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Rangelands: Where Anthromes Meet Their Limits

Peer-reviewed publication
Junho, 2017

Defining rangelands as anthromes enabled Ellis and Ramankutty (2008) to conclude that more than three-quarters of Earth’s land is anthropogenic; without rangelands, this figure would have been less than half. They classified all lands grazed by domestic livestock as rangelands, provided that human population densities were low; similar areas without livestock were excluded and classified instead as ‘wildlands’. This paper examines the empirical basis and conceptual assumptions of defining and categorizing rangelands in this fashion.

Remote sensing monitoring of land restoration interventions in semi-arid environments with a before–after control-impact statistical design

Journal Articles & Books
Junho, 2017

Restoration interventions to combat land degradation are carried out in arid and semi-arid areas to improve vegetation cover and land productivity. Evaluating the success of an intervention over time is challenging due to various constraints (e.g. difficult-to-access areas, lack of long-term records) and the lack of standardised and affordable methodologies. We propose a semi-automatic methodology that uses remote sensing data to provide a rapid, standardised and objective assessment of the biophysical impact, in terms of vegetation cover, of restoration interventions.

ICARDA Annual Report 2016

Reports & Research
Junho, 2017
Global

2016 was the hottest year on record – the third consecutive record-breaking year. It was a sign that we have to act fast to enhance the resilience of dryland farmers, who not only have to contend with more extreme temperatures but also face rapidly depleting water resources and the destructive effects of new pests and disease.

Note de Cadrage

Conference Papers & Reports
Maio, 2017
África

 Annoncés depuis un semestre, les ETP 2 ont été lancés le 3 juillet 2017 à Niamey, au Niger sous présidence effective du Ministre Délégué en charge de l’Elevage du Niger, M. Mohamed Boucha en présence du Représentant résident de la Banque mondiale, M. Siaka Bakayoko, du Charge du PRAPS NE, à la Banque mondiale, M/ Souleymane Fofana, l’ Administrateur Intérimaire du Centre Régional Agrhymet, Samba Souleymane Ly.

To mulch or to munch? Big modelling of big data

Journal Articles & Books
Maio, 2017

African farmers are poorly resourced, highly diverse and aground by poverty traps making them rather impervious to change. As a consequence R4D efforts usually result in benefits but also trade-offs that constraint adoption and change. A typical case is the use of crop residues as mulches or as feedstock. Here we linked a database of household surveys with a dynamic whole farm simulation model, to quantify the diversity of trade-offs from the alternative use of crop residues.

IN SEARCH OF THE SOLUTION TO FARMER–PASTORALIST CONFLICTS IN TANZANIA

Policy Papers & Briefs
Abril, 2017
Tanzania

Land-use conflict is not a new phenomenon for pastoralists and farmers in Tanzania with murders, the killing of livestock and the loss of property as a consequence of this conflict featuring in the news for many years now. Various actors, including civil society organisations, have tried to address farmer–pastoralist conflict through mass education programmes, land-use planning, policy reforms and the development of community institutions. However, these efforts have not succeeded in the conflict. Elsewhere in sub-Saharan Africa traditional systems are not making much headway either.

Evaluating fire severity in Sudanian ecosystems of Burkina Faso using Landsat 8 satellite images

Journal Articles & Books
Março, 2017
Burkina Faso
África
África Ocidental

The fire severity of the 2013–2014 fire season within Sudanian ecosystems in Burkina Faso was evaluated from Landsat 8 images using derivatives of the Normalized Burn Ratio algorithm (NBR). The relationship between the image-derived severity and the field observed severity i.e. Composite Burn Index (CBI) was best described by a nonlinear model of the form y = a + b*EXP(CBI *c) (R2 = 0.66). Classification of the image-derived burned area into burn severity classes achieved a classification Kappa accuracy statistic of 0.56.