2.2 Extent and Determinants of Genetic Extinction
19
2.2.1.2
Genetic Extinction in Agrobiodiversity
It is essential to define the underlying unit for PGRFA for the assessment of the
development of agrobiodiversity over time, as well as for an economic discussion
on the benefits and costs of PGRFA conservation. Diversity is characterized by
the genetic resources existent in a given framework as shown in Chapter 1. The
terminology of "plant genetic resources for food and agriculture" does not,
however, permit applications of economic concepts to the problems of scarcity,
conservation and transaction. Agrobiodiversity is often equated with richness in
crop varieties. In fact, crop varieties are the principal indicator for
agrobiodiversity-richness as well as the economic unit of benefit valuation. But
the correlation between phenotypic (expressed as differences in varieties) and
genetic diversity (on gene level) does not seem to be positive. After analyzing the
genetic diversity in some crops, and in spite of demonstrating much phenotypic
diversity, Clegg et al. (1992) found out that these crops had relatively narrow
primary and cultivated gene pools due to severe genetic bottlenecking, either
during the domestication process or later in the crop's evolutionary history. As
Smale states: "Plant populations that appear different may in fact carry the same
genes, and populations that appear the same may carry different genes." (1997,
p. 1259); this may lead to one conclusion: the same amount of varieties in two
different crops does not necessarily mean that the diversity of the two crops is
equally high in the region. The total genetic variation of all the different varieties
of one crop may be much less than that of the second crop, although the second
crop may have less varieties.
The conservators of PGRFA (the major actors of the supply side of PGRFA)
tend to favor the use of qualitative traits as marker genes to monitor the extent of
diversity. Often not agronomically relevant but frequently genetically linked to
agronomic traits, these traits are mostly components of the characterization data,
giving information on color, morphology or enzyme variants of accessions. The
major actors on the demand side of PGRFA (the breeders and the biotechnology
industry in general) are, however, more interested in quantitative traits, including
agronomic traits such as yield capacity or plant height. These quantitative traits,
which define the breeding goals, are lastly functions of certain biological
organisms. Often these traits are not due to single genes but rather to a
combination of genes representing one required function. For this reason Vogel
(1994) argues in favor of using the term "genetically coded function" (GCF) as a
basis for economic valuation of genetic resources exchange mechanisms.
Although this seems correct, GCF are determined by specific combinations of
genetically coded information (GCI). Finally, the actors (especially the
biotechnology industry), demand information, which determines certain functions.
As technologies improve, one objective will be the virtual construction and
reproduction of genetic basis (e.g., production of aminoacid sequences).
Consequently, in light of the emerging market, and the articulation of the demand
side, genetically coded information is recommended here as the unit, which can be
utilized for economic and - in the long run - institutional analysis, discussion and
19
2.2.1.2
Genetic Extinction in Agrobiodiversity
It is essential to define the underlying unit for PGRFA for the assessment of the
development of agrobiodiversity over time, as well as for an economic discussion
on the benefits and costs of PGRFA conservation. Diversity is characterized by
the genetic resources existent in a given framework as shown in Chapter 1. The
terminology of "plant genetic resources for food and agriculture" does not,
however, permit applications of economic concepts to the problems of scarcity,
conservation and transaction. Agrobiodiversity is often equated with richness in
crop varieties. In fact, crop varieties are the principal indicator for
agrobiodiversity-richness as well as the economic unit of benefit valuation. But
the correlation between phenotypic (expressed as differences in varieties) and
genetic diversity (on gene level) does not seem to be positive. After analyzing the
genetic diversity in some crops, and in spite of demonstrating much phenotypic
diversity, Clegg et al. (1992) found out that these crops had relatively narrow
primary and cultivated gene pools due to severe genetic bottlenecking, either
during the domestication process or later in the crop's evolutionary history. As
Smale states: "Plant populations that appear different may in fact carry the same
genes, and populations that appear the same may carry different genes." (1997,
p. 1259); this may lead to one conclusion: the same amount of varieties in two
different crops does not necessarily mean that the diversity of the two crops is
equally high in the region. The total genetic variation of all the different varieties
of one crop may be much less than that of the second crop, although the second
crop may have less varieties.
The conservators of PGRFA (the major actors of the supply side of PGRFA)
tend to favor the use of qualitative traits as marker genes to monitor the extent of
diversity. Often not agronomically relevant but frequently genetically linked to
agronomic traits, these traits are mostly components of the characterization data,
giving information on color, morphology or enzyme variants of accessions. The
major actors on the demand side of PGRFA (the breeders and the biotechnology
industry in general) are, however, more interested in quantitative traits, including
agronomic traits such as yield capacity or plant height. These quantitative traits,
which define the breeding goals, are lastly functions of certain biological
organisms. Often these traits are not due to single genes but rather to a
combination of genes representing one required function. For this reason Vogel
(1994) argues in favor of using the term "genetically coded function" (GCF) as a
basis for economic valuation of genetic resources exchange mechanisms.
Although this seems correct, GCF are determined by specific combinations of
genetically coded information (GCI). Finally, the actors (especially the
biotechnology industry), demand information, which determines certain functions.
As technologies improve, one objective will be the virtual construction and
reproduction of genetic basis (e.g., production of aminoacid sequences).
Consequently, in light of the emerging market, and the articulation of the demand
side, genetically coded information is recommended here as the unit, which can be
utilized for economic and - in the long run - institutional analysis, discussion and