The distribution of diversity: challenges and applications
49
methods in conservation biogeography include those
that incorporate a phylogenetic diversity metric (Faith
et al ., 2004b ), and a variety of genetic approaches to
evaluate the distinctiveness of populations and species
(Avise & Hamrick, 1996 ; Frankham et al ., 2002 ), patterns of endemism and biodiversity hotspots (Verboom
et al ., 2009 ). These metrics have considerable potential
for incorporation into protected area planning processes (Chapters 5 and 6 ).
3 Explaining the differences in numbers as well
as types of species among geographical areas
and along geographical gradients, including patterns related to area, isolation, latitude, elevation and depth.
One of the most pervasive patterns in nature, the
species – area relationship, was recognized rather soon
after geographically representative natural history
specimens began to accumulate from global explorations (Forster, 1778 ) and regional collections (De
Candolle, 1855 ; Watson, 1859 ). Formal mathematical
analyses were initiated early in the 20th century
(Arrhenius, 1921 ; Gleason, 1922 ). A long history of
theory and modelling in conservation biogeography
has developed, based on the predicted ‘ meltdown ’ in
species diversity following habitat fragmentation and
loss and the consequent impact on species – area relationships (Chapter 8 ). Several other themes in conservation biogeography have relied heavily on knowledge
of non - random distributions of species richness and
species types across geography; examples include the
grand clines of diversity from poles to the equator and
the concentration of endemic species in biodiversity
hotspots (Chapter 5 ; Myers et al ., 2000 ).
While the value of mapping biodiversity for strategic
conservation planning purposes is clear, the reality is
that there are still many gaps in our knowledge of what
is out there, how it is distributed and the extent to
which it is threatened with extinction. These are the
topics covered in the following section.
4.2 THREE KNOWLEDGE SHORTFALLS
4.2.1 The Linnean s hortfall
The Linnean shortfall is named after the Swedish naturalist Karl von Linne (1707 – 1778), better known
through his ‘ Latinized ’ sobriquet of Carolus Linnaeus.
He was the creator of the system of Latin binomials
and is widely regarded as the father of modern
1 Classifying geographical regions based on
their biotas.
Sclater (1858) and Wallace (1876) would have been
unable to construct the six great terrestrial biogeographical regions of the world that are still used today
with modifi cations (Cox, 2001 ; Kreft & Jetz, 2010 )
without recognition and analysis of non - random
global and regional distributions of birds, mammals,
and other groups. Within conservation biogeography,
these early representations of global biodiversity
became constituent building blocks of the Dasmann
(1973) and Udvardy (1975) IUCN Biogeographical
Regions framework discussed in Chapter 5 .
2 Reconstructing the historical development
of lineages and biotas, including their origin,
spread, and diversifi cation.
Both Darwin (1859) and Wallace (below) argued
strongly in favour of a ‘ natural ’ system of taxonomy
that formed the informational basis required to study
the geographical distribution of animals and plants:
A little consideration will convince us, that no
inquiry into the causes and laws which determine
the geographical distribution of animals or plants
can lead to satisfactory results, unless we have a tolerably accurate knowledge of the affi nities of the
several species, genera, and families to each other; in
other words, we require a natural classifi cation to
work upon.
(Wallace, 1876 , p. 83)
Most modern methods of reconstructing biogeographical history rely on either phylogenetic methods of
reconstructing ‘ natural classifi cations ’ of taxa based
on ‘ descent with modifi cation ’ (Hennig, 1966 ) or some
form of genetically - based population similarity analysis, with the mapping of these relationships onto geography (Avise, 2000 ; Riddle et al ., 2008 ). The use of
genetic data to investigate the geographical patterns of
historical and ongoing connections between populations within a single species or several closely - related
species is called phylogeography (Avise, 2000, 2009 ;
Riddle & Hafner, 2006 ), and this emerging sub - fi eld is
generally recognized as one of the most important
recent advances in biogeography. Phylogeography has
also spun off several newer approaches, including
landscape genetics and phylochronology (the idea of
focusing on change in genetic diversity of populations
in given localities over time; Hadly et al ., 2004 ).
Applications of phylogenetic and population genetic
49
methods in conservation biogeography include those
that incorporate a phylogenetic diversity metric (Faith
et al ., 2004b ), and a variety of genetic approaches to
evaluate the distinctiveness of populations and species
(Avise & Hamrick, 1996 ; Frankham et al ., 2002 ), patterns of endemism and biodiversity hotspots (Verboom
et al ., 2009 ). These metrics have considerable potential
for incorporation into protected area planning processes (Chapters 5 and 6 ).
3 Explaining the differences in numbers as well
as types of species among geographical areas
and along geographical gradients, including patterns related to area, isolation, latitude, elevation and depth.
One of the most pervasive patterns in nature, the
species – area relationship, was recognized rather soon
after geographically representative natural history
specimens began to accumulate from global explorations (Forster, 1778 ) and regional collections (De
Candolle, 1855 ; Watson, 1859 ). Formal mathematical
analyses were initiated early in the 20th century
(Arrhenius, 1921 ; Gleason, 1922 ). A long history of
theory and modelling in conservation biogeography
has developed, based on the predicted ‘ meltdown ’ in
species diversity following habitat fragmentation and
loss and the consequent impact on species – area relationships (Chapter 8 ). Several other themes in conservation biogeography have relied heavily on knowledge
of non - random distributions of species richness and
species types across geography; examples include the
grand clines of diversity from poles to the equator and
the concentration of endemic species in biodiversity
hotspots (Chapter 5 ; Myers et al ., 2000 ).
While the value of mapping biodiversity for strategic
conservation planning purposes is clear, the reality is
that there are still many gaps in our knowledge of what
is out there, how it is distributed and the extent to
which it is threatened with extinction. These are the
topics covered in the following section.
4.2 THREE KNOWLEDGE SHORTFALLS
4.2.1 The Linnean s hortfall
The Linnean shortfall is named after the Swedish naturalist Karl von Linne (1707 – 1778), better known
through his ‘ Latinized ’ sobriquet of Carolus Linnaeus.
He was the creator of the system of Latin binomials
and is widely regarded as the father of modern
1 Classifying geographical regions based on
their biotas.
Sclater (1858) and Wallace (1876) would have been
unable to construct the six great terrestrial biogeographical regions of the world that are still used today
with modifi cations (Cox, 2001 ; Kreft & Jetz, 2010 )
without recognition and analysis of non - random
global and regional distributions of birds, mammals,
and other groups. Within conservation biogeography,
these early representations of global biodiversity
became constituent building blocks of the Dasmann
(1973) and Udvardy (1975) IUCN Biogeographical
Regions framework discussed in Chapter 5 .
2 Reconstructing the historical development
of lineages and biotas, including their origin,
spread, and diversifi cation.
Both Darwin (1859) and Wallace (below) argued
strongly in favour of a ‘ natural ’ system of taxonomy
that formed the informational basis required to study
the geographical distribution of animals and plants:
A little consideration will convince us, that no
inquiry into the causes and laws which determine
the geographical distribution of animals or plants
can lead to satisfactory results, unless we have a tolerably accurate knowledge of the affi nities of the
several species, genera, and families to each other; in
other words, we require a natural classifi cation to
work upon.
(Wallace, 1876 , p. 83)
Most modern methods of reconstructing biogeographical history rely on either phylogenetic methods of
reconstructing ‘ natural classifi cations ’ of taxa based
on ‘ descent with modifi cation ’ (Hennig, 1966 ) or some
form of genetically - based population similarity analysis, with the mapping of these relationships onto geography (Avise, 2000 ; Riddle et al ., 2008 ). The use of
genetic data to investigate the geographical patterns of
historical and ongoing connections between populations within a single species or several closely - related
species is called phylogeography (Avise, 2000, 2009 ;
Riddle & Hafner, 2006 ), and this emerging sub - fi eld is
generally recognized as one of the most important
recent advances in biogeography. Phylogeography has
also spun off several newer approaches, including
landscape genetics and phylochronology (the idea of
focusing on change in genetic diversity of populations
in given localities over time; Hadly et al ., 2004 ).
Applications of phylogenetic and population genetic