Determination of ecosystem carbon-stock distributions in the flux footprint of an eddy-covariance tower in a coastal forest in British Columbia

2011 ◽  
Vol 41 (7) ◽  
pp. 1380-1393 ◽  
Author(s):  
Colin J. Ferster ◽  
J.A. (Tony) Trofymow ◽  
Nicholas C. Coops ◽  
Baozhang Chen ◽  
T. Andrew Black ◽  
...  
Keyword(s):  
Spatial Distribution ◽  
Regression Model ◽  
Eddy Covariance ◽  
Spatial Prediction ◽  
Geospatial Data ◽  
Data Sets ◽  
Forest Land ◽  
Flux Tower ◽  
C Stocks ◽  
C Stock

An important consideration when interpreting eddy-covariance (EC) flux-tower measurements is the spatial distribution of forest land surface cover and soil type within the EC flux-tower footprint. At many EC flux-tower sites, there is a range of geospatial data available with the ability to estimate the spatial distribution of forest land cover and soils. Developing methods that utilize multiple geospatial data sets will result in more thorough estimates of ecosystem C stock distributions. The objective of this study was to develop, apply, and validate methods to obtain comprehensive estimates of the spatial distribution of ecosystem C stock components from live-tree, detritus, and soil pools within an EC flux-tower footprint. First, a set of geospatial data sets was collected and assessed for its predictive ability for the measured aboveground C stocks. Next, large tree and snag aboveground C stocks were estimated using two methods: (i) a geospatial regression model, and (ii) most similar neighbor (k-MSN) spatial prediction methodology, and the results were compared with those of a multiple linear regression model using light detection and ranging (LiDAR) data alone. Finally, we applied the spatial prediction methodology to estimate the spatial distribution of other C stock components (including soil C and woody debris).

scholarly journals C Stock of Top Soil and It Spatial Distribution in Mangrove Community of Trimulyo, Semarang City

2018 ◽  
Vol 73 ◽  
pp. 03006
Author(s):  
Dhita Prasisca Mutiatari ◽  
Rudhi Pribadi ◽  
Nana Kariada Tri Martuti
Keyword(s):  
Spatial Distribution ◽  
Carbon Sink ◽  
Soil Layer ◽  
Mangrove Ecosystem ◽  
Soil C ◽  
Distribution Maps ◽  
Top Soil ◽  
C Stocks ◽  
Significant Difference ◽  
C Stock

Mangrove ecosystem plays important role as carbon sink, not only on mangrove community but also on the top soil. The purposes of this research were 1) to estimates and compare C-stocks in vegetation and non-vegetation mangrove soils (represented by aquaculture ponds and mudflats); 2) modeling the spatial distribution of soil C-stocks in the study area. The purposive sampling method was used to determine 16 sample plots representing vegetation and non-vegetation mangroves. In each plot, the soil samples were taken on top soil layer (0-10 cm). For general display of spatial distribution maps of soil C-stocks, spatial interpolation is used by the Ordinary Kriging method. The result showed that total of soil C-stocks in coastal area of Trimulyo was 148.53 MgC ha-1, with composition of 53.59% in mangrove vegetation, 38.82% and 7.57% in cultivation pond and mudflat, respectively. Statistical analysis with ANOVA test showed no significant difference (ρ = 0.972) between soil C stock in vegetation and non-vegetation mangrove. It shows that the water column on the coast of Trimulyo has great potential as a carbon store.

scholarly journals A Basin-Scale Estimation of Carbon Stocks of a Forest Ecosystem Characterized by Spatial Distribution and Contributive Features in the Liuxihe River Basin of Pearl River Delta

2016 ◽  
Author(s):  
Chao Zhang ◽  
Beicheng Xia ◽  
Junyu Lin
Keyword(s):  
Spatial Distribution ◽  
River Basin ◽  
Forest Ecosystem ◽  
Forest Ecosystems ◽  
Organic C ◽  
C Stocks ◽  
Basin Scale ◽  
Field Samples ◽  
C Stock ◽  
Forest C

Forest ecosystems make a greater contribution to carbon (C) stocks than any other terrestrial ecosystem. To understand the role of regional forest ecosystems in global climate change and carbon exchange, forest C stock and its spatial distribution within the small (2,300 km2) Liuxihe River basin were analyzed to determine the different contributors to the C stock. Forest C stocks were quantified by measuring the biomass of trees, understory vegetation, litter and roots, as well as soil organic C, using data from field samples and laboratory experiments. The results showed that forests stored 38.04 Tg C in the entire basin, with secondary and planted forests accounting for 89.82% and 10.18%, respectively, of the stored C. Five types of forests, a subtropical evergreen broad-leaved forest, a subtropical coniferous and broad-leaved mixed forest, a subtropical coniferous forest, a timber forest, and a non-wood forest, stored 257.55 ± 15.01, 218.92 ± 9.59, 195.24 ± 18.29, 177.42 ± 17.55, and 117.86 ± 6.04 Mg C ha−1, respectively. In the forest ecosystem C stocks of the basin, soils averagely contribute about 73.78%, not including root underground biomass. It provides a comprehensive method for forest ecosystem carbon investigation and forest management in small basin scale.

scholarly journals Increasing biomass carbon stocks in trees outside forests in China over the last three decades

2014 ◽  
Vol 11 (15) ◽  
pp. 4115-4122 ◽  
Author(s):  
Z. D. Guo ◽  
H. F. Hu ◽  
Y. D. Pan ◽  
R. A. Birdsey ◽  
J. Y. Fang
Keyword(s):  
Forest Inventory ◽  
Initial Period ◽  
Forest Biomass ◽  
National Forest Inventory ◽  
Forest Land ◽  
Trees Outside Forests ◽  
C Cycle ◽  
C Stocks ◽  
C Stock ◽  
Definition Of

Abstract. Trees outside forests (TOF) play important roles in national economies, ecosystem services, and international efforts for mitigating climate warming. Detailed assessment of the dynamics of carbon (C) stocks in China's TOF is necessary for fully evaluating the role of the country's trees in the national C cycle. This study is the first to explore the changes in biomass C stocks of China's TOF over the last three decades, using the national forest inventory data in six periods from 1977 to 2008. According to the definition of the forest inventory, China's TOF could be categorized into three groups: woodlands, shrubberies, and trees on non-forest land (including four-side greening trees, defined in the article, and scattered trees). We estimated biomass C stocks of woodlands and trees on non-forest land by using the provincial biomass-volume conversion equations derived from the data of low-canopy forests, and estimated the biomass C stocks of shrubberies using the provincial mean biomass density. Total TOF biomass C stock increased by 62.7% from 823 Tg C (1 Tg = 1012 g) in the initial period of 1977–1981 to 1339 Tg C in the last period of 2004–2008. As a result, China's TOF have accumulated biomass C of 516 Tg during the study period, with 12, 270, and 234 Tg in woodlands, shrubberies, and trees on non-forest land, respectively. The annual biomass C sink of China's TOF averaged 19.1 Tg C yr−1, offsetting 2.1% of the contemporary fossil-fuel CO2 emissions in the country. These estimates are equal to 16.5–20.7% of the contemporary total forest biomass C stock and 27.2% of the total forest biomass C sink in the country, suggesting that TOF are substantial components in China's tree C budget.

scholarly journals Forest Land Quality Evaluation and the Protection Zoning of Subtropical Humid Evergreen Broadleaf Forest Region Based on the PSO-TOPSIS Model and the Local Indicator of Spatial Association: A Case Study of Hefeng County, Hubei Province, China

Forests ◽  
2021 ◽  
Vol 12 (3) ◽  
pp. 325
Author(s):  
Li Wang ◽  
Yong Zhou ◽  
Qing Li ◽  
Qian Zuo ◽  
Haoran Gao ◽  
...  
Keyword(s):  
Spatial Distribution ◽  
Quality Evaluation ◽  
Spatial Association ◽  
Forest Land ◽  
Mountain Regions ◽  
Land Quality ◽  
Land Protection ◽  
Protection Zones ◽  
Forest Region ◽  
Topsis Model

Forest land is the carrier for growing forests. It is of great significance to evaluate the forest land quality scientifically and delineate forestland protection zones reasonably for realizing better forest land management, promoting ecological civilization construction, and coping with global climate change. In this study, taking Hefeng County, Hubei Province, a subtropical humid evergreen broad-leaved forest region in China, as the study area, 14 indicators were selected from four dimensions—climatic conditions, terrain, soil conditions, and socioeconomics—to construct a forest land quality evaluation index system. Based on the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) model, we introduced the Particle Swarm Optimization (PSO) algorithm to design the evaluation model to evaluate the forest land quality and analyze the distribution of forest land quality in Hefeng. Further, we used the Local Indicator of Spatial Association (LISA) to explore the spatial distribution of forest land quality and delineate the forest land protection zones. The results showed the following: (1) the overall quality of forest land was high, with some variability between regions. The range of Forest Land Quality Index (FLQI) in Hefeng was 0.4091–0.8601, with a mean value of 0.6337. The forest land quality grades were mainly first and second grade, with the higher-grade forest land mainly distributed in the central and southeastern low mountain regions of Zouma, Wuli, and Yanzi. The lower-grade forest land was mainly distributed in the northwestern middle and high mountain regions of Zhongying, Taiping, and Rongmei. (2) The global spatial autocorrelation index of forest land quality in Hefeng County was 0.7562, indicating that the forest land quality in the county had a strong spatial similarity. The spatial distribution of similarity types high-high (HH) and low-low (LL) was more clustered, while the spatial distribution of dissimilarity types high-low (HL) and low-high (LH) was generally dispersed. (3) Based on the LISA of forest land quality, forest land protection zones were divided into three types: key protection zones (KPZs), active protection zones (APZs), and general protection zones (GPZs). The forest land protection zoning basically coincided with the forest land quality. Combining the characteristics of self-correlated types in different forestland protection zones, corresponding management and protection measures were proposed. This showed that the PSO-TOPSIS model can be effectively used for forest land quality evaluation. At the same time, the spatial attributes of forest land were incorporated into the development of forest land protection zoning scheme, which expands the method of forest land protection zoning, and can provide a scientific basis and methodological reference for the reasonable formulation of forest land use planning in Hefeng County, while also serving as a reference for similar regions and countries.

scholarly journals Do galactic bars depend on environment?: an information theoretic analysis of Galaxy Zoo 2

2020 ◽  
Vol 501 (1) ◽  
pp. 994-1001
Author(s):  
Suman Sarkar ◽  
Biswajit Pandey ◽  
Snehasish Bhattacharjee
Keyword(s):  
Spatial Distribution ◽  
Mutual Information ◽  
Local Density ◽  
Statistical Significance ◽  
Distribution Functions ◽  
Cumulative Distribution ◽  
Host Galaxy ◽  
Data Sets ◽  
Data Set ◽  
Information Theoretic

ABSTRACT We use an information theoretic framework to analyse data from the Galaxy Zoo 2 project and study if there are any statistically significant correlations between the presence of bars in spiral galaxies and their environment. We measure the mutual information between the barredness of galaxies and their environments in a volume limited sample (Mr ≤ −21) and compare it with the same in data sets where (i) the bar/unbar classifications are randomized and (ii) the spatial distribution of galaxies are shuffled on different length scales. We assess the statistical significance of the differences in the mutual information using a t-test and find that both randomization of morphological classifications and shuffling of spatial distribution do not alter the mutual information in a statistically significant way. The non-zero mutual information between the barredness and environment arises due to the finite and discrete nature of the data set that can be entirely explained by mock Poisson distributions. We also separately compare the cumulative distribution functions of the barred and unbarred galaxies as a function of their local density. Using a Kolmogorov–Smirnov test, we find that the null hypothesis cannot be rejected even at $75{{\ \rm per\ cent}}$ confidence level. Our analysis indicates that environments do not play a significant role in the formation of a bar, which is largely determined by the internal processes of the host galaxy.

scholarly journals Effect of Restoration Actions on Organic Carbon Pools in the Lagoon—Delta Ciénaga Grande de Santa Marta, Colombian Caribbean

Water ◽  
2021 ◽  
Vol 13 (9) ◽  
pp. 1297
Author(s):  
Laura Victoria Perdomo-Trujillo ◽  
Jose Ernesto Mancera-Pineda ◽  
Jairo Humberto Medina-Calderón ◽  
David Alejandro Sánchez-Núñez ◽  
Marie-Luise Schnetter
Keyword(s):  
Organic Matter Content ◽  
Matter Content ◽  
Partial Recovery ◽  
Management Intervention ◽  
Management Measures ◽  
C Stocks ◽  
C Stock ◽  
Magdalena River ◽  
Indirect Relationship ◽  
Mangrove Degradation

Mangroves provide multiple ecosystem services and are essential for mitigating global warming owing to their capacity to store large carbon (C) stocks. Due to widespread mangrove degradation, actions have been implemented to restore them worldwide. An important representative case in Colombia is the Ciénaga Grande de Santa Marta’s restoration plan. This management intervention focused on restoring the natural hydrological functioning after massive mangrove mortality (~25,000 ha) due to soil hyper-salinization after river water input from the Magdalena River was eliminated. A partial recovery occurred during subsequent years, and hydrological management is still being implemented today. To understand how the degradation and subsequent management have affected mangrove C stocks, we compared C stocks in stands with different intervention levels reflected in their current forest structure. We found that the total C stock (398–1160 Mg C ha−1) was within the range measured in other neotropical mangroves without vegetation deterioration. The aboveground C was significantly higher in the stands where hydraulic connectivity was restored. By contrast, the belowground C was higher in the stands with low hydraulic connectivity due to channel clogging and a lack of sufficient maintenance. Our results show that hydrological management measures influenced above- and belowground C stocks, even at a 2 m depth. In addition, a strong indirect relationship useful for estimating carbon content from organic matter content was found.

scholarly journals Topographic Position, Land Use and Soil Management Effects on Soil Organic Carbon (Vineyard Region of Niš, Serbia)

Agronomy ◽  
2021 ◽  
Vol 11 (7) ◽  
pp. 1438
Author(s):  
Snežana Jakšić ◽  
Jordana Ninkov ◽  
Stanko Milić ◽  
Jovica Vasin ◽  
Milorad Živanov ◽  
...  
Keyword(s):  
Land Use ◽  
Surface Layer ◽  
Spatial Distribution ◽  
Soil Erosion ◽  
Organic Carbon ◽  
Soil Organic Carbon ◽  
Soil Compaction ◽  
Soil Management ◽  
Forest Land ◽  
Topographic Position

Spatial distribution of soil organic carbon (SOC) is the result of a combination of various factors related to both the natural environment and anthropogenic activities. The aim of this study was to examine (i) the state of SOC in topsoil and subsoil of vineyards compared to the nearest forest, (ii) the influence of soil management on SOC, (iii) the variation in SOC content with topographic position, (iv) the intensity of soil erosion in order to estimate the leaching of SOC from upper to lower topographic positions, and (v) the significance of SOC for the reduction of soil’s susceptibility to compaction. The study area was the vineyard region of Niš, which represents a medium-sized vineyard region in Serbia. About 32% of the total land area is affected, to some degree, by soil erosion. However, according to the mean annual soil loss rate, the total area is classified as having tolerable erosion risk. Land use was shown to be an important factor that controls SOC content. The vineyards contained less SOC than forest land. The SOC content was affected by topographic position. The interactive effect of topographic position and land use on SOC was significant. The SOC of forest land was significantly higher at the upper position than at the middle and lower positions. Spatial distribution of organic carbon in vineyards was not influenced by altitude, but occurred as a consequence of different soil management practices. The deep tillage at 60–80 cm, along with application of organic amendments, showed the potential to preserve SOC in the subsoil and prevent carbon loss from the surface layer. Penetrometric resistance values indicated optimum soil compaction in the surface layer of the soil, while low permeability was observed in deeper layers. Increases in SOC content reduce soil compaction and thus the risk of erosion and landslides. Knowledge of soil carbon distribution as a function of topographic position, land use and soil management is important for sustainable production and climate change mitigation.

scholarly journals Carbon stocks of homestead forests have a mitigation potential to climate change in Bangladesh

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Tarit Kumar Baul ◽  
Tajkera Akhter Peuly ◽  
Rajasree Nandi ◽  
Lars Holger Schmidt ◽  
Shyamal Karmakar
Keyword(s):  
Species Diversity ◽  
Stand Structure ◽  
Diversity Index ◽  
Carbon Stocks ◽  
Small Scale ◽  
Species Diversity Index ◽  
C Stocks ◽  
Homestead Forests ◽  
C Stock ◽  
Low Altitude

AbstractA total of 176 homestead forests at three altitudes in the Chittagong Hill Tracts, Bangladesh were randomly surveyed to estimate carbon (C) stocks and how stand structure affects the biomass C. All woody vegetations were measured, and litter and soil (0–30 cm depth) were sampled. The tree biomass C stock in the top two altitude forests was up to 37–48% higher than in low altitude, owing to significantly higher tree density and species diversity. An increase in species diversity index by one unit increased the biomass stock by 23 Mg C ha−1. The C stock of litterfall in low altitude forests was 22–28% higher than in the top two altitude due to the deposition of litters downslope and deliberate use of mulch for soil improvement and conservation, resulting in up to 5% higher total soil C. The topsoil C was 10–25% higher than the deeper soil, depending on the altitude. The forest stored 89 Mg C ha−1, indicating a potential for C sequestration in trees outside forest. This study would help policymakers to strengthen the recognition of small-scale forests for mitigation in REDD + (reducing emissions from deforestation and forest degradation, the role of conservation, sustainable management of forests, and enhancement of forest carbon stocks) and support owners through C credits from sustainably managed forests.

GENE SELECTION USING LOGISTIC REGRESSIONS BASED ON AIC, BIC AND MDL CRITERIA

2005 ◽  
Vol 01 (01) ◽  
pp. 129-145 ◽  
Author(s):  
XIAOBO ZHOU ◽  
XIAODONG WANG ◽  
EDWARD R. DOUGHERTY
Keyword(s):  
Logistic Regression ◽  
Regression Model ◽  
Logistic Regression Model ◽  
Gene Selection ◽  
Information Criterion ◽  
Cancer Classification ◽  
Data Sets ◽  
Classification Methods ◽  
Gene Expressions ◽  
Experimental Conditions

In microarray-based cancer classification, gene selection is an important issue owing to the large number of variables (gene expressions) and the small number of experimental conditions. Many gene-selection and classification methods have been proposed; however most of these treat gene selection and classification separately, and not under the same model. We propose a Bayesian approach to gene selection using the logistic regression model. The Akaike information criterion (AIC), the Bayesian information criterion (BIC) and the minimum description length (MDL) principle are used in constructing the posterior distribution of the chosen genes. The same logistic regression model is then used for cancer classification. Fast implementation issues for these methods are discussed. The proposed methods are tested on several data sets including those arising from hereditary breast cancer, small round blue-cell tumors, lymphoma, and acute leukemia. The experimental results indicate that the proposed methods show high classification accuracies on these data sets. Some robustness and sensitivity properties of the proposed methods are also discussed. Finally, mixing logistic-regression based gene selection with other classification methods and mixing logistic-regression-based classification with other gene-selection methods are considered.

scholarly journals Tree species richness increases ecosystem carbon storage in subtropical forests

2018 ◽  
Vol 285 (1885) ◽  
pp. 20181240 ◽  
Author(s):  
Xiaojuan Liu ◽  
Stefan Trogisch ◽  
Jin-Sheng He ◽  
Pascal A. Niklaus ◽  
Helge Bruelheide ◽  
...  
Keyword(s):  
Species Richness ◽  
Tree Species ◽  
C Sequestration ◽  
Stand Age ◽  
Southeast China ◽  
Subtropical Forests ◽  
C Stocks ◽  
C Stock ◽  
Below Ground ◽  
Time Periods

Forest ecosystems are an integral component of the global carbon cycle as they take up and release large amounts of C over short time periods (C flux) or accumulate it over longer time periods (C stock). However, there remains uncertainty about whether and in which direction C fluxes and in particular C stocks may differ between forests of high versus low species richness. Based on a comprehensive dataset derived from field-based measurements, we tested the effect of species richness (3–20 tree species) and stand age (22–116 years) on six compartments of above- and below-ground C stocks and four components of C fluxes in subtropical forests in southeast China. Across forest stands, total C stock was 149 ± 12 Mg ha −1 with richness explaining 28.5% and age explaining 29.4% of variation in this measure. Species-rich stands had higher C stocks and fluxes than stands with low richness; and, in addition, old stands had higher C stocks than young ones. Overall, for each additional tree species, the total C stock increased by 6.4%. Our results provide comprehensive evidence for diversity-mediated above- and below-ground C sequestration in species-rich subtropical forests in southeast China. Therefore, afforestation policies in this region and elsewhere should consider a change from the current focus on monocultures to multi-species plantations to increase C fixation and thus slow increasing atmospheric CO 2 concentrations and global warming.

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