Evaluation of Climate and Habitat Interactions Affecting the Conservation
and Management of Asian Elephants in Southeast Sri Lanka
Work Plan:
The work plan is divided into sections for A) Climate,
B) Hydrology, Vegetation and Habitat, C) Elephant Management
and D) Integration and Synthesis
Section A: Climate
In May 2000, the IRI entered into a partnership with the
Mahaweli Authority of Sri Lanka to provide climate and hydrological forecasts
for the Mahaweli and
Walawe River Basins. The methodology we propose will draw upon these
high quality, weather, climate and hydrological model output already developed
for this region by IRI.
Major Steps
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Data collection,
entry and arrangement in IRI data library
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Construct
climatologies and inter-annual variation patterns from the extensive network
of station data in Sri Lanka.
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Using
interpolation techniques, develop climatologies and inter-annual variation
patterns of precipitation and temperature for South-Eastern Sri Lanka at
a resolution of 1-km
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Downscale
GCM seasonal climate predictions available at the IRI to the available meteorological
stations and the high resolution grided data using statistical techniques
to relate the retrospective seasonal predictions to past climate data.
The principal sections of this portion of the
project will be:
1.
Data Collection:
Gaps in the IRI archives of climate data for Sri Lanka will be filled with
data collected from the Sri Lankan Departments of Meteorology and Irrigation.
Printed format data will be entered by hand by a research assistant. Thereafter
these data will be incorporated into the IRI data library for ready access,
manipulation and visualization.
2.
Construction of High-Resolution Climatology
: Based on the data that is available for Sri Lanka for 400 stations, interpolation
techniques will be used to construct climatologies of rainfall and temperature
at a 1-km grid resolution for use in GIS.
3.
Downscaling of Seasonal Climate Forecasts
: The GCM seasonal climate forecasts
available at IRI are typically at a scale of about 250 km. These forecasts
will be downscaled to the available stations and the high resolution grid
in the South-East of the island using relationships between IRI retrospective
forecasts and actual observed climate
Section B: Hydrology, Vegetation, Habitat
Among the fundamental questions underlying our understanding of the systems
supporting elephants for the proposed study area are:
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What
is the location, composition, structure, extent and use of the natural resources
(vegetation and surface water) and built systems present within the region
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How sensitive
are these systems to variability in climate (temperature and precipitation)
and can these key variables be forecast using downscaling systems?
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How best
can these patterns and processes be captured using digital geospatial technologies
Major Steps
§
Search
for and compile existing digital hydrology, land cover, habitat, NDVI history,
elevation, geology and soils data
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Generate
digital layers for detailed cover type, vegetation, and biophysical (elevation,
slope, aspect, soil moisture) and potential elephant habitat
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Compare
historic patterns and correlations between vegetation (NDVI) data and climate
§
Perform
downscaling of climate predictions to variables related to the key features
that impact elephant distribution, namely water and vegetation. This will
include downscaling to in-situ streamflow and hydrological analysis of streamflows,
and NDVI.
Sub-Section 1: Climate impact on available water for elephants:
Hydrological Analysis of Surface and Sub-surface Water
The main focus will be:
1.
Data Collection: A thorough hydrological
data search will be conducted, with the assistance of t
he Irrigation Department, the International Water Management Institute (IWMI),
and the Mahaweli Authority of Sri Lanka.
2.
Statistical
downscaling of climate predictions for streamflow estimation.
The critical in-situ variable in hydrological modeling is streamflow. Techniques
similar to that used for downscaling climate predictions to station climate
will be used to downscale climate forecasts to streamflow forecasts in key
sites on the rivers of the project area. (Mahaweli, Menik, Walawe).
3.
Hydrological Analysis:
Observations and downscaled forecasts of streamflow will be extended to other
variables such as soil moisture (plant available) and availability of water
(elephant available) in surficial features in parks, using hydrologic models,
statistical models and subjective inference.
Sub-Section 2: Climate impact on available fodder for elephants: Vegetation,
Habitat and Biogeographic Pattern Assessments
The main focus will be:
1.
Data Collection: a thorough geospatial
data search will be conducted, with the assistance of t
he Open University of Sri Lanka, the International Water Management Institute
(IWMI), and the Mahaweli Authority of Sri Lanka.
2.
Data Generation:
layers lacking adequate spatial, thematic or temporal resolution for land
cover, vegetation type, NDVI, elevation, slope, aspect, soil moisture and
geology will be augmented with output from satellite image classification
work, acquired and tailored for this project.
Construction of the final units will be derived to provide a best fit of
the size, productivity, composition, structure, contiguity, temporal and geomorphology
context of that range of cover types both preferred and utilized by elephants.
A hierarchical classification approach will be taken, covering multiple scales,
to assess the relevance and rank of importance of system components at the
watershed and regional levels.
3.
Statistical downscaling of climate predictions for vegetation related variables:
Drawing on the data generation, the impact of climate on variables relevant
for elephant fodder will be evaluated, and downscaled climate forecasts will
be attempted. For example, it is anticipated that NDVI will be a relevant
variable to make downscaled forecasts for.
The main limiting factors for elephants in Sri Lanka are the availability
of fodder and surface water. The
flux of these resources assume much greater significance than usual when
elephants are restricted to conservation areas and are prevented from
tracking changing resources. Human and elephant conflicts increase
around such zones, in the face of intensified resource competition. The ability
to assess seasonal variabilities of climate impact on habitat conditions
may allow remedial action to be taken that could pre-empt or mitigate crisis
situations. For instance, over most of it’s range in Sri Lanka, dry seasons
brings a time of limitations for the elephant, with water and fodder availability
increasing during the main rainy season (October to January).
If, through assessing short-term seasonal climate outlooks, (such
as associated with El Nino) rainfall is expected to be below average in a
given year, a greater effort can be expended in activities that will address
shortfalls in the coming term. eg. additional surface water can be collected
by modifying water holes and reservoir systems, and strategies such as habitat
modification can be adopted to increase browse availability within reserves.
If the rains are projected to fail entirely, plans can be made to provide
water and fodder artificially. While
such management interventions would promote the conservation of elephants
and other fauna in protected areas, they would also mitigate human-elephant
conflict. The presence of sufficient resources for elephants within conservation
areas can stem the likelihood of their preferentially moving into human dominated
areas.
Major Steps
1.
Data Collection: a meeting of
Asian elephant experts will be assembled, (with a possible teleconference
with Sri Lankan partners) where existing knowledge bases and knowledge gaps
will be compiled outlining elephant ecology within the study area and quantifying
the underlying assumptions driving elephant\habitat dynamics within the study.
2.
Data Generation:
our understanding of elephant ecology, (range maps, habitat affinity and
sensitivity) will be transferred to geospatial data layers, for consideration
and use within the GIS.
Section D. Integration and Synthesis:
Climate, Habitat, Elephant Ecology
Calibration between and integration of sections A, B, and
C will be ongoing throughout the project. For examples,
downscaling of forecasts to streamflow and vegetation in Section
B will draw on climate findings in Section A, and consideration of habitat
affinity and intervention strategies in section C will draw on the physical
findings in Sections A and B. Additional, output-oriented integration activities
and considerations will conclude with:
The main focus will be:
1.
Integration of Sub-Sections-
Formats: The component sub-sections
will be integrated and their relationships assessed using the combined
IRI data-library, ESRI GIS software and database systems and ERDAS Imagine
image processing programs. Output will be constructed to fit current geo-spatial
data standards and will be fully augmented with appropriate metadata. Compatibility
between sub-sections, data formats, coordinate systems and datums will be
addressed in early meetings to assure seamless integration of the assessment
of climate influences on elephant habitat.
2.
Scenario Analysis:
Current and historical integrated trends and correlations between vegetation,
climate and elephant habitat will be assessed
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Viability
of elephant affinity and sensitivity to extreme, short-term climatic stress
will be assessed
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A range
of water resource, habitat management and wildlife conservation strategies
that can be effective in different climatic regimes will be assessed with
an array of what-if scenario outputs
3. Validation of Integrated Model
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An expert
group on Asian elephant management (Sukumar, Fernando, Manthrithillake) will
be assembled to evaluate our validation and scenario analyses. Possible interventions
given climate outlooks for coming seasons will be considered.
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The integrated
scenario outputs will be compared with expert systems assessments to evaluate
reproducibility of projected biophysical, habitat, elephant, ecological and
management response to the seasonal climate cycle in SE Sri Lanka.
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Retrospective
simulations of the past few decades will be carried out to assess the model
output against ancillary biophysical data and collected elephant response
knowledge bases.