Comparing above-ground biomass among forest types in the Wet Tropics: Small stems and plantation types matter in carbon accounting

Abstract A generic regression model for above-ground biomass of forest stands was constructed based on published data (R2 = 0.88, RSE = 32.8 t/ha). The model was used 1) to verify two allometric regression models of trees from Scandinavia applied to repeated measurements of 275 sample plots from database of Estonian Network of Forest Research (FGN) in Estonia, 2) to analyse impact of between-tree competition on biomass, and 3) compare biomass estimates made with different European biomass models applied on standardized forest structures. The model was verified with biomass measurements from hemiboreal and tropical forests. The analysis of two Scandinavian models showed that older allometric regression models may give biased estimates due to changed growth conditions. More biomass can be stored in forest stands where competition between trees is stronger. The tree biomass calculation methods used in different countries have also substantial influence on the estimates at stand-level. A common database of forest biomass measurements from Europe in similar to pan-tropical tree measurement data may be helpful to harmonise carbon accounting methods.

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Above-ground carbon stock assessment in different forest types of Nepal

Banko Janakari ◽

10.3126/banko.v19i2.2979 ◽

1970 ◽

Vol 19 (2) ◽

pp. 10-14 ◽

Cited By ~ 18

Author(s):

SK Baral ◽

R Malla ◽

S Ranabhat

Keyword(s):

Carbon Sequestration ◽

Key Words ◽

Carbon Stock ◽

Stock Assessment ◽

Allometric Equations ◽

Biomass Carbon ◽

Above Ground Biomass ◽

Forest Types ◽

Ground Biomass ◽

Physiographic Regions

This study assessed the above-ground carbon stock in the five major forest types, representing two physiographic regions and four districts of Nepal. Altogether, 116 circular sample plots were laid out systematically in different forests types to inventory the forest. Total above-ground biomass was derived with allometric equations. Results indicated variation in age of the stand (18-75 years), above-ground carbon stock per hectare (34.30- 97.86 dry wt. ton ha-1) and rate of carbon sequestration (1.30-3.21 t ha-1yr-1), according to different forest types. The rate of carbon sequestration by different forest types depended on the growing nature of the forest stands. Tropical riverine and Alnus nepalensis forest types demonstrated the highest carbon sequestration rates in Nepal. Key Words: Above-ground biomass; carbon; forest types; Nepal DOI: 10.3126/banko.v19i2.2979 Banko Janakari, Vol. 19, No.2 2009 pp.10-14

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Canopy Height and Above-Ground Biomass Retrieval in Tropical Forests Using Multi-Pass X- and C-Band Pol-InSAR Data

Remote Sensing ◽

10.3390/rs11182105 ◽

2019 ◽

Vol 11 (18) ◽

pp. 2105 ◽

Cited By ~ 1

Author(s):

Berninger ◽

Lohberger ◽

Zhang ◽

Siegert

Keyword(s):

High Resolution ◽

Tropical Forests ◽

Forest Degradation ◽

Canopy Height ◽

Carbon Accounting ◽

Lidar Data ◽

Above Ground Biomass ◽

High Resolution Data ◽

Ground Biomass ◽

Resolution Data

Globally available high-resolution information about canopy height and AGB is important for carbon accounting. The present study showed that Pol-InSAR data from TS-X and RS-2 could be used together with field inventories and high-resolution data such as drone or LiDAR data to support the carbon accounting in the context of REDD+ (Reducing Emissions from Deforestation and Forest Degradation) projects.

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Allometry, above-ground biomass and nutrient distribution in Ceriops decandra (Griffith) Ding Hou dominated forest types of the Sundarbans mangrove forest, Bangladesh

Wetlands Ecology and Management ◽

10.1007/s11273-012-9274-2 ◽

2012 ◽

Vol 20 (6) ◽

pp. 539-548 ◽

Cited By ~ 9

Author(s):

Mahmood Hossain ◽

Mohammad Raqibul Hasan Siddique ◽

Arun Bose ◽

Sharif Hasan Limon ◽

Md. Rezaul Karim Chowdhury ◽

...

Keyword(s):

Mangrove Forest ◽

Above Ground Biomass ◽

Forest Types ◽

Nutrient Distribution ◽

Ground Biomass ◽

Ceriops Decandra ◽

Sundarbans Mangrove ◽

The Sundarbans

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Assessment of Above-Ground Biomass in Pakistan Forest Ecosystem’s Carbon Pool: A Review

Forests ◽

10.3390/f12050586 ◽

2021 ◽

Vol 12 (5) ◽

pp. 586

Author(s):

Ishfaq Ahmad Khan ◽

Waseem Razzaq Khan ◽

Anwar Ali ◽

Mohd Nazre

Keyword(s):

Climate Change ◽

Kyoto Protocol ◽

Carbon Stock ◽

National Level ◽

Well Being ◽

Forest Carbon ◽

Above Ground Biomass ◽

Forest Types ◽

Ground Biomass ◽

Stock Estimation

Climate change is acknowledged as a global threat to the environment and human well-being. Forest ecosystems are a significant factor in this regard as they act both as a sink and a source of carbon. Forest carbon evaluation has received more attention after the Paris Agreement. Pakistan has 5.1% forest cover of its total land area, which comprises nine forest types. This study covers the studies conducted on above-ground biomass and carbon stock in various forest types of Pakistan. Most of the studies on biomass and carbon stock estimation have been conducted during 2015–2020. The non-destructive method is mostly followed for carbon stock estimation, followed by remote sensing. The destructive method is used only for developing allometric equations and biomass expansion factors. The information available on the carbon stock and biomass of Pakistan forest types is fragmented and sporadic. Coniferous forests are more important in carbon sequestration and can play a vital role in mitigating climate change. Pakistan is a signatory of the Kyoto Protocol and still lacks regional and national level studies on biomass and carbon stock, which are necessary for reporting under the Kyoto Protocol. This study will help researchers and decision-makers to develop policies regarding Reducing Emissions from Deforestation and forest Degradation (REDD+), conservation, sustainable forest management and enhancement of forest carbon stocks

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ESTIMATION OF ABOVE GROUND BIOMASS OF THE THREE SITES (GRAZED SITE, PROTECTED SITE AND SEED SOWN SITE) FOR COMPARING THEIR PRODUCTIVITY IN KASHMIR VALLEY

FLORA AND FAUNA ◽

10.33451/florafauna.v23i2pp259-262 ◽

2017 ◽

Vol 23 (2) ◽

Author(s):

AFSHAN ANJUM BABA ◽

SYED NASEEM UL-ZAFAR GEELANI ◽

ISHRAT SALEEM ◽

MOHIT HUSAIN ◽

PERVEZ AHMAD KHAN ◽

...

Keyword(s):

Protected Areas ◽

Aboveground Biomass ◽

Plant Biomass ◽

Summer Season ◽

Above Ground Biomass ◽

Spring Season ◽

Kashmir Valley ◽

Ground Biomass ◽

Maximum Value ◽

Protected Site

The plant biomass for protected areas was maximum in summer (1221.56 g/m2) and minimum in winter (290.62 g/m2) as against grazed areas having maximum value 590.81 g/m2 in autumn and minimum 183.75 g/m2 in winter. Study revealed that at Protected site (Kanidajan) the above ground biomass ranged was from a minimum (1.11 t ha-1) in the spring season to a maximum (4.58 t ha-1) in the summer season while at Grazed site (Yousmarag), the aboveground biomass varied from a minimum (0.54 t ha-1) in the spring season to a maximum of 1.48 t ha-1 in summer seasonandat Seed sown site (Badipora), the lowest value of aboveground biomass obtained was 4.46 t ha-1 in spring while as the highest (7.98 t ha-1) was obtained in summer.

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The climatic imprint of bimodal distributions in vegetation cover for western Africa

Biogeosciences ◽

10.5194/bg-13-3343-2016 ◽

2016 ◽

Vol 13 (11) ◽

pp. 3343-3357 ◽

Cited By ~ 4

Author(s):

Zun Yin ◽

Stefan C. Dekker ◽

Bart J. J. M. van den Hurk ◽

Henk A. Dijkstra

Keyword(s):

Land Cover ◽

Congo Basin ◽

Shortwave Radiation ◽

Mean Annual Precipitation ◽

Above Ground Biomass ◽

Precipitation Regime ◽

Ground Biomass ◽

Western Africa ◽

Precipitation Regimes ◽

Woody Cover

Abstract. Observed bimodal distributions of woody cover in western Africa provide evidence that alternative ecosystem states may exist under the same precipitation regimes. In this study, we show that bimodality can also be observed in mean annual shortwave radiation and above-ground biomass, which might closely relate to woody cover due to vegetation–climate interactions. Thus we expect that use of radiation and above-ground biomass enables us to distinguish the two modes of woody cover. However, through conditional histogram analysis, we find that the bimodality of woody cover still can exist under conditions of low mean annual shortwave radiation and low above-ground biomass. It suggests that this specific condition might play a key role in critical transitions between the two modes, while under other conditions no bimodality was found. Based on a land cover map in which anthropogenic land use was removed, six climatic indicators that represent water, energy, climate seasonality and water–radiation coupling are analysed to investigate the coexistence of these indicators with specific land cover types. From this analysis we find that the mean annual precipitation is not sufficient to predict potential land cover change. Indicators of climate seasonality are strongly related to the observed land cover type. However, these indicators cannot predict a stable forest state under the observed climatic conditions, in contrast to observed forest states. A new indicator (the normalized difference of precipitation) successfully expresses the stability of the precipitation regime and can improve the prediction accuracy of forest states. Next we evaluate land cover predictions based on different combinations of climatic indicators. Regions with high potential of land cover transitions are revealed. The results suggest that the tropical forest in the Congo basin may be unstable and shows the possibility of decreasing significantly. An increase in the area covered by savanna and grass is possible, which coincides with the observed regreening of the Sahara.

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Above-ground biomass estimation of Indian tropical forests using X band Pol-InSAR and Random Forest

Remote Sensing Applications Society and Environment ◽

10.1016/j.rsase.2020.100462 ◽

2021 ◽

Vol 21 ◽

pp. 100462

Author(s):

Sadhana Yadav ◽

Hitendra Padalia ◽

Sanjiv K. Sinha ◽

Ritika Srinet ◽

Prakash Chauhan

Keyword(s):

Random Forest ◽

Tropical Forests ◽

Biomass Estimation ◽

Above Ground Biomass ◽

Ground Biomass ◽

X Band

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Comparison of Capability of SAR and Optical Data in Mapping Forest above Ground Biomass Based on Machine Learning

Environmental Sciences Proceedings ◽

10.3390/iecg2020-07916 ◽

2020 ◽

Vol 5 (1) ◽

pp. 13

Author(s):

Negar Tavasoli ◽

Hossein Arefi

Keyword(s):

Machine Learning ◽

Carbon Stock ◽

Vegetation Indices ◽

Forest Biomass ◽

Principal Component ◽

Optical Data ◽

Above Ground Biomass ◽

Ground Biomass ◽

Texture Characteristics ◽

Sentinel 2

Assessment of forest above ground biomass (AGB) is critical for managing forest and understanding the role of forest as source of carbon fluxes. Recently, satellite remote sensing products offer the chance to map forest biomass and carbon stock. The present study focuses on comparing the potential use of combination of ALOSPALSAR and Sentinel-1 SAR data, with Sentinel-2 optical data to estimate above ground biomass and carbon stock using Genetic-Random forest machine learning (GA-RF) algorithm. Polarimetric decompositions, texture characteristics and backscatter coefficients of ALOSPALSAR and Sentinel-1, and vegetation indices, tasseled cap, texture parameters and principal component analysis (PCA) of Sentinel-2 based on measured AGB samples were used to estimate biomass. The overall coefficient (R2) of AGB modelling using combination of ALOSPALSAR and Sentinel-1 data, and Sentinel-2 data were respectively 0.70 and 0.62. The result showed that Combining ALOSPALSAR and Sentinel-1 data to predict AGB by using GA-RF model performed better than Sentinel-2 data.

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