Title |
A quantitative review of pollination syndromes: do floral traits predict effective pollinators?
|
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Published in |
Ecology Letters, January 2014
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DOI | 10.1111/ele.12224 |
Pubmed ID | |
Authors |
Víctor Rosas‐Guerrero, Ramiro Aguilar, Silvana Martén‐Rodríguez, Lorena Ashworth, Martha Lopezaraiza‐Mikel, Jesús M. Bastida, Mauricio Quesada |
Abstract |
The idea of pollination syndromes has been largely discussed but no formal quantitative evaluation has yet been conducted across angiosperms. We present the first systematic review of pollination syndromes that quantitatively tests whether the most effective pollinators for a species can be inferred from suites of floral traits for 417 plant species. Our results support the syndrome concept, indicating that convergent floral evolution is driven by adaptation to the most effective pollinator group. The predictability of pollination syndromes is greater in pollinator-dependent species and in plants from tropical regions. Many plant species also have secondary pollinators that generally correspond to the ancestral pollinators documented in evolutionary studies. We discuss the utility and limitations of pollination syndromes and the role of secondary pollinators to understand floral ecology and evolution. |
X Demographics
Geographical breakdown
Country | Count | As % |
---|---|---|
Japan | 3 | 14% |
United States | 2 | 9% |
Australia | 1 | 5% |
Italy | 1 | 5% |
Mexico | 1 | 5% |
United Kingdom | 1 | 5% |
Unknown | 13 | 59% |
Demographic breakdown
Type | Count | As % |
---|---|---|
Members of the public | 19 | 86% |
Scientists | 2 | 9% |
Science communicators (journalists, bloggers, editors) | 1 | 5% |
Mendeley readers
Geographical breakdown
Country | Count | As % |
---|---|---|
Brazil | 8 | <1% |
United States | 7 | <1% |
Germany | 6 | <1% |
Colombia | 2 | <1% |
Finland | 2 | <1% |
Canada | 2 | <1% |
India | 1 | <1% |
United Kingdom | 1 | <1% |
Taiwan | 1 | <1% |
Other | 9 | <1% |
Unknown | 892 | 96% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Student > Ph. D. Student | 180 | 19% |
Student > Master | 167 | 18% |
Student > Bachelor | 130 | 14% |
Researcher | 118 | 13% |
Student > Doctoral Student | 57 | 6% |
Other | 131 | 14% |
Unknown | 148 | 16% |
Readers by discipline | Count | As % |
---|---|---|
Agricultural and Biological Sciences | 560 | 60% |
Environmental Science | 126 | 14% |
Biochemistry, Genetics and Molecular Biology | 30 | 3% |
Earth and Planetary Sciences | 11 | 1% |
Engineering | 5 | <1% |
Other | 29 | 3% |
Unknown | 170 | 18% |