T. B. Moya

503 total citations
12 papers, 371 citations indexed

About

T. B. Moya is a scholar working on Plant Science, Global and Planetary Change and Ecology, Evolution, Behavior and Systematics. According to data from OpenAlex, T. B. Moya has authored 12 papers receiving a total of 371 indexed citations (citations by other indexed papers that have themselves been cited), including 7 papers in Plant Science, 4 papers in Global and Planetary Change and 3 papers in Ecology, Evolution, Behavior and Systematics. Recurrent topics in T. B. Moya's work include Climate variability and models (3 papers), Rice Cultivation and Yield Improvement (3 papers) and Plant responses to elevated CO2 (3 papers). T. B. Moya is often cited by papers focused on Climate variability and models (3 papers), Rice Cultivation and Yield Improvement (3 papers) and Plant responses to elevated CO2 (3 papers). T. B. Moya collaborates with scholars based in Philippines, United States and Bangladesh. T. B. Moya's co-authors include J. C. O’Toole, Lewis H. Ziska, K. F. Bronson, David M. Olszyk, H. U. Neue, R. S. Lantin, O.S. Namuco, Reiner Waßmann, J. B. Aduna and Ben S. Malayang and has published in prestigious journals such as Global Change Biology, Plant and Soil and Field Crops Research.

In The Last Decade

T. B. Moya

12 papers receiving 338 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name	h						Papers	Cites
T. B. Moya Philippines	7	283	145	94	60	54	12	371
C.P. Whitfield United Kingdom	9	264 0.9×	60 0.4×	129 1.4×	18 0.3×	79 1.5×	10	324
Ayumi Tanaka‐Oda Japan	10	140 0.5×	220 1.5×	66 0.7×	41 0.7×	75 1.4×	21	430
H.Z. Enoch Israel	12	381 1.3×	229 1.6×	117 1.2×	48 0.8×	25 0.5×	33	462
Raymond Dempsey Australia	8	147 0.5×	198 1.4×	107 1.1×	43 0.7×	20 0.4×	10	367
Tetsushi Yonekura Japan	12	272 1.0×	125 0.9×	160 1.7×	15 0.3×	49 0.9×	22	310
Ignatious Matimati South Africa	8	163 0.6×	132 0.9×	60 0.6×	52 0.9×	37 0.7×	16	306
Aki Lindén Finland	9	99 0.3×	140 1.0×	68 0.7×	94 1.6×	29 0.5×	11	308
Rémy Schoppach Belgium	14	405 1.4×	322 2.2×	58 0.6×	83 1.4×	82 1.5×	21	549
Wang Biao China	10	112 0.4×	78 0.5×	55 0.6×	72 1.2×	20 0.4×	18	301
Leila R. Fletcher United States	7	200 0.7×	181 1.2×	65 0.7×	30 0.5×	44 0.8×	10	303

Countries citing papers authored by T. B. Moya

Since Specialization

Citations

This map shows the geographic impact of T. B. Moya'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 T. B. Moya with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites T. B. Moya more than expected).

Fields of papers citing papers by T. B. Moya

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by T. B. Moya. 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 T. B. Moya. The network helps show where T. B. Moya may publish in the future.

Co-authorship network of co-authors of T. B. Moya

This figure shows the co-authorship network connecting the top 25 collaborators of T. B. Moya. A scholar is included among the top collaborators of T. B. Moya 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 T. B. Moya. T. B. Moya is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

Sort: Min cites: Since: Top N: Style:

12 of 12 papers shown

1.

Ligaray, Mayzonee, et al.. (2024). Proof of concept for Bayesian inference of dynamic rating curve uncertainty in a sparsely gauged watershed. Hydrological Sciences Journal. 69(15). 2172–2201. 1 indexed citations

2.

Islam, Abu Reza Md. Towfiqul, et al.. (2015). Characterization of southwest monsoon onset over Myanmar. Meteorology and Atmospheric Physics. 127(5). 587–603. 12 indexed citations

3.

Moya, T. B. & Ben S. Malayang. (2003). Climate Variability and Deforestation—Reforestation Dynamics in the Philippines. Environment Development and Sustainability. 6(1-2). 261–277. 9 indexed citations

4.

Moya, T. B., et al.. (1999). Potential of on-farm reservoir use for increasing productivity of rainfed rice areas. 2 indexed citations

5.

Waßmann, Reiner, et al.. (1998). Rice and the global environment.. 205–224. 1 indexed citations

6.

Ziska, Lewis H., T. B. Moya, Reiner Waßmann, et al.. (1998). Long‐term growth at elevated carbon dioxide stimulates methane emission in tropical paddy rice. Global Change Biology. 4(6). 657–665. 78 indexed citations

7.

Moya, T. B., et al.. (1998). Growth dynamics and genotypic variation in tropical, field‐grown paddy rice (Oryza sativa L.) in response to increasing carbon dioxide and temperature. Global Change Biology. 4(6). 645–656. 113 indexed citations

8.

Moya, T. B., et al.. (1997). MICROCLIMATE IN OPEN-TOP CHAMBERS: IMPLICATIONS FOR PREDICTING CLIMATE CHANGE EFFECTS ON RICE PRODUCTION. Transactions of the ASAE. 40(3). 739–747. 12 indexed citations

9.

Moya, T. B.. (1986). The potential of farm reservoir use in increasing productivity of rainfed areas. Crop protection newsletter. 11(2). 125–132. 3 indexed citations

10.

O’Toole, J. C. & T. B. Moya. (1981). Comparison of pressure chamber and psychrometer estimates of leaf water potential in rice. Plant and Soil. 62(2). 313–317. 5 indexed citations

11.

O’Toole, J. C. & T. B. Moya. (1981). Water deficits and yield in upland rice. Field Crops Research. 4. 247–259. 35 indexed citations

12.

O’Toole, J. C. & T. B. Moya. (1978). Genotypic Variation in Maintenance of Leaf Water Potential in Rice¹. Crop Science. 18(5). 873–876. 100 indexed citations

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.

Explore authors with similar magnitude of impact