Skip to content
Home
About Us
Resources
Profiles Metrics
Authors Directory
Institutions Directory
Top Authors
Top Institutions
Top Sponsors
AI Digest
Contact Us
Menu
Home
About Us
Resources
Profiles Metrics
Authors Directory
Institutions Directory
Top Authors
Top Institutions
Top Sponsors
AI Digest
Contact Us
Home
About Us
Resources
Profiles Metrics
Authors Directory
Institutions Directory
Top Authors
Top Institutions
Top Sponsors
AI Digest
Contact Us
Menu
Home
About Us
Resources
Profiles Metrics
Authors Directory
Institutions Directory
Top Authors
Top Institutions
Top Sponsors
AI Digest
Contact Us
Publication Details
AFRICAN RESEARCH NEXUS
SHINING A SPOTLIGHT ON AFRICAN RESEARCH
earth and planetary sciences
Quantification of uncertainties in global grazing systems assessment
Global Biogeochemical Cycles, Volume 31, No. 7, Year 2017
Notification
URL copied to clipboard!
Description
Livestock systems play a key role in global sustainability challenges like food security and climate change, yet many unknowns and large uncertainties prevail. We present a systematic, spatially explicit assessment of uncertainties related to grazing intensity (GI), a key metric for assessing ecological impacts of grazing, by combining existing data sets on (a) grazing feed intake, (b) the spatial distribution of livestock, (c) the extent of grazing land, and (d) its net primary productivity (NPP). An analysis of the resulting 96 maps implies that on average 15% of the grazing land NPP is consumed by livestock. GI is low in most of the world's grazing lands, but hotspots of very high GI prevail in 1% of the total grazing area. The agreement between GI maps is good on one fifth of the world's grazing area, while on the remainder, it is low to very low. Largest uncertainties are found in global drylands and where grazing land bears trees (e.g., the Amazon basin or the Taiga belt). In some regions like India or Western Europe, massive uncertainties even result in GI > 100% estimates. Our sensitivity analysis indicates that the input data for NPP, animal distribution, and grazing area contribute about equally to the total variability in GI maps, while grazing feed intake is a less critical variable. We argue that a general improvement in quality of the available global level data sets is a precondition for improving the understanding of the role of livestock systems in the context of global environmental change or food security. ©2017. American Geophysical Union. All Rights Reserved.
Authors & Co-Authors
Havlik, Petr
Austria, Laxenburg
International Institute for Applied Systems Analysis, Laxenburg
Herrero, Mario
Australia, Canberra
Commonwealth Scientific and Industrial Research Organisation
Kaplan, Jed Oliver
Switzerland, Lausanne
Université de Lausanne Unil
Kastner, Thomas
Austria, Klagenfurt
Alpen-adria-universität Klagenfurt
Germany, Frankfurt am Main
Senckenberg Biodiversität Und Klima Forschungszentrum
Rolinski, Susanne
Germany, Potsdam
Potsdam Institut Fur Klimafolgenforschung
Searchinger, Timothy D.
United States, Princeton
Princeton University
Van Bodegom, Peter Michiel
Netherlands, Leiden
Universiteit Leiden
Erb, Karl Heinz
Austria, Klagenfurt
Alpen-adria-universität Klagenfurt
Statistics
Citations: 66
Authors: 8
Affiliations: 10
Identifiers
Doi:
10.1002/2016GB005601
ISSN:
08866236
Research Areas
Environmental
Food Security