150
Systematic conservation planning: past, present and future
• First, as natural landscapes become more fragmented, an increasing number of species will need to
disperse through an increasingly ‘ hostile ’ landscape
matrix if they are to maintain their genetic variability
in viable metapopulations. It is probable that connected landscapes improve the chances of this happening (Mackey et al ., 2008 ).
• Second, it is increasingly recognized that a large
number of species need a very large area to survive –
far larger than a protected area network will provide.
For example, the European goshawk ( Accipter principalis ) has a home range of 30 – 50 km
2 , and male
mountain lions ( Felis concolor ) in the western United
States have home ranges in excess of 400 km
2 (Wilcove
et al ., 1986 ). Moreover, many species have evolved to
be highly dispersive and regularly migrate vast distances to fi nd suitable conditions. These species clearly
require more space than could reasonably occur in a
small number of isolated protected areas, as the
resources they require for existence vary both spatially
and temporally (Gilmore et al . 2007 ). The survival of
these species will depend on their ability to move
between protected areas, and also the hostility of the
matrix habitat between protected areas.
• Third, habitat connectivity is likely to play an even
larger role with the onset of anthropogenic climate
change. Studies have estimated that by the middle of
the 21st century, range shifts due to climate change
will commonly span tens of kilometres (Kappelle et al .,
1999 ). There will be a clear need to have some form of
connectivity to fi nd suitable locations to which species
can migrate or take refuge (Peters & Darling, 1985 ;
Mackey et al ., 2008 ).
Planning for ‘ connectivity ’ has recently moved
beyond simply creating corridors or stepping - stones
between protected habitat patches. The concept of
connectivity conservation is now encompassed within
the concept of maintaining the ecological and evolutionary processes that generate and sustain biodiversity at various spatial and temporal scales (Soul é et al .,
2004 , Pressey et al ., 2007 ; Watson et al ., 2009 ).
Incorporating information on connectivity within a
systematic conservation planning framework enables
networks of priority areas to be designed with the goal
of maintaining genetic and demographical fl ows,
which may thus ensure the resilience of populations
to the effects of landscape conversion and climate
change.
To date, few studies have incorporated ecological
and evolutionary processes into conservation planning
multiple representations method selected the minimum
area needed to ensure that each species was represented in at least n sites (or the maximum number of
sites, if this was less than n ).
ii Percentage of range. This method was used to select
the minimum area of sites so that each species was
represented in at least p per cent of its range within the
study area.
iii Permanence rate. A permanence rate was calculated for each species in each site, being the frequency
with which a species was recorded in relation to the
number of visits to a site within a specifi ed time period.
The minimum area was selected so that each species
was represented in the site, or one of the sites, where it
has the highest permanence rate.
The results of the Rodrigues et al . (2000) study
clearly demonstrated that a single representation
strategy (a minimum of one site containing each
species) leads to very high effi ciency but low long -
term effectiveness. A multiple representation strategy
appeared to be safer than a strategy based on percentage of area. This is explained by the prioritization of
rare species that is an inevitable by - product of the
multiple representation approach. For example, if a
rare species only occurs in three sites and the multiple
representation criterion ( n ) is set to three sites or more,
then all the sites containing the species necessarily will
be included in the selection.
The drawback of a simple multiple representation
approach is that it assumes that all sites where the
species occur have a similar potential for sustaining
a population over a period of time. Strategies that
target sites where species are most likely to persist give
the greatest probability of long - term effectiveness
(Williams, 1998 ). Unsurprisingly then, the Rodrigues
et al . (2000) study found that choosing the best
site based on permanence rate was a better strategy
than investing in multiple, but blind, redundancy.
Unfortunately, estimating persistence rate requires a
lengthy and accurate time series, and other methods of
choosing the ‘ best ’ site such as using abundance data
are also expensive and time - consuming.
Ultimately, the decision about whether built - in
redundancy is a good way to select a reserve network
depends on data and resource availability (e.g. what
area/pattern of reserves can be maintained).
An additional approach beyond planning for multiple representation is to plan ways to maximize the biophysical connections among protected areas. This is
considered important for a number of reasons:
Systematic conservation planning: past, present and future
• First, as natural landscapes become more fragmented, an increasing number of species will need to
disperse through an increasingly ‘ hostile ’ landscape
matrix if they are to maintain their genetic variability
in viable metapopulations. It is probable that connected landscapes improve the chances of this happening (Mackey et al ., 2008 ).
• Second, it is increasingly recognized that a large
number of species need a very large area to survive –
far larger than a protected area network will provide.
For example, the European goshawk ( Accipter principalis ) has a home range of 30 – 50 km
2 , and male
mountain lions ( Felis concolor ) in the western United
States have home ranges in excess of 400 km
2 (Wilcove
et al ., 1986 ). Moreover, many species have evolved to
be highly dispersive and regularly migrate vast distances to fi nd suitable conditions. These species clearly
require more space than could reasonably occur in a
small number of isolated protected areas, as the
resources they require for existence vary both spatially
and temporally (Gilmore et al . 2007 ). The survival of
these species will depend on their ability to move
between protected areas, and also the hostility of the
matrix habitat between protected areas.
• Third, habitat connectivity is likely to play an even
larger role with the onset of anthropogenic climate
change. Studies have estimated that by the middle of
the 21st century, range shifts due to climate change
will commonly span tens of kilometres (Kappelle et al .,
1999 ). There will be a clear need to have some form of
connectivity to fi nd suitable locations to which species
can migrate or take refuge (Peters & Darling, 1985 ;
Mackey et al ., 2008 ).
Planning for ‘ connectivity ’ has recently moved
beyond simply creating corridors or stepping - stones
between protected habitat patches. The concept of
connectivity conservation is now encompassed within
the concept of maintaining the ecological and evolutionary processes that generate and sustain biodiversity at various spatial and temporal scales (Soul é et al .,
2004 , Pressey et al ., 2007 ; Watson et al ., 2009 ).
Incorporating information on connectivity within a
systematic conservation planning framework enables
networks of priority areas to be designed with the goal
of maintaining genetic and demographical fl ows,
which may thus ensure the resilience of populations
to the effects of landscape conversion and climate
change.
To date, few studies have incorporated ecological
and evolutionary processes into conservation planning
multiple representations method selected the minimum
area needed to ensure that each species was represented in at least n sites (or the maximum number of
sites, if this was less than n ).
ii Percentage of range. This method was used to select
the minimum area of sites so that each species was
represented in at least p per cent of its range within the
study area.
iii Permanence rate. A permanence rate was calculated for each species in each site, being the frequency
with which a species was recorded in relation to the
number of visits to a site within a specifi ed time period.
The minimum area was selected so that each species
was represented in the site, or one of the sites, where it
has the highest permanence rate.
The results of the Rodrigues et al . (2000) study
clearly demonstrated that a single representation
strategy (a minimum of one site containing each
species) leads to very high effi ciency but low long -
term effectiveness. A multiple representation strategy
appeared to be safer than a strategy based on percentage of area. This is explained by the prioritization of
rare species that is an inevitable by - product of the
multiple representation approach. For example, if a
rare species only occurs in three sites and the multiple
representation criterion ( n ) is set to three sites or more,
then all the sites containing the species necessarily will
be included in the selection.
The drawback of a simple multiple representation
approach is that it assumes that all sites where the
species occur have a similar potential for sustaining
a population over a period of time. Strategies that
target sites where species are most likely to persist give
the greatest probability of long - term effectiveness
(Williams, 1998 ). Unsurprisingly then, the Rodrigues
et al . (2000) study found that choosing the best
site based on permanence rate was a better strategy
than investing in multiple, but blind, redundancy.
Unfortunately, estimating persistence rate requires a
lengthy and accurate time series, and other methods of
choosing the ‘ best ’ site such as using abundance data
are also expensive and time - consuming.
Ultimately, the decision about whether built - in
redundancy is a good way to select a reserve network
depends on data and resource availability (e.g. what
area/pattern of reserves can be maintained).
An additional approach beyond planning for multiple representation is to plan ways to maximize the biophysical connections among protected areas. This is
considered important for a number of reasons: