Journal of Biogeography
SUPPORTING INFORMATION
Distribution mapping of world grassland types
A. P. Dixon, D. Faber-Langendoen, C. Josse, J. Morrison and C. J. Loucks
Appendix S1 Types of ecosystem classification and mapping approaches.
A variety of approaches can be used to characterize terrestrial ecosystems. We briefly describe four
major approaches relevant to classification of grassland ecosystems: vegetation-taxonomy;
ecosystem and economic assessment; ecoregional mapping; and remote sensing-based land cover.
The vegetation-taxonomy approach stresses the importance of vegetation as a primary
expression of a terrestrial ecosystem and incorporates a taxonomic approach in which plant species
assemblages are used to classify stands into finer-scaled plant community types (e.g. association,
alliance) and broader types (e.g. class, division, formation). The finer-scaled patterns are associated
with local and regional site, disturbance and biogeographical factors, whereas the patterns of the
broader vegetation types are associated with large-scale biogeographical and ecological patterns,
including climate, soils and landforms (Whittaker, 1962; Westhoff & van der Maarel, 1973; Werger
& Sprangers, 1982; Adam, 1992). Rarely have ecologists provided a series of vegetation types
across both sets ofscales. At finer scales, many kinds of floristically-based classifications exist, and
the most systematic and widely used is that of the Braun-Blanquet approach (Westhoff & van der
Maarel, 1973). At broader scales, the United Nations Educational, Scientific, and Cultural
Organization (UNESCO) (1973) International Mapping of Vegetation served as a major step towards
grouping major vegetation community types on a global basis using a nested hierarchy of
physiognomy and structure, but it did not incorporate species composition. Di Gregorio & Janssen
(1996) developed the Land Cover Classification System (LCCS), which provides a customizable
platform for users to characterize land cover, including grassland land cover types, through a
classification of remotely sensed information that emphasizes growth forms, with limited floristic
information. The LCCS does not, however, provide for a consistent classification system, as users
may choose various combinations of criteria to create their own units and map legend, based on
project needs. Nor does the LCCS provide a dynamic view of biodiversity since it primarily
describes structural and physiognomic characteristics, rather than dominant or diagnostic plant
species information, or provide other ecosystem characterization information. The International
Vegetation Classification (IVC) has recently emerged as a robust vegetation classification system,
which adapts many of the concepts present in the above publications, but integrates physiognomy
and floristics with biogeography and ecology from very broad to very fine scales (FaberLangendoen et al., 2014). We detail this classification in the manuscript, but we note that neither
the IVC, nor its predecessors, explicitly incorporate the geographic-spatial distribution of
ecosystems. That is, the vegetation types are not linked to a geographical framework that allows
users to determine spatial extent and ecology.
The economic and ecological assessment approach assesses grasslands based on critical
ecosystem services, and identifies grassland types based on the patterns of human land use across
grassland areas of the world. Types identified in this approach are labelled by usage, e.g. pastoral
vs. productive vs. hay grasslands (Coupland, 1979; White et al., 2001; Suttie et al., 2005). The
grassland types so defined may be similar to the first approach, but described through the lens of
regions that have certain kinds of land use histories, and the associated pressures exerted on
grasslands from agricultural intensification and neophyte (recent exotic) species introduction.
The ecoregional mapping approach emphasizes the combination of geographic-spatial and
bio-physical factors such as climate, landform, and soils to classify and map ecosystems. A
hierarchy of units is identified, based on the predominant set of controlling criteria at any given
level (Holdridge, 1967; Walter & Box, 1976; Schultz, 1995; Bailey, 2009). For example, Bailey’s
Ecoregions of the Continents (Bailey, 1998) provides a recent synthesis of biophysical factors and
landform drawn at a global scale, baesd on the combination of macroclimate, landforms and
continentality. The Terrestrial Ecoregions of the World (TEOW) takes a similar approach but relies
more strongly on species biogeography as one of the controlling factors (Olson et al., 2001; see also
White, 1983). A two-tiered approach was developed, with macroclimate and large scale vegetation
physiognomy as controlling factors for the top level, and combinations of biophysical factors and
biogeography for the second. Together, these two levels provide a set of globally, spatially explicit
biomes (Olson et al., 2001). Each of the ecoregions defined in the TEOW were drawn at a regional
scale, and therefore have much more detailed boundaries than Bailey’s (1998) world ecoregions.
The remote-sensing based land cover approach draws on ongoing advances in remote
sensing technology to map generalized patterns in vegetation, abiotic and anthropogenic cover on
the surface of the Earth (Defries et al., 1995; Loveland & Belward, 1997; Loveland et al., 2000;
Bontemps et al., 2011). The units mapped are based on simple, broadly recognizable categories,
such as evergreen forest, grassland, shrubland, and agriculture. Loveland & Belward (1997)
produced the DISCover global land cover dataset with remotely sensed imagery with a classification
system based on leaf phenology and morphology characteristics gleaned from NDVI composites.
Similarly, the aforementioned LCCS has identified the global extent of grassland, with its latest
application within the Globcover 2009 dataset (Bontemps et al., 2011). Additional biodiversity
information can be included, as suggested by Tomaselli et al. (2013), where General Habitat Types
are recognized by using the LCCS in combination with high resolution satellite imagery. Although
this approach advances the broad-scale mapping of grasslands, their simple categories lack the
information on ecological factors and biodiversity provided by the above more ecologically based
approaches to defining grasslands (Bailey, 2009) Nonetheless, these land cover data sets can
provide important inputs to studies that seek to relate land cover variables to ecological and
vegetation patterns (Lauver & Whistler, 1993; Muldavin et al., 2001; Chacón-Moreno, 2003; Lowry
et al., 2007).
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