Acoustic Complexity Index (ACI)

Benchmark Value

No specific value — see range

Range: 132.9 to 136.7 index

Optimal Range: 132.9 to 136.7

Direction: Higher is desirable ↑

Form: OptimalRange

Scoring Curve

This curve shows how a field measurement for this indicator would score across all available benchmark forms in this context.

Evidence & Context

"Heathy Dry Forest | 134.8 | 132.9 – 136.7"

Metric Definition:

Above-ground acoustic complexity calculated as the mean of the 95th percentile daily ACI values for heathy dry forest sites.

Benchmark Definition:

High-quality dry sclerophyll forest variant that serves as a direct spatial analogue for temperate dry woodland matrices.

Justification:

High-quality dry sclerophyll forest variant that serves as a direct spatial analogue for temperate dry woodland matrices.

Sources (1)

Preview of A REPORT ON A COMMUNITY PARTNERSHIP IN ECO-ACOUSTIC MONITORING IN MOUNT WORTH STATE PARK, VICTORIA, accessed May 14, 2026,

A REPORT ON A COMMUNITY PARTNERSHIP IN ECO-ACOUSTIC MONITORING IN MOUNT WORTH STATE PARK, VICTORIA, accessed May 14, 2026, Journal

A Report on a Community Partnership in Eco-Acoustic Monitoring in Brisbane Ranges

View Source

Supporting Sources (1)

Additional references from the underlying research that informed this benchmark.

Preview of Ulloa, N., et al., 2021. scikit-maad: An open-source and modular toolbox for quantitative soundscape analysis in Python. Methods in Ecology and Evolution, 12(12).

Ulloa, N., et al., 2021. scikit-maad: An open-source and modular toolbox for quantitative soundscape analysis in Python. Methods in Ecology and Evolution, 12(12).

Direct Evidence GreyLiterature

Five Rivers Reserve (70) – Australian Acoustic Observatory

View Source

Benchmark Value

Scoring Curve

Evidence & Context

Sources (1)

Supporting Sources (1)

Context

Lifecycle

Notes

Related Benchmarks