Browsing by Author "He, Fangliang"

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    Latitudinal gradients and ecological drivers of β-diversity vary across spatial scales in a temperate forest region
    (Wiley, 2020-03-12) Zhang, Chunyu; He, Fangliang; Zhang, Zhonghui; Zhao, Xiuhai; von Gadow, Klaus
    Aim: Our understanding of the mechanisms driving β-diversity is still rather rudimentary. This study evaluates the influences of environmental filtering versus spatial scale of regional communities on β-diversity across latitudes. Location: North-eastern China. Methods: The β-diversity was calculated in each regional community. The spatial extent of these “regional communities”, which included five or 10 plots, was ≤ 140 km. A random assembly null model was used to assess the effects of species abundance distribution on the β-diversity. Moreover, the deviation of observed β-diversity from a null model (called β-deviation) was also assessed. The variations of the β values were partitioned into environmental, latitudinal and their joint effects. Results: The observed β-diversity declined with increasing latitude, although the β-deviations showed a non-monotonic pattern as the latitude increased at two studied scales. All the regional communities consisting of five or 10 local plots exhibited significantly positive β-deviations. The total amount of variation in β-deviations explained by environmental and latitudinal variables increased dramatically with increasing scale. A significant pure environmental effect was observed at both scales, explaining 30% of the variation in β-deviation for regional communities consisting of five local plots and 58.7% for regional communities consisting of 10 local plots. The spatial variation in precipitation primarily accounted for the β-gradient. Main conclusions: This is one of the few multiscale analyses to investigate latitudinal patterns and driving mechanisms of tree β-diversity in temperate forests. The β-deviation showed a similar trend of change with latitude, but the variation of β-deviation explained by the environments and latitude was highly dependent on the scale of regional communities studied. Environmental filtering and the spatial scale of regional communities jointly accounted for the β-gradient, with environmental filtering appearing to determine the high variation of species turnover along the latitudinal gradient.
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    Upscaling biodiversity : estimating the species–area relationship from small samples
    (Ecological Society of America, 2018) Kunin, William E.; Harte, John; He, Fangliang; Hui, Cang; Jobe, R. Todd; Ostling, Annette; Polce, Chiara; Sizling, Arnost; Smith, Adam B.; Smith, Krister; Smart, Simon M.; Storch, David; Tjorve, Even; Ugland, Karl‐Inne; Ulrich, Werner; Varma, Varun
    The challenge of biodiversity upscaling, estimating the species richness of a large area from scattered local surveys within it, has attracted increasing interest in recent years, producing a wide range of competing approaches. Such methods, if successful, could have important applications to multi‐scale biodiversity estimation and monitoring. Here we test 19 techniques using a high quality plant data set: the GB Countryside Survey 1999, detailed surveys of a stratified random sample of British landscapes. In addition to the full data set, a set of geographical and statistical subsets was created, allowing each method to be tested on multiple data sets with different characteristics. The predictions of the models were tested against the “true” species–area relationship for British plants, derived from contemporaneously surveyed national atlas data. This represents a far more ambitious test than is usually employed, requiring 5–10 orders of magnitude in upscaling. The methods differed greatly in their performance; while there are 2,326 focal plant taxa recorded in the focal region, up‐scaled species richness estimates ranged from 62 to 11,593. Several models provided reasonably reliable results across the 16 test data sets: the Shen and He and the Ulrich and Ollik models provided the most robust estimates of total species richness, with the former generally providing estimates within 10% of the true value. The methods tested proved less accurate at estimating the shape of the species–area relationship (SAR) as a whole; the best single method was Hui's Occupancy Rank Curve approach, which erred on average by <20%. A hybrid method combining a total species richness estimate (from the Shen and He model) with a downscaling approach (the Šizling model) proved more accurate in predicting the SAR (mean relative error 15.5%) than any of the pure upscaling approaches tested. There remains substantial room for improvement in upscaling methods, but our results suggest that several existing methods have a high potential for practical application to estimating species richness at coarse spatial scales. The methods should greatly facilitate biodiversity estimation in poorly studied taxa and regions, and the monitoring of biodiversity change at multiple spatial scales.