Search results for " statistics"
showing 10 items of 1891 documents
Assessing the spatiotemporal persistence of fish distributions: a case study on two red mullet species (Mullus surmuletus and M. barbatus) in the wes…
2020
Understanding the spatiotemporal persistence of fish distributions is key to defining fish hotspots and effective fisheries-restricted areas (FRAs). Hierarchical Bayesian spatiotemporal models provide an excellent framework to understand these distributions, as they can accommodate different spatiotemporal behaviour in the data, primarily due to their flexibility. The aim of this research was to characterize the fundamental behavioural patterns of fish as persistent, opportunistic or progressive by comparing different spatiotemporal model structures in order to provide better information for marine spatial planning. To illustrate this method, the spatiotemporal distributions of 2 sympatric …
Empirical Bayes improves assessments of diversity and similarity when overdispersion prevails in taxonomic counts with no covariates
2019
Abstract The assessment of diversity and similarity is relevant in monitoring the status of ecosystems. The respective indicators are based on the taxonomic composition of biological communities of interest, currently estimated through the proportions computed from sampling multivariate counts. In this work we present a novel method to estimate the taxonomic composition able to work even with a single sample and no covariates, when data are affected by overdispersion. The presence of overdispersion in taxonomic counts may be the result of significant environmental factors which are often unobservable but influence communities. Following the empirical Bayes approach, we combine a Bayesian mo…
Managing for resilience: an information theory-based approach to assessing ecosystems
2016
Ecosystems are complex and multivariate; hence, methods to assess the dynamics of ecosystems should have the capacity to evaluate multiple indicators simultaneously. Most research on identifying leading indicators of regime shifts has focused on univariate methods and simple models which have limited utility when evaluating real ecosystems, particularly because drivers are often unknown. We discuss some common univariate and multivariate approaches for detecting critical transitions in ecosystems and demonstrate their capabilities via case studies. Synthesis and applications. We illustrate the utility of an information theory-based index for assessing ecosystem dynamics. Trends in this inde…
Efficient estimation of generalized linear latent variable models.
2019
Generalized linear latent variable models (GLLVM) are popular tools for modeling multivariate, correlated responses. Such data are often encountered, for instance, in ecological studies, where presence-absences, counts, or biomass of interacting species are collected from a set of sites. Until very recently, the main challenge in fitting GLLVMs has been the lack of computationally efficient estimation methods. For likelihood based estimation, several closed form approximations for the marginal likelihood of GLLVMs have been proposed, but their efficient implementations have been lacking in the literature. To fill this gap, we show in this paper how to obtain computationally convenient estim…
Sampling effort and information quality provided by rare and common species in estimating assemblage structure
2020
Made available in DSpace on 2020-12-12T01:06:11Z (GMT). No. of bitstreams: 0 Previous issue date: 2020-03-01 Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES) Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP) Academy of Finland Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq) Reliable biological assessments are essential to answer ecological and management questions but require well-designed studies and representative sample sizes. However, large sampling effort is rarely possible, because it demands large financial resources and time, restricting the number of sites sampled, the duration of the study and the sampling effort at each site. In…
A multivariate morphometric analysis of diagnostic traits in southern Italy and Sicily pubescent oaks
2020
AbstractSpecies identification within the species complex ofQ. pubescensis a well-known taxonomic challenge among European botanists. Some of the specific pubescent oak binomials currently accepted in various European floras and checklists were originally described in Sicily and southern Calabria. As a consequence, several species belonging to the pubescent oaks group (Q. pubescens,Q. amplifolia,Q. congesta,Q. dalechampii,Q. leptobalanaandQ. virgiliana) are reported in the taxonomic and phytosociological literature. To verify whether it was possible to associate a diverse set of morphological characters with each of these different taxa, thirteen natural populations of pubescent oak from Si…
Testing hypotheses in evolutionary ecology with imperfect detection: capture-recapture structural equation modeling.
2012
8 pages; International audience; Studying evolutionary mechanisms in natural populations often requires testing multifactorial scenarios of causality involving direct and indirect relationships among individual and environmental variables. It is also essential to account for the imperfect detection of individuals to provide unbiased demographic parameter estimates. To cope with these issues, we developed a new approach combining structural equation models with capture-recapture models (CR-SEM) that allows the investigation of competing hypotheses about individual and environmental variability observed in demographic parameters. We employ Markov chain Monte Carlo sampling in a Bayesian frame…
Quantifying and addressing the prevalence and bias of study designs in the environmental and social sciences
2020
Building trust in science and evidence-based decision-making depends heavily on the credibility of studies and their findings. Researchers employ many different study designs that vary in their risk of bias to evaluate the true effect of interventions or impacts. Here, we empirically quantify, on a large scale, the prevalence of different study designs and the magnitude of bias in their estimates. Randomised designs and controlled observational designs with pre-intervention sampling were used by just 23% of intervention studies in biodiversity conservation, and 36% of intervention studies in social science. We demonstrate, through pairwise within-study comparisons across 49 environmental da…
Hierarchical log Gaussian Cox process for regeneration in uneven-aged forests
2021
We propose a hierarchical log Gaussian Cox process (LGCP) for point patterns, where a set of points x affects another set of points y but not vice versa. We use the model to investigate the effect of large trees to the locations of seedlings. In the model, every point in x has a parametric influence kernel or signal, which together form an influence field. Conditionally on the parameters, the influence field acts as a spatial covariate in the intensity of the model, and the intensity itself is a non-linear function of the parameters. Points outside the observation window may affect the influence field inside the window. We propose an edge correction to account for this missing data. The par…
Variational Approximations for Generalized Linear Latent Variable Models
2017
Generalized linear latent variable models (GLLVMs) are a powerful class of models for understanding the relationships among multiple, correlated responses. Estimation, however, presents a major challenge, as the marginal likelihood does not possess a closed form for nonnormal responses. We propose a variational approximation (VA) method for estimating GLLVMs. For the common cases of binary, ordinal, and overdispersed count data, we derive fully closed-form approximations to the marginal log-likelihood function in each case. Compared to other methods such as the expectation-maximization algorithm, estimation using VA is fast and straightforward to implement. Predictions of the latent variabl…