br Experimental design materials and methods The details of

Experimental design, materials and methods The details of the sites have been described in our previous study [1]. In brief, the dataset collections order AZD1152-HQPA localized in Kenya and Tanzania. In Kenya, was situated in Taita Hills in South-Eastern Kenya (coastal region), between latitude 3°25′ and longitude 38°20′. In Tanzania, was situated in the Pangani river basin in North East (NE) Tanzania with a focus on the small catchment areas on the South Eastern slope of Mount Kilimanjaro approximately located between latitude 3°4′ and longitude 37°4′. The temperature, relative humidity and rainfall required for carrying out the spatial interpolation were obtained from local weather stations. Automatic onset ™HOBO data loggers (hourly records) and GENERALR wireless rain gauges were installed at station across study sites to keep track of daily temperatures, relative humidity and rainfall, respectively [1,2]. The x–y coordinates position and altitudes were recorded using a Global Positioning System (GPS) (German eTrex Vista(R)). The thin plate spline (TPS) algorithm [3] was used to interpolate temperature, rainfall and relative humidity dataset. Data processing and analysis were carried out with a computer program written in R software [4] and linked with Geographic Information System (GIS). The accuracy of the environmental variables surface was assessed by comparing surface values withheld from the interpolation procedure. Three statistical criteria were used to evaluate accuracy namely: (i) R-square (R2); (ii) the Root Mean Square Error (RMSE); and (iii) the Relative Root Mean Square Error (RMSEr).
Acknowledgments This work was supported by the Ministry for Foreign Affairs of Finland, under the Climate Change Impacts on Ecosystem Services and Food Security in Eastern Africa (CHIESA) project. Authors wish to thank the entire members of the Noctuid Stem Borer Biodiversity (NSBB) team, Environmental health team of the African Insect Science for Food and Health (icipe), and Dar es Salaam Institute of Technology for their support. The authors are grateful to Dr. George F. Obiero for his numerous constructive comments on the manuscript.
Data Herein, the data consists of tables and figures which help analyze the near-surface (~30cm depth) heavy metals contents of soils collected from 1050 geo-referenced points underlain by paragneisses and amphibolites parent materials [1] at the Maibele Airstrip North in Central Botswana (Fig. 1). Other heavy metals below detection limit (dl) including Mo, dl <5ppm; Cd, dl <10ppm; Sn, dl <20ppm; Sb, dl <20ppm; W, dl <10ppm; U, dl <5ppm; and Se, dl <5ppm had no values reported in the data (Supplementary Table 1). Portable x-ray fluorescence spectrophotometer in a “soil” mode was used to determine the heavy metals. The average of two readings on two samples (sieved and non-sieved) collected from the same point on the grid layout was recorded and reported.
Experimental design, materials and methods Soil samples were collected at intervals of 25m (thus a sample spacing of 25m) following straight marked lines. Sample line trend was from north to south and a total of 30 lines were sampled, each with 35 sampling points (Fig. 2a and b). A total distance of about 875m was covered for each line. A pit of about 30cm depth was dug to remove the topsoil (Ap horizon) and organic material before collecting soil samples. Two soil samples were collected for each point, one sample was sieved using the Fieldmaster soil sampling sieve set before being placed in a labeled transparent sample bag and the other was put in a sample bag as collected (not sieved). The two samples collected at a single point were label with the same sample number but differentiate by letters at the end (for example, 1105451a and 1105451b). All soil samples were taken to the base camp and allowed to air dry before analyzing using a portable x-ray fluorescence analyzer. Samples from the same point were analyzed consecutively, and the analyzer made an average analysis from the measurements it obtained from the two samples. The data was downloaded into a computer and an excel document showing the element contents for each sample was made (Supplementary Table 1).