a climate change vulnerability framework and interactive visualization tool

1. A Climate Change Vulnerability
Framework and Interactive
Visualization Tool
Adriana C. Bejarano and Jennifer L. Horsman
Research Planning, Inc. (RPI)

2. Acknowledgements
Funding for this project was provided by the U.S. Agency for International
Development (USAID) through the U.S. National Park Service (NPS).
The authors would like to thank Parque Nacionales Naturales de Colombia
for their significant contributions.

3. Research Planning, Inc.
(RPI), in partnership with
the National Park Service
and ICF International,
coordinated the
development of a scoring
framework and an
interactive visualization
tool to assesses the
vulnerability of one of the
Natural National Parks of
Colombia to impacts
associated with climate
change (e.g., sea level rise,
storm surge).

4. A climate change
vulnerability framework
was specifically
developed for Corales
del Rosario y San
Bernardo National
Natural Park
(PNNCRSB), Colombia, a
park designated to
protect coastal and
marine environments.

5. Corales del Rosario y San Bernardo
National Natural Park (PNNCRSB)
Islands comprising areas of PNNCRSB: a) Rosario; b) Tesoro (archipelago of Rosario); c) Mangle; and
d) Marvillosa (archipelago of San Bernardo). Photos: Esteban Zarza (b,c,d); Idalberto Peralta (a).
Source: Zarza-González and PNN, 2011

6. The primary objective of this
project was to use area-
specific information to assess
the vulnerability of coastal
and marine habitats, and
biological and socioeconomic
resources including
infrastructure to several
climate change factors.
Vulnerability scores were
developed based on resource-
specific sensitivity, exposure,
and adaptive capacity scores
associated with several
climate change factors (sea
surface and air temperature,
precipitation, ocean
acidification, sea level rise
and inundation from extreme
events).
Some PNNCRSB resources: a) Aerial view of coral reefs on Tintipán Island (archipelago of San Bernardo); b)
Mangrove forests; c) Sandy shoreline; d) Seagrasses; e) Coastal lagoons and sandy coasts; and f) Coral reef on
Tesoro Island (archipelago of Rosario). Photos: Cap. Jaime Borda (a,e); Esteban Zarza (b,c); Izumi Tsurita (d,f).
Source: Zarza-González and PNN, 2011

7. The climate change vulnerability framework
Sensitivity− the extent to which a resource is susceptible or sensitive to changes induced by one or more
climate change factors and is a function of resource-specific thresholds and tolerances to specific climate
change factors.
Exposure− the extent to which a resource is directly and physically impacted by changes induced by one
or more climate change factors. Exposure depends on the degree of exceedance of resource-specific
thresholds, as well as to the degree of physical exposure experienced by the resource.
Adaptive capacity− the potential capacity of a resource to adapt, adjust or cope with changes induced by
one or more climate change factors moderating, reducing or minimizing the magnitude of adverse direct
effects. These include responses leading to restored essential function, identity, structure and feedbacks.
Adaptive capacity could be greatly influenced by resource-specific inherent characteristics, which for the
purpose of this research included: dependency; level of specialization; dispersal/movement; functional
diversity; key features and uniqueness; conservation levels and status, management priority; existing threats.
These and possibly other non-climate change-related characteristics may contribute to a resource’s ability to
respond to climate change.
Vulnerability− the propensity or predisposition of a resource to be vulnerable or adversely impacted by
climate change. Vulnerability is a function of sensitivity, exposure and adaptive capacity.

8. Sensitivity
RESOURCE
TYPE
Habitats and
Biological
Resources
(29 attributes)
Turtle nesting sites
Socio-
economic,
infrastructure
and tourism
(18 attributes)
Hotels
Sea/air
temperature
Scoring supported by peer-review
literature, reports and/or best
professional judgment
Exposure* Adaptive
capacity Resource
Type
Resource
name
Sensitivity Exposure Adaptability Final
Vulnerability
ScoreS1 S2 … E4 E5 … A1 A2 …
Habitat and
Biological
Resources
B1
B2
…
B29
Socio-
economic,
infrastructure
and tourism
Infrastructure
E1
E2
…
E18
The color scheme presented here is for illustrative purposes only
CLIMATE CHANGE VULNERABILITY
SCORING EXAMPLE
Vulnerability
Scores
LOW
MODERATE
HIGH
Scores
LOW
HIGH
Scores
HIGH
MODERATE
LOW
CLIMATE CHANGE VULNERABILITY APPROACH FOR “CORALES DEL ROSARIO Y SAN BERNARDO”
NATIONAL NATURAL PARK, COLOMBIA
Precipitation
and
hydrological
regimes
Ocean
acidification
Sea level rise
Shoreline
changes,
erosion
Extreme
events,
inundation
Dependency
Level of
specialization
Dispersal/
movement
Functional
diversity
Key features,
uniqueness
Existing threats
Conservation
level and
status
Sea/air
temperature
Precipitation
and
hydrological
regimes
Ocean
acidification
Sea level rise
Extreme
events,
inundation
Birds
Corals
Mangroves
Lagoons
…
Crops
Recreational beaches
Docks
Coastal protection
projects
Park’s facilities
…
* Based on resource-specific thresholds and area-specific climate change scenarios
KEY COMPONENTS OF THE CLIMATE CHANGE
VULNERABILITY APPROACH

9. green 5-6
yellow 7-8
red 9-10
green 6-9
yellow 10-13
red 14-18
green 7-11
yellow 12-16
red 17-21
Sensitivity Adaptability
Exposure
time series
2010 - 2100
Final Vulnerability Scores
(Optimistic and Pessimistic
scenarios)
time series 2010-2100
5 year intervals
EXPOSURE SCORES
All exposure scores change with time.
For some resources, exposure is
spatially dependent upon permanent
inundation due to sea level rise (SLR)
and temporary inundation due to storm
surge.
SLR is calculated based on rates of 2.88
mm/yr and 5.64 mm/yr for optimistic
and pessimistic scenarios, respectively.
Storm surge values are 20 cm and 50
cm.
Subsidence rates of -3.66 mm/yr and -7
mm/yr are included in the calculation.

10. Weighted vulnerability is calculated by multiplying
a scale factor to the vulnerability scores based on
which management zone each grid cell is in. There
are 3 management zones (pictured at right):
High conservation priority zone – scale factor 1.5
Natural recovery zone – scale factor 1.25
Recreational zone – scale factor 1
Weighted vulnerability

11. Birds
Rocky shores
Algae
Soft bottoms
Dry forest
Corals
Coastal lagoons
Mangroves
Sea grasses
Sediments
Crops
Vegetation mosaic
Recreational beaches
Recreational lagoons
Shoreline protection
PNNCRSB facilities
Housing
Topo to Raster
(10 m) Magna-
Sirgas Central
Assign 1 for presence and
0 for absence to all AOI
grid cells for each resource
Point Density with
10 m raster output
Buffer
30 m
Data processing steps used to develop the PNNCRSB Climate Change tool
Cell Statistics MAX
+
Highest Position
Vector
Datasets
SRTM 30 m
DEM
Shorelines
Presence/Absence
(1/0) grids for all
resources
Sea Turtles
Clip to
PNNCRSB
boundary
snap to DEM
Clip to buffer and
PNNCRSB boundary
static scores
Sensitivity
scores
Adaptability
scores
Sensitivity Adaptability
Exposure
time series
2010 - 2100
Final Vulnerability Scores
(Optimistic and Pessimistic
scenarios)
time series 2010-2100
time
series
2010-2100
Inundation
due to sea
level rise
0/1
Inundation
due to
storm surge
0/1
Raster
Calculator
multiply
Exposure
scores
time series
2010 - 2100
Permanent
inundation
scores
time series
2010 - 2100
Temporary
inundation
scores
time series
2010 - 2100
Raster
Calculator
add
Area of
interest
(AOI) grid
Raster
Calculator
multiply
Raster
Calculator
add
Highest score in each cell

12. The original 30 m SRTM DEM is very coarse. The
most current (2005-2012) measured coastlines are
in red.
Using the Topo to Raster tool in ArcGIS, the 30 m
DEM was resampled to 10 m and the measured
coastlines were used to confine sea level.
Resampling the elevation model

13. The resampled 10 m zero-level contour (red lines)
matches the coastline in the imagery better than those
of the SRTM 30 m DEM (yellow lines).

14. A sea turtle density
surface was created
using the Point
Density tool in
ArcGIS on sea turtle
locations (in red)
with dates 2000 or
later. The density
surface was clipped
to a 30 m buffer
around the
shoreline.
Modeling sea turtle locations with a density surface

15. AOI grid colored by
grid cell unique ID:
12,834,567 cells
Presence/absence grids were
created for all resources
based on an area of interest
(AOI) grid and whether or not
a resource was present
(value=1) or not (value=0) in
each grid cell.
Presence/absence (0/1) grids for all resources

16. Developing the interactive visualization tool
The tool panel was developed
in VB .net with ArcObjects as
an ArcMap Add-In. It is a
dockable window that is
opened by clicking on a
control button in a custom
toolbar.
The toolbar currently has one
button, and it can be
customized to include other
tools such as zoom, pan, and
the time slider control.

20. The climate change vulnerability visualization tool panel
Switch symbology between optimistic and pessimistic scenarios
Switch symbology between weighted and unweighted vulnerability scores
Select a single resource to display vulnerability values for
Vulnerability scoring scale with 10 value ranges
Chart displaying the total area covered by each score range in the visible extent
Refresh
button turns
on Active
View Refresh
listener for
pan and
zoom events
Show table of
attributes for
resources
visible in the
current extent
Change transparency value for vulnerability score layer
Select an island to zoom to
Turn on/off inundation line, base map imagery, and pop-up info window
Display PDF instructions document

21. Questions?
Jennifer L. Horsman
Research Planning, Inc. (RPI)
jhorsman@researchplanning.com
803.608.8106
Paper (in press, Climate Research): A climate change vulnerability framework for
Corales del Rosario y San Bernardo National Natural Park, Colombia
http://www.researchplanning.com