STRIP TRANSECT DENSITY ESTIMATION CALCULATOR
============================================
A free, open-source single-file HTML wildlife density tool built for
StatsUnlock.com. Strip transect is the simplest of the three
distance-sampling methods — no detection function is fitted because
detection within the strip is assumed to be 100%.

WHAT IT DOES
------------
Given (a) a list of perpendicular distances from a transect line and
(b) a fixed strip half-width w, the tool computes:

  D̂ = n · E(s) / (2 · w · L)

where
  D̂      = animal density (per chosen area unit)
  n      = detections inside the strip (those with x ≤ w)
  E(s)   = expected cluster (group) size
  w      = strip half-width in meters (each side of the line)
  L      = transect length

Detection probability Pa is FIXED at 1.0 — no model is fitted, no AIC is
computed. This is the canonical assumption of strip transect sampling
(Buckland et al. 2001, §2.2; Burnham et al. 1980).

WHEN TO USE STRIP TRANSECT vs LINE TRANSECT
--------------------------------------------
Strip transect:   open habitat, conspicuous species, aerial surveys,
                  narrow strips where 100% detection is defensible.

Line transect:    dense cover, cryptic species, when you need to
                  estimate and correct for declining detection with
                  distance.

If you suspect detection within the strip is < 100%, use the StatsUnlock
LINE TRANSECT calculator with the same data — it fits a detection
function and corrects for imperfect detection.

INPUT FORMATS
-------------
Three tabs supported:
  1. Paste / Type Data — free text or column entry
  2. Upload CSV / Excel — single or multi-species
  3. Manual Table — row-by-row entry

For multi-species: one column per species, header row optional.
See multi-species-strip-transect-sample.csv for an example.

5 USA SAMPLE DATASETS (pre-loaded)
-----------------------------------
  0. White-tailed Deer | Pennsylvania State Forest (aerial strip)
     L=80 km, w=50 m, n=80, expected D ≈ 15/km²
  1. Pronghorn | Wyoming Sagebrush Steppe (aerial)
     L=200 km, w=200 m, n=60, density in /mi²
  2. Elk | Yellowstone NP Winter Range (aerial)
     L=60 km, w=300 m, cluster=8.5, density in /km²
  3. Multi-Species | Great Plains Aerial Survey (USA)
     L=150 km, w=100 m, deer + pronghorn + coyote
  4. Bighorn Sheep | Rocky Mountain NP (helicopter)
     L=25 km, w=400 m, cluster=6.5

OUTPUT
------
  • Summary cards: density, strip width, surveyed area, encounter rate
  • Detailed results table (no σ̂ / Pa / ESW columns — irrelevant for strip)
  • Distance histogram (chart 2)
  • Density 95% CI bar chart (chart 3) — single & multi-species
  • Methodology block (M1–M8) — ready for journal/thesis
  • 5 writing templates (Journal / Thesis / Policy / Conference / LTER)
  • Research poster (print-ready)
  • Doc / PDF download

UI / BRAND CONVENTIONS
----------------------
  • Green accent #16a34a + black H1
  • Soft green diagram section with mint border
  • All animals in the data-collection diagram have IDENTICAL opacity
    (uniform detection, unlike line transect / point count which show
     falloff)
  • Sample data auto-loads but analysis ONLY runs when user clicks
    the "Run Strip Transect Analysis" button (Reegan's standing rule).

DEPLOY
------
Single self-contained HTML file. Drop it on statsunlock.com — no build
step, no server, no external dependencies beyond Chart.js (loaded via
CDN). All sample data is embedded.

FILES IN THIS BUNDLE
--------------------
  • strip-transect-density-estimation.html   (the tool, ~205 KB)
  • multi-species-strip-transect-sample.csv  (50 rows × 3 USA species)
  • README-strip-transect.txt                (this file)

REFERENCES
----------
  • Buckland, S.T., Anderson, D.R., Burnham, K.P., Laake, J.L.,
    Borchers, D.L. & Thomas, L. (2001). Introduction to Distance
    Sampling. Oxford University Press. §2.2 (Strip Transects).
  • Burnham, K.P., Anderson, D.R. & Laake, J.L. (1980). Estimation of
    density from line transect sampling of biological populations.
    Wildlife Monographs, 72, 3–202.
  • Thomas, L. et al. (2010). Distance software: design and analysis of
    distance sampling surveys. J. Applied Ecology, 47(1), 5–14.
  • Miller, D.L. et al. (2019). Distance Sampling in R. J. Statistical
    Software, 89(1).
