Chia Hsieh

38 total papers · 668 total citations
15 papers, 458 citations indexed

About

Chia Hsieh is a scholar working on Ecology, Ecological Modeling and Molecular Biology. According to data from OpenAlex, Chia Hsieh has authored 15 papers receiving a total of 458 indexed citations (citations by other indexed papers that have themselves been cited), including 6 papers in Ecology, 4 papers in Ecological Modeling and 2 papers in Molecular Biology. Recurrent topics in Chia Hsieh's work include Species Distribution and Climate Change (4 papers), Wildlife Ecology and Conservation (4 papers) and Animal Ecology and Behavior Studies (3 papers). Chia Hsieh is often cited by papers focused on Species Distribution and Climate Change (4 papers), Wildlife Ecology and Conservation (4 papers) and Animal Ecology and Behavior Studies (3 papers). Chia Hsieh collaborates with scholars based in Taiwan, United States and Italy. Chia Hsieh's co-authors include Chien‐Jung Tien, Ching‐Chen Lee, Chun-Yi Wu, Yen‐Chung Lai, C.M. Kao, Lydia Beaudrot, Li–Chyong Chen, Jens‐Christian Svenning, Evan C. Fricke and Óscar Sanisidro and has published in prestigious journals such as Science, Ecology and Journal of Hazardous Materials.

In The Last Decade

Chia Hsieh

14 papers receiving 445 citations

Author Peers

Peers are selected by citation overlap in the author's most active subfields. citations · hero ref

Author						Papers	Cites
Chia Hsieh	115	115	102	89	84	15	458
Chuanbo Guo	29 0.3×	47 0.4×	172 1.7×	136 1.5×	97 1.2×	26	479
Inês C. Rosa	31 0.3×	123 1.1×	346 3.4×	27 0.3×	23 0.3×	21	550
Irene Gallego	44 0.4×	43 0.4×	170 1.7×	48 0.5×	150 1.8×	28	432
Liliana Zalizniak	29 0.3×	126 1.1×	246 2.4×	45 0.5×	50 0.6×	16	450
Na Zhao	20 0.2×	40 0.3×	314 3.1×	96 1.1×	60 0.7×	29	455
Erica Williams	12 0.1×	106 0.9×	198 1.9×	37 0.4×	32 0.4×	19	444
Swati Maurya	15 0.1×	40 0.3×	143 1.4×	89 1.0×	27 0.3×	23	509
Anderson de Souza Cabral	13 0.1×	36 0.3×	230 2.3×	36 0.4×	98 1.2×	26	489
Sam Lake	21 0.2×	72 0.6×	254 2.5×	58 0.7×	42 0.5×	11	502
Arco J. Wagenvoort	26 0.2×	142 1.2×	216 2.1×	63 0.7×	137 1.6×	16	470

Countries citing papers authored by Chia Hsieh

Since Specialization

Citations

This map shows the geographic impact of Chia Hsieh'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 Chia Hsieh with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Chia Hsieh more than expected).

Fields of papers citing papers by Chia Hsieh

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Chia Hsieh. 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 Chia Hsieh. The network helps show where Chia Hsieh may publish in the future.

Co-authorship network of co-authors of Chia Hsieh

This figure shows the co-authorship network connecting the top 25 collaborators of Chia Hsieh. A scholar is included among the top collaborators of Chia Hsieh based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Chia Hsieh. Chia Hsieh is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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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.

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