Search results for "Bayesian models"
showing 10 items of 18 documents
A hierarchical Bayesian Beta regression approach to study the effects of geographical genetic structure and spatial autocorrelation on species distri…
2019
Global climate change (GCC) may be causing distribution range shifts in many organisms worldwide. Multiple efforts are currently focused on the development of models to better predict distribution range shifts due to GCC. We addressed this issue by including intraspecific genetic structure and spatial autocorrelation (SAC) of data in distribution range models. Both factors reflect the joint effect of ecoevolutionary processes on the geographical heterogeneity of populations. We used a collection of 301 georeferenced accessions of the annual plant Arabidopsis thaliana in its Iberian Peninsula range, where the species shows strong geographical genetic structure. We developed spatial and nonsp…
Integrating spatial management measures into fisheries: The Lepidorhombus spp. case study
2020
Most fisheries management systems rely on a set of regulatory measures to achieve desired objectives. Controls on catch and effort are usually supplemented with gear restrictions, minimum landing sizes, and in the framework of the new common fisheries policy, limitation of discards and by-catch. However, the increasing use of spatial management measures such as conservation areas or spatial and temporal area closures faces new challenges for fishery managers. Here we present an integrated spatial framework to identify areas in which undersized commercial species are more abundant. Once these areas are identified they could be avoided by fishers, minimizing the fishing impact over the immatu…
Small-scale shrimp fisheries bycatch: a multi-criteria approach for data-poor situations
2020
Abstract Bycatch and discards from small-scale fisheries (SSF) are usually ignored when compared with industrial fisheries, not only by policy-makers, but also by scientists. Therefore, SSF social, economic and ecological impacts are poorly known and especially in the context of incidental catches, regardless of whether they become bycatch or discards. Such neglect is worrisome due to the role that SSF play in food security and poverty alleviation, particularly in coastal and rural communities in developing countries. In this study, a combination of sampling data and the fishers' behavior (specifically the basis of their decision on where to fish) were used. Bayesian models were applied to …
Habitat modeling for cetacean management: Spatial distribution in the southern Pelagos Sanctuary (Mediterranean Sea)
2017
International audience; Effective management and conservation of wild populations requires knowledge of their habitats, especially by mean of quantitative analyses of their spatial distributions. The Pelagos Sanctuary is a dedicated marine protected area for Mediterranean marine mammals covering an area of 90,000km2 in the north-western Mediterranean Sea between Italy, France and the Principate of Monaco. In the south of the Sanctuary, i.e. along the Sardinian coast, a range of diverse human activities (cities, industry, fishery, tourism) exerts several current ad potential threats to cetacean populations. In addition, marine mammals are recognized by the EU Marine Strategy Framework Direct…
Temporal Binding in Multisensory and Motor-Sensory Contexts: Toward a Unified Model
2021
Our senses receive a manifold of sensory signals at any given moment in our daily lives. For a coherent and unified representation of information and precise motor control, our brain needs to temporally bind the signals emanating from a common causal event and segregate others. Traditionally, different mechanisms were proposed for the temporal binding phenomenon in multisensory and motor-sensory contexts. This paper reviews the literature on the temporal binding phenomenon in both multisensory and motor-sensory contexts and suggests future research directions for advancing the field. Moreover, by critically evaluating the recent literature, this paper suggests that common computational prin…
A Fatty Acid Based Bayesian Approach for Inferring Diet in Aquatic Consumers
2015
We modified the stable isotope mixing model MixSIR to infer primary producer contributions to consumer diets based on their fatty acid composition. To parameterize the algorithm, we generated a 'consumer-resource library' of FA signatures of Daphnia fed different algal diets, using 34 feeding trials representing diverse phytoplankton lineages. This library corresponds to the resource or producer file in classic Bayesian mixing models such as MixSIR or SIAR. Because this library is based on the FA profiles of zooplankton consuming known diets, and not the FA profiles of algae directly, trophic modification of consumer lipids is directly accounted for. To test the model, we simulated hypothet…
Mesocarnivore community structuring in the presence of Africa's apex predator
2021
This work was supported by the Peace Parks Foundation; G.C.S. was funded by a doctoral grant from Fundacão para a Ciência e a Tecnologia (FCT: PD/BD/114037/2015); L.H.S. was supported by the National Research Foundation, South Africa (UID: 107099 and 115040) and by the African Institute for Conservation Ecology. Apex predator reintroductions have proliferated across southern Africa, yet their ecological effects and proposed umbrella benefits of associated management lack empirical evaluations. Despite a rich theory on top-down ecosystem regulation via mesopredator suppression, a knowledge gap exists relating to the influence of lions (Panthera leo) over Africa's diverse mesocarnivore (less …
Italian Deprivation Index and Dental Caries in 12-Year-Old Children: A Multilevel Bayesian Analysis
2014
Evidence from the literature has shown that people with a lower socioeconomic status enjoy less good health than people with a higher socioeconomic status. The Italian deprivation index (DI) was used with the aim to evaluate the association between the DMFT index and risk factors for dental caries, including city population and DI. The study included 4,305 12-year-old children living in 38 cities classified by demographic size as small, midsize and large. Zero-inflated negative binomial multilevel regression models were used to assess risk factors for DMFT and to address excess of zero DMFT and overdispersion through a Bayesian approach. The difference in the average level of DMFT among chi…
Joint Estimation of Relative Risk for Dengue and Zika Infections, Colombia, 2015–2016
2019
We jointly estimated relative risk for dengue and Zika virus disease (Zika) in Colombia, establishing the spatial association between them at the department and city levels for October 2015–December 2016. Cases of dengue and Zika were allocated to the 87 municipalities of 1 department and the 293 census sections of 1 city in Colombia. We fitted 8 hierarchical Bayesian Poisson joint models of relative risk for dengue and Zika, including area- and disease-specific random effects accounting for several spatial patterns of disease risk (clustered or uncorrelated heterogeneity) within and between both diseases. Most of the dengue and Zika high-risk municipalities varied in their risk distributio…
Markov chain Monte Carlo importance samplers for Bayesian models with intractable likelihoods
2019
Markov chain Monte Carlo (MCMC) is an approach to parameter inference in Bayesian models that is based on computing ergodic averages formed from a Markov chain targeting the Bayesian posterior probability. We consider the efficient use of an approximation within the Markov chain, with subsequent importance sampling (IS) correction of the Markov chain inexact output, leading to asymptotically exact inference. We detail convergence and central limit theorems for the resulting MCMC-IS estimators. We also consider the case where the approximate Markov chain is pseudo-marginal, requiring unbiased estimators for its approximate marginal target. Convergence results with asymptotic variance formula…