Landscape-scale variability of soil health indicators: Effects of cultivation on soil organic carbon in the Usambara Mountains of Tanzania

During the Phase I of the CCAFS project we conducted a systematic land and soil health assessment in Lushoto District in November 2012. These data were used to inform climate-smart agricultural interventions for the IFAD project as well as to parameterize DSSAT crop models for maize and beans. The land and soil health assessment that was carried out using the Land Degradation Surveillance Framework (LDSF). These data were also used to assess the effect of cultivation on soil organic carbon dynamics across the landscape. Finally, these data provide a biophysical assessment for the Lushoto CCAFS Climate Smart Village

Landscape-scale variability of soil health indicators: effects of cultivation on soil organic carbon in the Usambara Mountains of Tanzania

This article is published with open access at Springerlink.comLand-use change continues at an alarming rate in sub-Saharan Africa adversely affecting ecosystem services provided by soil. These impacts are greatly understudied, especially in biodiversity rich mountains in East Africa. The objectives of this study were to: conduct a biophysical baseline of soil and land health; assess the effects of cultivation on soil organic carbon (SOC); and develop a map of SOC at high resolution to enable farm-scale targeting of management interventions. Biophysical field surveys were conducted in a 100 km2 landscape near Lushoto, Tanzania, with composite soil samples collected from 160 sampling plots. Soil erosion prevalence was scored, trees were counted, and current and historic land use was recorded at each plot. The results of the study showed a decline in SOC as a result of cultivation, with cultivated plots (n = 105) having mean topsoil OC of 30.6 g kg-1, while semi-natural plots (n = 55) had 71 g OC kg-1 in topsoil. Cultivated areas were also less variable in SOC than seminatural systems. Prediction models were developed for the mapping of SOC based on RapidEye remote sensing data for January 2014, with good model performance (RMSEPcal = 8.0 g kg-1; RMSEPval = 10.5 g kg-1) and a SOC map was generated for the study. Interventions will need to focus on practices that increase SOC in order to enhance productivity and resilience of the farming system, in general. The highresolution maps can be used to spatially target interventions as well as for monitoring of changes in SOC

Landscape-scale variability of soil health indicators: effects of cultivation on soil organic carbon in the Usambara Mountains of Tanzania

This article is published with open access at Springerlink.comLand-use change continues at an alarming rate in sub-Saharan Africa adversely affecting ecosystem services provided by soil. These impacts are greatly understudied, especially in biodiversity rich mountains in East Africa. The objectives of this study were to: conduct a biophysical baseline of soil and land health; assess the effects of cultivation on soil organic carbon (SOC); and develop a map of SOC at high resolution to enable farm-scale targeting of management interventions. Biophysical field surveys were conducted in a 100 km2 landscape near Lushoto, Tanzania, with composite soil samples collected from 160 sampling plots. Soil erosion prevalence was scored, trees were counted, and current and historic land use was recorded at each plot. The results of the study showed a decline in SOC as a result of cultivation, with cultivated plots (n = 105) having mean topsoil OC of 30.6 g kg-1, while semi-natural plots (n = 55) had 71 g OC kg-1 in topsoil. Cultivated areas were also less variable in SOC than seminatural systems. Prediction models were developed for the mapping of SOC based on RapidEye remote sensing data for January 2014, with good model performance (RMSEPcal = 8.0 g kg-1; RMSEPval = 10.5 g kg-1) and a SOC map was generated for the study. Interventions will need to focus on practices that increase SOC in order to enhance productivity and resilience of the farming system, in general. The highresolution maps can be used to spatially target interventions as well as for monitoring of changes in SOC

Assessing drivers of soil properties and classification in the West Usambara mountains, Tanzania

Geoderma Regional 2017; Vol. 11:141 - 154Improved soil information in tropical montane regions is critical for conservation, sustainable agricultural management, and land use planning, but is often challenged by topographic and land-use heterogeneity. The West Usambara mountains are a part of the Eastern Arc chain of mountains of Tanzania and Kenya, a globally important tropical montane ecoregion made up of isolated fault-block mountain complexes characterized by high biological endemism, population density, and agronomic productivity. We synthesized novel and legacy soil data from published and unpublished studies to better understand the drivers of soil property distributions and soil diversity in the West Usambaras, and to serve as a foundation for improved soil mapping efforts across the Eastern Arc. Analysis of the resulting dataset of 468 sites (ranging in elevation from 1040 to 2230 m.a.s.l.) revealed that soil properties varied more significantly by land use and topography than by soil type, suggesting that future mapping efforts in the region should focus primarily on soil property prediction and secondarily on soil classification. Sites under cultivated land uses had the lowest topsoil soil organic carbon (SOC) concentrations and highest pH values, and SOC generally increased with increasing elevation. Valley soils had significantly lower surface SOC concentrations but higher exchangeable bases and pH values than all other landscape positions. Soil pH decreased by an average of 3.5 units across the entire elevation gradient and decreased by 1 unit with elevation even after SOC, land use and landscape position were included in multiple regression models. The relationship of cation exchange capacity (CEC) to SOC and clay content varied by landscape position. Therefore, particularly in montane regions where soils can vary significantly over short distances, multiple functions may be necessary to produce improved estimates of parameters such as CEC. Soil classification was driven most strongly by topography, with Acrisols (WRB Reference Group) and Ultisols (U.S. Soil Taxonomy (ST)) as the dominant soil types, located primarily on mid slope, upper slope and crest landscape positions, making up 47% and 75% of observed profiles, respectively. However, five ST Orders and seven WRB Reference Groups were present in the dataset, with the highest soil diversity occurring at lower slope landscape positions. Conclusions drawn from this large dataset support previous work in the West Usambaras and provide a conceptual foundation from which to build improved soil maps across the Eastern Arc and in other tropical montane systems throughout the world