Search results for " autocorrelation"
showing 10 items of 24 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…
Identifying potential areas of expansion for the endangered brown bear (Ursus arctos) population in the cantabrian mountains (NW Spain)
2019
Many large carnivore populations are expanding into human-modified landscapes and the subsequent increase in coexistence between humans and large carnivores may intensify various types of conflicts. A proactive management approach is critical to successful mitigation of such conflicts. The Cantabrian Mountains in Northern Spain are home to the last remaining native brown bear (Ursus arctos) population of the Iberian Peninsula, which is also amongst the most severely threatened European populations, with an important core group residing in the province of Asturias. There are indications that this small population is demographically expanding its range. The identification of the potential are…
Fruit body based inventories in wood-inhabiting fungi: Should we replicate in space or time?
2016
We assessed the effect of survey design on the results when conducting fruit body surveys of wood-inhabiting fungi. Our results demonstrate that the optimal design depends on the ecological question to be addressed, as well as the group of fungal species under research. If the aim is to record the total species richness in a dead wood unit or to estimate the population size of a species, repeating the survey over time is generally necessary. However, if the aim is to estimate the total species richness in the forest or to assess how environmental covariates influence species richness or community composition, it is generally more efficient to increase the number of dead wood units than to r…
The European Regional Convergence Process, 1980-1995: Do Spatial Regimes and Spatial Dependence Matter?
2002
International audience; The authors show that spatial dependence and spatial heterogeneity matter in the estimation of the ß-convergence process among 138 European regions over the 1980 to 1995 period. Using spatial econometrics tools, the authors detect both spatial dependence and spatial heterogeneity in the form of structural instability across spatial convergence clubs. The estimation of the appropriate spatial regimes spatial error model shows that the convergence process is different across regimes. The authors also estimate a strongly significant spatial spillover effect: the average growth rate of per capita GDP of a given region is positively affected by the average growth rate of …
Autocorrelation Metrics to Estimate Soil Moisture Persistence From Satellite Time Series: Application to Semiarid Regions
2021
Satellite-derived soil moisture (SM) products have become an important information source for the study of land surface processes in hydrology and land monitoring. Characterizing and estimating soil memory and persistence from satellite observations is of paramount relevance, and has deep implications in ecology, water management, and climate modeling. In this work, we address the problem of SM persistence estimation from microwave sensors using several autocorrelation metrics that, unlike traditional approaches, build on accurate estimates of the autocorrelation function from nonuniformly sampled time series. We show how the choice of the autocorrelation estimator can have a dramatic impac…
Application of Statistical Process Control to Continuous Processes
2002
Control charts represent an efficient and easy tool to assure the state of statistical quality control in a manufacturing process. These tools are also implemented in continuous processes, where the critical parameters are often monitored by on line sensors measuring data with short time intervals. In this paper a continuous process is monitored by using control charts and its dynamic is modeled through linear time series that allow the effects of the autocorrelation to be eliminated. In this way, the control charts can operate on residuals that result identically and independently distributed. A statistical analysis on EWMA, CUSUM and control charts for individual measurements has been car…
Space-time analysis of GDP disparities among European regions : a Markov chains approach
2004
The purpose of this paper is to study the evolution of the disparities between 138 European regions over the 1980-1995 period. We characterize the regional per capita GDP cross-sectional distribution by means of nonparametric estimations of density functions and we model the growth process as a first-order stationary Markov chain. Spatial effects are then introduced within the Markov chain framework using regional conditioning (Quah, 1996b) and spatial Markov chains (Rey, 2001). The results of the analysis indicate the persistence of regional disparities, a progressive bias toward a poverty trap and the importance of geography to explain the convergence process.
Intra-urban spatial distributions of population and employment : the case of the agglomeration of Dijon, 1999
2003
The aim of this paper is to analyze the intra-urban spatial distributions of population and employment in the agglomeration of Dijon (regional capital of Burgundy, France). We study whether this agglomeration has followed the general tendency of job decentralization observed in most urban areas or whether it is still characterized by a monocentric pattern. In that purpose, we use a sample of 136 observations at the communal and at the IRIS (infra-urban statistical area) levels with 1999 census data and the employment database SIRENE (INSEE). First; we study the spatial pattern of total employment and employment density using exploratory spatial data analysis. Apart from the CBD, few IRIS ar…
Exploratory spatial data analysis of the distribution of regional per capita GDP in Europe, 1980-1995
2000
The aim of this paper is to study the dynamics of European regional per capita product over time and space. This purpose is achieved by using the recently developed methods of Exploratory Spatial Data Analysis. Using a sample of European regions over the 1980-1995 period, we find strong evidence of global and local spatial autocorrelation in per capita GDP throughout the period. The detection of clusters of high and low per capita products during the period is an indication of the persistence of spatial disparities between European regions. This analysis is finally refined by the investigation of the spatial pattern of regional growth. Key words:exploratory spatial data analysis; distributi…
Econométrie spatiale (2, Hétérogénéité spatiale)
2000
Spatial econometric methods aim at taking into account the two special characteristics of spatial data: spatial autocorrelation, which is the lack of independence between geographical observations, and spatial heterogeneity, which is related to the differentiation of variables and behaviors in space. These techniques have been mostly developed the last ten years and are more often applied in empirical studies with geographical data. The aim of this article is to present the way spatial autocorrelation and spatial heterogeneity can be incorporated in regression relationships and to present the estimation and inference procedures adapted to the models incorporating these two effects. This art…