# The Main Factors Affecting the Minimum Sampling Area Determination Method: Based on Research of the Shrub Layer in Island Pinus massoniana Forests

## TL;DR

This study identifies factors affecting the minimum sampling area for shrub layer biodiversity in Pinus massoniana forests on islands.

## Contribution

The study introduces a method for determining the minimum sampling area using species richness and evenness in island shrub ecosystems.

## Key findings

- The power function model best fits the species-area relationship in the study.
- Species richness and evenness significantly influence the minimum sampling area.
- A 142 m² sampling area achieves 70% accuracy in biodiversity assessments.

## Abstract

What factors influence minimum sampling area size? We addressed this question through investigations of shrub layers in island Pinus massoniana forests. The research shows:, the power function model was identified as the best fit for the species-area relationship. Species richness and species distribution evenness were found to be the main factors affecting the determination of the minimum sampling area. Repeated sampling from four corners of the plot proved advantageous. Considering cost and accuracy, a 142 m2 minimum sampling area could achieve 70% sampling accuracy. The research provides a method for analyzing the minimum sampling area and valuable insights for biodiversity studies in island ecosystems and similar forest communities worldwide.

Determining the minimum sampling area is crucial for accurate and cost-effective biodiversity surveys. This study identifies the main factors (e.g., species richness and evenness) influencing the inflection point method and precision method, aiming to scientifically establish the minimum sampling area for studying the shrub layer diversity of the Pinus massoniana community on Sandu Island, Ningde. Using 64 nested samples (20 m × 20 m) from eight sampling plots, we analyzed the species–area relationship and minimum sampling area. Key findings include the following: (1) The power function model (S = 4.053A0.404) best described the species–area relationship. (2) Species richness significantly influenced the inflection point method, with rare species increasing the required sampling area. (3) Species distribution uniformity and sampling methods affected model outcomes. (4) Repeated sampling from the four corners of the plots reduced bias caused by uneven species distribution. (5) Considering cost, accuracy, and inflection points, a minimum sampling area of 142 m2 achieved 70% sampling accuracy. This study provides a methodological framework for accurate minimum sampling area analysis and offers valuable insights for biodiversity studies of P. massoniana shrub layers in island ecosystems, with implications for international research on similar forest communities.