Tianxiao Hao
- Ecological Modeling top 1%
- Species Distribution and Climate Change 5
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- Ecology and Vegetation Dynamics Studies 2
- Ecology top 5%
- Wildlife Ecology and Conservation 2
- Global and Planetary Change top 10%
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- COVID-19 epidemiological studies 3
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- Plant Pathogens and Fungal Diseases 3
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- Mycorrhizal Fungi and Plant Interactions 3
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- SARS-CoV-2 and COVID-19 Research 1
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- COVID-19 and Mental Health 1
- Co-authors
- José J. Lahoz‐MonfortGurutzeta Guillera‐ArroitaJane ElithTom W. MayDarren SouthwellDavid P. WilkinsonBrendan A. WintleRoozbeh Valavi
- Journals
- SHILAP Revista de lepidopterología (1 paper)Biological Conservation (1 paper)Vaccine (1 paper)
- Partner nations
- Australia
In The Last Decade
Tianxiao Hao
9 papers receiving 759 citations
Hit Papers
Peers
Comparison fields: 5 of 71
- Ecological Modeling 546
- Nature and Landscape Conservation 256
- Ecology 385
- Ecology, Evolution, Behavior and Systematics 163
- Global and Planetary Change 129
Countries citing papers authored by Tianxiao Hao
This map shows the geographic impact of Tianxiao Hao's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Tianxiao Hao with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Tianxiao Hao more than expected).
Fields of papers citing papers by Tianxiao Hao
This network shows the impact of papers produced by Tianxiao Hao. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Tianxiao Hao. The network helps show where Tianxiao Hao may publish in the future.
Co-authorship network
The 24 scholars most cited alongside Tianxiao Hao, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2025 | 1 | |
| 2 | 2025 | 1 | |
| 3 | 2024 | 3 | |
| 4 | 2022 | 3 | |
| 5 | 2021 | 6 | |
| 6 | 2021 | 1 | |
| 7 | Testing whether ensemble modelling is advantageous for maximising predictive performance of species distribution modelsbreakdown → | 2020 | 296 |
| 8 | 2020 | 38 | |
| 9 | A review of evidence about use and performance of species distribution modelling ensembles like BIOMODbreakdown → | 2019 | 420 |
About Tianxiao Hao
Tianxiao Hao is a scholar working on Ecological Modeling, Modeling and Simulation and Cell Biology, having authored 9 papers that have together received 769 indexed citations. Recurring topics across this work include Species Distribution and Climate Change (5 papers), COVID-19 epidemiological studies (3 papers), Plant Pathogens and Fungal Diseases (3 papers), Mycorrhizal Fungi and Plant Interactions (3 papers), Ecology and Vegetation Dynamics Studies (2 papers), Wildlife Ecology and Conservation (2 papers), SARS-CoV-2 and COVID-19 Research (1 paper) and COVID-19 and Mental Health (1 paper). The work is most often cited by research in Ecological Modeling (546 citations), Nature and Landscape Conservation (256 citations) and Ecology (385 citations). Tianxiao Hao has collaborated with scholars based in Australia. Frequent co-authors include José J. Lahoz‐Monfort, Gurutzeta Guillera‐Arroita, Jane Elith, Tom W. May, Darren Southwell, David P. Wilkinson, Brendan A. Wintle, Roozbeh Valavi, Adam S. Smart and Deborah Cromer. Their work appears in journals such as SHILAP Revista de lepidopterología, Biological Conservation and Vaccine.
Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.