Chapter 8: Climate change implications for conservation planning
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Slides: 27
Duration: 00:13:04
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presentations\Chapter8.Belinda Reyers - Conservation planning; climate change implications.ppt
Presenter Details:
Name: Belinda Reyers
Title: Dr
Email: breyers@csir.co.za
Bio: Dr Belinda Reyers has been involved in the field of conservation planning for some time, and has extensive publications.
Her research interests include the study, measurement and conservation of biodiversity, with particular focus on the grasslands
of South Africa. She contributed to the recently-published Global Ecosystem Assessment, is an editor of Animal Conservation
journal, and is a council member of the Zoological Society of Southern Africa. Dr Reyers is currently employed by CSIR
Environmentek in Stellenbosch.
Slide 1: Climate change implications
Duration: 00:00:14
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Conservation planning:
climate change
implications
Presented by
Belinda Reyers
CSIR Environmentek
Notes:
For Conservation Planners the effects of climate change are a very important consideration to include in conservation plans
Slide 2:Conservation planning
Duration: 00:00:25
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Conservation planning


Use of systematic procedures to identify priority
geographic areas for conservation attention
Margules & Pressey (2000)
Notes:
A brief introduction to conservation planning follows for those of you not familiar with the field
Basically, conservation planning is the use of systematic techniques to identify priority areas for conservation attention – be that protected areas or forms
of conservation management. Margules and Pressey present a good review of the field in the 2000 publication in Nature
Slide 3:The process of conservation planning
Duration: 00:00:29
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The process of conservation planning
Biodiversity data
Transformation
Protected areas
Targets
Software and GIS
Notes:
This slide summarises the process of conservation planning
Spatial data on biodiversity, land cover transformation and protected areas are inputs into the process, along with conservation targets for that biodiversity
e.g. the numbers of species or area of ecosystems desired as goals of the conservation plan. The software and GIS process these data and provide
outputs of conservation priority areas which can differ depending on the software, conservation plan and inputs
Slide 4: Conservation planning
Duration: 00:00:30
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Conservation planning


Static vs. dynamic focus
Biodiversity data
- Species distributions
- Habitat extent
- Ecological and evolutionary processes
Notes:
Traditionally the field of conservation planning has a very static focus and is based on the distribution of biodiversity at one point in time. More recently,
there has been a strong shift towards a dynamic approach to conservation management. This dynamic management process takes into account various
elements of available biodiversity data, including species distributions, the extent and types of habitat, and the ecological and evolutionary processes that
gave rise to (and act within) the area being studied.
Slide 5 : Climate change
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Climate change
0-4
5 - 12
13 - 20
21 - 29
30 - 41
50
Current
0
50
100
0-4
5 - 12
13 - 20
21 - 29
30 - 41
150 Kilometers
Future
50
0
50
100
150 Kilometers
Notes:
If one looks at this slide of the current distribution of species richness for a selected set of taxa in the grasslands of South Africa and compares it to the
predicted distribution of that species richness under conditions of climate change, one understands that planning for the conservation of these species will
differ between current and future scenarios of climate change. This is the challenge that must be met by modern conservation planners.
Slide 6: Climate change affects future species distributions
Duration: 00:00:35
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Notes:
Additionally this work on the distribution of species in South Africa shows how the current and future plant diversity and distributions of the country will
differ significantly, and thus a conservation plan based exclusively on current information will not cater for what the future holds. The blank spots on the
future distribution do not mean necessarily that the northern areas of the country will rapidly become desert, but rather that the species distribution in these
areas is likely to be dominated by weedy species, fast-spreading adapted aliens, and small numbers of the extant species that are existing in a marginal
habitat.
Slide 7: Future conservation planning
Duration: 00:00:43
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Future conservation planning

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Conservation strategies as we know them – soon obsolete
Formal flagship protected areas predicted to lose many of their
species (Rutherford et al. 1999; Erasmus et al. 2002)
Need to include implications of climate change into
conservation planning
Dynamic conservation planning
Future climate change constrained
Climate change-integrated conservation strategies (CCS)
Notes:
Work on conservation planning now indicates that the conservation strategies that we use today will soon be obsolete under conditions of climate change.
Examples in support of this statement are the predictions of what will happen to flagship protected areas in South Africa, where many of the current
endemic species are likely to be lost. For more details, the work of Rutherford et al, and Erasmus et al should be considered.
There is thus an urgent need to include the implications of climate change into conservation planning and ensure that conservation planning becomes
dynamic. Most importantly, it must include the constraints of future climate change. These novel conservation strategies have been termed climate
change-integrated strategies, or CCS for short.
Slide 8: Needs
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Needs
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Regional modeling of biodiversity response
Selection of protected areas with climate change as an
integral factor
Landscape level management of biodiversity
Regional coordination of management
Polluter pays
(Hannah et al, 2002)
Notes:
What is needed for these strategies to work? Hannah presents an overview of these climate change integrated strategies which specifies the needs for
regional modeling of biodiversity responses to climate change. The selection of new protected areas with climate change as an integral factor,
management of biodiversity at a broader landscape level, regional coordination of management, and the principle of polluter pays (currently being
implemented in many places) are being included in plans, and thus facilitate these CCS.
Slide 9: Currently
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Currently

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Range of methods available
- Biome movement
- Mapping gradients
- Detailed climate change studies on particular species of
conservation concern
Theoretical
Practical framework
- Data, infrastructure and expertise
- Type of CCS
Notes:
This presentation presents an overview of some of the CCS types of conservation planning available – these include biome movement models, gradient
mapping, and detailed climate change studies on particular species. These steps allow for planning of “escape routes” or movement corridors for species
under extensive threat of climate change.
At this stage, however, most of this planning is theoretical, with minimal integration with regional planning initiatives as yet.
The appropriate methods for a practical framework will depend on the data, infrastructure and expertise available, and to a large extent the types of
climate change-integrated strategies used will both be dependent on regional requirements, and determine the optimal integration framework.
Slide 10: Framework for climate change-integrated conservation strategies (CCS)
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TIER 3
CCS3
TIER 2
CCS2
TIER 1
CCS1
Increasing complexity of strategy
Data & expertise available
Framework for climate changeintegrated conservation strategies
(CCS)
Notes:
This framework presents the CCS methods and their requirements which will enable users to decide which is the most appropriate
The CCS methods are presented as Tier 1, 2, and 3 methods. As one moves from Tier 1 to 2 to 3 so the data and expertise requirement of the CCS
method increase, while the complexity of the strategy also increases. The following slides will work through this framework with examples
Slide 11: TIER 1 CCS 1 – Areas of stability/resilience
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TIER 1
CCS 1 – Areas of stability/resilience
Data available
Expertise
Method
Refinements
broad ecosystem map
topographical information
model future distribution of
ecosystems/biomes
Identify areas of greatest
stability under 1+ scenarios
Refine those using areas of high
topographic diversity
Notes:
Tier 1 Climate change-integrated conservation strategies aim to identify areas of greatest stability or resilience to climate change from a biodiversity
perspective. They require data on broad biomes (climatically defined), and if possible topographic information. They require expertise in modelling the
current and future distribution of these biomes climatically. The method uses the current and future distribution of biomes to identify areas of greatest
similarity or stability under 1 or more scenarios of climate change – it is then possible to refine these areas by selecting from them topographically diverse
regions
Slide 12: Projected future change in biomes
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Projected future change in biomes
Notes:
Herewith a slide demonstrating Tier 1 CCS methods. This is a slide of the current and future distribution of South Africa’s biomes taken from work done by
SANBI.
Slide 13: CCS 1 – Areas of stability/resilience
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CCS 1 – Areas of
stability/resilience
TIER 1
Notes:
This slide demonstrates the biomes and areas of highest stability in the biome under 3 scenarios of climate change – the darker areas are more stable
under more scenarios. From these stable areas – areas of topographic diversity can then be selected as demonstrated by the next map. These areas can
then be fed – along with other data – into a conservation plan
Slide 14: TIER 2 CCS 2 – Areas of current & future conservation value
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TIER 2
CCS 2 – Areas of current & future conservation
value
Data available
broad scale species distributions
(Presence/absence; interpolated; grid cell)
Expertise
model species distributions
conservation planning
Method
Identify areas of high conservation value
based on current & future species
distributions
Refinements
Assess overlap
Notes:
TIER 2 methods assess areas of current and future importance to conservation based on the predicted distributions of selected species.
The data requirements are broad scale species distribution data, and expertise required includes the ability to model species distributions and
conservation planning experience. The method involves identifying areas of high conservation value based on current and future species distributions
which can be refined to include areas of overlap
Slide 15: Conservation value
Duration: 00:00:11
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Conservation value
Irreplaceability
0 - 0.1
0.1 - 0.36
0.36 - 0.65
0.65 - 0.89
0.89 - 1
0-4
5 - 12
13 - 20
21 - 29
30 - 41
50
0
50
100
150 Kilometers
70
0
70 140 Kilometers
TIER 2
Notes:
This example from the grasslands of South Africa shows the conservation value of grid cells (measured as irreplaceability) for the current distribution of a
suite of species.
Slide 16: Conservation value
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Conservation value
0- 4
5 - 12
13 - 20
21 - 29
30 - 41
50
0
50
100 150 Kilometers
Irreplaceability
0 - 0.1
0.1 - 0.36
0.36 - 0.65
0.65 - 0.89
0.89 - 1
70
0
70 140 Kilometers
TIER 2
Notes:
This next slide shows the conservation value for the future predicted distribution of these same species
Slide 17: CCS 2 – Areas of conservation value
Duration: 00:00:20
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CCS 2 – Areas of conservation value
Irreplaceability
Irreplaceability
0 - 0.1
0.1 - 0.36
0.36 - 0.65
0.65 - 0.89
0.89 - 1
0 - 0.1
0.1 - 0.36
0.36 - 0.65
0.65 - 0.89
0.89 - 1
Current
70
0
70 140 Kilometers
Future
70
0
70 140 Kilometers
TIER 2
Notes:
One can use these 2 products, their differences and overlap in a conservation plan. Areas that remain important under current and future conditions are
critical, areas that are either not important currently but become so and areas that are important currently and lose this importance need to be assessed
and sensibly included.
Slide 18: CCS 3 – Species dispersal
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CCS 3 – Species dispersal

Data available: Expertise: Complex climate time
step modeling

Identify areas required by each species to track
climate change
Notes:
CCS 3 on the 3rd Tier acknowledges the fact that the species need to get from point A to point B as they track changing climate, but the data and
expertise requirements are very complex and demanding and are currently held by few institutions and individuals
Slide 19: Tier 3 CCS3 – Bioclimatic & Dispersal Time Slice modelling
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Tier 3
CCS3 – Bioclimatic & Dispersal Time
Slice modelling
Data available
species localities (fine scale)
life history information
Expertise
complex climate time slice modeling
Method
Identify areas/corridors required by
species to track climate change
Notes:
Data include information on fine scale species localities and life history information on these species required to model their movements from point A to
point B e.g. distance moved in a time slice. The expertise is complex. The method focuses on identifying areas and corridors required by the species to
track climate change
Slide 20: Tier 3 CCS3 – Bioclimatic & Dispersal Time Slice modelling
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Tier 3
CCS3 – Bioclimatic & Dispersal Time
Slice modelling


Midgley, Hughes et al. (In Press)
Uncertainties in projecting the impacts of climate
change on biodiversity
-
Assumptions of niche based modeling
GCM projections
Migration rate & dispersal abilities
•
•
2 extreme assumptions: full (instantaneous & unlimited) or null
migration
Species specific parameterization
Notes:
Work on this type of CCS is novel and is in press for a South African example. It relies on several assumptions (as do most CCS) these assumptions
include the basics assumptions of niche based modeling, the GCM projections and the assumptions of dispersal. Although this later assumption is dealt
with more explicitly in this CCS than in the previous ones. Usually the assumption is that the biodiversity features either have full migration from point A to
point B, or don’t make it at all. This CCS allows for species specific parameterisation and thus does not make the assumption of full or no migration.
Slide 21: Tier 3 CCS3 – Bioclimatic & Dispersal Time Slice modelling
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Tier 3
CCS3 – Bioclimatic & Dispersal Time
Slice modelling
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336 Protea species (Protea Atlas)
60 000 georeferenced sites
Presence-absence - 250 000 records
GCM HAD2
5 bioclimatic variables: Soil fertility and texture
1 minute grid
Modeled 10 year time intervals = decadal time slices
Migration rate determined per time slice based on
dispersal agent
-
1 cell per time slice for ant and rodents dispersed spp.
3 cells per time slice for wind dispersed spp.
Notes:
The work done by Midgley and Hughes worked with 336 protea species in 60 000 sites with 250 000 records of presence absence (a very detailed
database). Using the GCM HAD2 and 5 bioclimatic variables they modeled 10 year intervals of species movement under climate change. The migration
rate and thus distance moved was determined by the dispersal agent used by each species
Slide 22: Tier 3 CCS3 – Bioclimatic & Dispersal Time Slice modelling
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Tier 3
CCS3 – Bioclimatic & Dispersal Time
Slice modelling
Click to enlarge
Notes:
These maps show the movement of these species per decadal time slice and illustrate the outcomes for species using null, full and partial assumptions of
migration. As can be seen, assuming no migration, there is a good likelihood that the threatened species may face extinction within 50 years, given the
Hadley GCM’s predicted changes in climate. Assuming partial movement, the area in which the species still exists by 2050 is considerably reduced, and
limited to several mountain refugia that are close to extant areas. Even assuming full movement at the maximum rate available to each species, the area
of survival is considerably reduced, making it clear that climate change is likely to have a significant impact on the proteas of this region.
Slide 23: Tier 3 CCS3 – Bioclimatic & Dispersal Time Slice modelling
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Tier 3
CCS3 – Bioclimatic & Dispersal Time
Slice modelling


Method was applied to the problem of conservation planning in
Williams et al. In Press
Method for identifying multiple corridors of connectivity
through shifting habitat suitabilities that seeks to minimise
-


dispersal demands and then
the amount of land area required
Goal is to represent each species where possible in at least 35
grid cells (approximately 100 km²) at all times between 2000
and 2050 despite climate change.
Identify dispersal chains backwards
-
Heuristic algorithm in WORLDMAP
Suitable habitat within specified distance
Notes:
The method of time slice modelling was applied to the problem of conservation planning, as shown in a paper by Williams et al which is still currently in
press. Time slice modelling is a method of identifying multiple corridors of connectivity through changing habitats as they become suitable. It seeks to
minimise firstly the dispersal demands on a species (such as expecting it to cross large areas of transformed land), as well as minimising the amount of
land required for preparing these corridors. The ultimate goal is to represent each species wherever possible in at least 35 grid cells (each of which is
approximately 100 square kilometres), at all times between 2000 and 2050, despite the shifting of the climate.
This is done by identifying the dispersal chain backwards from feasible areas of survival in 2050 to current distributions. A heuristic algorithm in the
WORLDMAP package was used, and it selected only viable habitats within a specified distance of the population. This is all explained graphically in the
following slide.
Slide 24: Tier 3 CCS3 – Bioclimatic & Dispersal Time Slice modelling
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Tier 3
CCS3 – Bioclimatic & Dispersal Time
Slice modelling
Click to enlarge
Notes:
The method searches backwards from 2050 for corridors linking cells through the decadal times slides – the cells have to be a set distance apart
depending on the dispersal agent – this figure has a dispersal of one cell per time slice, so that each decadal transition must find a species in a cell
adjacent to the current distribution. This process in this case resulted in only one viable corridor linking the species moving 1 cell per 10 year from 2000 to
2050.
Slide 25: CCS 3 – Species dispersal
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CCS 3 – Species dispersal
• (light grey) cells with 66% or
more transformation of habitat
•(green) cells with existing
protection
•(red) cells chosen to
represent goal-essential
chains
•(blue) cells chosen to
complete chains for species
part-represented within
existing protected cells and
goal-essential cells
•(orange) cells chosen using
an iterative complementarity
algorithm based on greedy
richness.
Click to enlarge
Notes:
This is the output of one of these assessments for the Proteaceae
Slide 26: Test yourself
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Check your understanding of
Chapter 8
PASS MARK 80%
Please do not proceed further
until you have PASSED
Chapter 8: test yourself
Notes:
Slide 27: Links to other chapters
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Links to other chapters
Chapter
Chapter
Chapter
Chapter
Chapter
Chapter
Chapter
Next
1
2
3
4
5
6
7
The evidence for anthropogenic climate change
Global Climate Models
Climate change scenarios for Africa
Biodiversity response to past climates
Adaptations of biodiversity to climate change
Approaches to niche-based modelling
Ecosystem change under climate change
Chapter 8 Implications for strategic conservation planning
Chapter 9 Economic costs of conservation responses
I hope that found chapter 8 informative, and that you
enjoy chapter 9.
Notes:
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