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ArticleCan carbon be sequestered in Red Panda (Ailurus fulgens Cuvier 1825) habitats in Nepal?
XV World Forestry Congress, 2-6 May 2022
2022Also available in:
No results found.Forest carbon stock can provide alternative opportunity for the conservation of forests and biodiversity. Previous studies on red panda habitats in Nepal barely provide accurate information of carbon stock from those habitats which is critical for devising long term conservation plan for this species. Thus, the present study aims to document and describe carbon sequestration in red panda habitat to create the first-ever broad- scale scientific basis for the promotion of red panda conservation efforts with a limelight on carbon stock. Extensive field surveys conducted to record red panda presence only data in red panda range rural municipalities of Jajarkot district. A total of 261 red panda presence point were recorded and a quadrate of 10 m*10 m were laid to record the Diameter at Breast height (DBH) and height of trees. The study assessed the above ground and below ground tree biomass carbon stock. The above ground tree biomass was found 1952.49±1279.34 ton/ha whereas below ground tree biomass was 390.49±255.86 ton/ha. Likewise, above ground carbon stock was found 917.67±601.29 ton/ha and below ground was 183.53±120.25 ton/ha. Total carbon stock of the forest was 1101.21±721.55 ton/ha and CO2 equivalent is 4037.75±2645.68 ton/ha. This study gives way to link forest carbon stock and biodiversity conservation. Assessing the relationship between carbon stocks and biodiversity is important in understanding the trade-off between two major benefits of forest ecosystems. The study could be used as a background to suggest alternative strategies to conserve the red panda habitats, taking into account the social and economic concerns and climate change benefits from forests in low-income highland communities. Keywords: Biodiversity conservation, Climate change, Governance, Deforestation and forest degradation. ID: 3623924 -
ArticleDeveloping simultaneously modeling systems for improving the reliability of tree aboveground biomass- carbon and its components estimates for Machilus odoratissimus nees in the central highlands, Viet Nam
XV World Forestry Congress, 2-6 May 2022
2022Also available in:
No results found.Machilus odoratissimus Nees is a multi-purpose species with, high economic value and environmental protection, so this tree species is commonly used in agroforestry models. In plantation management, it demands modeling systems that predict accurately aboveground biomass- carbon and its components. At the same time, the developed models support computing carbon accumulation of forest trees in agroforestry models for the program of reducing emissions from deforestation and forest degradation (REDD). Twenty-two 300 m2 plots were measured within the full range of 1 to 7 ages in the Central Highlands of VietNam. A total of 22 quadratic mean diameter trees were destructively sampled to obtain a dataset of the dry iomass/carbon of the stem (Bst/Cst), bark (Bba/Cba), branches (Bbr/Cbr), leaves (Ble/Cle), and total tree aboveground biomass/carbon (AGB/AGC). We examined the performance of weighted nonlinear models fit by maximum likelihood and weighted nonlinear seemingly unrelated regression (SUR) fit by generalized least squares for predicting tree aboveground biomass- carbon and its components. The simultaneous estimation of AGB/AGC and its components produced a higher reliability than that of the models of tree components and the total developed separately. The selected forms of modeling systems were AGB = Bst + Bba + Bbr + Ble = a1×(D2H)b1 + a2×(D2H)b2 + a3×Db3 + a4×(D2H)b4 and AGC = Cst + Cba+ Cbr + Cle = a1×(D2H)b1 ++2×(D2H)b2 + a3×Db3 + a4×(D2H)b4 (where D is the diameter at breast height and H is the height of the tree). Keywords: Agroforestry, Machilus odoratissimus, seemingly unrelated regression (SUR), tree biomass- carbon ID: 3472953 -
ArticleThe tropical biomass & carbon project– An app for forest biomass and carbon estimates
XV World Forestry Congress, 2-6 May 2022
2022Also available in:
No results found.This article introduces the project called Tropical Biomass & Carbon – TB&C, available on the permanent link www.tropicalbiomass.com. The App requires input attributes of the forest stand or diameter class easily obtained, being: smallest and largest diameters, number of trees ha-1, and parameters of the diameter distribution. The output attributes are at the stand and tree levels. At stand level, the App delivers mean aboveground biomass (AGB) and carbon (AGC), in Mg ha-1, as well as their confidence intervals (CIs) and uncertainties. The tree-level outputs are AGB and diameter for every tree in the stand. The project TB&C comprises four Brazilian forest (and non-forest) formations: Campinarana, Floresta estacional, Floresta ombrofila, and Savana. This article aims to disclose the algorithm written for the TB&C App. This phase counts on a standardized database of 1,428 trees with dry AGB destructively measured. Model uncertainties were incorporated into the modeling process. In addition to its reliability, we cite as great advantages of the TB&C App; (i) simplicity and a user-friendly layout, (ii) AGB and AGC estimates provided along with robust CIs, and (iii) estimates at the stand and tree levels with consistent totals. As a secondary product, the project TB&C delivers a dataset of 64,000 simulated plots, informing dry AGB, tree density, basal area, Lorey’s height, and shape of the diameter distribution. Keywords: Tropical Forest, Aboveground biomass, Uncertainty analysis, Stand- and tree-level, estimates, Web application ID: 3623771
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