Camera Trap Detection Rate
Benchmark Value
Scoring Curve
The scoring engine could not generate a curve for this benchmark context. The primary form is CompositeFramework, but the benchmark data may be missing required fields (e.g., optimal range bounds for an OptimalRange benchmark). This is typically a data quality issue in the benchmark pipeline.
Evidence & Context
Based on the data for the long-nosed potoroo, a sensitive indicator species and ecosystem engineer, a detection rate of at least 2–5 detections per 100 trap-nights for key native indicator species (e.g., medium-sized digging marsupials like bandicoots and potoroos) is a reasonable expectation. Extrapolating from this, the total CTR for all native ground fauna in a high-health system would likely fall within the range of 10–20 detections per 100 trap-nights.
Camera Trap Rate (CTR), expressed as the number of independent detection events per 100 trap-nights.
This benchmark represents the expected range of camera trap detection rates for native ground fauna in a healthy temperate grassy woodland agricultural system, indicating a diverse and balanced ecosystem.
This value is a synthesized estimate representing the total native ground fauna activity in a 'best-on-offer' sustainable cropping system. It is derived from quantitative data for key indicator species (e.g., Potorous tridactylus) in high-integrity temperate woodland reserves, which showed a proxy rate of ~2 detections/100 trap-nights for a single species. The range of 10-20 represents an expert extrapolation to a diverse and healthy native faunal community, reflecting the aspirational condition observed in sites like the TERN Boyagin SuperSite.
Sources (1)
Elucidating Patterns in the Occurrence of Threatened Ground-Dwelling Marsupials Using Camera-Traps
View SourceSupporting Sources (2)
Additional references from the underlying research that informed this benchmark.
Site of the month: Boyagin Wandoo Woodland SuperSite - TERN Australia
View SourceWildlife Conservation in Farm Landscapes, David Lindenmayer ...
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