Snag Density

Pool unequal-area snag surveys with caller differential detection and independent Poisson count error; unlike existing fixed-plot tree expansion, correction/uncertainty require extra measured assumptions.

Description

Snag surveys can have unequal plot areas and detection probabilities.

Snag surveys can have unequal plot areas and detection probabilities. Detection-adjusted counts and a Poisson sampling model give a conditional density estimate and standard error.^[1]

When to use Snag Density

Use this tool to pool unequal-area snag surveys with caller differential detection and independent Poisson count error; unlike existing fixed-plot tree expansion, correction/uncertainty require extra measured assumptions.

Gather the tree inventory, plot measurements or model parameters. Check diameter, area, time and moisture conventions; keep paired observations aligned.

How to use Snag Density and understand its results

Gather the tree inventory, plot measurements or model parameters. Check diameter, area, time and moisture conventions; keep paired observations aligned.
Enter snagCountsByPlot, sampledPlotAreasHa, snagDetectionProbabilities using the field table and calculation rules, then run the tool.
Read detectionAdjustedSnagsPerHa, independentPoissonDensityStandardErrorPerHa. The explanation below defines the units, signs, ordering and any flags or placeholder values.
If the tool reports an input issue, correct the values and run it again. Apply the stated assumptions when interpreting a successfully returned result.

Input field	Meaning	Value type; see rules below	Requirement
snagCountsByPlot	Snag counts by plot	list of number	Required
sampledPlotAreasHa	Sampled plot areas ha	list of number	Required
snagDetectionProbabilities	Snag detection probabilities	list of number	Required

Pair nonnegative integer snag counts, positive plot hectares and detection probabilities in (0,1]. Pool adjusted counts per sampled area and return density and independent-Poisson standard error per hectare.

Paired lists must be nonempty and have equal lengths.

density=Σcount/detection /Σarea; SE=sqrt(Σcount/detection²)/Σarea

Units, indexing, boundary conditions and exceptional cases are defined in the calculation rules above.

Output field	Meaning	Value type
detectionAdjustedSnagsPerHa	Detection adjusted snags per ha	number
independentPoissonDensityStandardErrorPerHa	Independent poisson density standard error per ha	number

json

{
  "input": {
    "snagCountsByPlot": [
      2,
      3
    ],
    "sampledPlotAreasHa": [
      0.1,
      0.2
    ],
    "snagDetectionProbabilities": [
      0.5,
      1
    ]
  },
  "output": {
    "detectionAdjustedSnagsPerHa": 23.33333333333333,
    "independentPoissonDensityStandardErrorPerHa": 11.055415967851332
  }
}

Limitations and assumptions

Detection estimates and independent Poisson counts are assumptions. Zero observations return zero estimate/SE without proving absence.

Numeric inputs and returned numeric values must be finite; an unrepresentable returned value produces an error. Numeric lists are limited to 100,000 entries; the rules above may require smaller limits. Missing required fields, extra fields, wrong value types and violations of the calculation rules are input errors.

Alternative or Complementary methods

Use Gypsy Moth Egg-Mass Defoliation Threshold Checker: Screen observed egg-mass surveys with differential detection against caller density threshold; no embedded outbreak/defoliation model, species attribution or treatment recommendation. For a complementary task, use Plot Occurrence Frequency: Tabulate observed taxon occurrence across assessable plots from a binary inventory; unassessable plots are excluded, not assumed absent, and occurrence is not stem density.

References

Snag Density — tool.io

Similar or alternative tools

Gypsy Moth Egg-Mass Defoliation Threshold Checker
Screen observed egg-mass surveys with differential detection against caller density threshold; no embedded outbreak/defoliation model, species attribution or treatment recommendation.
Plot Occurrence Frequency
Tabulate observed taxon occurrence across assessable plots from a binary inventory; unassessable plots are excluded, not assumed absent, and occurrence is not stem density.