490
describing the structure, composition, and function of biodiversity across its hierarchical levels (Noss 1990). The entity addressed by an EBV can be of two broad
types, distinguished by the approach used to define the set of organisms forming
this entity.
In the first approach, entities are formed by grouping organisms primarily on the
basis of their species identity. In other words, EBVs of this broad type measure
particular attributes of species—i.e., genetic diversity within a species in the case of
the Genetic Composition Class; distribution and abundance of a species in the
Species Populations Class; and traits of a species in the Species Traits Class.
The second approach to forming entities involves grouping organisms primarily
on the basis of where they occur. EBVs of this broad type measure collective attributes of the entire ecosystem formed by all of the organisms occurring within a
defined area (most typically an individual cell within a regular grid)—i.e., structural attributes of the ecosystem in the case of the Ecosystem Structure Class; functional attributes of the ecosystem in the Ecosystem Function Class; and various
dimensions of compositional diversity (e.g., taxonomic, genetic/phylogenetic,
functional) of organisms occurring within the ecosystem in the Community
Composition Class.
The relationships between these six EBV classes is depicted in Fig. 18.2. A few
key aspects of this overall typology are worth noting. First, the two broad approaches
to defining the entity addressed by an EBV, species-focused and ecosystemfocused, essentially work with the same pool of individual organisms but view
these organisms from two different perspectives—one grouping organisms according to species identity and the other according to location. While the entity
employed in species- focused EBVs will typically be defined primarily on the basis
of species identity, this could in some instances be qualified to focus, for example,
on the population of a species occurring in a particular area. Likewise, ecosystemfocused EBVs might, in some instances, focus on measuring collective attributes of
a particular subset of organisms occurring in an ecosystem rather than all organisms, with this subset defined in terms of taxonomy (e.g., all birds) or any other
trait of interest (e.g., all pollinators). Finally, it is important to caution against
directly equating the species- focused versus ecosystem-focused typology with
major sources of in-situ versus RS observation. Many different sources and types
of data can, and should, contribute to the population of EBVs across this entire
framework. Any given EBV class can typically be populated using data from multiple sources of in-situ and remote- sensing observation, and any given source will
typically contribute data to more than one EBV class. For example, EBVs in the
Community Composition Class could be populated with data both from RS of
compositional diversity (e.g., Morsdorf et al., Chap. 4) and from aggregation of
in-situ species observations and models (e.g., Pinto-Ledezma and Cavender-Bares,
Chap. 9), with the latter also contributing data simultaneously to the Species
Populations Class.
N. Fernández et al.
describing the structure, composition, and function of biodiversity across its hierarchical levels (Noss 1990). The entity addressed by an EBV can be of two broad
types, distinguished by the approach used to define the set of organisms forming
this entity.
In the first approach, entities are formed by grouping organisms primarily on the
basis of their species identity. In other words, EBVs of this broad type measure
particular attributes of species—i.e., genetic diversity within a species in the case of
the Genetic Composition Class; distribution and abundance of a species in the
Species Populations Class; and traits of a species in the Species Traits Class.
The second approach to forming entities involves grouping organisms primarily
on the basis of where they occur. EBVs of this broad type measure collective attributes of the entire ecosystem formed by all of the organisms occurring within a
defined area (most typically an individual cell within a regular grid)—i.e., structural attributes of the ecosystem in the case of the Ecosystem Structure Class; functional attributes of the ecosystem in the Ecosystem Function Class; and various
dimensions of compositional diversity (e.g., taxonomic, genetic/phylogenetic,
functional) of organisms occurring within the ecosystem in the Community
Composition Class.
The relationships between these six EBV classes is depicted in Fig. 18.2. A few
key aspects of this overall typology are worth noting. First, the two broad approaches
to defining the entity addressed by an EBV, species-focused and ecosystemfocused, essentially work with the same pool of individual organisms but view
these organisms from two different perspectives—one grouping organisms according to species identity and the other according to location. While the entity
employed in species- focused EBVs will typically be defined primarily on the basis
of species identity, this could in some instances be qualified to focus, for example,
on the population of a species occurring in a particular area. Likewise, ecosystemfocused EBVs might, in some instances, focus on measuring collective attributes of
a particular subset of organisms occurring in an ecosystem rather than all organisms, with this subset defined in terms of taxonomy (e.g., all birds) or any other
trait of interest (e.g., all pollinators). Finally, it is important to caution against
directly equating the species- focused versus ecosystem-focused typology with
major sources of in-situ versus RS observation. Many different sources and types
of data can, and should, contribute to the population of EBVs across this entire
framework. Any given EBV class can typically be populated using data from multiple sources of in-situ and remote- sensing observation, and any given source will
typically contribute data to more than one EBV class. For example, EBVs in the
Community Composition Class could be populated with data both from RS of
compositional diversity (e.g., Morsdorf et al., Chap. 4) and from aggregation of
in-situ species observations and models (e.g., Pinto-Ledezma and Cavender-Bares,
Chap. 9), with the latter also contributing data simultaneously to the Species
Populations Class.
N. Fernández et al.