Precision and cost considerations for two-stage sampling in a panelized forest inventory design

Area of Science:

• Forestry
• Ecological Sampling
• Quantitative Ecology

Background:

• Forest inventories are costly, necessitating efficient sampling designs.
• Two-stage sampling, grouping spatially close plots into work zones, offers fieldwork efficiencies.
• Subsampling with unequal-sized units (SUUS) is a potential two-stage design.

Purpose of the Study:

• To compare the statistical and economic implications of SUUS versus simple random sampling (SRS) in a panelized forest inventory.
• To evaluate the effectiveness of post-stratification within these sampling designs.
• To assess the applicability of SUUS for different forest inventory contexts.

Main Methods:

• A case study in the Northeastern USA compared SUUS and SRS designs.
• Statistical errors and fieldwork costs were analyzed for both designs.
• Post-stratification was applied to assess its impact on sampling errors.

Main Results:

• SUUS exhibited 1.5-2.2 times larger sampling errors than SRS before inventory completion.
• Post-stratification significantly reduced sampling errors for SUUS zones.
• SRS with post-stratification consistently yielded lower sampling errors than SUUS.
• SUUS demonstrated potential fieldwork cost reductions of 2-7%.

Conclusions:

• SUUS can reduce forest inventory fieldwork costs, particularly in tropical regions with difficult access.
• The choice between SUUS and SRS depends on balancing statistical precision and economic efficiency.
• Post-stratification is a valuable tool for improving the precision of SUUS-based forest inventories.