Jonas Ardö
Professor
Estimating Grazing Potentials in Sudan Using Daily Carbon Allocation in Dynamic Vegetation Model
Författare
Summary, in English
Livestock production is important for local food security and as a source of income in sub-Saharan Africa. The human population of the region is expected to double by 2050, and at the same time climate change is predicted to negatively affect grazing resources vital to livestock. Therefore, it is essential to model the potential grazing output of sub-Saharan Africa in both present and future climatic conditions. Standard tools to simulate plant productivity are dynamic vegetation models (DVMs). However, as they typically allocate carbon to plant growth at an annual time step, they have a limited capability to simulate grazing. Here, we present a novel implementation of daily carbon allocation for grasses into the DVM Lund-Potsdam-Jena General Ecosystem Simulator (LPJ-GUESS) and apply this to study the grazing potential for the Kordofan region in Sudan. The results show a latitudinal split in grazing resources, where the northern parts of Kordofan are unexploited and southern parts are overused. Overall, we found that the modeled grazing potential of Kordofan is 16% higher than the livestock usage reported in the Food and Agricultural Organization of the United Nations, indicating a mitigation potential in the form of a spatial relocation of the herds.
Avdelning/ar
- Institutionen för naturgeografi och ekosystemvetenskap
- BECC: Biodiversity and Ecosystem services in a Changing Climate
- MERGE: ModElling the Regional and Global Earth system
Publiceringsår
2018-08-01
Språk
Engelska
Sidor
792-797
Publikation/Tidskrift/Serie
Rangeland Ecology and Management
Volym
71
Issue
6
Dokumenttyp
Artikel i tidskrift
Förlag
Society of Environmental Toxicology and Chemistry
Ämne
- Physical Geography
- Environmental Sciences
Nyckelord
- Sudan
- Climate change
- grazing
- Kordofan
- livestock
- LPJ-GUESS
- Africa
- Sahel
- Drylands
Status
Published
Projekt
- Global Savannah Phenology: Integrating Earth Observation, Ecosystem Modeling, and PhenoCams
ISBN/ISSN/Övrigt
- ISSN: 1550-7424