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Carbon Stocks in Aboveground and Belowground Biomass of Sub-Humid Tropical Forest in Southwestern Nigeria
Habeeb Ajibola Yusuf, Jesumbo Joseph Oludipe, Oluwatoyin Olajumoke Adeoye, Idowu Ezekiel Olorunfemi
Open Access Library Journal (OALib Journal) , 2019, DOI: 10.4236/oalib.1105588
This study aimed at estimation of carbon stocks in aboveground and below-ground biomass of sub-humid young forest land in south-western Nigeria. Different species of trees were analysed. Results gathered indicated that the forest studied had an average aboveground carbon stock of live trees as 0.00407 t. Terminalia superba (0.00698 t C) has the highest carbon stocks and diameter at breast height (Dbh) of 5.80 cm while Triplochiton scleroxy-lon contained the least stock of carbon (0.00212 t C) and Dbh of 3.55 cm. From the analysis, it was observed that total belowground biomass (BGB) was 32% of AGB. Positive linear relationship was observed between Dbh and the amount of carbon in the study area. It was also observed that a negative linear relationship exists between the aboveground biomass carbon (AGBC) and wood densities. This study indicates that the species of trees in the forest studied are effective carbon sink and can inhibit the effect of CO2 in the atmosphere. Three new models were developed using different input parameters and they all showed proximity to the 2005 allometric equation by Chave and his team.
Imputing forest carbon stock estimates from inventory plots to a nationally continuous coverage
Barry Tyler Wilson, Christopher W Woodall, Douglas M Griffith
Carbon Balance and Management , 2013, DOI: 10.1186/1750-0680-8-1
Abstract: Forest ecosystems represent the largest terrestrial carbon (C) sink on earth [1,2], such that the United Nations Framework Convention on Climate Change [3] has recognized their management as an effective strategy for offsetting greenhouse gas (GHG) emissions [4,5]. As part of the Convention, the U.S. has been submitting national reports, the National Greenhouse Gas Inventory (NGHGI), detailing emissions and removals of GHGs [3] on an annual basis for many years [6]. In addition to international reporting requirements, GHG budgets are being developed at sub-national scales including states (e.g., California) and ownerships (e.g, National Forest System climate change scorecard). Forest C stocks in the U.S. are estimated using data from the national forest inventory conducted by the USDA Forest Service, Forest Inventory and Analysis (FIA) program [7]. Broad forest ecosystem components (e.g., aboveground live biomass) have been delineated to generalize C stocks to meet international reporting agreements pursuant to refining understanding of global carbon cycling [2,3]. Carbon estimates for the ecosystem components of forest floor (inclusive of litter, fine woody debris, and humic soil horizons), down dead wood, belowground (BG) biomass, and soil organic matter are calculated by FIA using models based on geographic area, forest type, and, in some cases, stand age [6,8]. Estimates of aboveground (AG) standing live and dead tree C stocks are based on biomass estimates obtained from inventory tree data [6,9]. Although forest C stock estimates, such as those from FIA, are readily available at national and regional scales [6,7], there is increasing interest in disaggregating these large-scale numerical estimates into maps of continuous estimates to enable strategic forest management and monitoring activities geared toward offsetting GHG emissions [10] and advancing C dynamics research.Secondary to the need for spatially continuous forest C maps, numerous constituents (e.g., m
A Framework for Assessing Global Change Risks to Forest Carbon Stocks in the United States  [PDF]
Christopher W. Woodall, Grant M. Domke, Karin L. Riley, Christopher M. Oswalt, Susan J. Crocker, Gary W. Yohe
PLOS ONE , 2013, DOI: 10.1371/journal.pone.0073222
Abstract: Among terrestrial environments, forests are not only the largest long-term sink of atmospheric carbon (C), but are also susceptible to global change themselves, with potential consequences including alterations of C cycles and potential C emission. To inform global change risk assessment of forest C across large spatial/temporal scales, this study constructed and evaluated a basic risk framework which combined the magnitude of C stocks and their associated probability of stock change in the context of global change across the US. For the purposes of this analysis, forest C was divided into five pools, two live (aboveground and belowground biomass) and three dead (dead wood, soil organic matter, and forest floor) with a risk framework parameterized using the US's national greenhouse gas inventory and associated forest inventory data across current and projected future K?ppen-Geiger climate zones (A1F1 scenario). Results suggest that an initial forest C risk matrix may be constructed to focus attention on short- and long-term risks to forest C stocks (as opposed to implementation in decision making) using inventory-based estimates of total stocks and associated estimates of variability (i.e., coefficient of variation) among climate zones. The empirical parameterization of such a risk matrix highlighted numerous knowledge gaps: 1) robust measures of the likelihood of forest C stock change under climate change scenarios, 2) projections of forest C stocks given unforeseen socioeconomic conditions (i.e., land-use change), and 3) appropriate social responses to global change events for which there is no contemporary climate/disturbance analog (e.g., severe droughts in the Lake States). Coupling these current technical/social limits of developing a risk matrix to the biological processes of forest ecosystems (i.e., disturbance events and interaction among diverse forest C pools, potential positive feedbacks, and forest resiliency/recovery) suggests an operational forest C risk matrix remains elusive.
Estimation of biomass and carbon stocks: the case of the Atlantic Forest
Vieira, Simone Aparecida;Alves, Luciana Ferreira;Aidar, Marcos;Araújo, Luciana Spinelli;Baker, Tim;Batista, Jo?o Luís Ferreira;Campos, Mariana Cruz;Camargo, Plinio Barbosa;Chave, Jerome;Delitti, Welington Braz Carvalho;Higuchi, Niro;Honorio, Euridice;Joly, Carlos Alfredo;Keller, Michael;Martinelli, Luiz Antonio;Mattos, Eduardo Arcoverde de;Metzker, Thiago;Phillips, Oliver;Santos, Flavio Antonio Maes dos;Shimabukuro, M?nica Takako;Silveira, Marcos;Trumbore, Susan Elizabeth;
Biota Neotropica , 2008, DOI: 10.1590/S1676-06032008000200001
Abstract: the main objective of this paper is to present and discuss the best methods to estimate live above ground biomass in the atlantic forest. the methods presented and conclusions are the products of a workshop entitled "estimation of biomass and carbon stocks: the case of atlantic rain forest". aboveground biomass (agb) in tropical forests is mainly contained in trees. tree biomass is a function of wood volume, obtained from the diameter and height, architecture and wood density (dry weight per unit volume of fresh wood). it can be quantified by the direct (destructive) or indirect method where the biomass quantification is estimated using mathematical models. the allometric model can be site specific when elaborated to a particular ecosystem or general that can be used in different sites. for the atlantic forest, despite the importance of it, there are only two direct measurements of tree biomass, resulting in allometric models specific for this ecosystem. to select one or other of the available models in the literature to estimate agb it is necessary take into account what is the main question to be answered and the ease with which it is possible to measure the independent variables in the model. models that present more accurate estimates should be preferred. however, more simple models (those with one independent variable, usually dbh) can be used when the focus is monitoring the variation in carbon storage through the time. our observations in the atlantic forest suggest that pan-tropical relations proposed by chave et al. (2005) can be confidently used to estimated tree biomass across biomes as long as tree diameter (dbh), height, and wood density are accounted for in the model. in atlantic forest, we recommend the quantification of biomass of lianas, bamboo, palms, tree ferns and epiphytes, which are an important component in this ecosystem. this paper is an outcome of the workshop entitled "estimation of biomass and carbon stocks: the case of atlantic rain fore
Combined biomass inventory in the scope of REDD (Reducing Emissions from Deforestation and Forest Degradation)
D Plugge, T Baldauf, HR Ratsimba, G Rajoelison, M Kohl
Madagascar Conservation & Development , 2010,
Abstract: This paper presents an approach for combined biomass inventories in the scope of future REDD regimes. The focus is set on a sound and reliable method for measuring and monitoring the current state of carbon stocks and their changes over time. A reliable framework for measuring, reporting and verification is urgently needed to ensure the integrity and credibility of REDD efforts in general and REDD in the post - 2012 agreement which is assumed to be approved at COP 16 in Mexico in December 2010. The proposed approach was developed and successfully implemented in Madagascar within a multi - institutional REDD project, i.e., REDD - FORECA. It combines a multi - temporal remote sensing approach incorporating satellite sensors from medium to very high resolution with a terrestrial cluster sampling design, which proved to be operational for the whole spectrum from highly fragmented to pristine forest areas. This combination was implemented by a multi - phase sampling approach. The inventory is designed for the prerequisites of a continuous forest inventory to facilitate the quantification of possible CO2 reductions over time. The first field - assessments were accomplished in 2007 and 2008, and resulted in estimates of aboveground biomass on single tree level. Statistical upscaling procedures were utilised to aggregate these estimates on several levels. The results of the introduced methodology are presented and discussed.
The Inventory of Forest Carbon Stocks in the Province of Trento: some remarks on the sampling design and first comments on its results
Tabacchi G,Gasparini P
Forest@ , 2008, DOI: -
Abstract: Multiple sampling designs are commonly used in forest inventory to combine information collected in very large first-phase samples using remote sensing (satelite or aerial images) with the field data collected on smaller sub-samples. In Italy, during the seventies, double sampling designs were used in some regional forest inventories and, later, multiple sampling was adopted for the second National Forest Inventory and for the Inventory of Forest Carbon Stocks (InFoCarb) in the Province of Trento (Central-Eastern Alps). In this paper the main aspects of the design adopted for InFoCarb are discussed and the results of this inventory are compared with those obtained from the NFI for the same area. The estimates for the above-ground phytomass and the annual increment produced by the two inventories do not differ significantly, while the forest area estimates are significantly different as a consequence of differences in the dates of orthophotos used for the photointerpretation and in the classification procedure.
Accounting for density reduction and structural loss in standing dead trees: Implications for forest biomass and carbon stock estimates in the United States
Grant M Domke, Christopher W Woodall, James E Smith
Carbon Balance and Management , 2011, DOI: 10.1186/1750-0680-6-14
Abstract: Accounting for decay and structural loss in standing dead trees significantly decreased tree- and plot-level C stock estimates (and subsequent C stocks) by decay class and tree component. At a regional scale, incorporating adjustment factors decreased standing dead quaking aspen biomass estimates by almost 50 percent in the Lake States and Douglas-fir estimates by more than 36 percent in the Pacific Northwest.Substantial overestimates of standing dead tree biomass and C stocks occur when one does not account for density reductions or structural loss. Forest inventory estimation procedures that are descended from merchantability standards may need to be revised toward a more holistic approach to determining standing dead tree biomass and C attributes (i.e., attributes of tree biomass outside of sawlog portions). Incorporating density reductions and structural loss adjustments reduces uncertainty associated with standing dead tree biomass and C while improving consistency with field methods and documentation.The U.S. National Greenhouse Gas Inventory (NGHGI) produced annually by the U.S. Environmental Protection Agency recognizes five forest ecosystem carbon (C) pools [1]. Data from the USDA Forest Service, Forest Inventory and Analysis (FIA) program's network of permanent inventory plots across the Nation is used to either directly estimate (e.g., standing live trees) or simulate (e.g., litter) forest ecosystem C stocks. For example, C stock estimates for standing live tree biomass are based on inventory tree data, whereas estimates for down dead wood, litter, and soil organic matter are generated from models based on geographic area, forest type, and in some cases, stand age [2-4]. As the FIA inventory is the foundation for the U.S.'s NGHGI of managed forestland C stocks, improving the transparency and reliability of standing dead tree biomass and C stock estimation procedures is warranted. Currently, standing live and dead tree (SDT) biomass estimates are calculate
Aboveground Woody Biomass, Carbon Stocks Potential in Selected Tropical Forest Patches of Tripura, Northeast India  [PDF]
Koushik Majumdar, Bal Krishan Choudhary, Badal Kumar Datta
Open Journal of Ecology (OJE) , 2016, DOI: 10.4236/oje.2016.610057
Abstract: To estimate woody plant biomass stocks in different patches of forest ecosystems, total 20, 500 × 10 m (0.5 ha) sized line transects were laid in a protected area of Tripura, Northeast India. Overall, 9160 individuals were measured at ≥10 cm diameter at breast height (dbh) in 10 ha sampled area. Estimation of biomass suggested that highest coefficient for allometric relationships between density and biomass in 10 dbh classes was observed in bamboo brakes (R2 = 0.90) than lowest for semi evergreen patch (R2 = 0.48). The stock of carbon (C) was differ significantly along the forest patches (F = 7.01, df = 3.19; p < 0.01). Most of biomass stock (69.38%) was accumulated in lower dbh class (<30 cm) and only 23% of biomass was estimated at higher dbh classes (> 70 cm). Range of biomass stock (37.85 - 85.58 Mg ha-1) was low, compared to other tropical forest ecosystems in India, which implies that the proper management is required to monitor regional ecosystem C pool.
An Inventory of the Above Ground Biomass in the Mau Forest Ecosystem, Kenya  [PDF]
Mwangi James Kinyanjui, Petri Latva-K?yr?, Prasad Sah Bhuwneshwar, Patrick Kariuki, Alfred Gichu, Kepha Wamichwe
Open Journal of Ecology (OJE) , 2014, DOI: 10.4236/oje.2014.410052

Biomass assessment of the Mau Forest Ecosystem (MFE) was done as part of Kenya’s greenhouse gas inventory. Trans Mara and Mount Londiani forest blocks representing extremes of vegetation types in the MFE were selected for ground data. Based on canopy closure, four forest strata were identified as very dense, moderately dense, open and bamboo. In each stratum, 5 clusters each with 4 plots measuring 30 m × 30 m were located. Big trees (D1.3 ≥ 10 cm) were measured per species for diameter at breast height (D1.3) in the whole plot while height was measured for every 5th tree. Poles (10 cm > D1.3 ≤ 5) were measured for D1.3 in a 10 × 10 m concentric sub plot. Saplings (5 cm > D1.3; ht ≥ 1.5 m) and seedlings (ht < 1.5 m) were enumerated per species within 5 × 5 m and 2 × 2 m concentric sub plots, respectively. Data were recorded in a Personal Digital Assistant (PDA) and quality checked with Open Foris Collect software. Allometric equations that have been used for similar vegetation in Kenya were used to relate D1.3 and height with biomass. The tree data were uploaded to

Biomass carbon stocks in China’s forests between 2000 and 2050: A prediction based on forest biomass-age relationships
Bing Xu,ZhaoDi Guo,ShiLong Piao,JingYun Fang
Science China Life Sciences , 2010, DOI: 10.1007/s11427-010-4030-4
Abstract: China’s forests are characterized by young forest age, low carbon density and a large area of planted forests, and thus have high potential to act as carbon sinks in the future. Using China’s national forest inventory data during 1994–1998 and 1999–2003, and direct field measurements, we investigated the relationships between forest biomass density and forest age for 36 major forest types. Statistical approaches and the predicted future forest area from the national forestry development plan were applied to estimate the potential of forest biomass carbon storage in China during 2000–2050. Under an assumption of continuous natural forest growth, China’s existing forest biomass carbon (C) stock would increase from 5.86 Pg C (1 Pg=1015 g) in 1999–2003 to 10.23 Pg C in 2050, resulting in a total increase of 4.37 Pg C. Newly planted forests through afforestation and reforestation will sequestrate an additional 2.86 Pg C in biomass. Overall, China’s forests will potentially act as a carbon sink for 7.23 Pg C during the period 2000–2050, with an average carbon sink of 0.14 Pg C yr 1. This suggests that China’s forests will be a significant carbon sink in the next 50 years.
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