Santamaría, S., Enoksen, C. A., Olsen, J., Tavecchia, G., Rotger, A., Igual, J.M. and Traveset A. 2019.
Diet composition of the lizard Podarcis lilfordi (Lacertidae) on two small islands: an individual-resource network approach. Current Zoology, https://doi.org/10.1093/cz/zoz028
Abstract: Despite it is widely accepted that intrapopulation variation is
fundamental to ecological and evolutionary processes, this level of
information has only recently been included into network analysis of
species/population interactions. When done, it has revealed non-random
patterns in the distribution of trophic resources. Nestedness in
resource use among individuals is the most recurrent observed pattern,
often accompanied by an absence of modularity, but no previous studies
examine bipartite modularity. We use network analysis to describe the
diet composition of the Balearic endemic lizard
Podarcis lilfordi
in two islets at population and individual levels, based on the
occurrence of food items in fecal samples.
Our objectives are to 1)
compare niche structure at both levels, 2) characterize niche partition
using nestedness and modularity, and 3) assess how size, sex, season,
and spatial location influence niche structure. At population-level
niche width was wide, but narrow at the level of the individual. Both
islet networks were nested, indicating similar ranking of the food
preferences among individuals, but also modular, which was partially
explained by seasonality. Sex and body size did not notably affect diet
composition. Large niche overlap and therefore possibly relaxed
competition were observed among females in one of the islets and during
spring on both islets. Likewise, higher modularity in autumn suggests
that higher competition could lead to specialization in both
populations, because resources are usually scarce in this season. The
absence of spatial location influence on niche might respond to
fine-grained spatio-temporally distribution of food resources.
Behavioral traits, not included in this study, could also influence
resource partitioning.