Leaf synchrony and insect herbivory among tropical tree habitat specialists
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Growth defense tradeoff theory predicts that plants in low-resource habitats invest more energy in defense mechanisms against natural enemies than growth, whereas plants in high-resource habitats can afford higher leaf loss rates. A less-studied defense against herbivores involves the synchrony of leaf production, which can be an effective defense strategy if leaf biomass production exceeds the capacity of consumption by insects. The aim of this study was to determine whether leaf synchrony varied across habitats with different available resources and whether insects were able to track young leaf production among tree habitat specialists in a tropical forest of French Guiana. We predicted that high-resource habitats would exhibit more synchrony in leaf production due to the low cost and investment to replace leaf tissue. We also expected closer patterns of leaf synchrony and herbivory within related species, assuming that they shared herbivores. We simultaneously monitored leaf production and herbivory rates of five pairs of tree species, each composed of a specialist of terra firme or white-sand forests within the same lineage. Our prediction was not supported by the strong interaction of habitat and lineage for leaf synchrony within individuals of the same species; although habitat specialists differed in leaf synchrony within four of five lineages, the direction of the effect was variable. All species showed short time lags for the correlation between leaf production and herbivory, suggesting that insects are tightly tracking leaf production, especially for the most synchronous species. Leaf synchrony may provide an important escape defense against herbivores, and its expression appears to be constrained by both evolutionary history and environmental factors.
KeywordsPhenology Escape Herbivorous insects Resource availability Time lag French Guiana
We thank Eléonore Bernardo, Jocelyn Cazal, Jean-Yves Goret, and Antonin Leclercq for help in field work. This manuscript has been improved by the help of Q. Molto, P.-C. Zalamea, and C.E.T. Paine. Research was supported by a collaborative NSF Grant (DEB-0743103/0743800) to C. Baraloto and P.V.A. Fine, the Fond Social Européen (FSE) to G.P.A. Lamarre, and an INRA Package Grant to C. Baraloto. I. Mendoza benefited of a Brazilian CNPq Grant (150483/2012-0) during the writing of this paper. This work has benefited from an “Investissement d’Avenir” grant managed by Agence Nationale de la Recherche (CEBA, ref. ANR-10-LABX-25-01). This article is an output of the interaction held during the ATBC meeting in Bonito (June 2012).
- Aide TM (1991) Synchronous leaf production and herbivory in juveniles of Gustavia superba. Oecologia 88:511–514Google Scholar
- Baraloto C, Molto Q, Rabaud S, Hérault B, Valencia R, Blanc L, Fine PVA, Thompson J (2013) Rapid simultaneous estimation of aboveground biomass and tree diversity across Neotropical forests: a comparison of field inventory methods. Biotropica 45:288–298Google Scholar
- Fortunel C, Paine CET, Fine PVA, Kraft NJB, Baraloto C (2014) Environmental factors predict community functional composition in Amazonian forests. J Ecol 102:145–155Google Scholar
- Legendre P, Legendre L (1998) Numerical ecology. Elsevier, AmsterdamGoogle Scholar
- McKey D (1975) The ecology of coevolved seed dispersal systems. In: Gilbert LE, Raven PH (eds) Coevolution of plants and animals. University of Texas, Austin, pp 159–191Google Scholar
- McKey D (1989) Interactions between ants and leguminous plants. In: Stirton CH, Zarucchi JL (eds) Advances in legume biology. Monographs in Systematic Botany from the Missouri Botanical Garden, vol 29, pp 673–718Google Scholar
- Molino JF, Sabatier D, Prévost MF, Frame D, Gonzalez S, Bilot-Guérin V (2009) Etablissement d’une liste des espèces d’arbres de la Guyane française. IRD, CayenneGoogle Scholar
- Pennington TD, Gasson P, Hanson L, Kite G, Harborne J (1997) The genus Inga: botany. Royal Botanic Gardens, Richmond, UK, 844 ppGoogle Scholar
- R Development Core Team (2012) R: a language and environment for statistical computing. R Foundation for Statistical Computing, ViennaGoogle Scholar