Dataset Information

The patterns of vascular plant discoveries in China.

ABSTRACT:

Aim

(1) To understand geographic patterns of species discovery by examining the effect of growth form, range size, and geographic distribution on discovery probability of vascular plant species in China; (2) to find out which taxa harbor the largest number of undiscovered species and where those species locate; and (3) to find out the determinants of province-level mean discovery time and inventory completeness.

Location

China.

Methods

We compiled the discovery time and province-level geographic distributions of ~31,000 vascular plant species described between 1753 and 2013 from Flora of China. We used a Cox proportional hazard model to determine the biological and geographic correlates of discovery probability. Accumulation curves of species discoveries were fitted by a logistic discovery model to estimate inventory completeness of different growth forms and of different provinces. We then used linear regression to identify the determinants of mean discovery time and beta regression to identify the determinants of inventory completeness.

Results

We found that species with larger range size and distributed in northeastern part of China have a higher discovery probability. Coastal species were discovered earlier than inland species. Trees and shrubs of seed plants have the highest discovery probability while ferns have the lowest discovery probability. Herbs have the largest number of undiscovered species in China. Most undiscovered species will be found in southwest China, where three global biodiversity hot spots locate. Spatial patterns of mean discovery time and inventory completeness are mainly driven by the total number of species, human population density in an area, and latitude and longitude of a province.

Main conclusions

Socioeconomic factors primarily determine the discovery patterns of vascular plants in China. Undiscovered species are most likely to be narrow-ranged, inconspicuous endemic species such as herbs and ferns, which are prone to extinctions and locate in biodiversity hot spots in southwestern China.

SUBMITTER: Lu M

PROVIDER: S-EPMC8462150 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:BackgroundUnderstanding altitudinal patterns of biological diversity and their underlying mechanisms is critically important for biodiversity conservation in mountainous regions. The contribution of area to plant diversity patterns is widely acknowledged and may mask the effects of other determinant factors. In this context, it is important to examine altitudinal patterns of corrected taxon richness by eliminating the area effect. Here we adopt two methods to correct observed taxon richness: a power-law relationship between richness and area, hereafter "method 1"; and richness counted in equal-area altitudinal bands, hereafter "method 2". We compare these two methods on the Jade Dragon Snow Mountain, which is the nearest large-scale altitudinal gradient to the Equator in the Northern Hemisphere.ResultsWe find that seed plant species richness, genus richness, family richness, and species richness of trees, shrubs, herbs and Groups I-III (species with elevational range size <150, between 150 and 500, and >500 m, respectively) display distinct hump-shaped patterns along the equal-elevation altitudinal gradient. The corrected taxon richness based on method 2 (TRcor2) also shows hump-shaped patterns for all plant groups, while the one based on method 1 (TRcor1) does not. As for the abiotic factors influencing the patterns, mean annual temperature, mean annual precipitation, and mid-domain effect explain a larger part of the variation in TRcor2 than in TRcor1.ConclusionsIn conclusion, for biodiversity patterns on the Jade Dragon Snow Mountain, method 2 preserves the significant influences of abiotic factors to the greatest degree while eliminating the area effect. Our results thus reveal that although the classical method 1 has earned more attention and approval in previous research, method 2 can perform better under certain circumstances. We not only confirm the essential contribution of method 1 in community ecology, but also highlight the significant role of method 2 in eliminating the area effect, and call for more application of method 2 in further macroecological studies.