Using systematic, random, and haphazard sampling techniques, I assessed tree species density and diversity, focusing on their effectiveness in capturing both common and rare species.
Among the three methods, systematic sampling proved to be the most time-efficient, requiring 12 hours and 35 minutes to complete. Haphazard sampling followed closely at 12 hours and 40 minutes, while random sampling was the slowest, taking 12 hours and 58 minutes. While speed is a key consideration, accuracy in estimating species abundance and diversity is equally critical.
Common Species
Red Maple:
Systematic: 3.89% error
Random: 3.22% error
Haphazard: 0.92% error
Haphazard sampling had the lowest error for Red Maple, indicating its effectiveness for this dominant species.
White Oak:
Systematic: 24.83% error
Random: 6.31% error
Haphazard: 32.89% error
Random sampling showed the highest accuracy for White Oak, significantly outperforming the other methods.
Rare Species
Striped Maple:
Systematic: 100% error
Random: 69.12% error
Haphazard: 38.97% error
Haphazard sampling was the most effective at capturing Striped Maple, though the error remained high due to its low density.
White Pine:
Systematic: 56.25% error
Random: 100% error
Haphazard: 62.5% error
Systematic sampling yielded the lowest error for White Pine, suggesting its utility for rare species.
Patterns in Accuracy
Common Species: Haphazard and random sampling generally provided more accurate estimates for common species, particularly for Red Maple and White Oak.
Rare Species: Systematic sampling was more reliable for detecting rare species, such as Striped Maple and White Pine, likely due to its structured approach.
Reflections on Sampling Methods
Systematic Sampling: The fastest method and most accurate for rare species, systematic sampling ensures even coverage of the study area. However, it struggled with certain common species like White Oak.
Random Sampling: Despite being the slowest, random sampling excelled in accuracy for common species. However, it missed some rare species entirely, leading to significant errors.
Haphazard Sampling: While less structured, haphazard sampling provided the lowest error for Red Maple, the most abundant species. However, its performance for rare species was inconsistent.
Given the trade-offs between speed and accuracy, the choice of sampling method should depend on the study’s objectives: For common species: Haphazard or random sampling may be more effective, especially with larger sample sizes. For rare species: Systematic sampling offers the best chance of detecting and accurately estimating their densities. Increasing the number of sample points would likely improve accuracy across all methods, particularly for rare species. With only 24 quadrats sampled, the data may not fully capture the spatial heterogeneity of the Mohn Mill area.