Forest proximity and lowland mosaic increase robustness of tropical pollination networks in mixed fruit orchards

Tuanjit Sritongchuay*, Alice C. Hughes, Jane Memmott, Sara Bumrungsri

*Corresponding author for this work

Research output: Contribution to journalArticle (Academic Journal)peer-review

5 Citations (Scopus)


More than 30% of global crop plants rely on pollinators to set fruit or seed. While several studies have documented the negative effects of habitat degradation and distance from natural habitats on pollinator diversity in tropical areas, such studies have focused on single crops in particular areas without examining entire plant-pollinator communities. Here, we compared the plant-pollinator network structure between mixed fruit orchards that were near to (<1 km) and far from (>7 km) tropical forests and further investigated the effect of landscape composition in surrounding areas on plant-pollinator network structure. Our ten pairs of orchards were in Thailand and grew a range of tropical fruits pollinated by insects, birds and bats. The average number of visitor-flower interactions was higher at sites near the forest. Similarly, network robustness (the resistance of the network to losing species as a result of primary species removal) and interaction evenness (evenness of interactions among species) were higher at the sites closer to the forest. Robustness was strongly positively influenced by the proportion of lowland mosaic within a 1 km radius, while interaction evenness was positively affected by the proportion of urban area and montane mosaic within a 4 km radius of each site. Conservation of (semi-) natural habitats is therefore important for maintaining the diversity of wild pollinators and agricultural production.

Original languageEnglish
Article number103646
Number of pages11
JournalLandscape and Urban Planning
Early online date20 Sep 2019
Publication statusPublished - 1 Dec 2019


  • Forest proximity
  • Interaction evenness
  • Landscape composition
  • Mixed fruit orchard
  • Pollination network
  • Robustness

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