Biophysical regions of the Southern Highlands, Tanzania: regionalization in a data scarce environment with open geospatial data and statistical methods

Abstract

Spatially explicit, evidence-based and regionally contextualized data on biophysical landscape characteristics is an essential basis for regionally sustainable landscape management schemes. In many regions of the Global South, the availability of such information is poor, especially at the subnational level, and the spatial management is often based on generic and outdated information, leading to severe threats for land sustainability. We have developed a biophysical regionalization of the Southern Highlands area of Tanzania. The map is based on open-source global datasets depicting climate, soil, topography and vegetation. Through replicable statistical and geospatial analyses, we have identified 7 regions and 18 subsections with biophysically similar and spatially distinctive environmental conditions. The regions provide spatially contextualized support for understanding and managing the landscapes of the Southern Highlands. The applications for such data sets are numerous, from screening suitability areas for e.g. afforestation schemes to evaluating the distinctiveness and vulnerability of landscapes to degradation.

Selected soil properties and small-holder dairy farmers perceptions on improved forage varieties in the Southern highlands of Tanzania

“…Studied dairy farmers were weeding and harvesting their forage at 40 days after re-growth which was within 25 to 45 days but shorter than the 60 to 75 days rotation recommended for improved pasture varieties during rainy and dry seasons, respectively (Ohmstedt and Mwendia, 2018). The 40 days rotation is explained by the long rainy period (up to 9 months) in the studied area (Koskikala et al, 2020), hence farmers experienced prolonged rainy season. It could also be because at the younger stage pastures are highly digestible and have higher water soluble carbohydrates to meet the energy requirement of dairy cattle (Calvache et al, 2020).…”

Tanzania Craton, Serengeti Plain and Eastern Rift Valley: mapping of geospatial data by scripting techniques

“…In fact, the majority of the existing maps of Tanzania use ArcGIS or QGIS (e.g. Schweikart et al 2014;Nijbroek and Andelman 2016;Koskikala et al 2020;Mseli et al 2021). This is mostly explained by the relative simplicity of the traditional GIS.…”

The Curse or Fertility of Land Clearing: How Migrant Labour Modified Gender-Based Division of Labour in the Southern Highlands of Tanzania

“…Its climatic conditions favour crop and livestock production: the altitude ranges from 400 to 3,000 metres above sea level with temperatures between 10˚ and 22˚C; annual rainfall distribution, mainly observed during the wet season from November to April, varies from 750 to 2,600 mm (cf. Guni and Katule 2013;Koskikala, Kisanga and Käyhkö 2020). Such climatic conditions make the region a grain basket for the country (Santorum and Tibaijuka 1992;Kangalawe 2012).…”