scholarly journals Factors Affecting Spatial Variation in Vegetation Carbon Density in Pinus massoniana Lamb. Forest in Subtropical China

Forests ◽  
2019 ◽  
Vol 10 (10) ◽  
pp. 880 ◽  
Author(s):  
Pan ◽  
Sun ◽  
Ouyang ◽  
Zang ◽  
Rao ◽  
...  
Keyword(s):  
Carbon Sequestration ◽  
Forest Management ◽  
Spatial Variation ◽  
Pinus Massoniana ◽  
Moran’S I ◽  
Spatial Clusters ◽  
Carbon Density ◽  
Moran's I ◽  
Pinus Massoniana Lamb ◽  
Vegetation Carbon

Carbon density is an important indicator of carbon sequestration capacity in forest ecosystems. We investigated the vegetation carbon density of Pinus massoniana Lamb. forest in the Jiangxi Province. Based on plots investigation and measurement of the carbon content of the samples, the influencing factors and spatial variation of vegetation carbon density (including the tree layer, understory vegetation layer and litter layer) were analysed. The results showed that the average vegetation carbon density value of P. massoniana forest was 52 Mg·ha−1. The vegetation carbon density was significantly (p < 0.01) and positively correlated with the stand age, mean annual precipitation, elevation and stand density and negatively correlated with the slope and mean annual temperature. Forest management had a significant impact on vegetation carbon density. To manage P. massoniana forest for carbon sequestration as the primary objective, near-natural forest management theory should be followed, e.g., replanting broadleaf trees. These measures would promote positive succession and improve the vegetation carbon sequestration capacity of forests. The results from the global Moran’s I showed that the vegetation carbon density of P. massoniana forest had significant positive spatial autocorrelation. The results of local Moran’s I showed that the high-high spatial clusters were mainly distributed in the southern, western and eastern parts of the province. The low-low spatial clusters were distributed in the Yushan Mountains and in the northern part of the province. The fitting results of the semivariogram models showed that the spherical model was the best fitting model for vegetation carbon density. The ratio of nugget to sill was 0.45, indicating a moderate spatial correlation of carbon density. The vegetation carbon density based on kriging spatial interpolation was mainly concentrated in the range of 32.5–69.8 Mg·ha−1. The spatial distribution of vegetation carbon density regularity was generally low in the middle region and high in the peripheral region, which was consistent with the terrain characteristics of the study area.

scholarly journals Analysis of correlation and variation of Cadmium in soil around Enterprises in Fujiang River Basin

2021 ◽  
Author(s):  
REN Jiaguo ◽  
FAN Kun ◽  
SHI Chenxue ◽  
ZHANG Yutao ◽  
WU qianqian ◽  
...  
Keyword(s):  
Spatial Variation ◽  
River Basin ◽  
Quality Standard ◽  
Moran’S I ◽  
Moderate Intensity ◽  
Moran's I ◽  
Risk Screening ◽  
Spatial Differences ◽  
Cluster Points ◽  
Soil Cd

Abstract In order to explore the correlation and spatial variation law of Cadmium (Cd) content in the soil around enterprises in the Fujiang River Basin, Global Moran's I and Anselin Local Moran's I were used to analyze the correlation, and the spatial structure was analyzed by using semivariogram. The results show that: the overall level of Cd in the soil around the enterprises in Fujiang River Basin is relatively low, which does not exceed the risk screening value of the national soil environmental quality standard (GB15618-2018), and only the content in some regions exceeds the risk screening value; The spatial correlation of soil Cd in different directions and distances is different. The distribution of high value cluster points and abnormal value points of soil Cd is less, most of them belong to low value cluster points and insignificant points, and they have a certain correlation with the number of enterprise distribution and geological background; The spatial variation of Cd in soil is of moderate intensity, and the spatial differences in different directions are different, according to the order from large to small: 0° > 90° > 45° >135°, the spatial differences are consistent with the distribution of local cold hot spots and outliers.

The application of Local Moran's I to identify spatial clusters and hot spots of Pb, Mo and Ti in urban soils of Yerevan

2019 ◽  
Vol 104 ◽  
pp. 116-123 ◽  
Author(s):  
Gevorg Tepanosyan ◽  
Lilit Sahakyan ◽  
Chaosheng Zhang ◽  
Armen Saghatelyan
Keyword(s):  
Hot Spots ◽  
Urban Soils ◽  
Moran’S I ◽  
Spatial Clusters ◽  
Moran's I

Carbon sequestration in tropical meandering rivers

2020 ◽  
Author(s):  
Luca Salerno ◽  
Francesca Bassani ◽  
Carlo Camporeale
Keyword(s):  
Carbon Sequestration ◽  
Riparian Vegetation ◽  
Amazon Basin ◽  
Riparian Zone ◽  
Anthropogenic Activities ◽  
Active Role ◽  
Carbon Density ◽  
Meandering Rivers ◽  
Vegetation Carbon ◽  
Lateral Erosion

&lt;p&gt;Lateral activity and morphological evolutions of fluvial corridors play an active role in the river carbon cycle that is not completely understood so far. Organic carbon (OC) is produced and conveyed by river dynamics, but a quantification of OC sequestration from river systems is still lacking.&lt;br&gt;By combining stochastic processes and deterministic modeling for the meandering evolution, we develop a minimalistic model to evaluate the amount of carbon moved by tropical meandering rivers through the reworking of riverbed and riparian vegetation. The model assess the eroded area (by river sinuosity) and couples it with satellite-based data of vegetation carbon density. We assess the carbon sequestration in riparian zone of six fluvial reaches of the Amazon basin, and test the results with satellite-based data of vegetated area lost in the same regions. The process of continuous rejuvenation of the riparian community, due to uprooting of trees by the stream followed by recolonization, allows the riparian zone to produce more OC compared to an equivalent riparian vegetated area not subjected to flood disturbances and lateral erosion. This study shows that river carbon sequestration is closely connected to the river activity and is negatively affected by the anthropogenic activities, such as damming and mining.&lt;/p&gt;

scholarly journals Spatial Clustering Analysis of the COVID-19 Pandemic: A Case Study of the Fourth Wave in Vietnam

2021 ◽  
Vol 14 (4) ◽  
pp. 140-147 ◽  
Author(s):  
Danh-tuyen Vu ◽  
Tien-thanh Nguyen ◽  
Anh-huy Hoang
Keyword(s):  
Spatial Clustering ◽  
Moran’S I ◽  
Spatial Clusters ◽  
Moran's I ◽  
Auto Correlation ◽  
Two Phases ◽  
Novel Coronavirus ◽  
Almost All ◽  
Spatial Outliers ◽  
Fourth Wave

An outbreak of the 2019 Novel Coronavirus Disease (COVID-19) in China caused by the emergence of Severe Acute Respiratory Syndrome CoronaVirus 2 (SARSCoV2) spreads rapidly across the world and has negatively affected almost all countries including such the developing country as Vietnam. This study aimed to analyze the spatial clustering of the COVID-19 pandemic using spatial auto-correlation analysis. The spatial clustering including spatial clusters (high-high and low-low), spatial outliers (low-high and high-low), and hotspots of the COVID-19 pandemic were explored using the local Moran’s I and Getis-Ord’s G* i statistics. The local Moran’s I and Moran scatterplot were first employed to identify spatial clusters and spatial outliers of COVID-19. The Getis-Ord’s G* i statistic was then used to detect hotspots of COVID-19. The method has been illustrated using a dataset of 86,277 locally transmitted cases confirmed in two phases of the fourth COVID-19 wave in Vietnam. It was shown that significant low-high spatial outliers and hotspots of COVID-19 were first detected in the NorthEastern region in the first phase, whereas, high-high clusters and low-high outliers and hotspots were then detected in the Southern region of Vietnam. The present findings confirm the effectiveness of spatial auto-correlation in the fight against the COVID-19 pandemic, especially in the study of spatial clustering of COVID-19. The insights gained from this study may be of assistance to mitigate the health, economic, environmental, and social impacts of the COVID-19 pandemic.

scholarly journals Using Moran's I and GIS to study the spatial pattern of forest litter carbon density in a subtropical region of southeastern China

2014 ◽  
Vol 11 (8) ◽  
pp. 2401-2409 ◽  
Author(s):  
W. J. Fu ◽  
P. K. Jiang ◽  
G. M. Zhou ◽  
K. L. Zhao
Keyword(s):  
Spatial Pattern ◽  
Spatial Patterns ◽  
Forest Ecosystem ◽  
Forest Litter ◽  
Zhejiang Province ◽  
Moran’S I ◽  
Carbon Density ◽  
Southeastern China ◽  
Moran's I ◽  
Density Values

Abstract. Spatial pattern information of carbon density in forest ecosystem including forest litter carbon (FLC) plays an important role in evaluating carbon sequestration potentials. The spatial variation of FLC density in the typical subtropical forests in southeastern China was investigated using Moran's I, geostatistics and a geographical information system (GIS). A total of 839 forest litter samples were collected based on a 12 km (south–north) × 6 km (east–west) grid system in Zhejiang province. Forest litter carbon density values were very variable, ranging from 10.2 kg ha−1 to 8841.3 kg ha−1, with an average of 1786.7 kg ha−1. The aboveground biomass had the strongest positive correlation with FLC density, followed by forest age and elevation. Global Moran's I revealed that FLC density had significant positive spatial autocorrelation. Clear spatial patterns were observed using local Moran's I. A spherical model was chosen to fit the experimental semivariogram. The moderate "nugget-to-sill" (0.536) value revealed that both natural and anthropogenic factors played a key role in spatial heterogeneity of FLC density. High FLC density values were mainly distributed in northwestern and western part of Zhejiang province, which were related to adopting long-term policy of forest conservation in these areas, while Hang-Jia-Hu (HJH) Plain, Jin-Qu (JQ) Basin and coastal areas had low FLC density due to low forest coverage and intensive management of economic forests. These spatial patterns were in line with the spatial-cluster map described by local Moran's I. Therefore, Moran's I, combined with geostatistics and GIS, could be used to study spatial patterns of environmental variables related to forest ecosystem.

scholarly journals The Impact of Near Natural Forest Management on the Carbon Stock and Sequestration Potential of Pinus massoniana (Lamb.) and Cunninghamia lanceolata (Lamb.) Hook. Plantations

Forests ◽  
2019 ◽  
Vol 10 (8) ◽  
pp. 626 ◽  
Author(s):  
Angang Ming ◽  
Yujing Yang ◽  
Shirong Liu ◽  
You Nong ◽  
Hua Li ◽  
...  
Keyword(s):  
Climate Change ◽  
Forest Management ◽  
Pinus Massoniana ◽  
Natural Forest ◽  
Sequestration Potential ◽  
C Stock ◽  
Pinus Massoniana Lamb ◽  
The Impact ◽  
Natural Forest Management

Quantifying the impact of forest management on carbon (C) stock is important for evaluating and enhancing the ability of plantations to mitigate climate change. Near natural forest management (NNFM) through species enrichment planting in single species plantations, structural adjustment, and understory protection is widely used in plantation management. However, its long-term effect on forest ecosystem C stock remains unclear. We therefore selected two typical coniferous plantations in southwest China, Pinus massoniana (Lamb.) and Cunninghamia lanceolate (Lamb.) Hook., to explore the effects of long-term NNFM on ecosystem C storage. The C content and stock of different components in the pure plantations of P. massoniana (PCK) and C. lanceolata (CCK), and their corresponding near natural managed forests (PCN and CCN, respectively), were investigated during eight years of NNFM beginning in 2008. In 2016, there was no change in the vegetation C content, while soil C content in the 0–20 cm and 20–40 cm layers significantly increased, compared to the pure forests. In the P. massoniana and C. lanceolata plantations, NNFM increased the ecosystem C stock by 31.8% and 24.3%, respectively. Overall, the total C stock of soil and arborous layer accounted for 98.2%–99.4% of the whole ecosystem C stock. The increase in the biomass of the retained and underplanted trees led to a greater increase in the arborous C stock in the near natural forests than in the controls. The NNFM exhibited an increasingly positive correlation with the ecosystem C stock over time. Long-term NNFM enhances ecosystem C sequestration by increasing tree growth rate at individual and stand scales, as well as by likely changing the litter decomposition rate resulting from shifts in species composition and stand density. These results indicated that NNFM plays a positive role in achieving multi-objective silviculture and climate change mitigation.

scholarly journals Spatial Filtering with EViews and MATLAB

2016 ◽  
Vol 36 (1) ◽  
Author(s):  
Robert Ferstl
Keyword(s):  
Data Analysis ◽  
Spatial Autocorrelation ◽  
Spatial Data ◽  
Spatial Filtering ◽  
Spatial Data Analysis ◽  
Moran’S I ◽  
Spatial Clusters ◽  
Moran's I ◽  
Detection Of Outliers ◽  
Filtering Procedure

This article summarizes the ideas behind a few programs we developed for spatial data analysis in EViews and MATLAB. They allow the user to check for spatial autocorrelation using Moran’s I and provide a spatial filtering procedure based on the Gi statistic by Getis and Ord (1992). We have also implemented graphical tools like Moran Scatterplots for the detection of outliers or local spatial clusters.

scholarly journals Using Moran's I and GIS to study spatial pattern of forest litter carbon density in typical subtropical region, China

2013 ◽  
Vol 10 (12) ◽  
pp. 19245-19270 ◽  
Author(s):  
W. J. Fu ◽  
P. K. Jiang ◽  
G. M. Zhou ◽  
K. L. Zhao
Keyword(s):  
Spatial Patterns ◽  
Spherical Model ◽  
Forest Litter ◽  
Zhejiang Province ◽  
Geographical Information ◽  
Moran’S I ◽  
Anthropogenic Factors ◽  
Carbon Density ◽  
Moran's I ◽  
Density Values

Abstract. The spatial variation of forest litter carbon (FLC) density in the typical subtropical forests in southeast China was investigated using Moran's I, geostatistics and a geographical information system (GIS). A total of 839 forest litter samples were collected based on a 12 km (South–North) × 6 km (East–West) grid system in Zhejiang Province. Forest litter carbon density values were very variable, ranging from 10.2 kg ha−1 to 8841.3 kg ha−1, with an average of 1786.7 kg ha−1. The aboveground biomass had the strongest positive correlation with FLC density, followed by forest age and elevation. Global Moran's I revealed that FLC density had significant positive spatial autocorrelation. Clear spatial patterns were observed using Local Moran's I. A spherical model was chosen to fit the experimental semivariogram. The moderate "nugget-to-sill" (0.536) value revealed that both natural and anthropogenic factors played a key role in spatial heterogeneity of FLC density. High FLC density values were mainly distributed in northwestern and western part of Zhejiang province, which were related to adopting long-term policy of forest conservation in these areas. While Hang-Jia-Hu (HJH) Plain, Jin-Qu (JQ) basin and coastal areas had low FLC density due to low forest coverage and intensive management of economic forests. These spatial patterns in distribution map were in line with the spatial-cluster map described by local Moran's I. Therefore, Moran's I, combined with geostatistics and GIS could be used to study spatial patterns of environmental variables related to forest ecosystem.

Sign in / Sign up

Export Citation Format

Share Document