Using Conceptual Models to Select Indicators for Monitoring Conditions on Rangelands Bob Breckenridg

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Using Conceptual Models to Select Indicators for
Monitoring Conditions on RangelandsBob
Breckenridge
October 20, 2003
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Purpose

• To use existing conceptual models from the
  literature, combined with field experience to
  address questions about the conditions of
  rangelands on appropriate temporal and spatial
  scales

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TO ACCOMPLISH THIS A set of selection criteria
was developed and submitted to stakeholders for
evaluation (e.g., weighting). PRODUCT The
outcome from this effort could be a
consensus-driven approach useful for evaluating
candidate indicators for assessing change to
sensitive receptors and process that could be
field tested.
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• Criteria for Indicator
• Selection
• Applicable and readily interpretable across
  different regions
• Correlation with change in ecosystem process
• Temporal and spatial variability
• Best periods to sample (index period)
• Ability to be quantified by synoptic or automated
  monitoring
• Labor, eqiupment, analytical and data analysis
  costs

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• Criteria for Indicator Selection (continued)
• Amount and quality of available data
• Ability to assess shift between ecotones
• Responsive/sensitive to change
• Is anticipatory (has early warning potential)
• Degree of environmental impact from sampling
• Status of method
• (established vs. experimental)
• Cost-effectiveness

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• INDICATORS SELECTED
• Spectral properties includes albedo and the
  Normalized Difference Vegetation Index (NDVI)
  measured using spectral reflectance and verified
  with ground measurements
• Vegetation composition, structure, and above
  ground biomass includes leaf Area Index (LAI)
  as a measure of productivity
• Biogeochemistry includes CNP ratio, soil,
  litter, and vegetation samples
• Energy balance includes air temperature,
  monthly precipitation, Bowens Ratio, and Palmer
  Drought Severity Index (PDSI) for assessing
  energy balance

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INDICATORS SELECTED Landscape patterns
description of the geometry of land cover
patterns, I.e., fractal dimensions, patch size,
and connectivity Water balance/water quality
includes conductivity, N,P,K organic carbon,
alkalinity, and benthic macroinvertebrates.
Water quantity water balance on watershed and
groundwater basin level, infiltration
rates Retrospective index developed using
dendrochronology, PDSI records, pollen records,
packrat middens, and charcoal records
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INDICATORS SELECTED Fauna includes the
Breeding Bird Census, ants and ground beetle
abundance, composition and distribution Erosion
index developed using soil loss values from
wind and water loss equations Soil physical
profile characteristics includes surface and
soil profile description and physical properties.
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• Decision Analysis Using the Kepner-Tregoe (K-T)
  Process
• Define decision statement in terms of must
  objectives (mandatory) and want objectives
  (desirable)
• Weight the want objectives from most important
  to least (ID what matters most and what could be
  done without)
• Evaluate alternative indicators against must
  (go/no go) and want criteria from best meets
  and score others relative to it (which best
  fulfills the criteria)
• Evaluate consequences of alternatives (evaluate
  probability and seriousness)
• Make final decision

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Total Weighted Score for each Indicator Indicato
r Category Total weighted K-T score Spectral
properties 750 Vegetation composition and
cover 710 Energy balance (Bowens
ratio) 676 Erosion index 628 Biogeochemistry
625 Landscape patterns 620 Retrospective
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EMAP-Arid Indicator Categories Spectral
Reflectance (NDVI, Albedo) Vegetation
Composition, Abundance, and Structure (LAI,
HLI) Energy Balance (Bowens Ratio, APAR) Erosion
Index (WEPP, RUSLE) Biogeochemistry (CNP
Ratios) Landscape Ecology (Fractal
Dimension) Water Balance (Infiltration
Rate) Faunal (Species Richness, Trophic Structure)
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