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Assessing soil and land health across two landscapes in eastern Rwanda to inform restoration activities
Soil  (IF5.841),  Pub Date : 2021-11-25, DOI: 10.5194/soil-7-767-2021
Leigh Ann Winowiecki, Aida Bargués-Tobella, Athanase Mukuralinda, Providence Mujawamariya, Elisée Bahati Ntawuhiganayo, Alex Billy Mugayi, Susan Chomba, Tor-Gunnar Vågen

Land degradation negatively impacts water, food, and nutrition security and is leading to increased competition for resources. While landscape restoration has the potential to restore ecosystem function, understanding the drivers of degradation is critical for prioritizing and tracking interventions. We sampled 300–1000 m2 plots using the Land Degradation Surveillance Framework across Nyagatare and Kayonza districts in Rwanda to assess key soil and land health indicators, including soil organic carbon (SOC), erosion prevalence, vegetation structure and infiltration capacity, and their interactions. SOC content decreased with increasing sand content across both sites and sampling depths and was lowest in croplands and grasslands compared to shrublands and woodlands. Stable carbon isotope values (δ13C) ranged from 15.35 ‰ to 21.34 ‰, indicating a wide range of historic and current plant communities with both C3 and C4 photosynthetic pathways. Field-saturated hydraulic conductivity (Kfs) was modeled, with a median of 76 mm h−1 in Kayonza and 62 mm h−1 in Nyagatare, respectively. Topsoil OC had a positive effect on Kfs, whereas pH, sand, and erosion had negative effects. Soil erosion was highest in plots classified as woodland and shrubland. Maps of soil erosion and SOC at 30 m resolution were produced with high accuracy and showed strong variability across the study landscapes. These data demonstrate the importance of assessing multiple biophysical properties in order to assess land degradation, including the spatial patterns of soil and land health indicators across the landscape. By understanding the dynamics of land degradation and interactions between biophysical indicators, we can better prioritize interventions that result in multiple benefits as well as assess the impacts of restoration options.