Impacts of road networks on the geography of floristic collections in China

doi:10.1016/j.pld.2025.02.001

Plant Diversity ›› 2025, Vol. 47 ›› Issue (03): 403-414.DOI: 10.1016/j.pld.2025.02.001

Impacts of road networks on the geography of floristic collections in China

Jingyang He^a,b, Wenjing Yang^a,b, Qinghui You^c, Qiwu Hu^b, Mingyang Cong^c, Chao Tian^a,b, Keping Ma^d

a. Key Laboratory of Poyang Lake Wetland and Watershed Research (Jiangxi Normal University), Ministry of Education, Nanchang 330022, China;
b. School of Geography and Environment, Jiangxi Normal University, Nanchang 330022, China;
c. Key Laboratory of Biodiversity Conservation and Bioresource Utilization of Jiangxi Province, College of Life Sciences, Jiangxi Normal University, Nanchang 330022, China;
d. State Key Laboratory of Vegetation and Environmental Change, Institute of Botany, Chinese Academy of Sciences, 20 Nanxincun, Xiangshan, Beijing 100093, China

收稿日期:2024-11-13 修回日期:2025-02-15 出版日期:2025-05-25 发布日期:2025-05-21
通讯作者: Wenjing Yang,E-mail:yangwenjing@jxnu.edu.cn
基金资助:
This research was funded by National Natural Science Foundation of China (32460276, 32060275), and Jiangxi Provincial Natural Science Foundation (20232BAB203058, 20242BAB27001).

Impacts of road networks on the geography of floristic collections in China

Jingyang He^a,b, Wenjing Yang^a,b, Qinghui You^c, Qiwu Hu^b, Mingyang Cong^c, Chao Tian^a,b, Keping Ma^d

a. Key Laboratory of Poyang Lake Wetland and Watershed Research (Jiangxi Normal University), Ministry of Education, Nanchang 330022, China;
b. School of Geography and Environment, Jiangxi Normal University, Nanchang 330022, China;
c. Key Laboratory of Biodiversity Conservation and Bioresource Utilization of Jiangxi Province, College of Life Sciences, Jiangxi Normal University, Nanchang 330022, China;
d. State Key Laboratory of Vegetation and Environmental Change, Institute of Botany, Chinese Academy of Sciences, 20 Nanxincun, Xiangshan, Beijing 100093, China

Received:2024-11-13 Revised:2025-02-15 Online:2025-05-25 Published:2025-05-21
Contact: Wenjing Yang,E-mail:yangwenjing@jxnu.edu.cn
Supported by:
This research was funded by National Natural Science Foundation of China (32460276, 32060275), and Jiangxi Provincial Natural Science Foundation (20232BAB203058, 20242BAB27001).

摘要/Abstract

摘要： Biological collections are critical for the understanding of species distributions and for formulating biodiversity conservation strategies. However, biological collections are susceptible to various biases, including the “road-map effect”, meaning that the geography of biological collections can be influenced by road networks. Here, using species occurrence records derived from 921,233 plant specimens, we quantified the intensity of the “road-map effect” on floristic collections of China, and investigated its relationships with various environmental and socio-economic variables. Species occurrence records mainly distributed in major mountain ranges, while lowlands were underrepresented. The distance of species occurrence records to the nearest road decreased from 19.54 km in 1960s to 3.58 km in 2010s. These records showed significant clustering within 5 km and 10 km buffer zones of roads. The road density surrounding these records was significantly higher than that in random patterns. Collectively, our results confirmed a significant “road-map effect” in the floristic collections of China, and this effect has substantially intensified from the 1960s to the 2010s, even after controlling for the impact of road network expansion. Topographic, climatic and socio-economic variables that determine regional species diversity, vegetation cover and human impact on vegetation played crucial roles in predicting the intensity of the “road-map effect”. Our findings indicate that biological surveys have become increasingly dependent on road networks, a trend rarely reported in published studies. Future floristic surveys in China should prioritize the lowland areas that have experienced stronger human disturbances, as well as remote areas that may harbor more unique and rare species.

关键词: Biological sampling, Environmental and socio-economic variables, Plants, Road-map effect, Species occurrence records

Abstract: Biological collections are critical for the understanding of species distributions and for formulating biodiversity conservation strategies. However, biological collections are susceptible to various biases, including the “road-map effect”, meaning that the geography of biological collections can be influenced by road networks. Here, using species occurrence records derived from 921,233 plant specimens, we quantified the intensity of the “road-map effect” on floristic collections of China, and investigated its relationships with various environmental and socio-economic variables. Species occurrence records mainly distributed in major mountain ranges, while lowlands were underrepresented. The distance of species occurrence records to the nearest road decreased from 19.54 km in 1960s to 3.58 km in 2010s. These records showed significant clustering within 5 km and 10 km buffer zones of roads. The road density surrounding these records was significantly higher than that in random patterns. Collectively, our results confirmed a significant “road-map effect” in the floristic collections of China, and this effect has substantially intensified from the 1960s to the 2010s, even after controlling for the impact of road network expansion. Topographic, climatic and socio-economic variables that determine regional species diversity, vegetation cover and human impact on vegetation played crucial roles in predicting the intensity of the “road-map effect”. Our findings indicate that biological surveys have become increasingly dependent on road networks, a trend rarely reported in published studies. Future floristic surveys in China should prioritize the lowland areas that have experienced stronger human disturbances, as well as remote areas that may harbor more unique and rare species.

Key words: Biological sampling, Environmental and socio-economic variables, Plants, Road-map effect, Species occurrence records

Jingyang He, Wenjing Yang, Qinghui You, Qiwu Hu, Mingyang Cong, Chao Tian, Keping Ma. Impacts of road networks on the geography of floristic collections in China[J]. Plant Diversity, 2025, 47(03): 403-414.

参考文献

Ai, M., Chen, X., Yu, Q., 2024. Spatial correlation analysis between human disturbance intensity (HDI) and ecosystem services value (ESV) in the Chengdu-Chongqing urban agglomeration. Ecol. Indic. 158, 111555.
Badgley, C., Smiley, T. M., Terry, R., et al., 2017. Biodiversity and topographic complexity: modern and geohistorical perspectives. Trends Ecol. Evol. 32, 211-226.
Beck, J., Ballesteros-Mejia, L., Nagel, P., et al., 2013. Online solutions and the “Wallacean shortfall”: what does GBIF contribute to our knowledge of species' ranges? Divers. Distrib. 19, 1043-1050.
Borcard, D., Legendre, P., 2002. All-scale spatial analysis of ecological data by means of principal coordinates of neighbour matrices. Ecol. Model. 153, 51-68.
Bordelon, A., 2022. Herbarium: the quest to preserve and classify the world's plants. J. Bot. Res. Inst. Tex. 16, 448.
Bowler, D. E., Callaghan, C. T., Bhandari, N., et al., 2022. Temporal trends in the spatial bias of species occurrence records. Ecography 2022, e06219.
Canhos, V., Souza, S., De Giovanni, R., et al., 2004. Global biodiversity informatics: setting the scene for a “new world” of ecological modeling. Biodivers. Inform. 1, 1-13.
Chapman, A. D., Busby, J. R., 1994. Linking plant species information to continental biodiversity inventory, climate modeling and environmental monitoring. In: Miller, R.I. (Ed.), Mapping the Diversity of Nature. Springer, Dordrecht, pp. 179-195.
Chen, C., 1994. History of plant taxonomy in China. In: Wang, Z. (Ed.), History of Chinese Botany. Science Press, Beijing, pp. 121-144.
China Cartographic Publishing House, 1962. China Transportation and Travel Map. China Cartographic Publishing House, Beijing.
China Cartographic Publishing House, 1974. China Transportation Map. China Cartographic Publishing House, Xi’an.
China Cartographic Publishing House, 1986. China Transportation Atlas. China Cartographic Publishing House, Beijing.
Coelho, M. T. P., Barreto, E., Rangel, T. F., et al., 2023. The geography of climate and the global patterns of species diversity. Nature 622, 537-544.
Cosentino, F., Maiorano, L., 2021. Is geographic sampling bias representative of environmental space? Ecol. Inform. 64, 101369.
Crisp, M. D., Laffan, S., Linder, H. P., et al., 2001. Endemism in the Australian flora. J. Biogeogr. 28, 183-198.
Daru, B. H., Park, D. S., Primack, R. B., et al., 2018. Widespread sampling biases in herbaria revealed from large-scale digitization. New Phytol. 217, 939-955.
Department of Comprehensive Statistics of National Bureau of Statistics, 2010. China Compendium of Statistics 1949-2008. China Statistics Press, Beijing.
Diniz-Filho, J. A. F., Bini, L. M., 2005. Modelling geographical patterns in species richness using eigenvector-based spatial filters. Global Ecol. Biogeogr. 14, 177-185.
Diniz-Filho, J. A. F., Bini, L. M., Hawkins, B. A., 2003. Spatial autocorrelation and red herrings in geographical ecology. Global Ecol. Biogeogr. 12, 53-64.
Freitag, S., Hobson, C., Biggs, H. C., et al., 1998. Testing for potential survey bias: the effect of roads, urban areas and nature reserves on a southern African mammal data set. Anim. Conserv. 1, 119-127.
Grilo, C., Bissonette, J., Cramer, P., 2010. Mitigation measures to reduce impacts on biodiversity. In: Jones, S. R. (Ed.), Highways: Construction, Management, and Maintenance. Nova Science Publishers, Inc, Hauppauge, pp. 73-114.
Hu, X., Wu, C., Wang, J., et al., 2018. Identification of spatial variation in road network and its driving patterns: economy and population. Reg. Sci. Urban Econ. 71, 37-45.
Huang, J., Chen, J., Ying, J., et al., 2011. Features and distribution patterns of Chinese endemic seed plant species. J. Systemat. Evol. 49, 81-94.
Husak, G., Michaelsen, J., Funk, C., 2007. Use of the gamma distribution to represent monthly rainfall in Africa for drought monitoring applications. Int. J. Climatol. 27, 935-944.
Irl, S. D. H., Harter, D. E. V., Steinbauer, M. J., et al., 2015. Climate vs. topography - spatial patterns of plant species diversity and endemism on a high-elevation island. J. Ecol. 103, 1621-1633.
Johnson, J. B., Omland, K. S., 2004. Model selection in ecology and evolution. Trends Ecol. Evol. 19, 101-108.
Kadmon, R., Farber, O., Danin, A., 2004. Effect of roadside bias on the accuracy of predictive maps produced by bioclimatic models. Ecol. Appl. 14, 401-413.
Kleinschroth, F., Laporte, N., Laurance, W. F., et al., 2019. Road expansion and persistence in forests of the Congo Basin. Nat. Sustain. 2, 628-634.
Lituma, C., Buehler, D., 2016. Minimal bias in surveys of grassland birds from roadsides. Condor 118, 715-727.
Liu, D., Liu, L., You, Q., et al., 2022a. Development of a landscape-based multi-metric index to assess wetland health of the Poyang Lake. Remote Sens. 14, 1082.
Liu, H., Qin, H., Bao, B., et al., 2022b. Analysis of digitized specimens of higher plants in China. Guihaia 42, 29-45.
Loiselle, B. A., Joergensen, P. M., Consiglio, T., et al., 2008. Predicting species distributions from herbarium collections: does climate bias in collection sampling influence model outcomes? J. Biogeogr. 35, 105-116.
Meyer, C., Kreft, H., Guralnick, R., et al., 2015. Global priorities for an effective information basis of biodiversity distributions. Nat. Commun. 6, 8221.
Ministry of Transport of the People's Republic of China, 2005. The Second National Road Census Data Compilation. China Communications Press, Beijing.
National Bureau of Statisitics of China, 2009-2020. China Statistical Yearbook. China Statistics Press, Beijing.
Nualart, N., Ibanez, N., Soriano, I., et al., 2017. Assessing the relevance of herbarium collections as tools for conservation biology. Bot. Rev. 83, 303-325.
Oliveira, U., Paglia, A. P., Brescovit, A. D., et al., 2016. The strong influence of collection bias on biodiversity knowledge shortfalls of Brazilian terrestrial biodiversity. Divers. Distrib. 22, 1232-1244.
Pan, J., Zhao, X., Guo, W., et al., 2024. Characterizing China's road network development from a spatial entropy perspective. J. Transport Geogr. 116, 103848.
Parnell, J. A. N., Simpson, D. A., Moat, J., et al., 2003. Plant collecting spread and densities: their potential impact on biogeographical studies in Thailand. J. Biogeogr. 30, 193-209.
Peng, H. E., Chen, J., Kong, H., et al., 2021. Important supporting role of biological specimen in biodiversity conservation and research. Bull. Chin. Acad. Sci. 36, 425-435.
Petersen, T. K., Speed, J. D. M., Groetan, V., et al., 2021. Species data for understanding biodiversity dynamics: the what, where and when of species occurrence data collection. Ecol. Solut. Evid. 2, e12048.
Qian, H., Kissling, W. D., 2010. Spatial scale and cross-taxon congruence of terrestrial vertebrate and vascular plant species richness in China. Ecology 91, 1172-1183.
Rahbek, C., Graves, G. R., 2001. Multiscale assessment of patterns of avian species richness. Proc. Natl. Acad. Sci. U.S.A. 98, 4534-4539.
Reddy, S., Davalos, L. M., 2003. Geographical sampling bias and its implications for conservation priorities in Africa. J. Biogeogr. 30, 1719-1727.
Sipek, M., Sajna, N., 2024. Lowland forest fragment characteristics and anthropogenic disturbances determine alien plant species richness and composition. Biol. Invasions 26, 1595-1614.
U.S. Geological Survey (USGS), 1996. GTOPO30. DOI: 10.5066/F7DF6PQS. Accessed July 19, 2023. https://www.usgs.gov/centers/eros/science/usgs-eros-archive-digital-elevation-hydro1k#overview. Data repository: USGS Earth Resources Observation and Science (EROS) Center.
Valavi, R., Elith, J., Lahoz-Monfort, J. J., et al., 2021. Modelling species presence-only data with random forests. Ecography 44, 1731-1742.
Van Buskirk, J., Jansen van Rensburg, A., 2020. Relative importance of isolation-by-environment and other determinants of gene flow in an alpine amphibian. Evolution 74, 962-978.
van der Maaten, E., Hamann, A., van der Maaten-Theunissen, M., et al., 2017. Species distribution models predict temporal but not spatial variation in forest growth. Ecol. Evol. 7, 2585-2594.
Vargas, C. A., Bottin, M., Sarkinen, T., et al., 2022. Environmental and geographical biases in plant specimen data from the Colombian Andes. Bot. J. Linn. Soc. 200, 451-464.
Venables, W. N., Ripley, B. D., 2002. Modern Applied Statistics with S, fouth ed., Springer, New York.
Wang, Z., Fang, J., Tang, Z., et al., 2012. Geographical patterns in the beta diversity of China's woody plants: the influence of space, environment and range size. Ecography 35, 1092-1102.
Wong, H. L., Wang, Y., Luo, R., et al., 2017. Local governance and the quality of local infrastructure: evidence from village road projects in rural China. J. Publ. Econ. 152, 119-132.
Yang, W., Liu, D., You, Q., et al., 2021. Taxonomic bias in occurrence information of angiosperm species in China. Sci. China Life Sci. 64, 584-592.
Yang, W., Ma, K., Kreft, H., 2013. Geographical sampling bias in a large distributional database and its effects on species richness-environment models. J. Biogeogr. 40, 1415-1426.
Yang, W., Ma, K., Kreft, H., 2014. Environmental and socio-economic factors shaping the geography of floristic collections in China. Global Ecol. Biogeogr. 23, 1284-1292.
Zhang, J., Xiao, C., Duan, X., et al., 2024. Species' geographical range, environmental range and traits lead to specimen collection preference of dominant plant species of grasslands in Northern China. Plant Divers. 46, 353-361.
Zhang, T., Sun, Y., Guan, M., et al., 2022. Human activity intensity in China under multi-factor interactions: spatiotemporal characteristics and influencing factors. Sustainability 14, 3113.
Zhuang, H., Wang, C., Wang, Y., et al., 2021. Native useful vascular plants of China: a checklist and use patterns. Plant Divers. 43, 134-141.
Zhou, Y., Tong, C., Wang, Y., 2022. Road construction, economic growth, and poverty alleviation in China. Growth Change 53, 1306-1332.
Zizka, A., Antonelli, A., Silvestro, D., 2021. sampbias, a method for quantifying geographic sampling biases in species distribution data. Ecography 44, 25-32.

[1]	Fei-Fei Li, Qiang Hao, Xia Cui, Ruo-Zhu Lin, Bin-Sheng Luo, Jin-Shuang Ma. Global invasive alien plant management lists: Assessing current practices and adapting to new demands[J]. Plant Diversity, 2025, 47(04): 666-680.
[2]	Hong Qian, Jian Wang, Shenhua Qian, Michael Kessler. Geographic patterns and climatic drivers of the mean genus age of liverworts in North America[J]. Plant Diversity, 2024, 46(06): 723-731.
[3]	Joeime F. Meñiza, Monica M. Pasco, Jemer A. Alimbon. A review of ethnobotanical studies reveals over 500 medicinal plants in Mindanao, Philippines[J]. Plant Diversity, 2024, 46(05): 551-564.
[4]	Tana Wuyun, Lu Zhang, Tiina Tosens, Bin Liu, Kristiina Mark, José ángel Morales-Sánchez, Jesamine Jöneva Rikisahedew, Vivian Kuusk, ülo Niinemets. Extremely thin but very robust: Surprising cryptogam trait combinations at the end of the leaf economics spectrum[J]. Plant Diversity, 2024, 46(05): 621-629.
[5]	Haibin Yu, Man Yang, Zixin Lu, Weitao Wang, Fangyuan Yu, Yonghua Zhang, Xue Yin, Hongjun Yu, Junjie Hu, David C. Deane. A phylogenetic approach identifies patterns of beta diversity and floristic subregions of the Qinghai-Tibet Plateau[J]. Plant Diversity, 2024, 46(01): 59-69.
[6]	Yan Ke, Feng-Ping Zhang, Yun-Bing Zhang, Wei Li, Qin Wang, Da Yang, Jiao-Lin Zhang, Kun-Fang Cao. Convergent relationships between flower economics and hydraulic traits across aquatic and terrestrial herbaceous plants[J]. Plant Diversity, 2023, 45(05): 601-610.
[7]	Thant Sin Aung, Alice C. Hughes, Phyo Kay Khine, Bo Liu, Xiao-Li Shen, Ke-Ping Ma. Patterns of floristic inventory and plant collections in Myanmar[J]. Plant Diversity, 2023, 45(03): 302-308.
[8]	Yi Jin, Hong Qian. U.PhyloMaker:An R package that can generate large phylogenetic trees for plants and animals[J]. Plant Diversity, 2023, 45(03): 347-352.
[9]	Ya-Dong Zhou, Hong Qian, Yi Jin, Ke-Yan Xiao, Xue Yan, Qing-Feng Wang. Geographic patterns of taxonomic and phylogenetic β-diversity of aquatic angiosperms in China[J]. Plant Diversity, 2023, 45(02): 177-184.
[10]	Li-Guo Zhang, Xiao-Qian Li, Wei-Tao Jin, Yu-Juan Liu, Yao Zhao, Jun Rong, Xiao-Guo Xiang. Asymmetric migration dynamics of the tropical Asian and Australasian floras[J]. Plant Diversity, 2023, 45(01): 20-26.
[11]	Yi Jin, Hong Qian. V.PhyloMaker2：An updated and enlarged R package that can generate very large phylogenies for vascular plants[J]. Plant Diversity, 2022, 44(04): 335-339.
[12]	Wei-Bo Du, Peng Jia, Guo-Zhen Du. Current patterns of plant diversity and phylogenetic structure on the Kunlun Mountains[J]. Plant Diversity, 2022, 44(01): 30-38.
[13]	Zhihua Zhou, Ronghong Shi, Yu Zhang, Xiaoke Xing, Xiaohua Jin. Orchid conservation in China from 2000 to 2020: Achievements and perspectives[J]. Plant Diversity, 2021, 43(05): 343-349.
[14]	Jun Yang, Jifeng Luo, Qiliang Gan, Leiyu Ke, Fengming Zhang, Hairu Guo, Fuwei Zhao, Yuehu Wang. An ethnobotanical study of forage plants in Zhuxi County in the Qinba mountainous area of central China[J]. Plant Diversity, 2021, 43(03): 239-247.
[15]	Juan Yue, Rong Li. Phylogenetic relatedness of woody angiosperm assemblages and its environmental determinants along a subtropical elevational gradient in China[J]. Plant Diversity, 2021, 43(02): 111-116.

Impacts of road networks on the geography of floristic collections in China

Impacts of road networks on the geography of floristic collections in China

PDF (PC)

可视化

摘要/Abstract

引用本文

使用本文

参考文献

相关文章 15

编辑推荐

Metrics

本文评价