Carbon sequestration potential of natural vegetation under grazing influence in Southern Tigray, Ethiopia: implication for climate change mitigation

Abstract

The management influence on carbon sequestration potential of different land use types are least known at the national level. This research was conducted to assess the impact of area exclusion on carbon sequestration potential in the two land use systems: protected natural vegetation (PNV) and communal grazing land (CGL). Data of vegetation, litter, and soils were collected using systematic sampling methods, laying 19 transects and 62 quadrats each with 20 m × 20 m for trees, 5 m × 5 m sub-quadrats for shrubs, and 1 m × 1m sub-quadrats for herbs/grasses, litter biomass, and soil sample. Aboveground biomass carbon (AGC), belowground biomass carbon (BGC), soil organic carbon (SOC), and total carbon stock (TC) were estimated using allometric equations. The mean difference level of carbon stocks (P < 0.05) of the two land use systems was tested through unequal variance t-test using R-software. The mean above ground and below ground carbon stock of PNV, 21.05 ton/ha, 10.39 ton/ha, was higher than CGL, 15.31 ton/ha, 7.65 ton/ha, respectively. The average values of SOC was 16.60 ton/ha from PNV and 13.76 ton/ha from CGL. The mean value of SOC was higher at the PNV than CGL and significantly different (P < 0.05). The total carbon stock estimate of PNV and CGL were 50.74 ton/ha and 37.11 ton/ha, respectively, which is significantly different (P < 0.05). We concluded that, establishment of PNV as the best practice of restoration programs through exclusion of livestock from free grazing and human interference provides cost effective mechanism that yields a high carbon sequestration potential with multiple benefits for biodiversity conservation, livelihood support, and climate change mitigation.

Total Carbon Stock and Potential Carbon Sequestration Economic Value of Mukogodo Forest-Landscape Ecosystem in Drylands of Northern Kenya

“…The high contribution of living biomass over soil to overall carbon were in agreement with Meena et al (2019) who reported that living plant biomass contribute about 40% to 49% and Simegn et al, 2014 who reported about 57% of the total carbon from living biomass. Abere et al (2017) and Atsbha et al (2019) also reported findings that were within the range found in the study. This was, however contrary to the findings by other studies undertaken in nearly similar dry ecosystems (Dabasso et al, 2014;Solomon et al, 2018;Gebeyehu et al, 2019) who found soil to contribute the greatest carbon storage potential than the other carbon pools.…”

“…Further, Zhao et al (2019) indicated that the variation in data sources, estimation methods, scope of study area and environmental variables with different biotic and abiotic conditions and response to climate change may lead to significant variation in carbon storage estimates. Moreover, Keiluweit et al (2015) The mean carbon stock from this study was slightly lower compared to those reported for nearly similar landscape in northern Kenya and Ethiopia (Dabasso et al, 2014;Gebeyehu et al, 2019), but was within the reported range in other dry forest-landscapes (Tiessen et al, 1998;Glenday, 2008;Simegn et al, 2014;Abere et al, 2017;Atsbha et al, 2019;Srinivas and Sundarapandian, 2019). The effects of vegetation and landscape type were significant on carbon stocks.…”

Environmental Product Declarations for plants and soils: how to quantify carbon uptake in landscape design and construction?

“…In practice, the underground C stocks of plants are typically included in soil C stocks due to methodological difficulties in separating living roots from various soil organic matter components. For woody species, root biomass is commonly estimated to be 27% of aboveground biomass (Atsbha 2019). For agricultural crops, an agroecosystem model (Crop-DNDC) integrates detailed crop growth algorithms with an existing soil biogeochemical model and simulates C, nitrogen, and water cycles in agroecosystems with a relatively complete scope (Zhang et al 2002;Li et al 1992).…”

Spatiotemporal patterns of the forage-livestock balance in the Xilin Gol steppe, China: implications for sustainably utilizing grassland-ecosystem services

“…The global demand for beef, mutton, and dairy was estimated to increase by 13.9%, 22.0%, and 22.2%, respectively, between 2011 and 2020 (OECD-FAO, 2011). The grazing management mode could strongly impact the regional richness, biomass, carbon sequestration capacity, and ecological health of grasslands (Atsbha et al, 2019). Therefore, animal husbandry and grassland ecosystem services are complementary and mutually restricted.…”