Major Research Directions: Biodiversity Modeling

1. Diversity Response Mechanisms and Theoretical Frameworks

Investigate how diversity responds to environmental changes, considering key factors such as species ecological variables, genetic diversity, and dispersal ability. Propose the Life Strategy Index (LSI) as a comprehensive assessment standard to predict extinction risks for different animal groups under climate change, providing scientific support for endangered species management and global biodiversity conservation.

2. Biodiversity Indicator System Construction

Construct a biodiversity indicator system by systematically summarizing historical literature and the latest research progress. Summarize statistical indicators for detecting and evaluating distribution aggregation, covering various field survey methods, research models, and sampling scales. Propose principles for developing new distribution aggregation indicators, providing guidance for future statistical method and indicator development.

3. Large-scale Biodiversity Assessment

Focus on the delayed response of biodiversity to temporal and spatial changes (e.g., climate debt). Evaluate the accumulation of climate debt in amphibians across different global regions and analyze the impact of landscape heterogeneity on spatial climate debt patterns, offering insights for global amphibian conservation under various climate change scenarios.

4. Diversity Patterns at Field Survey Scales

Study species spatial distribution patterns and propose a new additive framework to partition the local multi-species distribution aggregation level for field biodiversity data analysis. This framework divides species spatial distribution into regional abundance variation and local spatial inertia effects, with potential applications in field ecology and macroecology research.

Research Objectives:

1. Deepen understanding of the mechanisms by which biodiversity responds to environmental changes.

2. Develop and refine methods and indicators for biodiversity assessment and monitoring.

3. Provide scientific basis and tools to support global biodiversity conservation and management decisions.

Application Areas:

Biodiversity Conservation

Ecosystem Management

Climate Change Research

Environmental Policy Formulation

Chen, Y., & Shen, T. (2024). Distributional ecology: Opening new research windows by addressing aggregation‐related puzzles. Diversity and Distributions, 30(4), e13818. https://doi.org/10.1111/ddi.13818

Wu, N., Chung, H. V., Shi, S., Shi, X., Liu, F., Jiang, J., & Chen, Y. (2024).  Additive partitioning of multispecies distributional aggregation of local assemblages. Journal of Animal Ecology.

Fan, H., Liu, T., Chen, Y., Liao, Z., Chen, J., Hu, Y., Qiao, G., & Wei, F. (2024). Geographical patterns and determinants of insect biodiversity in China. Science China Life Sciences. https://doi.org/10.1007/s11427-023-2483-0

Liang, L., Liao, Z., Shi, X., Zhang, W., Xiao, Q., Wu, N., Jiang, J., Chen Y. (2023) The spatiotemporal dynamic pattern and development trend of global national parks. National Park, 1(4): 255-263. https://doi.org/10.20152/j.np.202311120029

Li, Z., Guo, X., Guo, Z., Shi, X., Zhou, J., Liu, Z., Xiao, Q., & Chen, Y. (2024). 3D Morphological Scanning and Environmental Correlates of Bufo gargarizans in the Yellow River Basin. Animals, 14(3), 369. https://doi.org/10.3390/ani14030369

Chen, Y., Dai, Q., Zhou, J., Tang, D., Li, D., Wei, F., & Zhan, X. (2024). Toward a predictable cask theory of species extinction assessment in the Anthropocene. Frontiers in Ecology and the Environment, 22(3), e2714. https://doi.org/10.1002/fee.2714

Liao, Z., Zhou, J., Shen, T.-J., & Chen, Y. (2023). Inferring single- and multi-species distributional aggregation using quadrat sampling. Ecological Indicators, 156, 111085. https://doi.org/10.1016/j.ecolind.2023.111085

Chen, Y., Wang, R.-H., & Shen, T.-J. (2023). Biodiversity survey and estimation for line-transect sampling. Frontiers in Plant Science, 14, 1159090. https://doi.org/10.3389/fpls.2023.1159090

Zhang, W., Liao, Z., Xiao, Q., Zhou, J., Shi, X., Li, C., Chen, Y., & Xu, W. (2023). Habitat-specific conservation priorities of multidimensional diversity patterns of amphibians in China effectively contribute to the ‘3030’ target. Science of The Total Environment, 901, 165959. https://doi.org/10.1016/j.scitotenv.2023.165959

Chen, Y., Wu, Y., Chang, C.-H., & Shen, T.-J. (2023). How close is an undiscovered species to you after conducting biodiversity sampling? Ecological Indicators, 154, 110482. https://doi.org/10.1016/j.ecolind.2023.110482

Yang, F., Liu, Z., Zhou, J., Guo, X., & Chen, Y. (2023). Microbial Species-Area Relationships on the Skins of Amphibian Hosts. Microbiology Spectrum, 11(3), e01771-22. https://doi.org/10.1128/spectrum.01771-22

He, Y., Liao, Z., Chen, X., & Chen, Y. (2023). Climatic debts for global amphibians: Who, where and why? Biological Conservation, 279, 109929. https://doi.org/10/grtrf3

Chen, Y., Wu, Y., Zhou, J., Zhang, W., Lin, H.-D., Liu, X., Pan, K., Shen, T.-J., & Pan, Z. (2021). Effectively inferring overall spatial distribution pattern of species in a map when exact coordinate information is missing. Methods in Ecology and Evolution. 12, 971–984. https://doi.org/10.1111/2041-210X.13590.

Zhao, T., Zhang, W., Zhou, J., Zhao, C., Liu, X., Liu, Z., Shu, G., Wang, S., Li, C., Xie, F., Chen, Y., & Jiang, J. (2020). Niche divergence of evolutionarily significant units with implications for repopulation programs of the world’s largest amphibians. Sci Total Environ, 738, 140269. https://doi.org/10/gh3shx

Chen, Y., & Shen, T.-J. (2020). Unifying conspecific-encounter index v and Moran’s I index. Ecography 43, 1902–1904. https://doi.org/10.1111/ecog.05281.

Chen, Y. H., Shen, T. J., Chung, H. V., Shi, S. C., Jiang, J. P., Condit, R., & Hubbell, S. P. (2019). Inferring multispecies distributional aggregation level from limited line transect-derived biodiversity data. Methods in Ecology and Evolution, 10, 1015–1023. https://doi.org/10/gh3shp

Chen, Y., Shen, T.-J., Condit, R., & Hubbell, S.P. (2018). Community-level species’ correlated distribution can be scale-independent and related to the evenness of abundance. Ecology 99, 2787–2800. https://doi.org/10.1002/ecy.2544.

Since taking his current position, he has led 14 projects and participated in 8, including 3 national projects, 9 provincial and ministerial projects, and 1 horizontal cooperation project, with a total funding of 11.5 million RMB. The following are some of the representative projects he has led or participated in:

1. CAS B-Class Leading Sub-Project, "Biodiversity Extinction Risk Assessment and Critical Point Inference,"  Principal Investigator.

2. CAS B-Class Leading Project, "Quantitative Indicative Indicator System and Hypergeometric Theory Model of Three Major Driving Forces," Principal Investigator.

3. National Key R&D Program, "Research on Coordination and Trade-off of Multiple Protection Goals," Principal Investigator.

4. CAS Defense Technology Innovation Key Deployment Project, Principal Investigator.

5. National Natural Science Foundation Regional Innovation Development Joint Fund Key Project, "Revealing Adaptation and Evolution Mechanisms of Amphibians to Environmental Changes Based on Multi-omics: A Case Study of the Middle and Lower Yellow River Transition Zone," Principal Investigator.