Determinants of Mammal and Bird Species Richness in China Based on Habitat Groups

Zhi

et al. 2018

Ecology and Evolution

Self Cite

Protected areas are considered as an essential strategy to halt the decline of biodiversity. Ecological representation in protected areas is crucial for assessment on the progress toward conservation targets. Although China has established a large number of protected areas since the 1950s, ecological representation of protected areas is poorly understood. Here, we performed the complementarity analysis to evaluate ecological representation of protected areas in China. We used a database of the geographical distribution for 10,396 woody plant species, 2,305 fern species, 406 amphibian species, 460 reptile species, 1,364 bird species, and 590 mammal species from 2,376 counties across China. We identified complementary sets of counties for all species or threatened species of plant and vertebrate species using a complementarity algorithm. We evaluated ecological representation of 3,627 protected areas and discerned conservation gaps by comparing the distribution of protected areas with complementary sets. The results show that the spatially representative and complementary sites for biodiversity are poorly covered, and a fairly large proportion of protected areas is not designed to efficiently represent biodiversity at the national scale. Our methodology can serve as a generic framework for assessment on ecological representation of protected areas at the national scale.

Section: Methodsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

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Low ecological representation in the protected area network of China

Zhi

et al. 2018

Ecology and Evolution

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“…We used a database of the geographical distribution for 561 mammal species, 1347 bird species, 387 reptile species, 359 amphibian species, 1111 inland water fish species, and 30519 vascular plant species from 2376 counties (their mean size: 3908.7 km 2 ; standard deviation: 9287.6 km 2 ) across China (Xu et al , 2015(Xu et al , 2016. As far as we know, it is the most comprehensive database ever developed in the country.…”

Section: Methods Datamentioning

confidence: 99%

“…We adopted 'county' as the basic sampling unit in this study (the sampling population across China is 2376 counties) (Xu et al 2015(Xu et al , 2016. The richness data were collected from (i) species distribution information from over 1000 monographs and representative papers on fauna and flora across China; (ii) record information of specimens in herbaria of the Chinese Academy of Sciences and relevant universities; and (iii) field surveys in different regions (Xu et al , 2015(Xu et al , 2016. We considered respectively all species, threatened species and species endemic to China.…”

Section: Methods Datamentioning

confidence: 99%

Optimized monitoring sites for detection of biodiversity trends in China

et al. 2017

Biodivers Conserv

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Properly designed monitoring networks can generate data to understand status and trends of biodiversity, and to assess progress towards conservation targets. However, biodiversity monitoring is often affected by poor sampling design. We proposed an approach to choosing optimized monitoring sites among large areas. Based on comprehensive distribution data of 34,284 vertebrates and vascular plants from 2376 counties in China, we selected 564 optimized monitoring sites (counties) through complementarity analysis and pre-existing knowledge of nature reserves. The optimized monitoring sites are complementary to each other and reasonably distributed, to ensure that maximum species are covered while the total number of sites and monitoring costs are minimized. Incongruence of optimized monitoring sites among different taxa indicates that taxa with different ecological features should be selected for large-scale monitoring programmes. The results of this study have been applied in the design and operation of China Biodiversity Observation Network.

Varying congruence among spatial patterns of vascular plants and vertebrates based on habitat groups

et al. 2017

Ecology and Evolution

Self Cite

Proxies are adopted to represent biodiversity patterns due to inadequate information for all taxa. Despite the wide use of proxies, their efficacy remains unclear. Previous analyses focused on overall species richness for fewer groups, affecting the generality and depth of inference. Biological taxa often exhibit very different habitat preferences. Habitat groupings may be an appropriate approach to advancing the study of richness patterns. Diverse geographical patterns of species richness and their potential mechanisms were then examined for habitat groups. We used a database of the spatial distribution of 32,824 species of mammals, birds, reptiles, amphibians and plants from 2,376 counties across China, divided the five taxa into 30 habitat groups, calculated Spearman correlations of species richness among taxa and habitat groups, and tested five hypotheses about richness patterns using multivariate models. We identified one major group [i.e., forest‐ and shrub‐dependent (FS) groups], and some minor groups such as grassland‐dependent vertebrates and desert‐dependent vertebrates. There were mostly high or moderate correlations among FS groups, but mostly low or moderate correlations among other habitat groups. The prominent variables differed among habitat groups of the same taxon, such as birds and reptiles. The sets of predictors were also different within the same habitat, such as forests, grasslands, and deserts. Average correlations among the same habitat groups of vertebrates and among habitat groups of a single taxon were low or moderate, except correlations among FS groups. The sets of prominent variables of species richness differed strongly among habitat groups, although elevation range was the most important variable for most FS groups. The ecological and evolutionary processes that underpin richness patterns might be disparate among different habitat groups. Appropriate groupings based on habitats could reveal important patterns of richness gradients and valuable biodiversity components.