1) Calculating benefits when threats are discrete (presence/absence) | Not proportional probability of persistence | 2) Calculating benefits when threats are continuous | Example with continuous intensities of threats | References

Overview | Workflow | Usage | Planning units data | Features data | Threats data | Boundary data | Step 1: Initialize the problem | Step 2: Create the mathematical model | Step 3: Solve the model | Getting information about solutions | getActions() | getSolutionBenefit() | getCost() | getConnectivityPenalty() | getPerformance() | Sensitivity analyses on blm, budget and target parameters | References

1) Preparing and analyzing input data | 2) Base model | 3) Model with different curve param | 4) Model with connectivity requirements | 5) Conclusions

1) Model I: Only recovery targets | 2) Model II: Recovery and conservation targets | 3) Model III: Only recovery targets and connectivity | 4) Model IV: Recovery and conservation targets and connectivity

Experimental settings | Gurobi | CPLEX | CBC | Symphony | Results | Academic solvers: gurobi vs CPLEX | Non-academic solvers: CBC vs symphony | Conclusions