Conservation planning in a changing world
213
8.4 NESTEDNESS
The concept of nestedness was fi rst introduced some
70 years ago (see Ulrich et al. , 2009 ) to describe patterns of species composition within continental biotas
and among isolated habitats such as islands and landscape fragments. In a perfect nested pattern, when a
set of habitat patches is ordered by increasing species
richness, it will be found that the smallest assemblages
make up a subset of the species found in the next larger
assemblage, and so on, throughout the series (see
Figure 8.10 ).
Nestedness is thus a particular form of non -
randomness of assemblage composition across a set of
isolates. Any such non - random pattern is potentially
of interest to conservation biogeographers, as it may
inform judgements about the design of protected area
systems within landscapes and regions. Nestedness
may, in theory, arise from differential dispersal and
colonization abilities (especially for young islands); or
differential rates of extinction (e.g. for land bridge
islands or newly fragmented habitat islands); or from a
strong nestedness of habitat types with increasing
‘ island ’ size (Whittaker & Fern á ndez - Palacios, 2007 );
or possibly from other processes (Table 8.3 ).
Nestedness analyses became popular among
ecologists and biogeographers only after Patterson
and Atmar (1986) developed a statistically rigorous
approach for analysing nested subsets. They were
interested in nestedness patterns derived by extinction
of species from land bridge islands, and their metric
refl ects this emphasis. They proposed that nestedness
patterns for such islands most likely refl ect orderly
sequences of extinctions on such islands and in fragmented landscapes (see their Fig. 4). They introduced
an intuitive ‘ matrix temperature ’ metric to quantify
the pattern of nestedness. Hot matrices are those with
more random presences of species and cool matrices
are those where species presences are more nested. The
matrix temperature could be calculated with a software package, The Nestedness Temperature Calculator
(Atmar & Patterson, 1993, 1995 ).
The nestedness concept, as applied by Patterson and
Atmar, is based on ordering the data matrix by the
size of fauna or fl ora, i.e. it is richness - ordered nestedness. Some authors, however, have ordered the data
matrix not by species richness but by island area,
which has been termed area - ordered nestedness, or
even by island isolation, i.e. distance - ordered nestedness (e.g. Lomolino & Davis, 1997 ; Whittaker &
landscape may sustain a metapopulation but, for
dispersal - limited snails, they can at best sustain isolated populations.
Metapopulation models, therefore, are not generally
applicable to all organisms in fragmented systems
(Fahrig & Paloheimo, 1988 ). Hoopes & Harrison
(1998) caution against the general use of such models
in conservation decision - making because of the prevalence of situations where functional metapopulation
dynamics either do not occur, or where they fail to
match the assumptions of the models.
The following are additional important shortcomings of the metapopulation approach:
• Several authors have noted that metapopulation
models are extremely data - demanding and usually
require data that are very diffi cult to obtain (Kindvall
& Ahl é n, 1992 ; Doak & Mills, 1994 ). Moreover, model
results tend to be very sensitive to poorly estimated
parameters, and the predictions of such models have
therefore frequently been found to be inaccurate (e.g.
Harrison et al ., 1993 ; Wilson et al. , 1994 ).
• Most empirical examples of metapopulations pertain
to single species or a group of interacting species
(Hanski & Gilpin, 1991 ), but not to multi - species ecological communities.
• Most metapopulation models assume no distance
effects (Fahrig & Merriam, 1994 ) although, in practice,
dispersal abilities vary from species to species. For
instance, metapopulations of frogs may be infl uenced
by the availability of suitable habitat in the surrounding ≈ 500 m, whereas for birds this distance may be
≈ 3 km, because of large differences in mobility resulting in the different abilities of frogs and birds to disperse. The issue of ‘ scale ’ has therefore been considered
important in studying fragmented landscapes (e.g.
Doak et al. , 1992 ) – an issue which classic metapopulation models do not address.
• It is important for conservationists to recognize that
many local populations may not be at equilibrium and
regional processes may be critical in sustaining metapopulations (Hanski 1999 ).
In conclusion, metapopulation theory offers a useful
framework for thinking about isolation and fragmentation (Hanski, 1999 ) but, if the concept is to be useful
as a theoretical framework for conservation decision -
making, it must be extended from the original simplistic models to allow for the differing degrees of
population connectivity in fragmented landscapes and
differing forms of inter - patch relationships, as in real -
world systems.
213
8.4 NESTEDNESS
The concept of nestedness was fi rst introduced some
70 years ago (see Ulrich et al. , 2009 ) to describe patterns of species composition within continental biotas
and among isolated habitats such as islands and landscape fragments. In a perfect nested pattern, when a
set of habitat patches is ordered by increasing species
richness, it will be found that the smallest assemblages
make up a subset of the species found in the next larger
assemblage, and so on, throughout the series (see
Figure 8.10 ).
Nestedness is thus a particular form of non -
randomness of assemblage composition across a set of
isolates. Any such non - random pattern is potentially
of interest to conservation biogeographers, as it may
inform judgements about the design of protected area
systems within landscapes and regions. Nestedness
may, in theory, arise from differential dispersal and
colonization abilities (especially for young islands); or
differential rates of extinction (e.g. for land bridge
islands or newly fragmented habitat islands); or from a
strong nestedness of habitat types with increasing
‘ island ’ size (Whittaker & Fern á ndez - Palacios, 2007 );
or possibly from other processes (Table 8.3 ).
Nestedness analyses became popular among
ecologists and biogeographers only after Patterson
and Atmar (1986) developed a statistically rigorous
approach for analysing nested subsets. They were
interested in nestedness patterns derived by extinction
of species from land bridge islands, and their metric
refl ects this emphasis. They proposed that nestedness
patterns for such islands most likely refl ect orderly
sequences of extinctions on such islands and in fragmented landscapes (see their Fig. 4). They introduced
an intuitive ‘ matrix temperature ’ metric to quantify
the pattern of nestedness. Hot matrices are those with
more random presences of species and cool matrices
are those where species presences are more nested. The
matrix temperature could be calculated with a software package, The Nestedness Temperature Calculator
(Atmar & Patterson, 1993, 1995 ).
The nestedness concept, as applied by Patterson and
Atmar, is based on ordering the data matrix by the
size of fauna or fl ora, i.e. it is richness - ordered nestedness. Some authors, however, have ordered the data
matrix not by species richness but by island area,
which has been termed area - ordered nestedness, or
even by island isolation, i.e. distance - ordered nestedness (e.g. Lomolino & Davis, 1997 ; Whittaker &
landscape may sustain a metapopulation but, for
dispersal - limited snails, they can at best sustain isolated populations.
Metapopulation models, therefore, are not generally
applicable to all organisms in fragmented systems
(Fahrig & Paloheimo, 1988 ). Hoopes & Harrison
(1998) caution against the general use of such models
in conservation decision - making because of the prevalence of situations where functional metapopulation
dynamics either do not occur, or where they fail to
match the assumptions of the models.
The following are additional important shortcomings of the metapopulation approach:
• Several authors have noted that metapopulation
models are extremely data - demanding and usually
require data that are very diffi cult to obtain (Kindvall
& Ahl é n, 1992 ; Doak & Mills, 1994 ). Moreover, model
results tend to be very sensitive to poorly estimated
parameters, and the predictions of such models have
therefore frequently been found to be inaccurate (e.g.
Harrison et al ., 1993 ; Wilson et al. , 1994 ).
• Most empirical examples of metapopulations pertain
to single species or a group of interacting species
(Hanski & Gilpin, 1991 ), but not to multi - species ecological communities.
• Most metapopulation models assume no distance
effects (Fahrig & Merriam, 1994 ) although, in practice,
dispersal abilities vary from species to species. For
instance, metapopulations of frogs may be infl uenced
by the availability of suitable habitat in the surrounding ≈ 500 m, whereas for birds this distance may be
≈ 3 km, because of large differences in mobility resulting in the different abilities of frogs and birds to disperse. The issue of ‘ scale ’ has therefore been considered
important in studying fragmented landscapes (e.g.
Doak et al. , 1992 ) – an issue which classic metapopulation models do not address.
• It is important for conservationists to recognize that
many local populations may not be at equilibrium and
regional processes may be critical in sustaining metapopulations (Hanski 1999 ).
In conclusion, metapopulation theory offers a useful
framework for thinking about isolation and fragmentation (Hanski, 1999 ) but, if the concept is to be useful
as a theoretical framework for conservation decision -
making, it must be extended from the original simplistic models to allow for the differing degrees of
population connectivity in fragmented landscapes and
differing forms of inter - patch relationships, as in real -
world systems.