Migration paths saturations in meta-epidemic systems

In this paper we consider a simple two-patch model in which a population affected by a disease can freely move. We assume that the capacity of the interconnected paths is limited, and thereby influencing the migration rates. Possible habitat disruptions due to human activities or natural events are accounted for. The demographic assumptions prevent the ecosystem to be wiped out, and the disease remains endemic in both populated patches at a stable equilibrium, but possibly also with an oscillatory behavior in the case of unidirectional migrations. Interestingly, if infected cannot migrate, it is possible that one patch becomes disease-free. This fact could be exploited to keep disease-free at least part of the population

Reduction of a metapopulation genetic model to an effective one island model

We explore a model of metapopulation genetics which is based on a more ecologically motivated approach than is frequently used in population genetics. The size of the population is regulated by competition between individuals, rather than by artificially imposing a fixed population size. The increased complexity of the model is managed by employing techniques often used in the physical sciences, namely exploiting time-scale separation to eliminate fast variables and then constructing an effective model from the slow modes. Remarkably, an initial model with 2$\mathcal{D}$ variables, where $\mathcal{D}$ is the number of islands in the metapopulation, can be reduced to a model with a single variable. We analyze this effective model and show that the predictions for the probability of fixation of the alleles and the mean time to fixation agree well with those found from numerical simulations of the original model.Comment: 16 pages, 4 figures. Supplementary material: 22 pages, 3 figure

Scaling up the effects of inbreeding depression from individuals to metapopulations

Abstract Inbreeding is common in nature, and many laboratory studies have documented that inbreeding depression can reduce the fitness of individuals. Demonstrating the consequences of inbreeding depression on the growth and persistence of populations is more challenging because populations are often regulated by density- or frequency-dependent selection and influenced by demographic and environmental stochasticity. A few empirical studies have shown that inbreeding depression can increase extinction risk of local populations. The importance of inbreeding depression at the metapopulation level has been conjectured based on population-level studies but has not been evaluated. We quantified the impact of inbreeding depression affecting the fitness of individuals on metapopulation persistence in heterogeneous habitat networks of different sizes and habitat configuration in a context of natural butterfly metapopulations. We developed a spatial individual-based simulation model of metapopulations with explicit genetics. We used Approximate Bayesian Computation to fit the model to extensive demographic, genetic, and life-history data available for the well-studied Glanville fritillary butterfly (Melitaea cinxia) metapopulations in the Åland islands in SW Finland. We compared 18 semi-independent habitat networks differing in size and fragmentation. The results show that inbreeding is more frequent in small habitat networks, and consequently, inbreeding depression elevates extinction risks in small metapopulations. Metapopulation persistence and neutral genetic diversity maintained in the metapopulations increase with the total habitat amount in and mean patch size of habitat networks. Dispersal and mating behavior interact with landscape structure to determine how likely it is to encounter kin while looking for mates. Inbreeding depression can decrease the viability of small metapopulations even when they are strongly influenced by stochastic extinction-colonization dynamics and density-dependent selection. The findings from this study support that genetic factors, in addition to demographic factors, can contribute to extinctions of small local populations and also of metapopulations. This article is protected by copyright. All rights reserved.Peer reviewe

Variation in metapopulation dynamics of a wetland mammal: The effect of hydrology.

Key factors affecting metapopulation dynamics of animals include patch size, isolation, and patch quality. For wetland-associated species, hydrology can affect patch availability, connectivity, and potentially habitat quality; and therefore drive metapopulation dynamics. Wetlands occurring on natural river floodplains typically have more dynamic hydrology than anthropogenic wetlands. Our overall objective was to assess the multiyear spatial and temporal variation in occupancy and turnover rates of a semi-aquatic small mammal at two hydrologically distinct wetland complexes. We live-trapped marsh rice rats (Oryzomys palustris) for 3 yr and \u3e50 000 trap nights at nine wetland patches on the Mississippi River floodplain and 14 patches at a reclaimed surface mine in southern Illinois. We used dynamic occupancy modeling to estimate initial occupancy, detection, colonization, and extinction rates at each complex. Catch per unit effort (rice rats captured/1000 trap nights) was markedly higher at the floodplain site (28.1) than the mining site (8.1). We found no evidence that temperature, rainfall, or trapping effort affected detection probability. Probability of initial occupancy was similar between sites and positively related to patch size. Patch colonization probability at both sites was related negatively to total rainfall 3 weeks prior to trapping, and varied across years differently at each site. We found interacting effects of site and rainfall on extinction probability: extinction increased with total rainfall 3 months prior to trapping but markedly more at the floodplain site than at the mining site. These site-specific patterns of colonization and extinction are consistent with the rice rat metapopulation in the floodplain exhibiting a habitat-tracking dynamic (occupancy dynamics driven by fluctuating quality), whereas the mineland complex behaved more as a classic metapopulation (stochastic colonization & extinction). Our study supports previous work demonstrating metapopulation dynamics in wetland systems being driven by changes in patch quality (via hydrology) rather than solely area and isolation

Predation effects on mean time to extinction under demographic stochasticity

Methods for predicting the probability and timing of a species' extinction are typically based on a combination of theoretical models and empirical data, and focus on single species population dynamics. Of course, species also interact with each other, forming more or less complex networks of interactions. Models to assess extinction risk often lack explicit incorporation of these interspecific interactions. We study a birth and death process in which the death rate includes an effect from predation. This predation rate is included via a general nonlinear expression for the functional response of predation to prey density. We investigate the effects of the foraging parameters (e.g. attack rate and handling time) on the mean time to extinction. Mean time to extinction varies by orders of magnitude when we alter the foraging parameters, even when we exclude the effects of these parameters on the equilibrium population size. In particular we observe an exponential dependence of the mean time to extinction on handling time. These findings clearly show that accounting for the nature of interspecific interactions is likely to be critically important when estimating extinction risk.Comment: 11 pages, 4 figures; Typos removed. For further discussion about the paper go to http://purl.org/net/extinctio

Globally coupled chaotic maps and demographic stochasticity

The affect of demographic stochasticity of a system of globally coupled chaotic maps is considered. A two-step model is studied, where the intra-patch chaotic dynamics is followed by a migration step that coupled all patches; the equilibrium number of agents on each site, $N$, controls the strength of the discreteness-induced fluctuations. For small $N$ (large fluctuations) a period-doubling cascade appears as the coupling (migration) increases. As $N$ grows an extremely slow dynamic emerges, leading to a flow along a one-dimensional family of almost period 2 solutions. This manifold become a true solutions in the deterministic limit. The degeneracy between different attractors that characterizes the clustering phase of the deterministic system is thus the $N \to \infty$ limit of the slow dynamics manifold

Hemangioma in a pulmonary hilar lymph node: Case report

<p>Abstract</p> <p>Background</p> <p>Different types of vascular proliferation may occur in lymph nodes, but hemangiomas in lymph nodes are extremely rare.</p> <p>Case Presentation</p> <p>A 73-year-old man was found to have a 15-mm nodular shadow in the left lung on computed tomography, and bronchoscopic brush cytology yielded a diagnosis of squamous cell carcinoma. Chest computed tomography showed no evidence of hilar or mediastinal lymphadenopathy. Left lower lobectomy with hilar and mediastinal lymph node dissection was performed. Postoperative histopathological examination revealed squamous cell carcinoma and no lymph node metastasis. On the other hand, a lobar bronchial lymph node presented a small lesion showing the dense proliferation of capillary blood vessels with elastic change. Immunohistochemically, the lesion was positive for factor VIII and CD34, leading to a diagnosis of primary hemangioma of the lymph node.</p> <p>Conclusion</p> <p>To our knowledge, this is the first case reported in the literature of hemangioma in a pulmonary hilar lymph node. Intranodal hemangioma needs to be differentiated from malignant vascular tumors.</p

Incorporating the geometry of dispersal and migration to understand spatial patterns of species distributions

Dispersal and migration can be important drivers of species distributions. Because the paths followed by individuals of many species are curvilinear, spatial statistical models based on rectilinear coordinates systems would fail to predict population connectivity or the ecological consequences of migration or species invasions. I propose that we view migration/dispersal as if organisms were moving along curvilinear geometrical objects called smooth manifolds. In that view, the curvilinear pathways become the ‘shortest realised paths’ arising from the necessity to minimise mortality risks and energy costs. One can then define curvilinear coordinate systems on such manifolds. I describe a procedure to incorporate manifolds and define appropriate coordinate systems, with focus on trajectories (1D manifolds), as parts of mechanistic ecological models. I show how a statistical method, known as ‘manifold learning’, enables one to define the manifold and the appropriate coordinate systems needed to calculate population connectivity or study the effects of migrations (e.g. in aquatic invertebrates, fish, insects and birds). This approach may help in the design of networks of protected areas, in studying the consequences of invasion, range expansions, or transfer of parasites/diseases. Overall, a geometrical view to animal movement gives a novel perspective to the understanding of the ecological role of dispersal and migration