scholarly journals SPATIAL DISTRIBUTION OF FIREWOOD PRODUCTION IN NORTHEASTERN BRAZIL (1994-2013)

2018 ◽  
Vol 42 (4) ◽  
Author(s):  
Luiz Moreira Coelho Junior ◽  
Kalyne de Lourdes da Costa Martins ◽  
Pablo Aurélio Lacerda de Almeida Pinto ◽  
Magno Vamberto Batista da Silva
Keyword(s):  
Spatial Distribution ◽  
Spatial Data ◽  
Nearest Neighbors ◽  
Spatial Cluster ◽  
Weight Matrix ◽  
Northeastern Brazil ◽  
Northeast Brazil ◽  
Spatial Clusters ◽  
Exploratory Approach ◽  
Production Value

ABSTRACT This paper analyzed the effects of the spatial distribution of the firewood gross production value (GPV) of northeast Brazil through an exploratory approach using spatial data for the period from 1994 to 2013. Identification of spatial clusters in firewood production through the spatial weighting matrices of 2 nearest neighbors and “queen” and “rook” contiguity matrices were used. Based on the analyses, the following can be concluded: there is a positive autocorrelation for firewood GPV; the high-high spatial cluster was formed predominantly in the Bahia region; the high-high spatial cluster, which considers the weight matrix per area, was composed of the Ceará and Pernambuco mesoregions; the low-low spatial cluster consisted of the Sergipe and Alagoas mesoregions; and the low-low cluster, which considers the weight matrix per area, was formed by the Sergipe, Alagoas and Piauí regions.

scholarly journals Anurofauna of a remnant of Atlantic Forest in northeast Brazil

2020 ◽  
Vol 15 (4) ◽  
pp. 415-425
Author(s):  
Gessica Gomes Barbosa ◽  
Camila Nascimento de Oliveira ◽  
Umberto Diego Rodrigues de Oliveira ◽  
Gilberto Gonçalves Rodrigues
Keyword(s):  
Spatial Distribution ◽  
Atlantic Forest ◽  
Research Area ◽  
Northeastern Brazil ◽  
Northeast Brazil ◽  
Pitfall Traps ◽  
Night Time ◽  
Forest Remnant ◽  
Richness Estimators ◽  
Collection Methods

Studies on spatial occupation are fundamental to understand amphibian communities. The aim of this study was to record information on the spatial distribution of anurans in the Tejipió forest, state of Pernambuco, Northeastern Brazil. Fieldwork was carried out weekly between October 2011 and April 2012, with daytime and night-time excursions for time-constrained active searching, in forested and open areas, military construction area and water bodies. Pitfall traps and accidental sightings were also used as alternative collection methods. Data were used to calculate richness, rarefaction curves and richness estimators. A total of 21 species were recorded, distributed in six families: Bufonidae (2 spp.); Craugastoridae (1 sp.); Hylidae (8 spp.); Leptodactylidae (8 spp.); Microhylidae (1 sp.) and Phyllomedusidae (1 sp.). Only the species Rhinella jimi was found occupying all sampled habitats in the research area. Adenomera hylaedactyla and Pristimantis ramagii deserve special care in the area because they are specialists, occupying a smaller number of habitats and microhabitats. The community of anurans of the Tejipió forest is similar to those recorded in other areas of the Atlantic Forest at the Pernambuco State, and its knowledge is essential as a basis for conservation of the area. The gradual recovery of this Atlantic Forest remnant would favor the recolonization of fauna and flora and the conservation of local biodiversity.

scholarly journals sparrpowR: a flexible R package to estimate statistical power to identify spatial clustering of two groups and its application

2021 ◽  
Vol 20 (1) ◽  
Author(s):  
Ian D. Buller ◽  
Derek W. Brown ◽  
Timothy A. Myers ◽  
Rena R. Jones ◽  
Mitchell J. Machiela
Keyword(s):  
Relative Risk ◽  
Statistical Power ◽  
Risk Function ◽  
R Package ◽  
Cancer Epidemiology ◽  
Spatial Cluster ◽  
Cluster Detection ◽  
Detection Technique ◽  
Power Calculation ◽  
Spatial Clusters

Abstract Background Cancer epidemiology studies require sufficient power to assess spatial relationships between exposures and cancer incidence accurately. However, methods for power calculations of spatial statistics are complicated and underdeveloped, and therefore underutilized by investigators. The spatial relative risk function, a cluster detection technique that detects spatial clusters of point-level data for two groups (e.g., cancer cases and controls, two exposure groups), is a commonly used spatial statistic but does not have a readily available power calculation for study design. Results We developed sparrpowR as an open-source R package to estimate the statistical power of the spatial relative risk function. sparrpowR generates simulated data applying user-defined parameters (e.g., sample size, locations) to detect spatial clusters with high statistical power. We present applications of sparrpowR that perform a power calculation for a study designed to detect a spatial cluster of incident cancer in relation to a point source of numerous environmental emissions. The conducted power calculations demonstrate the functionality and utility of sparrpowR to calculate the local power for spatial cluster detection. Conclusions sparrpowR improves the current capacity of investigators to calculate the statistical power of spatial clusters, which assists in designing more efficient studies. This newly developed R package addresses a critically underdeveloped gap in cancer epidemiology by estimating statistical power for a common spatial cluster detection technique.

scholarly journals Spatial Agglomeration of China’s Forest Products Manufacturing Industry: Measurement, Characteristics and Determinants

Forests ◽  
2021 ◽  
Vol 12 (8) ◽  
pp. 1006
Author(s):  
Zhenhuan Chen ◽  
Hongge Zhu ◽  
Wencheng Zhao ◽  
Menghan Zhao ◽  
Yutong Zhang
Keyword(s):  
Spatial Distribution ◽  
Spatial Data ◽  
Large Scale ◽  
Manufacturing Industry ◽  
Economies Of Scale ◽  
Forest Products ◽  
Spatial Data Analysis ◽  
Forest Protection ◽  
Spatial Agglomeration ◽  
Continuous Space

China’s forest products manufacturing industry is experiencing the dual pressure of forest protection policies and wood scarcity and, therefore, it is of great significance to reveal the spatial agglomeration characteristics and evolution drivers of this industry to enhance its sustainable development. Based on the perspective of large-scale agglomeration in a continuous space, in this study, we used the spatial Gini coefficient and standard deviation ellipse method to investigate the spatial agglomeration degree and location distribution characteristics of China’s forest products manufacturing industry, and we used exploratory spatial data analysis to investigate its spatial agglomeration pattern. The results show that: (1) From 1988 to 2018, the degree of spatial agglomeration of China’s forest products manufacturing industry was relatively low, and the industry was characterized by a very pronounced imbalance in its spatial distribution. (2) The industry has a very clear core–periphery structure, the spatial distribution exhibits a “northeast-southwest” pattern, and the barycenter of the industrial distribution has tended to move south. (3) The industry mainly has a high–high and low–low spatial agglomeration pattern. The provinces with high–high agglomeration are few and concentrated in the southeast coastal area. (4) The spatial agglomeration and evolution characteristics of China’s forest products manufacturing industry may be simultaneously affected by forest protection policies, sources of raw materials, international trade and the degree of marketization. In the future, China’s forest products manufacturing industry should further increase the level of spatial agglomeration to fully realize the economies of scale.

scholarly journals Isognomon bicolor (C. B. Adams, 1845) (Mollusca: Bivalvia): first record of this invasive species for the States of Paraíba and Alagoas and new records for other localities of Northeastern Brazil

Check List ◽  
2013 ◽  
Vol 9 (1) ◽  
pp. 157 ◽  
Author(s):  
Thelma Lúcia Pereira Dias ◽  
Ellori Laíse Silva Mota ◽  
Anne Isabelley Gondim ◽  
Jacicleide Macedo Oliveira ◽  
Emanuelle Fontenele Rabelo ◽  
...  
Keyword(s):  
Invasive Species ◽  
New Record ◽  
New Records ◽  
Rio Grande ◽  
First Record ◽  
The State ◽  
Northeastern Brazil ◽  
Northeast Brazil ◽  
Littoral Region ◽  
Exotic Invasive

This study provides the first record of the exotic invasive bivalve Isognomon bicolor for the State of Paraíba, Northeastern Brazil. It has been found to occur in at least twelve coastal reefs along the coast. We also present its first record for the State of Alagoas and new record localities for the States of Rio Grande do Norte and Pernambuco, including its occurrence in hypersaline estuaries. From these records the distribution range of I. bicolor has been expanded to the littoral region of Northeast Brazil, where this invasive species seems well established.

scholarly journals SPATIAL AND STATISTICAL ANALYSIS OF LEPTOSPIROSIS IN GUILAN PROVINCE, IRAN

2015 ◽  
Vol XL-1-W5 ◽  
pp. 497-502 ◽  
Author(s):  
A. Mohammadi Nia ◽  
A. Alimohammadi ◽  
R. Habibi ◽  
M. R. Shirzadi
Keyword(s):  
Spatial Distribution ◽  
Pathogenic Bacteria ◽  
Rice Field ◽  
Health Planning ◽  
World Health ◽  
Nearest Neighbour ◽  
Clustering Methods ◽  
Spatial Clusters ◽  
North Of Iran ◽  
Health Organization

The most underdiagnosed water-borne bacterial zoonosis in the world is Leptospirosis which especially impacts tropical and humid regions. According to World Health Organization (WHO), the number of human cases is not known precisely. Available reports showed that worldwide incidences vary from 0.1-1 per 100 000 per year in temperate climates to 10-100 per 100 000 in the humid tropics. Pathogenic bacteria that is spread by the urines of rats is the main reason of water and soil infections. Rice field farmers who are in contact with infected water or soil, contain the most burden of leptospirosis prevalence. In recent years, this zoonotic disease have been occurred in north of Iran endemically. Guilan as the second rice production province (average=750 000 000 Kg, 40% of country production) after Mazandaran, has one of the most rural population (Male=487 679, Female=496 022) and rice workers (47 621 insured workers) among Iran provinces. The main objectives of this study were to analyse yearly spatial distribution and the possible spatial clusters of leptospirosis to better understand epidemiological aspects of them in the province. Survey was performed during the period of 2009–2013 at rural district level throughout the study area. Global clustering methods including the average nearest neighbour distance, Moran’s I and General G indices were utilized to investigate the annual spatial distribution of diseases. At the end, significant spatial clusters have been detected with the objective of informing priority areas for public health planning and resource allocation.

scholarly journals Seroprevalence and spatial distribution dynamics of Yersinia pestis antibodies in dogs and cats from plague foci in the State of Ceará, Northeastern Brazil

2017 ◽  
Vol 50 (6) ◽  
pp. 769-776 ◽  
Author(s):  
Larissa Leão Ferrer de Sousa ◽  
Carlos Henrique Morais de Alencar ◽  
Alzira Maria Paiva de Almeida ◽  
Luciano Pamplona de Góes Cavalcanti
Keyword(s):  
Spatial Distribution ◽  
Yersinia Pestis ◽  
The State ◽  
Northeastern Brazil ◽  
Distribution Dynamics

Mapping the Spatial Distribution Patterns of Personal Time Spent Based on Trip Purpose

2018 ◽  
Vol 9 (2) ◽  
pp. 1-13 ◽  
Author(s):  
Ko Ko Lwin ◽  
Yoshihide Sekimoto
Keyword(s):  
Spatial Distribution ◽  
Survey Data ◽  
Spatial Data ◽  
Distribution Patterns ◽  
Spatial Data Mining ◽  
Urban Transport ◽  
Social Characteristics ◽  
Public Facility ◽  
Spatial Distribution Patterns ◽  
Trip Purpose

Understanding the spatial distribution patterns of the time spent by people based on their trip purpose and other social characteristics is important for sustainable urban transport planning, public facility management, socio-economic development, and other types of policy planning. Although personal trip survey data includes travel behavior and other social characteristics, many are lacking in detail regarding the spatial distribution patterns of individual movements based on time spent, typically due to privacy issues and difficulties in converting non-spatial survey data into a spatial format. In this article, geospatially-enabled personal trip data (Geospatial Big Data), converted from traditional paper-based survey data, are subjected to a spatial data mining process in order to examine the detailed spatial distribution patterns of time spent by the public based on various trip purposes and other social characteristics, using the Tokyo metropolitan area as a case study.

scholarly journals Approach to Urban Environmental Justice Using Exploratory Spatial Data Analysis. The Case of Valencia’s Monumental Trees

2020 ◽  
Vol 12 (18) ◽  
pp. 7760
Author(s):  
Alfonso Gallego-Valadés ◽  
Francisco Ródenas-Rigla ◽  
Jorge Garcés-Ferrer
Keyword(s):  
Spatial Distribution ◽  
Data Analysis ◽  
Environmental Justice ◽  
Spatial Data ◽  
Urban Trees ◽  
Spatial Data Analysis ◽  
Exploratory Spatial Data Analysis ◽  
The Public ◽  
Object Of Study ◽  
The City

Environmental justice has been a relevant object of analysis in recent decades. The generation of patterns in the spatial distribution of urban trees has been a widely addressed issue in the literature. However, the spatial distribution of monumental trees still constitutes an unknown object of study. The aim of this paper was to analyse the spatial distribution of the monumental-tree heritage in the city of Valencia, using Exploratory Spatial Data Analysis (ESDA) methods, in relation to different population groups and to discuss some implications in terms of environmental justice, from the public-policy perspective. The results show that monumental trees are spatially concentrated in high-income neighbourhoods, and this fact represents an indicator of environmental inequality. This diagnosis can provide support for decision-making on this matter.

Ticks (Acari: Argasidae and Ixodidae) infesting amphibians and reptiles in Northeastern Brazil

2018 ◽  
Vol 23 (8) ◽  
pp. 1497 ◽  
Author(s):  
Edna Paulino Alcantara ◽  
Cristiana Ferreira Silva ◽  
Robson Waldemar Ávila ◽  
Richard Campos Pacheco ◽  
Thiago Fernandes Martins ◽  
...  
Keyword(s):  
Northeastern Brazil ◽  
Northeast Brazil ◽  
Brazilian Northeast ◽  
Host Associations

Ticks collected on 21 different species of amphibians and reptiles captured during 2001 to 2017 in the northeast Brazil were identified. Overall, 227 individuals (185 larvae, 32 nymphs, 7 adults females and 3 males) identified as follow: Amblyomma dissimile, Amblyomma rotundatum, Amblyomma sp. larvae, Ornithodoros mimon, Ornithodoros rietcorreai, and an Ornithodoros sp. Herein, we present 25 new tick-host associations, thus contributing to the knowledge on tick-fauna associated to amphibians and reptiles from Brazilian northeast.

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