How to use the seed dispersal distance calculator
Estimate the share of seeds that land beyond a given distance from the parent plant, assuming exponential dispersal. Enter mean dispersal distance, distance from parent in the fields above; the fraction of seeds beyond distance, fraction within distance are computed instantly and plotted on the chart so you can see how the answer changes.
Common searches this calculator answers include “seed dispersal distance”, “fraction of seeds travelling”, “seed dispersal kernel”, “calculate seed dispersal distance”, “find fraction of seeds beyond distance”.
Formula
Variables
- mean — Mean dispersal distance (m)
- d — Distance from parent (m)
Worked example
With mean dispersal distance = 20 m, distance from parent = 50 m, the calculator gives fraction of seeds beyond distance ≈ 8.2085 %; fraction within distance ≈ 91.7915 %.
Frequently asked questions
What is the seed dispersal distance calculator used for?
Estimate the share of seeds that land beyond a given distance from the parent plant, assuming exponential dispersal. It helps with questions such as “seed dispersal distance”, “fraction of seeds travelling”, “seed dispersal kernel”.
What is the formula for the seed dispersal distance calculation?
Fraction of seeds beyond distance (%) = 100 × exp(-d / mean). Fraction within distance (%) = 100-[Fraction of seeds beyond distance]. Here mean is mean dispersal distance (m), d is distance from parent (m).
What inputs do I need for the seed dispersal distance calculator?
You need mean dispersal distance in m, distance from parent in m. Each field is pre-filled with a typical example so you can see how the result responds as you edit the numbers.
How do I use the seed dispersal distance calculator?
Type values into the input fields. Results and the chart update instantly. Use Reset to restore the example values, Copy results to paste them elsewhere, or Share to copy a link that preserves your inputs.
Is the seed dispersal distance result exact?
Calculations use standard formulas and double-precision arithmetic, then display about seven significant figures. Real-world measurements carry uncertainty, so treat results as estimates unless your inputs are exact.