Table 1.
Differentiation of animal movements and dispersion with progressively increasing realism over three levels of testing.
Figure 1.
Sample output from three combinations of simulated daily travel paths and densities.
Box plots with outliers are shown; each data point represents the numbers of intersections per transect (500 iterations) across five arbitrary levels of travel path tortuosity.
Figure 2.
Displacement of simulated animal travel paths over levels of tortuosity.
Fifty travel paths of equal length originate from a common centroid for each level of tortuosity (numerals indicate the number of random turn angles).
Figure 3.
Effect of daily travel distance (column panels) and path tortuosity (row panels) on FMP estimate precision.
Mean densities and 95% CIs are shown from applying the FMP formula to 10 km transects sampling virtual populations at 2 km−2. Dotted lines indicate the accuracy of mean density estimates at 1200 replicates, which vary within 2% of the true density. Note that both day range and tortuosity influenced achievable precision.
Figure 4.
Empirical daily movements dispersed randomly in simulation space.
Image capture (1∶50 000) shows a single iteration of simulation runs at 2 km−2 density for (A) gemsbok and (B) steenbok. Approximately half of the randomly oriented transect (black) appears diagonally, underlying travel paths (grey). Note that both gemsbok and steenbok have similar daily travel distances but display different tortuosity in their movements, resulting in different spatial use.
Figure 5.
Estimates from simulated densities (2 km−2) using empirical movements of (A) gemsbok and (B) steenbok.
FMP point estimates of density from a random cumulative increase in survey effort (10 km transects) are displayed along with 95% CIs.
Figure 6.
Density estimates of two empirical populations using the FMP formula and Distance sampling.
Displayed with 95% bootstrap CIs.