Effects of land cover on ecosystem services in Tanzania: A spatial assessment of soil organic carbon

AbstractThe multiple ecosystem services provided by healthy soil are well known and include soil carbon sequestration to mitigate climate change, a medium for plant and agricultural production and regulating the hydrologic cycle. Despite the wide recognition of the importance of these services, drivers of soil organic carbon (SOC) dynamics across various land uses in East Africa are poorly understood. The objectives of this study were threefold: to quantify SOC stocks across Tanzania; assess the effect of land cover and erosion on SOC; and investigate the relationship between inherent and dynamic soil properties under diverse land uses. The Land Degradation Surveillance Framework (LDSF) was used to assess the variability of ecological metrics at different spatial scales. SOC was quantified within and between different land cover types (forest, woodland, shrubland, grassland and cropland) in Tanzania. A total of 2052 soil samples from 1082–1000m2 plots were collected from seven 100-km2 sentinel sites in 2010. Composite soil samples were collected at each plot from two depths (0–20 and 20–50cm) and cumulative soil mass samples were collected to 100cm. Soil samples were analyzed using a combination of traditional analytical laboratory methods and mid-infrared spectroscopy (MIR). Model performance of MIR spectral predictions for carbon was good, with an R2 of >0.95 and RMSEP of 4.3gkg−1, when using an independent validation datasets. Woodland and cropland were the most frequently occurring vegetation structure types in the sampled sites, with 388 and 246 plots, respectively. Average topsoil OC (and range) was 12.4 (1.5–81.4) gCkg−1 (n=1082) and average subsoil OC (and range) was 7.3 (0.64–53.8) gCkg−1 (n=970) for the seven sites. Forested plots had the highest mean topsoil organic carbon concentrations (17.3gCkg−1) followed by cropland (13.3gCkg−1), for all sites included in the study, but with high levels of variability between sites. Soil mass at 30cm was measured and these data were used to calculate carbon stocks for the different land cover types. An approach based on remote sensing was explored for the mapping of SOC stocks at 30cm for Tanzania using Moderate Resolution Imaging Spectroradiometer (MODIS) imagery from 2012. Results indicate that the use of image reflectance for the mapping of SOC stocks has promising potential, with R2 values ranging from 0.77 to 0.81 and RMSEP values from 0.90 to 1.03kgm−2 for the three validation datasets. There is high utility of these maps for strategic land management interventions that prioritize ecosystem services

Trait-based approaches for guiding the restoration of degraded agricultural landscapes in East Africa

Functional ecology provides a framework that can link vegetation characteristics of various land uses with ecosystem function. However, this application has been mostly limited to [semi-]natural systems and small spatial scales. Here, we apply functional ecology to five agricultural landscapes in Kenya, Uganda and Ethiopia, and ask to what extent vegetation characteristics contribute to soil functions that are key to farmers’ livelihoods. We used the Land Degradation Surveillance Framework (LDSF), a multi-scale assessment of land health. Each LDSF site is a 10 × 10 km landscape in which vegetation cover and erosion prevalence were measured, a tree inventory was carried out, and topsoil (0–20 cm) samples were collected for organic carbon (SOC) analysis in approximately 160 × 1,000 m2 plots. Land degradation is a recurring phenomenon across the five landscapes, indicated by high erosion prevalence (67%–99% of the plots were severely eroded). We used mixed models to assess if vegetation cover, above-ground woody biomass and the functional properties of woody vegetation (weighted-mean trait values, functional diversity [FD]) explain variation in SOC and erosion prevalence. We found that the vegetation cover and above-ground biomass had strong positive effects on soil health by increasing SOC and reducing soil erosion. After controlling for cover and biomass, we found additional marginal effects of functional properties where FD was positively associated with SOC and the abundance of invasive species was associated with higher soil erosion. Synthesis and applications. This work illustrates how functional ecology can provide much-needed evidence for designing strategies to restore degraded agricultural land and the ecosystem services on which farmers depend. We show that to ensure soil health, it is vital to avoid exposed soil, maintain or promote tree cover, while ensuring functional diversity of tree species, and to eradicate invasive species

Review of Methodologies for Land Degradation Neutrality Baselines: Sub-National case studies from Costa Rica and Namibia

The objective of this report is to identify entry points and challenges for subnational LDN baselines in order to inform subnational planning processes as potential vehicle for the implementation of LDN targets on the ground. For this purpose two focus regions were chosen within two of the countries – namely Namibia and Costa Rica – that participated in the first LDN pilot phase. The focus areas in Namibia and Costa Rica are the regions of Otjozondjupa and Rio Jesus Maria watershed respectively. Both Namibia and Costa Rica provide interesting case studies given the differences in types of land degradation, national capacities, and land resources

Drivers of field-saturated soil hydraulic conductivity: Implications for restoring degraded tropical landscapes

Water security represents a major challenge in East Africa, affecting the livelihoods of millions of people and hindering sustainable development. Predicted increases in rainfall intensity and variability are expected to exacerbate water insecurity and land degradation. Improving soil infiltrability is an effective strategy for addressing water insecurity and land degradation. Research on soil infiltrability is often highly localized; therefore, scientific understanding of the drivers of infiltrability on larger spatial scales is limited. The aim of this study was to understand the main drivers of infiltrability across five contrasting landscapes in Kenya. We measured field-saturated hydraulic conductivity (Kfs) in 257 plots and collected data for variables representing soil properties (sand content, soil organic carbon (SOC) and pH), land degradation (grazing pressure and presence of erosion), vegetation quantity (woody aboveground biomass), and vegetation quality (functional properties and diversity). We used generalized mixed-effects models to test for the effects of these variables on Kfs. Median Kfs for the five sites ranged between 23.8 and 101.8 mm h−1. We found that Kfs was positively associated with sand content (standardized effect 0.39), SOC content (0.15), and functional diversity of woody vegetation (0.09), while it had a negative relationship with the presence of erosion (−0.24) and grazing pressure (−0.09). Subsequently, we conclude that infiltrability can be enhanced through using land restoration strategies which specifically target parameters that affect Kfs. The results further support that Kfs is not solely dictated by inherent soil properties, and that management interventions which boost SOC, reduce erosion, and minimize unsustainable grazing can help address water scarcity by restoring soil hydrological function

Data on how tree planting and management practices influence tree seedling survival in Kenya and Ethiopia

Understanding which trees farmers prefer, what determines their survival and enhancing farmer knowledge of tree management is key to increasing tree cover in agricultural landscapes. This article presents data on tree seedling survival under different tree planting and management practices in Kenya and Ethiopia. Data were collected from 1600 households across three Counties in Kenya and 173 households across four Woredas in Ethiopia, using a structured questionnaire which was administered through the Open Data Kit. Data on seedling survival were collected at least six months after tree seedlings were planted. To understand how planting and management practices influence tree planting across the different socioeconomic and biophysical contexts, both household level and individual tree level data were collected. Household level data included socio-economic and biophysical characteristics of the households while tree specific data included when the tree seedling was planted, where it was planted, the management practices employed and whether surviving. The datasets described in this article help understand which options confer the best chance survival for the planted seedlings and in which socio-economic and biophysical contexts they are most successful. [Abstract copyright: © 2021 The Author(s). Published by Elsevier Inc.