Anti-Poaching Patrol Coverage Simulator

Patrol Allocation

Ranger teams 8

External poaching pressure Medium

Simulation speed 1.0×

Reserve Status

Population

120

Simulated time

0 mo

Poached (total)

Incidents / mo

0.0

Reserve area under active patrol (≥50% deterrence)

How it works

Poaching pressure at a point in the reserve is modelled as a local encounter rate λ(x,z), following the well-documented pattern that poaching incidents cluster near park boundaries and roads and fall off with distance into the interior, and are suppressed by nearby ranger presence:

λ(x,z) = P · exp(−d_edge / L) · (1 − C(x,z))
d_edge = distance from (x,z) to the nearest reserve boundary
L      = edge risk decay length (~6 units)
C(x,z) = Σᵢ exp(−dᵢ² / 2σ²), capped at 1  (cumulative patrol deterrence,
         dᵢ = distance to ranger i, σ = patrol detection radius)

Each animal is a Poisson process: the chance it is poached in a short interval dt (in simulated months) is P(event) = 1 − e^(−λ·dt). This is the same "distance-decay of poaching risk from the edge, suppressed by patrol effort" pattern reported in SMART/MIST ranger-patrol datasets from real protected areas.

The population itself follows logistic growth reduced by poaching losses:

dN/dt = r·N·(1 − N/K) − poaching losses

Ranger teams — how many patrol units are deployed (each contributes its own Gaussian deterrence bubble to C(x,z)).
Risk-based — rangers concentrate along the high-risk boundary strip, mirroring intelligence-led patrolling.
Uniform grid — rangers are spread evenly across the whole reserve regardless of where the risk actually is.
Unplanned — rangers wander with no fixed pattern, a low-effectiveness baseline.
External poaching pressure — the base demand-driven pressure P before any patrol suppression is applied.

Wildlife Ranger patrol low → high poaching risk

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