Post 4: Sampling Strategies

To compare the efficiency of sampling techniques, we can look at the estimated time spent sampling. Based on the provided data:

– Area, random or systematic: Estimated time to sample = 2 hours, 40 minutes
– Area, haphazard: Estimated time to sample = 2 hours, 39 minutes
– Distance, haphazard: Estimated time to sample = 1 hour, 1 minute
– Distance, random or systematic: Estimated time to sample = 1 hour, 2 minutes

From this, we can see that the distance-based sampling techniques (haphazard and random or systematic) are more efficient in terms of time spent sampling compared to area-based techniques.

Now, let’s compare the actual densities with the estimated densities for both common and rare species and calculate the percentage error:

Common Species:
– Red Maple:
– Actual Density: 403.7
– Estimated Density (Distance, Haphazard): 480.0
– Percentage Error: ((480.0 – 403.7) / 403.7) * 100 = 18.9%

– White Oak:
– Actual Density: 74.5
– Estimated Density (Area, Haphazard): 140.0
– Percentage Error: ((140.0 – 74.5) / 74.5) * 100 = 88.6%

– Witch Hazel:
– Actual Density: 142.4
– Estimated Density (Area, Random or Systematic): 300.0
– Percentage Error: ((300.0 – 142.4) / 142.4) * 100 = 110.9%

Rare Species:
– Hawthorn:
– Actual Density: 4.5
– Estimated Density (Area, Random or Systematic): 0.0
– Percentage Error: ((0.0 – 4.5) / 4.5) * 100 = -100.0%

– Sweet Birch:
– Actual Density: 1.2
– Estimated Density (Area, Random or Systematic): 20.0
– Percentage Error: ((20.0 – 1.2) / 1.2) * 100 = 1566.7%

– American Basswood:
– Actual Density: 1.5
– Estimated Density (Area, Random or Systematic): 0.0
– Percentage Error: ((0.0 – 1.5) / 1.5) * 100 = -100.0%

Analysis: The most accurate sampling strategy for common species seems to be the Distance, Haphazard technique, as it had the lowest percentage error for Red Maple. For rare species, there isn’t a clear most accurate strategy, as the percentage errors vary widely. However, it seems that distance-based techniques tend to perform better for rare species compared to area-based techniques.
The accuracy generally declines for rare species, as indicated by the higher percentage of errors compared to common species. Whether 24 sample points are sufficient depends on various factors such as the size of the community, the distribution of species, and the desired level of accuracy. In general, increasing the number of sample points can improve the accuracy of abundance estimation.
24 sample points may not be enough to accurately estimate the abundance of all species, especially rare ones, as indicated by the high percentage of errors for some species. Increasing the number of sample points or using more efficient sampling techniques may be necessary to improve accuracy.