Maina Muniafu

668 citations
7 papers · 17 · h-index 2

Impact in

Papers in

    • Ethnobotanical and Medicinal Plants Studies 1
    • Indigenous Knowledge Systems and Agriculture 1
    • Species Distribution and Climate Change 2

Maina Muniafu

4 papers receiving 13 citations

Peers

Maina Muniafu
Comparison fields: 5 of 23
  • Forestry 4
  • Business and International Management 1
  • Ecological Modeling 2
  • Soil Science 3
  • Agronomy and Crop Science 3
Replace Everton Cristo de Almeida with:
Everton Cristo de Almeida Brazil
G. Fernández Spain
Henintsoa Razanajatovo Madagascar
Manisha Awasthi South Korea
Tiago S. Malucelli Brazil
Jorcely Barroso Brazil
Md. Hedayetullah India
Christine Ogola United States
Philip M. Crim United States
Maina Muniafu relative to Everton Cristo de Almeida Brazil Everton Cristo de Almeida's profile →
Citations per field
00.5×1.5×
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Citations per year

Countries citing papers authored by Maina Muniafu

Since Specialization
Citations

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

Fields of papers citing papers by Maina Muniafu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 14 scholars most cited alongside Maina Muniafu, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Maina Muniafu Line = papers co-authored together Maina Muniafu links everyone, so they are left out of the graph.

All Works

7 of 7 papers shown

About Maina Muniafu

Maina Muniafu is a scholar working on Plant Science, Ecological Modeling, Ecology, Evolution, Behavior and Systematics, Agronomy and Crop Science and Public Health, Environmental and Occupational Health, having authored 7 papers that have together received 17 indexed citations. Recurring topics across this work include Species Distribution and Climate Change (2 papers), Crop Yield and Soil Fertility (1 paper), Malaria Research and Control (1 paper), Ethnobotanical and Medicinal Plants Studies (1 paper), Indigenous Knowledge Systems and Agriculture (1 paper), Mosquito-borne diseases and control (1 paper), Agriculture and Rural Development Research (1 paper) and Soil Management and Crop Yield (1 paper). The work is most often cited by research in Forestry (4 citations), Business and International Management (1 citation), Ecological Modeling (2 citations), Soil Science (3 citations) and Agronomy and Crop Science (3 citations). Maina Muniafu has collaborated with scholars based in United States, France and Austria. Frequent co-authors include J. I. Kinyamario, Ryan M. Carney, Laban Njoroge, A.P. Long, Frederic Bartumeus, John R.B. Palmer, Johnny A. Uelmen, Sarah Zohdy, Peter Elias and Sriram Chellappan. Their work appears in journals such as Citizen Science Theory and Practice, Planta Medica, Nature and University of Nairobi Research Archive (University of Nairobi).

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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