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Landscape Ecology of Savannas

From Disturbance Regime to Management Strategies
  • Anja Linstädter
Chapter
Part of the Studies in Human Ecology and Adaptation book series (STHE, volume 4)

Abstract

In this contribution, the sustainability of range management in savannas is related to dynamics within a savanna landscape. Concepts of landscape ecology may help to identify crucial aspects of a sustainable management, such as a specific disturbance regime. Some important goals for future research activities are identified, either related to the process and implementation of research, or to the content of research.

The transdisciplinary science of landscape ecology studies the structure, function, and development of landscapes. It is still passing through a process of self-discovery and does not yet offer a unified theory. As its roots are deep in geography as well as in geobotany and land management, self-discovery comprises the search for the unification of landscape ecology as a discipline, the relation between basic research and application, and between sectoral and holistic approaches.

The key landscape types for landscape ecology have been the cultural landscapes in Europe and North America. Some of the concepts developed for these landscapes are difficult to transfer to African savannas. Nevertheless, the dynamics in a savanna are best dealt with on the spatial and conceptual level of a landscape. Here the different disturbances can be integrated into a disturbance regime, and their functional aspects can be discussed. It is argued that the sustainable use of a savanna landscape by nomadic herders implies a disturbance regime roughly similar to the regime occurring under natural conditions. A sustainable use has to ensure fodder reserves as an ecological buffer against temporal variability, and it has to be adapted to spatial variability on a landscape level.

Keywords

Landscape Ecology Perennial Grass Disturbance Regime Tree Layer Annual Grass 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Notes

Acknowledgements

Financial support by the Deutsche Forschungsgemeinschaft (SFB 389) and by the Volkswagen Foundation (AZ: II/79 041) is gratefully acknowledged.

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Authors and Affiliations

  • Anja Linstädter
    • 1
  1. 1.Botanical InstituteUniversity of CologneCologneGermany

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