Model outbreaks using adjustable growth and mortality rates. Compare logistic and exponential projections quickly. Plan scouting and treatments with confidence across seasons.
Use the form to forecast pest populations over time.
Sample inputs and expected behavior for quick testing.
| Scenario | N0 | Growth % | Mortality % | Time | Model |
|---|---|---|---|---|---|
| Warm season aphids | 120 | 18 | 4 | 30 days | Logistic |
| Cool weather slowdown | 120 | 12 | 6 | 30 days | Logistic |
| Short burst outbreak | 60 | 25 | 3 | 14 days | Exponential |
This calculator estimates pest counts using a net growth rate.
Where r is growth, m is mortality, T is temperature factor, S is season factor, and K is carrying capacity.
Population forecasting turns scattered scouting notes into a practical action window. When you estimate how fast pests multiply, you can time cultural controls, beneficial releases, or targeted sprays before damage escalates. Forecasts also support threshold-based decisions, so treatments are applied only when the projected density approaches an economic or aesthetic limit. Clear projections improve labor planning, helping you group tasks and avoid emergency spraying during peak bloom.
Exponential growth assumes unlimited resources and is most useful for short outbreaks on young plantings or confined hotspots. Logistic growth adds a carrying capacity that reflects food, shelter, and space constraints, so projections flatten as colonies saturate a bed. In gardens, capacity effects appear quickly when predators, plant stress, and competition rise together.
The calculator combines a reproduction rate and a mortality rate into one net rate per chosen period. Temperature and season factors scale that net rate to reflect weather-driven development, dormancy, or host availability. Keep units consistent: if scouting is weekly, use weekly rates; if you log daily counts, use daily rates and shorter steps. For mixed conditions, average rates across the same interval you will rescout.
The series table helps you plan the next inspection date rather than guessing. If the model shows a sharp rise between two steps, shorten the step size and rescout earlier. When numbers stabilize under logistic assumptions, focus on hotspots and plant health instead of blanket actions. Exported CSV files are useful for tracking multiple beds.
Run scenarios by increasing mortality to represent hand removal, soap sprays, or predator activity. Compare results to understand how much suppression is required to keep populations below your threshold. After treatment, update N0 from your next count and reforecast. Saving the PDF summary creates a consistent record for seasonal learning and better planning for future reference.
Use two scouting counts from the same bed and interval. Estimate percent increase per period, then adjust downward if predators, weather, or poor plant vigor slowed the outbreak.
Choose logistic when food and space are limited, plants are maturing, or natural enemies are active. It produces more realistic plateaus for garden beds than unlimited growth.
It is the approximate maximum pest count your plants and microclimate can sustain. Dense foliage, stressed plants, and sheltered sites raise capacity; pruning, airflow, and diverse plantings lower it.
Start at 1.0. Increase toward 1.2–2.0 during warm, favorable periods, and decrease toward 0.3–0.8 during cool, rainy, or off‑season conditions. Recalibrate after each new count.
Doubling time is shown only when net growth is positive. If mortality meets or exceeds reproduction, populations decline or stay flat, so a doubling estimate is not meaningful.
Yes. Increase mortality to represent control pressure and rerun scenarios. After the next inspection, update the initial population and refine rates based on observed outcomes.
Important Note: All the Calculators listed in this site are for educational purpose only and we do not guarentee the accuracy of results. Please do consult with other sources as well.