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

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 <i>Pinus massoniana</i> 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 (<i>S</i> = 4.053<i>A</i><sup>0.404</sup>) 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 m<sup>2</sup> achieved 70% sampling accuracy. This study provides a methodological framework for accurate minimum sampling area analysis and offers valuable insights for biodiversity studies of <i>P. massoniana</i> shrub layers in island ecosystems, with implications for international research on similar forest communities.

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Journal
Biology
Published
2025-04-03
DOI
https://doi.org/10.3390/biology14040372
Primary Topic
Ecology and Vegetation Dynamics Studies
Type
article
Field-Weighted Citation Impact
0.00

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article

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

Zhifei Zhong, Feifan Weng, Qingyan Wen, Yanqiu Xie et al.
2 links
Biology
Ecology and Vegetation Dynamics Studies
article

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

Zhifei Zhong, Feifan Weng, Qingyan Wen, Yanqiu Xie, Yingxue Wang, Jihong Xiao, Chuanyuan Deng, Xing Cai, Yu‐Chen Lin, Guochang Ding
article en

Abstract

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 <i>Pinus massoniana</i> 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 (<i>S</i> = 4.053<i>A</i><sup>0.404</sup>) 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 m<sup>2</sup> achieved 70% sampling accuracy. This study provides a methodological framework for accurate minimum sampling area analysis and offers valuable insights for biodiversity studies of <i>P. massoniana</i> shrub layers in island ecosystems, with implications for international research on similar forest communities.

BiologyVol. 14(4)
Fujian Agriculture and Forestry University (CN)
Fujian Agriculture and Forestry University
Life in Land
Openalex Percentile: Top 93%
Ecology and Vegetation Dynamics Studies
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