Ecological Restoration in Semi‐Arid Landscapes: Comparing Exclosures and Pasture for Vegetation, Soil Nutrients, and Carbon Stocks

ABSTRACT Land degradation in semi‐arid regions poses a major threat to Sustainable Development Goal 15 (SDG 15) by undermining ecosystem services and biodiversity. Although restoration strategies like exclosures are gaining attention, there remains a critical gap in quantifying their long‐term ecological and carbon sequestration benefits, particularly in severely degraded landscapes such as Ethiopia's Tigray region. This study addresses that gap by comparing 15‐year‐old exclosures with adjacent open pasture using a mixed‐methods approach. We assessed 62 plots (31 per land use type) for species diversity (Shannon‐Wiener and Simpson indices), biomass (via allometric equations), soil properties (at 0–15 cm and 15–30 cm depths), and carbon stocks, employing Principal Component Analysis (PCA) and Pearson correlation. Results showed that exclosures significantly outperformed pasture, supporting 174 plant species versus 69, higher soil organic carbon (18.71 g/100 g vs. 15.91 g/100 g at 0–15 cm, p < 0.001), and greater above‐ground biomass (40.72 t/ha vs. 14.24 t/ha, p < 0.001). These findings underscore the potential of exclosures as a scalable and cost‐effective strategy for restoring degraded semi‐arid ecosystems, offering robust empirical evidence to inform national policy integration, advance SDG 15, and support climate change mitigation across similar regions globally.

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Publication Details

Journal
African Journal of Ecology
Published
2025-05-08
DOI
https://doi.org/10.1111/aje.70056
Primary Topic
Rangeland and Wildlife Management
Type
article
Field-Weighted Citation Impact
0.00

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article

Ecological Restoration in Semi‐Arid Landscapes: Comparing Exclosures and Pasture for Vegetation, Soil Nutrients, and Carbon Stocks

Marta Sibhat, Xiang‐Zhou Meng, Gedion Tsegay, George Lartey‐Young et al.
African Journal of Ecology
Rangeland and Wildlife Management
article

Ecological Restoration in Semi‐Arid Landscapes: Comparing Exclosures and Pasture for Vegetation, Soil Nutrients, and Carbon Stocks

Marta Sibhat, Xiang‐Zhou Meng, Gedion Tsegay, George Lartey‐Young, Yunze Gao
article en

Abstract

ABSTRACT Land degradation in semi‐arid regions poses a major threat to Sustainable Development Goal 15 (SDG 15) by undermining ecosystem services and biodiversity. Although restoration strategies like exclosures are gaining attention, there remains a critical gap in quantifying their long‐term ecological and carbon sequestration benefits, particularly in severely degraded landscapes such as Ethiopia's Tigray region. This study addresses that gap by comparing 15‐year‐old exclosures with adjacent open pasture using a mixed‐methods approach. We assessed 62 plots (31 per land use type) for species diversity (Shannon‐Wiener and Simpson indices), biomass (via allometric equations), soil properties (at 0–15 cm and 15–30 cm depths), and carbon stocks, employing Principal Component Analysis (PCA) and Pearson correlation. Results showed that exclosures significantly outperformed pasture, supporting 174 plant species versus 69, higher soil organic carbon (18.71 g/100 g vs. 15.91 g/100 g at 0–15 cm, p < 0.001), and greater above‐ground biomass (40.72 t/ha vs. 14.24 t/ha, p < 0.001). These findings underscore the potential of exclosures as a scalable and cost‐effective strategy for restoring degraded semi‐arid ecosystems, offering robust empirical evidence to inform national policy integration, advance SDG 15, and support climate change mitigation across similar regions globally.

African Journal of EcologyVol. 63(4)
Tongji University (CN), Shanghai Institute of Pollution Control and Ecological Security
National Key Research and Development Program of China
Openalex Percentile: Top 90%
Rangeland and Wildlife Management
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Ecological Restoration in Semi‐Arid Landscapes: Comparing Exclosures and Pasture for Vegetation, Soil Nutrients, and Carbon Stocks — Marta Sibhat, Xiang‐Zhou Meng, et al. · African Journal of Ecology (2025) | TGRS Research Map | TGRS