El Niño is a climatic event that can have large-scale impacts on global rainfall patterns, causing severe droughts in some regions and floods in others. The frequency of strong El Niño events is expected to increase in the future under scenarios of climate change. Despite this, the consequences of El Niño-induced droughts for ecological interactions are poorly understood. Here I applied DNA barcoding to assess the diets of frugivorous and insectivorous bats in the dry forest and rainforest of Costa Rica during one of the strongest El Niño on record (2015) and compare it with a non-El Niño year. My data indicated that the mutualistic network structure observed during the El Niño event was similar in both dry forest and rainforest, despite these habitats experiencing droughts and flooding, respectively. However, during the non-El Niño wet season in the dry forest, niche overlap was higher than the El Niño event. Antagonistic networks showed little change in the overall size and diversity of modules of interaction, but there were significant changes in modularity and the position of the nodes between the networks constructed during the El Niño year versus the normal year in dry forest. Additionally, I evaluated the relationship between wing morphology and diet specialization and differentiation of individuals. I observed that individuals of a common insectivorous bat species, Pteronotus mesoamericanus, showed differences in diet that correlated with wing morphology. To conclude, El Niño was associated with similar changes in the organisation of mutualistic networks in both dry and wet forests, as well as with modifications at the node level in antagonistic networks of dry forest. Such changes could have profound impacts for network resilience and the maintenance of interactions and species at both sites over time.
| Identifer | oai:union.ndltd.org:bl.uk/oai:ethos.bl.uk:766259 |
| Date | January 2018 |
| Creators | de Oliveira, Hernani Fernandes Magalhães |
| Publisher | Queen Mary, University of London |
| Source Sets | Ethos UK |
| Detected Language | English |
| Type | Electronic Thesis or Dissertation |
| Source | http://qmro.qmul.ac.uk/xmlui/handle/123456789/54053 |
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