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Published May 2019 | Version Supplemental Material
Journal Article Open

Species-level predation network uncovers high prey specificity in a Neotropical army ant community

  • 1. ROR icon TU Darmstadt
  • 2. ROR icon University of Würzburg
  • 3. ROR icon California Institute of Technology
  • 4. ROR icon Rockefeller University
  • 5. ROR icon National Polytechnic School
  • 6. ROR icon University of Guelph
  • 7. ROR icon University of Valle

Abstract

Army ants are among the top arthropod predators and considered keystone species in tropical ecosystems. During daily mass raids with many thousand workers, army ants hunt live prey, likely exerting strong top‐down control on prey species. Many tropical sites exhibit a high army ant species diversity (>20 species), suggesting that sympatric species partition the available prey niches. However, whether and to what extent this is achieved has not been intensively studied yet. We therefore conducted a large‐scale diet survey of a community of surface‐raiding army ants at La Selva Biological Station in Costa Rica. We systematically collected 3,262 prey items from eleven army ant species (genera Eciton, Nomamyrmex and Neivamyrmex). Prey items were classified as ant prey or non‐ant prey. The prey nearly exclusively consisted of other ants (98%), and most booty was ant brood (87%). Using morphological characters and DNA barcoding, we identified a total of 1,103 ant prey specimens to the species level. One hundred twenty‐nine ant species were detected among the army ant prey, representing about 30% of the known local ant diversity. Using weighted bipartite network analyses, we show that prey specialization in army ants is unexpectedly high and prey niche overlap very small. Besides food niche differentiation, we uncovered a spatiotemporal niche differentiation in army ant raid activity. We discuss competition‐driven multidimensional niche differentiation and predator–prey arms races as possible mechanisms underlying prey specialization in army ants. By combining systematic prey sampling with species‐level prey identification and network analyses, our integrative approach can guide future research by portraying how predator–prey interactions in complex communities can be reliably studied, even in cases where morphological prey identification is infeasible.

Additional Information

© 2019 John Wiley & Sons Ltd. Version of Record online: 02 May 2019; Manuscript accepted: 15 March 2019; Manuscript revised: 14 March 2019; Manuscript received: 27 November 2018. Funding Information: Deutsche Forschungsgemeinschaft. Grant Number: BE 5177/4-1; Life Sciences Research Foundation; German National Academic Foundation.

Attached Files

Supplemental Material - mec15078-sup-0001-appendixs1.pdf

Supplemental Material - mec15078-sup-0002-appendixs2.xlsx

Supplemental Material - mec15078-sup-0003-appendixs3.zip

Supplemental Material - mec15078-sup-0004-appendixs4.pdf

Supplemental Material - mec15078-sup-0005-appendixs5.pdf

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Additional details

Identifiers

Eprint ID
95422
Resolver ID
CaltechAUTHORS:20190513-084120939

Funding

Deutsche Forschungsgemeinschaft (DFG)
BE 5177/4-1
Life Sciences Research Foundation
Studienstiftung des Deutschen Volkes

Dates

Created
2019-05-13
Created from EPrint's datestamp field
Updated
2022-01-05
Created from EPrint's last_modified field