and Glann na Ri. Archived 0-group plaice, for Ballyloughan and Silverstrand, from 2004, were processed. Results were compared to findings from a previous study carried out in 2002 and 2003 (Allen 2004). Otolith microstructure analysis was used to determine hatching dates, larval duration, settlement dates, post-larval age and daily growth rates of 0-group plaice in April and May 2005. Results were compared to a previous study (Allen 2004). Hatching dates in Galway Bay ranged from late January to early April in 2005. No significant difference in hatching dates was observed between years or between beaches sampled. Larval duration of 0-group plaice in Galway Bay ranged from 21 to 45 days for fish sampled in April and May 2005. No significant difference was observed in larval age between beaches sampled in Galway Bay or between years in April 2003 and 2005. A significant difference was observed between larval age and years in May 2003 and 2005, however no significant difference was observed between beaches. Settlement timing was calculated using push-net data and otolith microstructure analysis. Settlement of 0-group plaice in Galway Bay generally started in early March and finished in May. Settlement patterns, calculated using otolith microstructure analysis, in 2003 and 2005, were not significantly different to one another. There was also no difference in settlement patterns between the beaches sampled. Results from the present study showed no spatial difference in the pelagic life cycle stages of fish caught in April and May 2003 and 2005.

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The economic value of flounder from shore angling around Ireland was assessed. Flounder catches from shore angling tournaments around Ireland were related to domestic and overseas shore angling expenditure in order to determine an economic value for the species. Temporal trends in flounder angling catches, and specimen (trophy) flounder reports were also investigated. Flounder was found to be the most caught shore angling species in competitions around Ireland constituting roughly one third of the shore angling competition catch although this did vary by area. The total value of flounder from shore angling tourism was estimated to be of the order of €8.4 million. No significant temporal trends in flounder angling catches and specimen reports were found. Thus there is no evidence from the current study for any decline in flounder stocks. The population dynamics of 0-group flounder during the early benthic stage was investigated at estuarine sites in Galway Bay, west of Ireland. Information was analysed from the March to June sampling period over five years (2002 to 2006). Spatial and temporal variations in settlement and population length structure were analysed between beach and river habitats and sites. Settlement of flounder began from late March to early May of each year, most commonly in April. Peak settlement was usually in April or early May. Settlement was recorded earlier than elsewhere, although most commonly was similar to the southern part of the UK and northern France. Settlement was generally later in tidal rivers than on sandy beaches. Abundance of 0-group flounder in Galway Bay did not exhibit significant inter -annual variability. 0-group flounder were observed in dense aggregations of up to 105 m'2, which were patchy in distribution. Highest densities of 0-group flounder were recorded in limnetic and oligohaline areas as compared with the lower densities in polyhaline and to a lesser extent mesohaline areas. Measurements to of salinity allowed the classification of beaches, and tidal river sections near the mouth, into a salinity based scheme for length comparisons. Beaches were classified as polyhaline,the lower section of rivers as mesohaline, and the middle and upper sections as oligohaline. Over the March to June sampling period 0-group flounder utilised different sections at different length ranges and were significantly larger in more upstream sections. During initial settlement in April, 0-group flounder of 8-10 mm (standard length, SL) were present in abundance on polyhaline sandy beaches. By about 10mm (SL), flounder were present in all polyhaline, mesohaline and (oligohaline) sections. 0-group flounder became absent or in insignificant numbers in polyhaline and mesohaline sections in a matter of weeks after first appearance. From April to June, 0-group flounder of 12-30mm (SL) were found in more upstream locations in the oligohaline sections. About one month (May or June) after initial settlement, 0-group flounder became absent from the oligohaline sections. Concurrently, flounder start to reappear in mesohaline and polyhaline areas at approximately 30mm (SL) in June. The results indicate 0-group flounder in the early benthic stage are associated with low salinity areas, but as they grow, this association diminishes. Results strongly suggest that migration of 0-group flounder between habitats takes place during the early benthic phase.

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The Triannulatus Complex of Anopheles (Nyssorhynchus) consists of at least three sibling species, namely Anopheles triannulatus s.s., Anopheles halophylus and a third undescribed member herein referred to as An. triannulatus "C". Sympatric anophelines belonging to species complexes, even though closely related, may exploit different environments such as larval habitats. In this paper we hypothesize that rainfall and seasonal flooding would distinctly influence the availability of larval habitats and consequently the seasonal population dynamics of sympatric members of the Triannulatus Complex. A reflection of this is distinct seasonal biting frequencies exhibited by three members of the Triannulatus Complex at a site in Central Brazil. Population dynamics seem to be influenced by the water level in the local rivers, although biting frequency of all three species was negatively influenced by rainfall. An. triannulatus s.s. was more abundant following the end of the rainy season, but notably 30 to 60 days after flooding. On the other hand, An. halophylus and An. triannulatus C peaked during the middle of the dry season, when water impoundments have no inflow, are somewhat reduced in size and the water becomes brackish. Differences in population dynamics were greater between An. triannulatus s.s. and An. halophylus and An. triannulatus C than between An. halophylus and An. triannulatus C. This might reflect differences in larval habitat exploitation and therefore spatial segregation among these members of the complex.

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Summary Ecotones are sensitive to change because they contain high numbers of species living at the margin of their environmental tolerance. This is equally true of tree-lines, which are determined by attitudinal or latitudinal temperature gradients. In the current context of climate change, they are expected to undergo modifications in position, tree biomass and possibly species composition. Attitudinal and latitudinal tree-lines differ mainly in the steepness of the underlying temperature gradient: distances are larger at latitudinal tree-lines, which could have an impact on the ability of tree species to migrate in response to climate change. Aside from temperature, tree-lines are also affected on a more local level by pressure from human activities. These are also changing as a consequence of modifications in our societies and may interact with the effects of climate change. Forest dynamics models are often used for climate change simulations because of their mechanistic processes. The spatially-explicit model TreeMig was used as a base to develop a model specifically tuned for the northern European and Alpine tree-line ecotones. For the latter, a module for land-use change processes was also added. The temperature response parameters for the species in the model were first calibrated by means of tree-ring data from various species and sites at both tree-lines. This improved the growth response function in the model, but also lead to the conclusion that regeneration is probably more important than growth for controlling tree-line position and species' distributions. The second step was to implement the module for abandonment of agricultural land in the Alps, based on an existing spatial statistical model. The sensitivity of its most important variables was tested and the model's performance compared to other modelling approaches. The probability that agricultural land would be abandoned was strongly influenced by the distance from the nearest forest and the slope, bath of which are proxies for cultivation costs. When applied to a case study area, the resulting model, named TreeMig-LAb, gave the most realistic results. These were consistent with observed consequences of land-abandonment such as the expansion of the existing forest and closing up of gaps. This new model was then applied in two case study areas, one in the Swiss Alps and one in Finnish Lapland, under a variety of climate change scenarios. These were based on forecasts of temperature change over the next century by the IPCC and the HadCM3 climate model (ΔT: +1.3, +3.5 and +5.6 °C) and included a post-change stabilisation period of 300 years. The results showed radical disruptions at both tree-lines. With the most conservative climate change scenario, species' distributions simply shifted, but it took several centuries reach a new equilibrium. With the more extreme scenarios, some species disappeared from our study areas (e.g. Pinus cembra in the Alps) or dwindled to very low numbers, as they ran out of land into which they could migrate. The most striking result was the lag in the response of most species, independently from the climate change scenario or tree-line type considered. Finally, a statistical model of the effect of reindeer (Rangifer tarandus) browsing on the growth of Pinus sylvestris was developed, as a first step towards implementing human impacts at the boreal tree-line. The expected effect was an indirect one, as reindeer deplete the ground lichen cover, thought to protect the trees against adverse climate conditions. The model showed a small but significant effect of browsing, but as the link with the underlying climate variables was unclear and the model was not spatial, it was not usable as such. Developing the TreeMig-LAb model allowed to: a) establish a method for deriving species' parameters for the growth equation from tree-rings, b) highlight the importance of regeneration in determining tree-line position and species' distributions and c) improve the integration of social sciences into landscape modelling. Applying the model at the Alpine and northern European tree-lines under different climate change scenarios showed that with most forecasted levels of temperature increase, tree-lines would suffer major disruptions, with shifts in distributions and potential extinction of some tree-line species. However, these responses showed strong lags, so these effects would not become apparent before decades and could take centuries to stabilise. Résumé Les écotones son sensibles au changement en raison du nombre élevé d'espèces qui y vivent à la limite de leur tolérance environnementale. Ceci s'applique également aux limites des arbres définies par les gradients de température altitudinaux et latitudinaux. Dans le contexte actuel de changement climatique, on s'attend à ce qu'elles subissent des modifications de leur position, de la biomasse des arbres et éventuellement des essences qui les composent. Les limites altitudinales et latitudinales diffèrent essentiellement au niveau de la pente des gradients de température qui les sous-tendent les distance sont plus grandes pour les limites latitudinales, ce qui pourrait avoir un impact sur la capacité des espèces à migrer en réponse au changement climatique. En sus de la température, la limite des arbres est aussi influencée à un niveau plus local par les pressions dues aux activités humaines. Celles-ci sont aussi en mutation suite aux changements dans nos sociétés et peuvent interagir avec les effets du changement climatique. Les modèles de dynamique forestière sont souvent utilisés pour simuler les effets du changement climatique, car ils sont basés sur la modélisation de processus. Le modèle spatialement explicite TreeMig a été utilisé comme base pour développer un modèle spécialement adapté pour la limite des arbres en Europe du Nord et dans les Alpes. Pour cette dernière, un module servant à simuler des changements d'utilisation du sol a également été ajouté. Tout d'abord, les paramètres de la courbe de réponse à la température pour les espèces inclues dans le modèle ont été calibrées au moyen de données dendrochronologiques pour diverses espèces et divers sites des deux écotones. Ceci a permis d'améliorer la courbe de croissance du modèle, mais a également permis de conclure que la régénération est probablement plus déterminante que la croissance en ce qui concerne la position de la limite des arbres et la distribution des espèces. La seconde étape consistait à implémenter le module d'abandon du terrain agricole dans les Alpes, basé sur un modèle statistique spatial existant. La sensibilité des variables les plus importantes du modèle a été testée et la performance de ce dernier comparée à d'autres approches de modélisation. La probabilité qu'un terrain soit abandonné était fortement influencée par la distance à la forêt la plus proche et par la pente, qui sont tous deux des substituts pour les coûts liés à la mise en culture. Lors de l'application en situation réelle, le nouveau modèle, baptisé TreeMig-LAb, a donné les résultats les plus réalistes. Ceux-ci étaient comparables aux conséquences déjà observées de l'abandon de terrains agricoles, telles que l'expansion des forêts existantes et la fermeture des clairières. Ce nouveau modèle a ensuite été mis en application dans deux zones d'étude, l'une dans les Alpes suisses et l'autre en Laponie finlandaise, avec divers scénarios de changement climatique. Ces derniers étaient basés sur les prévisions de changement de température pour le siècle prochain établies par l'IPCC et le modèle climatique HadCM3 (ΔT: +1.3, +3.5 et +5.6 °C) et comprenaient une période de stabilisation post-changement climatique de 300 ans. Les résultats ont montré des perturbations majeures dans les deux types de limites de arbres. Avec le scénario de changement climatique le moins extrême, les distributions respectives des espèces ont subi un simple glissement, mais il a fallu plusieurs siècles pour qu'elles atteignent un nouvel équilibre. Avec les autres scénarios, certaines espèces ont disparu de la zone d'étude (p. ex. Pinus cembra dans les Alpes) ou ont vu leur population diminuer parce qu'il n'y avait plus assez de terrains disponibles dans lesquels elles puissent migrer. Le résultat le plus frappant a été le temps de latence dans la réponse de la plupart des espèces, indépendamment du scénario de changement climatique utilisé ou du type de limite des arbres. Finalement, un modèle statistique de l'effet de l'abroutissement par les rennes (Rangifer tarandus) sur la croissance de Pinus sylvestris a été développé, comme première étape en vue de l'implémentation des impacts humains sur la limite boréale des arbres. L'effet attendu était indirect, puisque les rennes réduisent la couverture de lichen sur le sol, dont on attend un effet protecteur contre les rigueurs climatiques. Le modèle a mis en évidence un effet modeste mais significatif, mais étant donné que le lien avec les variables climatiques sous jacentes était peu clair et que le modèle n'était pas appliqué dans l'espace, il n'était pas utilisable tel quel. Le développement du modèle TreeMig-LAb a permis : a) d'établir une méthode pour déduire les paramètres spécifiques de l'équation de croissance ä partir de données dendrochronologiques, b) de mettre en évidence l'importance de la régénération dans la position de la limite des arbres et la distribution des espèces et c) d'améliorer l'intégration des sciences sociales dans les modèles de paysage. L'application du modèle aux limites alpines et nord-européennes des arbres sous différents scénarios de changement climatique a montré qu'avec la plupart des niveaux d'augmentation de température prévus, la limite des arbres subirait des perturbations majeures, avec des glissements d'aires de répartition et l'extinction potentielle de certaines espèces. Cependant, ces réponses ont montré des temps de latence importants, si bien que ces effets ne seraient pas visibles avant des décennies et pourraient mettre plusieurs siècles à se stabiliser.

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The control of whitefly Bemisia tabaci (Gennadius) biotype B (Hemiptera: Aleyrodidae) on okra (Abelmoschus esculentus L.) consists primarily in the use of insecticides, due to the lack of information on other mortality factors. The objective of this study was to evaluate the spatial and temporal population dynamics of the whitefly B. tabaci biotype B on two successive A. esculentus var. "Santa Cruz" plantations. Leaf chemical composition, leaf nitrogen and potassium contents, trichome density, canopy height, plant age, predators, parasitoids, total rainfall and median temperature were evaluated and their relationships with whitefly on okra were determined. Monthly number estimates of whitefly adults, nymphs (visual inspection) and eggs (magnifying lens) occurred on bottom, middle and apical parts of 30 plants/plantation (one leaf/plant). Plants senescence and natural enemies, mainly Encarsia sp., Chrysoperla spp. and Coccinellidae, were some of the factors that most contributed to whitefly reduction. The second okra plantation, 50 m apart from the first, was strongly attacked by whitefly, probably because of the insect migration from the first to the second plantation. No significant effects of the plant canopy on whitefly eggs and adults distribution were found. A higher number of whitefly nymphs was found on the medium part than on the bottom part.

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The main goal of this paper is to propose a convergent finite volume method for a reactionâeuro"diffusion system with cross-diffusion. First, we sketch an existence proof for a class of cross-diffusion systems. Then the standard two-point finite volume fluxes are used in combination with a nonlinear positivity-preserving approximation of the cross-diffusion coefficients. Existence and uniqueness of the approximate solution are addressed, and it is also shown that the scheme converges to the corresponding weak solution for the studied model. Furthermore, we provide a stability analysis to study pattern-formation phenomena, and we perform two-dimensional numerical examples which exhibit formation of nonuniform spatial patterns. From the simulations it is also found that experimental rates of convergence are slightly below second order. The convergence proof uses two ingredients of interest for various applications, namely the discrete Sobolev embedding inequalities with general boundary conditions and a space-time $L^1$ compactness argument that mimics the compactness lemma due to Kruzhkov. The proofs of these results are given in the Appendix.

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To identify the causes of population decline in migratory birds, researchers must determine the relative influence of environmental changes on population dynamics while the birds are on breeding grounds, wintering grounds, and en route between the two. This is problematic when the wintering areas of specific populations are unknown. Here, we first identified the putative wintering areas of Common House-Martin (Delichon urbicum) and Common Swift (Apus apus) populations breeding in northern Italy as those areas, within the wintering ranges of these species, where the winter Normalized Difference Vegetation Index (NDVI), which may affect winter survival, best predicted annual variation in population indices observed in the breeding grounds in 1992–2009. In these analyses, we controlled for the potentially confounding effects of rainfall in the breeding grounds during the previous year, which may affect reproductive success; the North Atlantic Oscillation Index (NAO), which may account for climatic conditions faced by birds during migration; and the linear and squared term of year, which account for nonlinear population trends. The areas thus identified ranged from Guinea to Nigeria for the Common House-Martin, and were located in southern Ghana for the Common Swift. We then regressed annual population indices on mean NDVI values in the putative wintering areas and on the other variables, and used Bayesian model averaging (BMA) and hierarchical partitioning (HP) of variance to assess their relative contribution to population dynamics. We re-ran all the analyses using NDVI values at different spatial scales, and consistently found that our population of Common House-Martin was primarily affected by spring rainfall (43%–47.7% explained variance) and NDVI (24%–26.9%), while the Common Swift population was primarily affected by the NDVI (22.7%–34.8%). Although these results must be further validated, currently they are the only hypotheses about the wintering grounds of the Italian populations of these species, as no Common House-Martin and Common Swift ringed in Italy have been recovered in their wintering ranges.

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Background: Microtine species in Fennoscandia display a distinct north-south gradient from regular cycles to stable populations. The gradient has often been attributed to changes in the interactions between microtines and their predators. Although the spatial structure of the environment is known to influence predator-prey dynamics of a wide range of species, it has scarcely been considered in relation to the Fennoscandian gradient. Furthermore, the length of microtine breeding season also displays a north-south gradient. However, little consideration has been given to its role in shaping or generating population cycles. Because these factors covary along the gradient it is difficult to distinguish their effects experimentally in the field. The distinction is here attempted using realistic agent-based modelling. Methodology/Principal Findings: By using a spatially explicit computer simulation model based on behavioural and ecological data from the field vole (Microtus agrestis), we generated a number of repeated time series of vole densities whose mean population size and amplitude were measured. Subsequently, these time series were subjected to statistical autoregressive modelling, to investigate the effects on vole population dynamics of making predators more specialised, of altering the breeding season, and increasing the level of habitat fragmentation. We found that fragmentation as well as the presence of specialist predators are necessary for the occurrence of population cycles. Habitat fragmentation and predator assembly jointly determined cycle length and amplitude. Length of vole breeding season had little impact on the oscillations. Significance: There is good agreement between our results and the experimental work from Fennoscandia, but our results allow distinction of causation that is hard to unravel in field experiments. We hope our results will help understand the reasons for cycle gradients observed in other areas. Our results clearly demonstrate the importance of landscape fragmentation for population cycling and we recommend that the degree of fragmentation be more fully considered in future analyses of vole dynamics.

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Observational evidence is scarce concerning the distribution of plant pathogen population sizes or densities as a function of time-scale or spatial scale. For wild pathosystems we can only get indirect evidence from evolutionary patterns and the consequences of biological invasions.We have little or no evidence bearing on extermination of hosts by pathogens, or successful escape of a host from a pathogen. Evidence over the last couple of centuries from crops suggest that the abundance of particular pathogens in the spectrum affecting a given host can vary hugely on decadal timescales. However, this may be an artefact of domestication and intensive cultivation. Host-pathogen dynamics can be formulated mathematically fairly easily–for example as SIR-type differential equation or difference equation models, and this has been the (successful) focus of recent work in crops. “Long-term” is then discussed in terms of the time taken to relax from a perturbation to the asymptotic state. However, both host and pathogen dynamics are driven by environmental factors as well as their mutual interactions, and both host and pathogen co-evolve, and evolve in response to external factors. We have virtually no information about the importance and natural role of higher trophic levels (hyperpathogens) and competitors, but they could also induce long-scale fluctuations in the abundance of pathogens on particular hosts. In wild pathosystems the host distribution cannot be modelled as either a uniform density or even a uniform distribution of fields (which could then be treated as individuals). Patterns of short term density-dependence and the detail of host distribution are therefore critical to long-term dynamics. Host density distributions are not usually scale-free, but are rarely uniform or clearly structured on a single scale. In a (multiply structured) metapopulation with coevolution and external disturbances it could well be the case that the time required to attain equilibrium (if it exists) based on conditions stable over a specified time-scale is longer than that time-scale. Alternatively, local equilibria may be reached fairly rapidly following perturbations but the meta-population equilibrium be attained very slowly. In either case, meta-stability on various time-scales is a more relevant than equilibrium concepts in explaining observed patterns.