Fish Population Estimate Calculator
Estimate fish population size using the Lincoln-Petersen mark-recapture method with Chapman correction and 95% confidence intervals.
About this calculator
This calculator estimates a fish population from mark-recapture data using the Chapman modification of the classic Lincoln-Petersen estimator: N̂ = ((M+1)(C+1)/(R+1)) − 1, where M is the number marked and released, C is the size of the second capture, and R is how many of those were marked recaptures. This is the estimator D.G. Chapman introduced in 1951 ("Some properties of the hypergeometric distribution with applications to zoological sample censuses"). The plain Lincoln-Petersen formula (N = M×C/R) is intuitive — if a known fraction of the population was marked, the same fraction should reappear in a second sample — but it's biased upward when recapture counts are small, so this calculator always applies Chapman's +1 adjustment in numerator and denominator, which is standard practice in fisheries science for exactly that reason.
It also computes the Chapman variance estimator to build a 95% confidence interval around the point estimate, since a single population number without an uncertainty range is easy to over-trust. From the population estimate, the calculator derives density (fish per hectare, using the survey area you provide) and the raw recapture rate (R/C as a percentage). That recapture rate matters beyond being a reported output: as a rule of thumb, estimates become unreliable when R/C drops much below 0.05, because too few recaptures make the variance — and therefore the confidence interval — extremely wide. The method's core assumptions are that the population is closed (no births, deaths, immigration, or emigration between samples), marking doesn't affect catchability or survival, and marked fish mix randomly back into the population before the second capture — violations of any of these will bias the estimate.
Inputs
Results
Estimated population (N̂)
743
How to Use This Calculator
- Enter the number of fish captured and marked in the first sampling event (M).
- Input the number captured in the second event (C) and the number of recaptures (R).
- Review the Lincoln-Petersen population estimate: N = (M × C) / R.
- Check the confidence interval — the estimate is unreliable if recapture rate R/C is below 0.05.
- Use the Chapman modification for small samples to reduce bias in the estimator.
How the result changes with Marked & released (M)
| Marked & released (M) | Estimated population (N̂) |
|---|---|
| 50 | 375 |
| 75 | 559 |
| 150 | 1,111 |
| 250 | 1,847 |
What each input means
- Marked & released (M)
- Number of fish captured, marked, and released in the first sampling event.
- Second capture (C)
- Total number of fish captured in the second sampling event.
- Recaptured (R)
- Number of marked fish found in the second capture. Must be ≤ both M and C.
- Survey area (hectares)
- Total area surveyed, used to calculate population density per hectare.
What each result means
- Estimated population (N̂)
- Chapman-corrected Lincoln-Petersen population estimate.
- 95% CI lower bound
- Lower bound of the 95% confidence interval.
- 95% CI upper bound
- Upper bound of the 95% confidence interval.
- Standard error
- Standard error of the Chapman estimator.
- Density (fish/ha)
- Estimated number of fish per hectare of surveyed area.
- Recapture rate (%)
- Percentage of second capture that were marked recaptures.
How this is calculated
Worked example, using the default values
- Identify Input Parameters4 parametersMarked & released (M) = 100, Second capture (C) = 80, Recaptured (R) = 10, Survey area (hectares) = 10 = 4 input(s) provided
- Calculate Estimated populationEstimated population = max(marked, round(chapmanN))743 = 743
- Calculate 95% CI lower bound95% CI lower bound373 = 373
- Calculate 95% CI upper bound95% CI upper bound1112 = 1112
Figures and sources
- Chapman's modified Lincoln-Petersen estimator for mark-recapture population size (1951) — Chapman, D.G. (1951). "Some properties of the hypergeometric distribution with applications to zoological sample censuses." University of California Publications in Statistics, 1(7), 131-160. Formula and standard fisheries-science usage as applied to stream fish abundance discussed in McNair, J.N., et al. (2018), "Reducing effects of dispersal on the bias of 2-sample mark-recapture estimators of stream fish abundance," PLoS ONE 13(8): e0200733.
Engine last updated . Checked against 3 independently-derived tests — how we verify calculators. Built by Paul Gunder, a software engineer, not a licensed financial, medical, or legal professional.
Frequently Asked Questions
Why does this calculator use the Chapman modification instead of the plain Lincoln-Petersen formula?
The plain formula (N = M×C/R) is undefined when R is zero and tends to overestimate population size when recapture counts are small. The Chapman estimator adds 1 to M, C, and R before dividing and subtracts 1 at the end, which corrects most of that small-sample bias and is standard practice in fisheries science.
Why is my confidence interval so wide even though the population estimate looks reasonable?
The Chapman variance formula is extremely sensitive to the number of recaptures — R appears squared and cubed in the denominator — so a low recapture count produces a large standard error and a correspondingly wide 95% CI, even when M and C are both large. This is exactly why the recapture rate output matters: a rate much below 5% is a signal the interval is probably too wide to be useful.
What happens if I enter a recaptured count that's inconsistent with my marked and captured numbers?
The calculator doesn't validate that recaptured is less than or equal to both marked and captured — the method assumes recaptures can never exceed either sample size. Violating that produces a nonsensical or negative variance result, so keep R within the bounds of your actual field counts.
Does the population estimate account for fish that died or emigrated between the two sampling events?
No — the method assumes a closed population between samples (no births, deaths, immigration, or emigration) and that marked fish redistribute randomly and aren't more or less catchable than unmarked ones. Any of those assumptions breaking down biases the estimate, and nothing in the inputs alone lets the calculator spot or compensate for it.
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