102 resultados para Norms modelling
Resumo:
Aims: To assess the potential distribution of an obligate seeder and active pyrophyte, Cistus salviifolius, a vulnerable species in the Swiss Red List; to derive scenarios by changing the fire return interval; and to discuss the results from a conservation perspective. A more general aim is to assess the impact of fire as a natural factor influencing the vegetation of the southern slopes of the Alps. Locations: Alps, southern Switzerland. Methods: Presence-absence data to fit the model were obtained from the most recent field mapping of C. salviifolius. The quantitative environmental predictors used in this study include topographic, climatic and disturbance (fire) predictors. Models were fitted by logistic regression and evaluated by jackknife and bootstrap approaches. Changes in fire regime were simulated by increasing the time-return interval of fire (simulating longer periods without fire). Two scenarios were considered: no fire in the past 15 years; or in the past 35 years. Results: Rock cover, slope, topographic position, potential evapotranspiration and time elapsed since the last fire were selected in the final model. The Nagelkerke R-2 of the model for C. salviifolius was 0.57 and the Jackknife area under the curve evaluation was 0.89. The bootstrap evaluation revealed model robustness. By increasing the return interval of fire by either up to 15 years, or 35 years, the modelled C. salviifolius population declined by 30-40%, respectively. Main conclusions: Although fire plays a significant role, topography and rock cover appear to be the most important predictors, suggesting that the distribution of C. salviifolius in the southern Swiss Alps is closely related to the availability of supposedly competition-free sites, such as emerging bedrock, ridge locations or steep slopes. Fire is more likely to play a secondary role in allowing C. salviifolius to extend its occurrence temporarily, by increasing germination rates and reducing the competition from surrounding vegetation. To maintain a viable dormant seed bank for C. salviifolius, conservation managers should consider carrying out vegetation clearing and managing wild fire propagation to reduce competition and ensure sufficient recruitment for this species.
Resumo:
Remote sensing using airborne imaging spectroscopy (AIS) is known to retrieve fundamental optical properties of ecosystems. However, the value of these properties for predicting plant species distribution remains unclear. Here, we assess whether such data can add value to topographic variables for predicting plant distributions in French and Swiss alpine grasslands. We fitted statistical models with high spectral and spatial resolution reflectance data and tested four optical indices sensitive to leaf chlorophyll content, leaf water content and leaf area index. We found moderate added-value of AIS data for predicting alpine plant species distribution. Contrary to expectations, differences between species distribution models (SDMs) were not linked to their local abundance or phylogenetic/functional similarity. Moreover, spectral signatures of species were found to be partly site-specific. We discuss current limits of AIS-based SDMs, highlighting issues of scale and informational content of AIS data.
Resumo:
Understanding and anticipating biological invasions can focus either on traits that favour species invasiveness or on features of the receiving communities, habitats or landscapes that promote their invasibility. Here, we address invasibility at the regional scale, testing whether some habitats and landscapes are more invasible than others by fitting models that relate alien plant species richness to various environmental predictors. We use a multi-model information-theoretic approach to assess invasibility by modelling spatial and ecological patterns of alien invasion in landscape mosaics and testing competing hypotheses of environmental factors that may control invasibility. Because invasibility may be mediated by particular characteristics of invasiveness, we classified alien species according to their C-S-R plant strategies. We illustrate this approach with a set of 86 alien species in Northern Portugal. We first focus on predictors influencing species richness and expressing invasibility and then evaluate whether distinct plant strategies respond to the same or different groups of environmental predictors. We confirmed climate as a primary determinant of alien invasions and as a primary environmental gradient determining landscape invasibility. The effects of secondary gradients were detected only when the area was sub-sampled according to predictions based on the primary gradient. Then, multiple predictor types influenced patterns of alien species richness, with some types (landscape composition, topography and fire regime) prevailing over others. Alien species richness responded most strongly to extreme land management regimes, suggesting that intermediate disturbance induces biotic resistance by favouring native species richness. Land-use intensification facilitated alien invasion, whereas conservation areas hosted few invaders, highlighting the importance of ecosystem stability in preventing invasions. Plants with different strategies exhibited different responses to environmental gradients, particularly when the variations of the primary gradient were narrowed by sub-sampling. Such differential responses of plant strategies suggest using distinct control and eradication approaches for different areas and alien plant groups.
Resumo:
The major goal of evolutionary thermal biology is to understand how variation in temperature shapes phenotypic evolution. Comparing thermal reaction norms among populations from different thermal environments allows us to gain insights into the evolutionary mechanisms underlying thermal adaptation. Here, we have examined thermal adaptation in six wild populations of the fruit fly (Drosophila melanogaster) from markedly different natural environments by analyzing thermal reaction norms for fecundity, thorax length, wing area, and ovariole number under ecologically realistic fluctuating temperature regimes in the laboratory. Contrary to expectation, we found only minor differences in the thermal optima for fecundity among populations. Differentiation among populations was mainly due to differences in absolute (and partly also relative) thermal fecundity performance. Despite significant variation among populations in the absolute values of morphological traits, we observed only minor differentiation in their reaction norms. Overall, the thermal reaction norms for all traits examined were remarkably similar among different populations. Our results therefore suggest that thermal adaptation in D. melanogaster predominantly involves evolutionary changes in absolute trait values rather than in aspects of thermal reaction norms.
Resumo:
Depth-averaged velocities and unit discharges within a 30 km reach of one of the world's largest rivers, the Rio Parana, Argentina, were simulated using three hydrodynamic models with different process representations: a reduced complexity (RC) model that neglects most of the physics governing fluid flow, a two-dimensional model based on the shallow water equations, and a three-dimensional model based on the Reynolds-averaged Navier-Stokes equations. Row characteristics simulated using all three models were compared with data obtained by acoustic Doppler current profiler surveys at four cross sections within the study reach. This analysis demonstrates that, surprisingly, the performance of the RC model is generally equal to, and in some instances better than, that of the physics based models in terms of the statistical agreement between simulated and measured flow properties. In addition, in contrast to previous applications of RC models, the present study demonstrates that the RC model can successfully predict measured flow velocities. The strong performance of the RC model reflects, in part, the simplicity of the depth-averaged mean flow patterns within the study reach and the dominant role of channel-scale topographic features in controlling the flow dynamics. Moreover, the very low water surface slopes that typify large sand-bed rivers enable flow depths to be estimated reliably in the RC model using a simple fixed-lid planar water surface approximation. This approach overcomes a major problem encountered in the application of RC models in environments characterised by shallow flows and steep bed gradients. The RC model is four orders of magnitude faster than the physics based models when performing steady-state hydrodynamic calculations. However, the iterative nature of the RC model calculations implies a reduction in computational efficiency relative to some other RC models. A further implication of this is that, if used to simulate channel morphodynamics, the present RC model may offer only a marginal advantage in terms of computational efficiency over approaches based on the shallow water equations. These observations illustrate the trade off between model realism and efficiency that is a key consideration in RC modelling. Moreover, this outcome highlights a need to rethink the use of RC morphodynamic models in fluvial geomorphology and to move away from existing grid-based approaches, such as the popular cellular automata (CA) models, that remain essentially reductionist in nature. In the case of the world's largest sand-bed rivers, this might be achieved by implementing the RC model outlined here as one element within a hierarchical modelling framework that would enable computationally efficient simulation of the morphodynamics of large rivers over millennial time scales. (C) 2012 Elsevier B.V. All rights reserved.
Resumo:
This paper investigates the use of ensemble of predictors in order to improve the performance of spatial prediction methods. Support vector regression (SVR), a popular method from the field of statistical machine learning, is used. Several instances of SVR are combined using different data sampling schemes (bagging and boosting). Bagging shows good performance, and proves to be more computationally efficient than training a single SVR model while reducing error. Boosting, however, does not improve results on this specific problem.
Resumo:
Les pressions écologiques peuvent varier tant en nature qu'en intensité dans le temps et l'espace. C'est pourquoi, un phénotype unique ne peut pas forcément conférer la meilleure valeur sélective. La plasticité phénotypique peut être un moyen de s'accommoder de cette situation, en augmentant globalement la tolérance aux changements environnementaux. Comme pour tout trait de caractère, une variation génétique doit persister pour qu'évoluent les traits plastiques dans une population donnée. Cependant, les pressions extérieures peuvent affecter l'héritabilité, et la direction de ces changements peut dépendre du caractère en question, de l'espèce mais aussi du type de stress. Dans la présente thèse, nous avons cherché à élucider les effets des pressions pathogéniques sur les phénotypes et la génétique quantitative de plusieurs traits plastiques chez les embryons de deux salmonidés, la palée (Coregonus palaea), et la truite de rivière (Salmo trutta). Les salmonidés se prêtent à de telles études du fait de leur extraordinaire variabilité morphologique, comportementale et des traits d'histoire de vie. Par ailleurs, avec le déclin des salmonidés dans le monde, il est important de savoir combien la variabilité génétique persiste dans les normes de réaction afin d'aider à prédire leur capacité à répondre aux changements de leur milieu. Nous avons observé qu'une augmentation de la croissance des communautés microbiennes symbiotiques entraînait une mortalité accrue et une éclosion précoce chez la palée, et dévoilait la variance génétique additive pour ces deux caractères (Chapitres 1-2). Bien qu'aucune variation génétique n'ait été trouvée pour les normes de réaction, nous avons observé une variabilité de la plasticité d'éclosion. Néanmoins, on a trouvé que les temps d'éclosion étaient corrélés entre les environnements, ce qui pourrait limiter l'évolution de la norme de réaction. Le temps d'éclosion des embryons est lié à la taille des géniteurs mâles, ce qui indique des effets pléiotropiques. Dans le Chapitre 3, nous avons montré qu'une interaction triple entre la souche bactérienne {Pseudomonas fluorescens}, l'état de dévelopement de l'hôte ainsi que ses gènes ont une influence sur la mortalité, le temps d'éclosion et la taille des alevins de la palée. Nous avons démontré qu'une variation génétique subsistait généralement dans les normes de réaction des temps d'éclosion, mais rarement pour la taille des alevins, et jamais pour la mortalité. Dans le même temps, nous avons exhibé que des corrélations entre environnements dépendaient des caractères phénotypiques, mais contrairement au Chapitre 2, nous n'avons pas trouvé de preuve de corrélations transgénérationnelles. Le Chapitre 4 complète le chapitre précédent, en se plaçant du point de vue moléculaire, et décrit comment le traitement d'embryons avec P. fluorescens s'est traduit par une régulation négative d'expression du CMH-I indépendemment de la souche bactérienne. Nous avons non seulement trouvé une variation génétique des caractères phénotypiques moyens, mais aussi de la plasticité. Les deux derniers chapitres traitent de l'investigation, chez la truite de rivière, des différences spécifiques entre populations pour des normes de réaction induites par les pathogènes. Dans le Chapitre 5, nous avons illustré que le métissage entre des populations génétiquement distinctes n'affectait en rien la hauteur ou la forme des normes de réaction d'un trait précoce d'histoire de vie suite au traitement pathogénique. De surcroît, en dépit de l'éclosion tardive et de la réduction de la taille des alevins, le traitement n'a pas modifié la variation héritable des traits de caractère. D'autre part, dans le Chapitre 6, nous avons démontré que le traitement d'embryons avec des stimuli contenus dans l'eau de conspécifiques infectés a entraîné des réponses propre à chaque population en terme de temps d'éclosion ; néanmoins, nous avons observé peu de variabilité génétique des normes de réaction pour ce temps d'éclosion au sein des populations. - Ecological stressors can vary in type and intensity over space and time, and as such, a single phenotype may not confer the highest fitness. Phenotypic plasticity can act as a means to accommodate this situation, increasing overall tolerance to environmental change. As with any trait, for plastic traits to evolve in a population, genetic variation must persist. However, environmental stress can alter trait heritability, and the direction of this shift can be trait, species, and stressor-dependent. In this thesis, we sought to understand the effects of pathogen stressors on the phenotypes and genetic architecture of several plastic traits in the embryos of two salmonids, the whitefish (Coregonus palaea), and the brown trout (Salmo trutta). Salmonids lend themselves to such studies because their extraordinary variability in morphological, behavioral, and life-history traits. Also, with declines in salmonids worldwide, knowing how much genetic variability persists in reaction norms may help predict their ability to respond to environmental change. We found that increasing growth of symbiotic microbial communities increased mortality and induced hatching in whitefish, and released additive genetic variance for both traits (Chapters 1-2). While no genetic variation was found for survival reaction norms, we did find variability in hatching plasticity. Nevertheless, hatching time was correlated across environments, which could constrain evolution of the reaction norm. Hatching time in the induced environment was also correlated to sire size, indicating pleiotropic effects. In Chapter 3 we report that a three-way interaction between bacterial strain (Pseudomonas fluorescens), host developmental stage, and host genetics impacted mortality, hatching time, and hatchling size in whitefish. We also showed that genetic variation generally persisted in hatching age reaction norms, but rarely for hatchling length, and never for mortality. At the same time, we demonstrated that cross-environmental correlations were trait-dependent, and unlike Chapter 2, we found no evidence of cross-generational correlations. Chapter 4 expands on the previous chapter, moving to the molecular level, and describes how treatment of embryos with P. fluorescens resulted in strain-independent downregulation of MHC class I. Genetic variation was evident not only in trait means, but also in plasticity. In the last two chapters, we investigated population level differences in pathogen- induced reaction norms in brown trout. In Chapter 5, we found that interbreeding between genetically distinct populations did not affect the elevation or shapes of the reaction norms of early life-history traits after pathogen challenge. Moreover, despite delaying hatching and reducing larval length, treatment produced no discernable shifts in heritable variation in traits. On the other hand, in Chapter 6, we found that treatment of embryos with water-borne cues from infected conspecifics elicited population-specific responses in terms of hatching time; however, we found little evidence of genetic variability in hatching reaction norms within populations. We have made considerable progress in understanding how pathogen stressors affect various early life-history traits in salmonid embryos. We have demonstrated that the effect of a particular stressor on heritable variation in these traits can vary according to the trait and species under consideration, in addition to the developmental stage of the host. Moreover, we found evidence of genetic variability in some, but not all reaction norms in whitefish and brown trout.
Resumo:
Background: Bone health is a concern when treating early stage breast cancer patients with adjuvant aromatase inhibitors. Early detection of patients (pts) at risk of osteoporosis and fractures may be helpful for starting preventive therapies and selecting the most appropriate endocrine therapy schedule. We present statistical models describing the evolution of lumbar and hip bone mineral density (BMD) in pts treated with tamoxifen (T), letrozole (L) and sequences of T and L. Methods: Available dual-energy x-ray absorptiometry exams (DXA) of pts treated in trial BIG 1-98 were retrospectively collected from Swiss centers. Treatment arms: A) T for 5 years, B) L for 5 years, C) 2 years of T followed by 3 years of L and, D) 2 years of L followed by 3 years of T. Pts without DXA were used as a control for detecting selection biases. Patients randomized to arm A were subsequently allowed an unplanned switch from T to L. Allowing for variations between DXA machines and centres, two repeated measures models, using a covariance structure that allow for different times between DXA, were used to estimate changes in hip and lumbar BMD (g/cm2) from trial randomization. Prospectively defined covariates, considered as fixed effects in the multivariable models in an intention to treat analysis, at the time of trial randomization were: age, height, weight, hysterectomy, race, known osteoporosis, tobacco use, prior bone fracture, prior hormone replacement therapy (HRT), bisphosphonate use and previous neo-/adjuvant chemotherapy (ChT). Similarly, the T-scores for lumbar and hip BMD measurements were modeled using a per-protocol approach (allowing for treatment switch in arm A), specifically studying the effect of each therapy upon T-score percentage. Results: A total of 247 out of 546 pts had between 1 and 5 DXA; a total of 576 DXA were collected. Number of DXA measurements per arm were; arm A 133, B 137, C 141 and D 135. The median follow-up time was 5.8 years. Significant factors positively correlated with lumbar and hip BMD in the multivariate analysis were weight, previous HRT use, neo-/adjuvant ChT, hysterectomy and height. Significant negatively correlated factors in the models were osteoporosis, treatment arm (B/C/D vs. A), time since endocrine therapy start, age and smoking (current vs. never).Modeling the T-score percentage, differences from T to L were -4.199% (p = 0.036) and -4.907% (p = 0.025) for the hip and lumbar measurements respectively, before any treatment switch occurred. Conclusions: Our statistical models describe the lumbar and hip BMD evolution for pts treated with L and/or T. The results of both localisations confirm that, contrary to expectation, the sequential schedules do not seem less detrimental for the BMD than L monotherapy. The estimated difference in BMD T-score percent is at least 4% from T to L.