Efficiency of sector sampling for estimating juniper forest attributes vs. fixed area plot
Mohammad Hussein Seraj and
Bahman Kiani
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Mohammad Hussein Seraj: Department of Forest Science, Faculty of Natural Resources, Yazd University, Yazd, Iran
Journal of Forest Science, 2017, vol. 63, issue 10, 463-469
Abstract:
Juniper forests grow in mountain areas and many difficulties are encountered in their sampling. Sector sampling as an unbiased and cost-effective method was tested for the sampling of a 12.5-ha juniper forest. To begin with, a point-map of trees was created and 50 quadrats were determined systematically. Fixed area plots were measured within these 50 × 50 m quadrats. In each quadrat, eight sectors with 45° angle were determined. One-sector and two-sector scenarios randomly besides four-sector scenario systematically were conducted. Accuracy and precision of sampling methods were compared. Also, statistical analysis was conducted to compare sector sampling scenarios with fixed area plot (FAP) and real data. Results showed that four-sector scenario estimates were close to FAP method in precision and accuracy. Statistical analysis showed that there was no significant difference between sector sampling scenarios and FAP and in real data. But in correlation analysis only the four-sector scenario could compete with FAP method. Regarding consumed time and sampling error simultaneously, the efficiency of sector sampling was higher than that of FAP method for estimating density and close to FAP method for estimating crown cover. It can be concluded that in laborious situations such as in juniper forests, sector sampling can be competitive with FAP method with noticeable parsimony. But more study is still needed to decrease sampling error and optimize sector angle with the purpose of cost saving.
Keywords: accuracy; crown cover; density; precision; plot shape (search for similar items in EconPapers)
Date: 2017
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Persistent link: https://EconPapers.repec.org/RePEc:caa:jnljfs:v:63:y:2017:i:10:id:22-2017-jfs
DOI: 10.17221/22/2017-JFS
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