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Effects of tree density on wildlife, grasses, and forage production

Effects of tree density on wildlife, grasses, and forage production. Corinna Riginos. Graduate Group in Ecology, University of California, Davis, CA, USA and Mpala Research Centre, Nanyuki, Kenya. Introduction. Experimental Test.

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Effects of tree density on wildlife, grasses, and forage production

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  1. Effects of tree density on wildlife, grasses, and forage production Corinna Riginos Graduate Group in Ecology, University of California, Davis, CA, USA and Mpala Research Centre, Nanyuki, Kenya Introduction Experimental Test • In collaboration with Jacob Goheen and Kari Veblen, I have set up a large-scale experiment, in which 60 x 60 m patches of whistling thorn savanna were either thinned, cleared of all trees, or left untouched. I will be monitoring these plots for: • wild and domestic herbivore use • tree growth, reproduction, and browse damage • grass productivity and grazing damage • grass layer species composition Savannas can range from open plains with scattered trees to dense woodlands. In African savannas, changes in tree density have been linked with range management practices. For example, wild herbivores, especially elephants, often cause a decrease in tree density, whereas cattle grazing often causes an increase in tree density. Since trees and grasses compete for the same water and nutrients, an increase in tree density may mean less grass for cattle and wildlife. At the same time, wild herbivores may avoid areas with a high number of trees, where predators are hard to see. This could affect the interactions between trees and grasses — either preventing or encouraging further changes in tree density. My research addresses these issues in an attempt to disentangle the complex links among trees, grasses, wildlife, and cattle grazing. Expected Outcomes • I hope to provide mechanistic answers to the following questions: • Do wild herbivores prefer more open areas? • Is grass productivity lower where there are more trees? • Is tree growth and reproduction lower where there are more trees? • Does tree density affect grass species composition? Preliminary Work Conclusions • From a descriptive survey in the black cotton -whistling thorn (Acacia drepanolobium) savanna of MRC and Jessel Ranch, I found that: •  Wild herbivores preferred areas with fewer trees. This was true of almost all of the major herbivore species, including zebras, Grant’s gazelles, hartebeests, giraffes, and oryx. •  Zebras avoided areas that had been grazed more by cattle. •  Out of five dominant grass species, one (Pennisetum stramineum) was more abundant where tree density was higher. •  Two other species (Pennisetum mezianum and Themeda triandra – red oat) were less abundant where tree density was higher. My preliminary results show that tree density can have important consequences for both wildlife and grasses. In the next phase, I will uncover the mechanisms underlying these patterns and more fully illuminate the interactions among trees, grasses, wildlife, and forage productivity. The results of my research are important for understanding the consequences of the increases in tree abundance that continue to occur in savannas across Africa. Cattle grazing is generally thought to cause these increases. In order to make effective, long-term plans for sustainable land management, we must understand both what causes tree density to increase, and what the consequences of these increases are for wildlife and cattle production. Figure 2. Red oat grass is more abundant where there are fewer trees Figure 1. Wild herbivores prefer areas with fewer trees Conclusions Acknowledgements My thanks to: Truman Young, for his advice and support; Kari Veblen and Jake Goheen, for their collaboration in setting up experimental plots; Nick Georgiadis and Peter Jessel for their permission to work on Mpala Research Centre and Jessel properties; Jackson Ekadeli, Frederick Erii, Patrick Etelej, John Lochukuya, James Ekiru, Abdikadir Ali Hassan, and Simon Lima for assistance in the field; Dan Kelly for satellite image analysis and GIS work; and to Ken Wreford-Smith, Kerry Outram and Joe Petters for logistical support. This research is supported by NSF LTREB BSR-03-16402 to T.P. Young, and by an NSF Graduate Research Fellowship, a Jastro-Shields fellowship, a Ben Madson fellowship, and an NSF Doctoral Dissertation Improvement Grant to C. Riginos.

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