AWF Project in MLW Watershed, DRC Yamboyo LDSF Site: soil health results

The Maringa-Lopori-Wamba Landscape (MLW) in DRC encompasses a wide range of land cover types, including dense moist semi-deciduous alongside smallholder agricultural systems. Regional interventions aimed to increase productivity was conserving natural resources have lacked baseline information on soil and land health for making informed decisions. This initiative aimed to fill gaps related to biophysical constraints in order to inform decisions

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

Landscape-scale assessments of stable carbon isotopes in soil under diverse vegetation classes in East Africa : application of near-infrared spectroscopy

Stable carbon isotopes are important tracers used to understand ecological food web processes and vegetation shifts over time. However, gaps exist in understanding soil and plant processes that influence delta C-13 values, particularly across smallholder farming systems in sub-Saharan Africa. This study aimed to develop predictive models for delta C-13 values in soil using near infrared spectroscopy (NIRS) to increase overall sample size. In addition, this study aimed to assess the delta C-13 values between five vegetation classes. The Land Degradation Surveillance Framework (LDSF) was used to collect a stratified random set of soil samples and to classify vegetation. A total of 154 topsoil and 186 subsoil samples were collected and analyzed using NIRS, organic carbon (OC) and stable carbon isotopes. Forested plots had the most negative average delta C-13 values, -26.1aEuro degrees; followed by woodland, -21.9aEuro degrees; cropland, -19.0aEuro degrees; shrubland, -16.5aEuro degrees; and grassland, -13.9aEuro degrees. Prediction models were developed for delta C-13 using partial least squares (PLS) regression and random forest (RF) models. Model performance was acceptable and similar with both models. The root mean square error of prediction (RMSEP) values for the three independent validation runs for delta C-13 using PLS ranged from 1.91 to 2.03 compared to 1.52 to 1.98 using RF. This model performance indicates that NIR can be used to predict delta C-13 in soil, which will allow for landscape-scale assessments to better understand carbon dynamics

Project #25: Improving HFH Overall Hospital Quality Star Rating through CMS Patient Safety Indicators (PSI) 90

This project’s aim is to improve the publicly reported Overall Hospital Quality Star Rating for Henry Ford Hospital as calculated by the Centers for Medicare & Medicaid Services (CMS) through Patient Safety Indicator (PSI) 90 case validation.https://scholarlycommons.henryford.com/qualityexpo2022/1003/thumbnail.jp

Land Degradation Surveillance Framework (LSDF): field guide

The field methods employed in the soil health component of the AfSIS (Africa Soil Information Service) project are referred to as the Land Degradation Surveillance Framework (LDSF). This field guide outlines field protocols for measuring indicators of the “health” of an ecosystem, including vegetation cover, structure and floristic composition, historic land use, visible signs of soil degradation, and soil physical characteristics. It is designed to provide a biophysical baseline at landscape level, and a monitoring and evaluation framework for assessing processes of land degradation and the effectiveness of rehabilitation measures over time