PioLaG: a piosphere landscape generator for savanna rangeland modelling
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RESEARCH ARTICLE
PioLaG: a piosphere landscape generator for savanna rangeland modelling Bastian Hess . Niels Dreber . Yihui Liu . Kerstin Wiegand Marvin Ludwig . Hanna Meyer . Katrin M. Meyer
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Received: 14 January 2020 / Accepted: 29 June 2020 Ó The Author(s) 2020
Abstract Context Piospheres describe herbivore utilization gradients around watering points, as commonly found in grass-dominated ecosystems. Spatially explicit, dynamic models are ideal tools to study the ecological and economic problems associated with the resulting land degradation. However, there is a need for appropriate landscape input maps to these models that depict plausible initial vegetation patterns under a range of scenarios. Electronic supplementary material The online version of this article (https://doi.org/10.1007/s10980-020-01066-w) contains supplementary material, which is available to authorized users. B. Hess (&) N. Dreber Y. Liu K. Wiegand K. M. Meyer Department of Ecosystem Modelling, Faculty of Forest Sciences and Forest Ecology, University of Go¨ttingen, Bu¨sgenweg 4, 37077 Go¨ttingen, Germany e-mail: [email protected] Present Address: B. Hess Federal Research Centre for Cultivated Plants, Julius Ku¨hn-Institute, Messeweg 11/12, 38104 Brunswick, Germany
Objectives Our goal was to develop a spatiallyexplicit piosphere landscape generator (PioLaG) for semi-arid savanna rangelands with a focus on realistic vegetation zones and spatial patterns of basic plant functional types around livestock watering points. Methods We applied a hybrid modelling approach combining aspects of both process- and pattern-based modelling. Exemplary parameterization of PioLaG was based on literature data and expert interviews in reference to Kalahari savannas. PioLaG outputs were compared with piosphere formations identified on aerial images. Results PioLaG allowed to create rangeland landscapes with piospheres that can be positioned within M. Ludwig H. Meyer Environmental Informatics, Faculty of Geography, Philipps-University Marburg, Deutschhausstrasse 12, 35032 Marburg, Germany Present Address: H. Meyer Environmental Remote Sensing, Institute for Geoinformatics, University of Mu¨nster, Heisenbergstrasse 2, 48149 Mu¨nster, Germany
Present Address: N. Dreber Division Social-Ecological Research, Department Environment and Sustainability, DLR Project Management Agency, Heinrich-Konen-Straße 1, 53227 Bonn, Germany
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Landscape Ecol
flexible arrangements of grazing units (camps). The livestock utilization gradients showed distinct vegetation patterns around watering points, which varied according to the pre-set initial rangeland condition, grazing regime and management type. The spatial characteristics and zoning of woody and herbaceous vegetation were comparable to real piosphere patterns. Conclusions PioLaG can provide important input data for spatial rangeland models that simulate sitespecific savanna dynamics. The created landscapes can also be used as a direct decision support for
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