887 resultados para phylogeography, consensus approach, ensemble modeling, Pleistocene, ENM, ecological niche modeling


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Aim: Previous studies revealed that diversification events in the western clade of the alpine Primula sect. Auricula were concentrated in the Quaternary cold periods. This implies that allopatric speciation in isolated glacial refugia was the most common mode of speciation. In the first part of the present dissertation, this hypothesis is further investigated by locating refugial areas of two sister species, Primula marginata & P. latifolia during the last glacial maximum, 21,000 years ago. In the second part, the glacial and postglacial history of P. hirsuta and P. daonensis is investigated. Location: European Alps. Methods: Glacial refugia were located using species distribution models, which are projected to last glacial maximum climate. These refugia are validated with geographic distribution patterns of intra-specific genetic diversity, rarity and variation. Results 1) Speciation: Glacial refugia of the sister taxa Primula marginata and P. latifolia were largely separated, only a small overlapping zone at the southern margin of the former glacier in the Maritime Alps exists. This overlapping zone is too small to indicate sympatric speciation. The largely separated glacial distribution of both species rather confirms our hypothesis of allopatric speciation in isolated glacial refugia. Results 2) Glacial and postglacial history: Surprizingly, the modelled potential refugia of three out of four Primula species are situated within the former ice-shield, except for P. marginata. This indicates that peripheral and central nunataks played an important role for the glacial survival in P. latifolia, P. hirsuta and P. daonensis, while peripheral refugia outside the maximum extend of the glacier were crucial in P. marginata. In P. hirsuta and P. latifolia SDMs allowed to exclude several hypothetical refugial areas that overlap with today’s distribution as potential refugia for the species. In P. marginata, hypothetical refugial areas at the periphery of the former ice-shield that overlap with today’s distribution were confirmed by the models. The results from the SDMs are confirmed by population genetic patterns in three out of four species. P. daonensis represents an exception, where population genetic data contradict the SDMs. Main conclusions: Species distribution models provide species specific scenarios of glacial distribution and postglacial re-colonization, which can be validated using population genetic analyses. This combined approach is useful and helps to understand the complex processes that have lead to the genetic and floristic patterns of biodiversity that is found today in the Alps.

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First described more that 150 years ago, the systematics of the genera Geomalacus and Letourneuxia (Arionidae, Gastropoda, Pulmonata) is still challenging. The taxonomic classification of arionid species is based on extremely labile characters such as body size or color that depends both on diet and environment, as well as age. Moreover, there is little information on the genetic diversity and population structure of the Iberian slugs that could provide extra clues to disentangle their problematic classification. The present work uses different analytical tools such as habitat suitability (Ecological Niche Modeling - ENM), cytogenetic analysis and phylogeography to establish the geographical distribution and evolutionary history of these pulmonate slugs. The potential distribution of the four Geomalacus species was modeled using ENM, which allowed the identification of new locations for G. malagensis, including a first report in Portugal. Also, it was predicted a much wider distribution for G. malagensis and G. oliveirae than previously known. Classical cytogenetic analyses were assayed with reproductive and a novel use of somatic tissues (mouth and tentacles) returning the number of chromosomes for the four Geomalacus species and L. numidica (n = 31, 2n = 62) and the respective karyotypes. G. malagensis and L. numidica present similar chromosome morphologies and karyotypic formulae, being more similar to each other than the Geomalacus among themselves. We further reconstructed the phylogeny of the genera Geomalacus and Letourneuxia using partial sequences of the mitochondrial cytochrome oxidase subunit I (COI) and the nuclear ribosomal small subunit (18S rRNA), and applied an independent evolutionary rate method, the indicator vectors correlation, to evaluate the existence of cryptic diversity within species. The five nominal species of Geomalacus and Letourneuxia comprise 14 well-supported cryptic lineages. Letourneuxia numidica was retrieved as a sister group of G. malagensis. G. oliveirae is paraphyletic with respect to G. anguiformis. According to our dating estimates, the most recent common ancestor of Geomalacus dates back to the Middle Miocene (end of the Serravallian stage). The major lineage splitting events within Geomalacus occurred during the dry periods of the Zanclean stage (5.3-3.6 million years) and some lineages were confined to more humid mountain areas of the Iberian Peninsula, which lead to a highly geographically structured mitochondrial genetic diversity. The major findings of this are the following: (1) provides updated species distribution maps for the Iberian Geomalacus expanding the known geographic distribution of the concerned species, (2) unravels the cryptic diversity within the genera Geomalacus and Letourneuxia, (3) Geomalacus oliveirae is paraphyletic with G. anguiformis and (4) Letourneuxia numidica is sister group of G. malagensis.

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A fractional differential equation is used to describe a fractal model of mobile/immobile transport with a power law memory function. This equation is the limiting equation that governs continuous time random walks with heavy tailed random waiting times. In this paper, we firstly propose a finite difference method to discretize the time variable and obtain a semi-discrete scheme. Then we discuss its stability and convergence. Secondly we consider a meshless method based on radial basis functions (RBFs) to discretize the space variable. In contrast to conventional FDM and FEM, the meshless method is demonstrated to have distinct advantages: calculations can be performed independent of a mesh, it is more accurate and it can be used to solve complex problems. Finally the convergence order is verified from a numerical example which is presented to describe a fractal model of mobile/immobile transport process with different problem domains. The numerical results indicate that the present meshless approach is very effective for modeling and simulating fractional differential equations, and it has good potential in the development of a robust simulation tool for problems in engineering and science that are governed by various types of fractional differential equations.

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A coupled methodology for simulating the simultaneous growth and motion of equiaxed dendrites in solidifying melts is presented. The model uses the volume-averaging principles and combines the features of the enthalpy method for modeling growth, immersed boundary method for handling the rigid solid-liquid interfaces, and the volume of fluid method for tracking the advection of the dendrite. The algorithm also performs explicit-implicit coupling between the techniques used. A two-dimensional framework with incompressible and Newtonian fluid is considered. Validation with available literature is performed and dendrite growth in the presence of rotational and buoyancy driven flow fields is studied. It is seen that the flow fields significantly alter the position and morphology of the dendrites. (C) 2012 Elsevier Inc. All rights reserved.

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The present paper considers the problem of autonomous synchronization of attitudes in a swarm of spacecraft. Building upon our recent results on consensus on manifolds, we model the spacecraft as particles on SO(3) and drive these particles to a common point in SO(3). Unlike the Euler angle or quaternion descriptions, this model suffers no singularities nor double-points. Our approach is fully cooperative and autonomous: we use no leader nor external reference. We present two types of control laws, in terms of applied control torques, that globally drive the swarm towards attitude synchronization: one that requires tree-like or all-to-all inter-satellite communication (most efficient) and one that works with nearly arbitrary communication (most robust).

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This paper proposes a methodology to stabilize relative equilibria in a model of identical, steered particles moving in three-dimensional Euclidean space. Exploiting the Lie group structure of the resulting dynamical system, the stabilization problem is reduced to a consensus problem. We first derive the stabilizing control laws in the presence of all-to-all communication. Providing each agent with a consensus estimator, we then extend the results to a general setting that allows for unidirectional and time-varying communication topologies. © 2007 IEEE.

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Assuming that daily spot exchange rates follow a martingale process, we derive the implied time series process for the vector of 30-day forward rate forecast errors from using weekly data. The conditional second moment matrix of this vector is modelled as a multivariate generalized ARCH process. The estimated model is used to test the hypothesis that the risk premium is a linear function of the conditional variances and covariances as suggested by the standard asset pricing theory literature. Little supportt is found for this theory; instead lagged changes in the forward rate appear to be correlated with the 'risk premium.'. © 1990.

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Aim: Ecological niche modelling can provide valuable insight into species' environmental preferences and aid the identification of key habitats for populations of conservation concern. Here, we integrate biologging, satellite remote-sensing and ensemble ecological niche models (EENMs) to identify predictable foraging habitats for a globally important population of the grey-headed albatross (GHA) Thalassarche chrysostoma. Location: Bird Island, South Georgia; Southern Atlantic Ocean. Methods: GPS and geolocation-immersion loggers were used to track at-sea movements and activity patterns of GHA over two breeding seasons (n = 55; brood-guard). Immersion frequency (landings per 10-min interval) was used to define foraging events. EENM combining Generalized Additive Models (GAM), MaxEnt, Random Forest (RF) and Boosted Regression Trees (BRT) identified the biophysical conditions characterizing the locations of foraging events, using time-matched oceanographic predictors (Sea Surface Temperature, SST; chlorophyll a, chl-a; thermal front frequency, TFreq; depth). Model performance was assessed through iterative cross-validation and extrapolative performance through cross-validation among years. Results: Predictable foraging habitats identified by EENM spanned neritic (<500 m), shelf break and oceanic waters, coinciding with a set of persistent biophysical conditions characterized by particular thermal ranges (3–8 °C, 12–13 °C), elevated primary productivity (chl-a > 0.5 mg m−3) and frequent manifestation of mesoscale thermal fronts. Our results confirm previous indications that GHA exploit enhanced foraging opportunities associated with frontal systems and objectively identify the APFZ as a region of high foraging habitat suitability. Moreover, at the spatial and temporal scales investigated here, the performance of multi-model ensembles was superior to that of single-algorithm models, and cross-validation among years indicated reasonable extrapolative performance. Main conclusions: EENM techniques are useful for integrating the predictions of several single-algorithm models, reducing potential bias and increasing confidence in predictions. Our analysis highlights the value of EENM for use with movement data in identifying at-sea habitats of wide-ranging marine predators, with clear implications for conservation and management.

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Aim: Ecological niche modelling can provide valuable insight into species' environmental preferences and aid the identification of key habitats for populations of conservation concern. Here, we integrate biologging, satellite remote-sensing and ensemble ecological niche models (EENMs) to identify predictable foraging habitats for a globally important population of the grey-headed albatross (GHA) Thalassarche chrysostoma. Location: Bird Island, South Georgia; Southern Atlantic Ocean. Methods: GPS and geolocation-immersion loggers were used to track at-sea movements and activity patterns of GHA over two breeding seasons (n = 55; brood-guard). Immersion frequency (landings per 10-min interval) was used to define foraging events. EENM combining Generalized Additive Models (GAM), MaxEnt, Random Forest (RF) and Boosted Regression Trees (BRT) identified the biophysical conditions characterizing the locations of foraging events, using time-matched oceanographic predictors (Sea Surface Temperature, SST; chlorophyll a, chl-a; thermal front frequency, TFreq; depth). Model performance was assessed through iterative cross-validation and extrapolative performance through cross-validation among years. Results: Predictable foraging habitats identified by EENM spanned neritic (<500 m), shelf break and oceanic waters, coinciding with a set of persistent biophysical conditions characterized by particular thermal ranges (3–8 °C, 12–13 °C), elevated primary productivity (chl-a > 0.5 mg m−3) and frequent manifestation of mesoscale thermal fronts. Our results confirm previous indications that GHA exploit enhanced foraging opportunities associated with frontal systems and objectively identify the APFZ as a region of high foraging habitat suitability. Moreover, at the spatial and temporal scales investigated here, the performance of multi-model ensembles was superior to that of single-algorithm models, and cross-validation among years indicated reasonable extrapolative performance. Main conclusions: EENM techniques are useful for integrating the predictions of several single-algorithm models, reducing potential bias and increasing confidence in predictions. Our analysis highlights the value of EENM for use with movement data in identifying at-sea habitats of wide-ranging marine predators, with clear implications for conservation and management.

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In this paper, a method for modeling diffusive boundaries in finite difference time domain (FDTD) room acoustics simulations with the use of impedance filters is presented. The proposed technique is based on the concept of phase grating diffusers, and realized by designing boundary impedance filters from normal-incidence reflection filters with added delay. These added delays, that correspond to the diffuser well depths, are varied across the boundary surface, and implemented using Thiran allpass filters. The proposed method for simulating sound scattering is suitable for modeling high frequency diffusion caused by small variations in surface roughness and, more generally, diffusers characterized by narrow wells with infinitely thin separators. This concept is also applicable to other wave-based modeling techniques. The approach is validated by comparing numerical results for Schroeder diffusers to measured data. In addition, it is proposed that irregular surfaces are modeled by shaping them with Brownian noise, giving good control over the sound scattering properties of the simulated boundary through two parameters, namely the spectral density exponent and the maximum well depth.