OBJECTIVES Strategy for Monitoring Post-fire Rehabilitation Treatments

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OBJECTIVESStrategy for Monitoring Post-fire
Rehabilitation Treatments

• Troy Wirth and David Pyke
• USGS Biological Resources Division
• Forest and Rangeland Ecosystem Science Center
• Corvallis, Oregon

U.S. Department of Interior U.S. Geological Survey
Supported by USGS - BLM Interagency Agreement
HAI040045
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Monitoring Approach

• Objectives
• Stratification
• Control Plots
• Random Sampling
• Data Quality
• Statistical Analysis
• Repeatable, objective field methods using
  Rangeland Monitoring Database

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Objectives

• Objectives are statements of conditions that
  result in a successful treatment
• Objectives should be clearly defined prior to ESR
  treatment implementation
• Quantitative
• Measurable
• Attain, increase, decrease a level of a certain
  parameter
• Compare objective to monitoring data to make a
  determination of success

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Objectives

• Two types of Objectives Management and Sampling
• Management Objectives - set specific goals for a
  parameter or ecological condition
• Sampling Objectives - set specific goals for the
  measurement of the parameter or ecological
  condition

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Management Objectives

• Components of a management objective (From
  Elzinga et al. 1998)
• Action attain, decrease, increase
• Attribute cover, density, etc.
• Species or Habitat Indicator ARTR2 or shrub
  height
• Location where the objective applies
• Status numerical goal
• Time Frame when the objective will be met

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Example Management Objective

• Management Objective Attain (action) a density
  (attribute) of perennial native seeded grasses
  (species or indicator) in monitoring unit 1
  (location) of at least 2.5 plants/m2 (status) by
  the end of the third growing season (time frame)
  following treatment.
• Management Objective Attain 35 cover of native
  perennial grasses in monitoring unit 2 by the end
  of the third growing season.

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Sampling Objectives

• Companion sampling objectives are written for
  each management objective
• Two types Target and change objectives
  depending on the action of the management
  objective
• Target set quantitative objective
• Change change from one time period to another or
  difference rather than a quantified target,
  expressed as an absolute value or a percentage of
  a measured value (control)

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Sampling Objectives

• Target objectives consist of
• Confidence Level how confident are you that the
  true mean lies within the confidence interval
• Confidence Interval interval around the
  estimated mean where you believe the true mean
  lies
• Precision ½ confidence interval width

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Example Target Sampling Objectives

• Obtain estimates of mean number of plants/m2 with
  90 confidence (confidence level) that are within
  20 (confidence interval width or precision) of
  the estimated density (a 0.1, d 0.2)
• Estimate the percent cover of bluebunch
  wheatgrass with 95 confidence that is within
  25 of the estimated cover (a 0.05, d 0.25)

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Using Target Sampling Objectives
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Sampling Change Objectives

• Change objectives consist of
• Acceptable Type I and Type II error
• Type I (false-change error)
• Type II (missed-change error)
• Minimum detectable change
• The change that can be detected by the monitoring
  effort. Depends on variability in the monitoring
  data.

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Example Sampling Change Objective

• Change Sampling Objective Detect a change
  (positive or negative) of 20 (MDC) in the mean
  number of plants/m2 with 90 confidence (Type I).
  We are also willing to take a 20 chance (Type
  II) that we will conclude there is no change when
  there was a change.

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Using Change Objectives