Fynbos Node, South African Environmental Observation Network (SAEON), Centre for Biodiversity Conservation, Kirstenbosch Gardens, Private Bag X7, Rhodes Drive, Claremont, Cape Town, South Africa; Department of Botany and Zoology, Stellenbosch University, Private Bag X1, Matieland, Stellenbosch, South Africa; Biodiversity and Climate Research Centre, Senckenberg Research Institute, Natural History Museum, Senckenberganlage 25, Frankfurt am Main, Germany; Centre for Statistics in Ecology, Environment and Conservation, Department of Biological Sciences, University of Cape Town, Private Bag X3, Rondebosch, South Africa; Department of Botany, University of Otago, P.O. Box 56, Dunedin, New Zealand
Moncrieff, G.R., Fynbos Node, South African Environmental Observation Network (SAEON), Centre for Biodiversity Conservation, Kirstenbosch Gardens, Private Bag X7, Rhodes Drive, Claremont, Cape Town, South Africa, Department of Botany and Zoology, Stellenbosch University, Private Bag X1, Matieland, Stellenbosch, South Africa; Scheiter, S., Biodiversity and Climate Research Centre, Senckenberg Research Institute, Natural History Museum, Senckenberganlage 25, Frankfurt am Main, Germany; Slingsby, J.A., Fynbos Node, South African Environmental Observation Network (SAEON), Centre for Biodiversity Conservation, Kirstenbosch Gardens, Private Bag X7, Rhodes Drive, Claremont, Cape Town, South Africa, Centre for Statistics in Ecology, Environment and Conservation, Department of Biological Sciences, University of Cape Town, Private Bag X3, Rondebosch, South Africa; Higgins, S.I., Department of Botany, University of Otago, P.O. Box 56, Dunedin, New Zealand
The distribution of South African biomes is expected to be drastically altered as a result of climatic change and increasing atmospheric CO2 in the 21st century. Developing the capacity to anticipate change is of critical importance if we are to mitigate and efficiently adapt to the reorganization of South African vegetation cover. Dynamic Vegetation Models (DVMs) simulate the distribution and functioning of plant functional types (PFTs) and their interactions. Outputs include biome distribution maps, assessments of carbon cycling and the quantification of plant productivity, all of which can be produced for past, present and future conditions. DVMs were originally conceived of as analogs to general circulation models (GCMs) and applied globally, but to be unbiased globally necessitates choosing parameters and representing processes that may not be regionally appropriate. Models populated with a modified suite of PFTs and parameterized appropriately for local conditions are better suited to studies concerned with vegetation dynamics and global change impacts at the country or continent-scale. In their current form DGVMs do not include the plant types and key processes of many South African biomes. Therefore, while projections of global change impacts are available for biomes dominated by forest trees, savanna trees and grasses, little can be learned about some of our most biodiverse and threatened biomes, particularly the Fynbos and Thicket biomes, and the Succulent Karoo. We outline the limitations of existing DVMs and improvements required before reliable projections of global change impacts on South African biomes can be produced. Reparameterization of some PFTs and fire models could easily be achieved, and would lead to large improvements in model simulations. However, there remain numerous processes and facets of the ecology of South African vegetation that will limit the applicability of DVMs in their current form. © 2015 South African Association of Botanists.