Weighting Points Combining Designs and · 2019-10-21 · Consult with the NOC, Jornada, and NAMC...
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Combining Designs and Weighting Points AIM – Assessment, Inventory, and Monitoring BLM Objectives ▪ Understand what weighting is and both its uses and assumptions ▪ See how weights are calculated ▪ Understand when weighted estimates are more appropriate than point counting and vice versa Sage-Grouse Habitat Greenback Cutthroat Trout Habitat Oil Well Pad Installation Grazing Area Noxious Weed Encroachment Standardized data collection Probabilistic sample design Electronic data capture and storage AIM AIM Collect once, use many times
Transcript of Weighting Points Combining Designs and · 2019-10-21 · Consult with the NOC, Jornada, and NAMC...
Combining Designs and Weighting Points
AIM
– Assessm
ent, In
vento
ry, a
nd M
onito
ring
BL
MObjectives
▪ Understand what weighting is and both its uses and assumptions
▪ See how weights are calculated▪ Understand when weighted estimates are more
appropriate than point counting and vice versa
Sage-Grouse HabitatGreenback
Cutthroat Trout Habitat
Oil Well Pad Installation
Grazing Area
Noxious Weed Encroachment
Standardized data
collection
Probabilistic sample design
Electronic data
capture and
storage
AIM
AIMCollect once, use many
times
AIM
– Assessm
ent, In
vento
ry, a
nd M
onito
ring
BL
MWhat are weights?Weights are units of area or length that the point represents.
For a point with a weight of 100 acres, we expect that there are 100 acres somewhere within the reporting unit that look like that point.
This is allows you to estimate proportions of the landscape/stream.
AIM
– Assessm
ent, In
vento
ry, a
nd M
onito
ring
BL
MCalculating Weights
= Randomly Selected Monitoring Point
1000 acres / 20 points = 50 acres/pt
Representative area of an individual monitoring point
Weight =area of interest (acres or km)
# of points sampled
AIM
– Assessm
ent, In
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ry, a
nd M
onito
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BL
M
Weight = area of interest (acres or km)
# of points sampled
1000 acres / 20 points = 50 acres/pt
100 acres / 10 points = 10 acres/pt200 acres / 5 points = 40 acres/pt
200 acres / 2 points = 100 acres/pt
Calculating Weights
AIM
– Assessm
ent, In
vento
ry, a
nd M
onito
ring
BL
M
Weight = area of interest (acres or km)
# of points sampled
1000 acres / 20 points = 50 acres/pt
100 acres / 10 points = 10 acres/pt200 acres / 5 points = 40 acres/pt
200 acres / 2 points = 100 acres/pt
Calculating Weights
AIM
– Assessm
ent, In
vento
ry, a
nd M
onito
ring
BL
M
1000 acres / 20 points = 50 acres/pt
Weight = area of interest (acres or km)
# of points sampled
100 acres / 10 points = 10 acres/pt200 acres / 5 points = 40 acres/pt
200 acres / 2 points = 100 acres/pt
500 acres / 3 points = 166.7 acres/pt
Calculating WeightsA
IM – A
ssessm
ent, In
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ry, a
nd M
onito
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BL
MEffects of weights: Point Counting
9 plots
11 plots
= 45 % of plots
= 55 % of plots
= Meeting= Not Meeting
AIM
– Assessm
ent, In
vento
ry, a
nd M
onito
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BL
MEffects of weights: Weighting
3 plots 7 plots
= 30 acres= 70 acres
3 plots 2 plots
= 120 acres= 80 acres
2 plots 1 plot
= 100 acres= 100 acres
1 plot 1 plot
= 333 acres= 167 acres
58%
42%
583 acres or 58.3% of area
417 acres or41.7% of area
= Meeting= Not Meeting
Objective: 50% of the landscape is meeting the benchmark
Point Counting
Proportional Estimate/ Weighting approach
Conclusion: Monitoring objective is not met and we have no confidence intervals
Conclusion: Monitoring objective is met with 80% confidence.
AIM
– Assessm
ent, In
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ry, a
nd M
onito
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BL
MConsiderations before and during analysis
• Consider how points were selected:– What was the target population(s)? – Was the design(s) stratified?
• Consider when these data were collected: – Climate variability among years?
– Management variability among years?
• Consider design management:– Plot locations are random?
■ Weather, fire, etc. can disrupt proper implementation of sample order
– Have the missing data and rejection criteria been implemented and tracked properly?
AIM
– Assessm
ent, In
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ry, a
nd M
onito
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BL
MProportional estimated, point counting, mix
When considering how to analyze your data first look at your Management and Monitoring Objectives.
– Are you aiming for a known level of confidence in your
results?
– Does your policy require a report of the percent of a
resource?
– Are you analyzing a large area or large number of stream
km? Both statistically as well as logically
– How many points are available?
– Do those points all apply to your questions?
– Which approach is more defensible and appropriate for
your management questions and monitoring objectives?
AIM
– Assessm
ent, In
vento
ry, a
nd M
onito
ring
BL
MHow to answer these questions
✓ Policy✓ ID teams✓ Project design worksheets✓ Management and climate records✓ AquADat and TerrADat✓ Visual inspection in GIS✓ Consult with the NOC, Jornada,
and NAMC
→ Document your analysis decisions!
AIM
– Assessm
ent, In
vento
ry, a
nd M
onito
ring
BL
MPoint-Counting: Best Practices
▪ Look at one of the many successful examples▪ Use plot location/type as context for how you interpret
results ▪ Site characteristics▪ Management/disturbance history ▪ Spatial distribution
▪ Can also use random points as context for how you interpret results
▪ Caution against interpreting percentages of plots as the proportion of the reporting unit
AIM
– Assessm
ent, In
vento
ry, a
nd M
onito
ring
BL
MWeighting/Proportional estimates: Best Practices
▪ Look at examples on AIM website or AIM in your state▪ Ensure you’ve set appropriate benchmarks for all types of
sites (ESDs, stream types, etc.)▪ Do not assume you know where the plot weight represents▪ Understand what area your results are making inference
when interpreting results▪ Understand assumptions
→ NOC, NAMC, and Jornada are available to help with all of this!
