Plant species-area relationship in a 42-hm<SUP>2</SUP> research plot of coniferous and board-leaved mixed forest in Jiaohe, Jilin Province, China

Abstract

Aims The Species Area Relationship (SAR) is a fundamental pattern in ecology. Recent analyses have often demonstrated substantial uncertainty in selecting the best SAR model for a data set. Our objective was to under- stand the effects of sample design on species-area relations, in order to suggest a more appropriate SAR model for the given plot data. Methods A long-term 42 hm 2 forest plot was established in conifer and board-leaved mixed forest in Jiaohe, China. All trees with diameter at breast height (DBH) > 1 cm were tagged and their height, DBH and crown di- ameter recorded. We propose three SARs models (logarithmic function, power function and logistic function) to compare SARs constructed from nested design and random design. We use Akaike Information Criterion (AIC) to compare the quality fit of each SAR model given the data. Important findings The way of constructing SARs influences the outcome. The random design showed signifi- cantly better goodness of fit of SARs model than the nested design. Among the three SAR models, Logistic func- tion model from the random design was the best, suggesting it provided a reasonable description of the spe- cies-area relationship in the plot. This study demonstrates the significance of scale variance in species-area rela- tionships; the effects of area on species richness are variable and can be scale dependent. However, because the species distribution patterns and spatial scale vary greatly, further work is needed to consider environmental ef- fects and the community succession on different spatial scales.