If counting active burrows only: Dtotal = D / a (a = activity factor).
Apply correction: D = D × m (m = multiplier).
- Choose a sampling method and enter site area.
- Enter transect/plot details, or direct sampled area.
- Input observed burrows and indicate count type.
- Set detection, activity, occupancy, and multiplier values.
- Calculate, then export a record for reporting.
| Date | Zone | Method | Sampled area (m²) | Burrows observed | Detection | Density (per ha) | Estimated total (site) |
|---|---|---|---|---|---|---|---|
| 2026-01-18 | Zone A | Transect | 2,000 | 28 | 0.85 | 164.71 | 2,059 |
| 2026-01-19 | Zone B | Plots | 250 | 9 | 0.90 | 400.00 | 1,520 |
| 2026-01-20 | Zone C | Direct | 1,500 | 14 | 0.80 | 116.67 | 875 |
- Density is computed from sampled area and scaled to the full site.
- Detection probability helps correct under-counting in difficult terrain.
- Activity factor can convert active burrow counts to total burrows.
- The confidence interval is approximate and based on count variability.
Sampling Coverage Metrics for Site Screening
Effective burrow estimates start with coverage. Transect belts compute sampled area as N×L×W, while plots use P×Aplot. Many site surveys target 5–20% coverage in accessible zones, then increase effort near stockpiles, drains, or quiet verges where burrows cluster. Record the same belt width or plot size each visit so density changes reflect field conditions, not method drift.
Density Normalization Across Units
This calculator converts all areas to square meters internally, then reports density per m², hectare, or acre. Conversions matter when teams mix drawings and field notes. One hectare equals 10,000 m² and one acre is 4,046.86 m². If a project expands, keep the report unit consistent across zones to make weekly comparisons and threshold triggers straightforward.
Correction Factors and Bias Controls
Detection probability corrects for missed burrows in rough ground, vegetation, or poor light. Values often range 0.70–0.95 depending on visibility. If you counted only active burrows, the activity factor scales to total burrows; if you counted all burrows, the factor estimates active burrows instead. Use the multiplier for known biases, such as partial access, observer training differences, or revisits that reclassify collapsed openings.
Interpreting Intervals and Burrow Spacing
The confidence interval shown is count based and uses a normal approximation to Poisson variation. Wider intervals usually indicate small counts or small sampled area, suggesting more transects or plots are needed. The spacing indicator is a rough mean distance derived from 1/√density; it helps visualize whether burrows are sparse across haul roads or concentrated along undisturbed margins.
Reporting Outputs for Construction Compliance
Exported CSV and PDF outputs support audits and daily logs. Capture project name, date, zone, method, and all correction assumptions. Use occupied burrows as a conservative impact proxy when occupancy data exists. When mitigation is required, compare densities before and after barriers, relocation, or scheduling changes to demonstrate measurable reduction. Maintain a photo record and GPS points for repeatable verification.
1) What detection probability should I start with?
If visibility is good and ground is open, start around 0.90. In tall grass, rubble, or uneven slopes, 0.70–0.85 is more realistic. Update the value after a supervised double-pass count or peer review.
2) When are transects better than plots?
Use transects for long corridors such as access roads, fence lines, and pipeline routes. Use plots when habitat is patchy or you need fixed points for repeat monitoring. Either method works if sampled area and effort are documented.
3) How can I set the activity factor?
Define “active” consistently, such as fresh spoil, tracks, or a clear opening. Divide active burrows by total burrows in a representative subset, then use that proportion. Recheck after heavy rain or grading, which can change signs quickly.
4) Why can’t sampled area exceed total site area?
The calculator scales density from sampled area to the full site. If sampled area is larger than the site, densities become artificially low and totals are distorted. Recheck units, transect dimensions, or plot counts when this happens.
5) How should I interpret the confidence interval?
It is an approximate interval based on count variability, not a full ecological model. It reflects uncertainty from limited observations, but it does not include errors from detection estimates, activity classification, or uneven habitat. Increase coverage to narrow it.
6) Can I report multiple zones in one file?
Yes. Run the calculator per zone and export each result set. Then combine the CSV rows in a spreadsheet to summarize totals and compare densities. Keeping consistent units and assumptions makes the combined report defensible.