Feed and grazing management affect both the quantity and quality of animal manure and consequently nutrient cycling in the mixed crop-livestock systems in West Africa Sahel. Dietary measures can significantly influence the composition of manure and hence it’s agricultural value. High nutrient feed will generally result in higher nutrient content of the manure whereas a decline in feed quality will generally lead to increase in the indigestible fractions in the feeds.
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Library ResourceJournal Articles & BooksDecember, 2018Algeria, Burkina Faso, Nigeria, Mauritania, Mali, Ethiopia, Eritrea, Cameroon, South Sudan, Central African Republic, Senegal, Chad, Niger, Sudan, Western Africa, Africa
Library ResourceJournal Articles & BooksAugust, 2019Africa, Eastern Africa, Kenya
Livestock-wildlife interactions promote the transmission of a wide range of infectious diseases that constraint livestock production. We used a participatory appraisal approach to find out and rank infectious diseases of concern to pastoralists in a zone of intense wildlife-livestock interaction and another zone with limited interactions. Four villages were selected purposively in areas with intensive cattle-wildlife interactions (zone 1), and another two in areas with low to moderate cattle-wildlife interactions (zone 2).
Library ResourceJournal Articles & BooksDecember, 2016Ghana
In this article, the attempt is made to address regime interaction in environmental governance by emphasising human livelihood action as a causal factor in this interaction. The paper elucidates how governing human behaviour on environmental resources is a process of interaction between different environmental governance regimes.
Library ResourceJournal Articles & BooksDecember, 2014Togo
Remote-sensing data for protected areas in northern Togo, obtained in three different years (2007, 2000, and 1987), were used to assess and map changes in land cover and land use for this drought prone zone. The normalized difference vegetation index (NDVI) was applied to the images to map changes in vegetation. An unsupervised classification, followed by classes recoding, filtering, identifications, area computing and post-classification process were applied to the composite of the three years of NDVI images.