The sampling strategies I tried in the virtual forest tutorial included systematic plots, random plots, and haphazard plots. The fastest sampling strategy was random systematic plots which took 12 hrs and 37 minutes. Next fastest were the random plots at 12 hrs and 38 minutes, and finally haphazard plots took 12 hrs 43 minutes.
The two most common species overall were Eastern hemlock and Red maple, whereas the rarest species were White pine and Striped maple.
Table 1 compares the percent error calculated, based on sampling strategy for the two most common vs the two rarest species.
Table 1. Percent Error of Sampling Techniques for Most Common vs. Rare Species
| Status | Species | Systematic Sampling | Random Sampling | Haphazard Sampling |
| Most Common | Eastern hemlock | 13.2% | 4.7% | 34.8% |
| Red maple | 17.7% | 40.5% | 12.1% | |
| Rarest | White pine | Absent | 147.6% | 98.8% |
| Striped maple | 105.7% | Absent | Absent |
The three sampling strategies presented varying accuracy according to the error percentage results. The percent error seemed to be influenced by species abundance, with relatively high error associated with less abundant species and relatively low error associated with highly abundant species. The sampling error percentage was overall lower for systematic and random plots compared to haphazard plots for more abundant species. The rarest species had very high percentage error or absent results across sampling techniques. One was not better than the other to capture all rare species in the 24 spatial replicates.
This pattern indicates that rare species may not be captured by the limited surveys and number of plots (24). More sampling for a more robust data set is indicated, and may help improve accuracy of abundance estimates.