Effects of Spatial Subsidies and Habitat Structure on the Foraging Ecology and Size of Geckos

<div><p>While it is well established that ecosystem subsidies—the addition of energy, nutrients, or materials across ecosystem boundaries—can affect consumer abundance, there is less information available on how subsidy levels may affect consumer diet, body condition, trophic position, and resource partitioning among consumer species. There is also little information on whether changes in vegetation structure commonly associated with spatial variation in subsidies may play an important role in driving consumer responses to subsidies. To address these knowledge gaps, we studied changes in abundance, diet, trophic position, size, and body condition of two congeneric gecko species (<em>Lepidodactylus</em> spp.) that coexist in palm dominated and native (hereafter dicot dominated) forests across the Central Pacific. These forests differ strongly both in the amount of marine subsidies that they receive from seabird guano and carcasses, and in the physical structure of the habitat. Contrary to other studies, we found that subsidy level had no impact on the abundance of either gecko species; it also did not have any apparent effects on resource partitioning between species. However, it did affect body size, dietary composition, and trophic position of both species. Geckos in subsidized, dicot forests were larger, had higher body condition and more diverse diets, and occupied a much higher trophic position than geckos found in palm dominated, low subsidy level forests. Both direct variation in subsidy levels and associated changes in habitat structure appear to play a role in driving these responses. These results suggest that variation in subsidy levels may drive important behavioral responses in predators, even when their numerical response is limited. Strong changes in trophic position of consumers also suggest that subsidies may drive increasingly complex food webs, with longer overall food chain length.</p> </div

Differences across species and forest type in gecko body size (SVL), body condition, and trophic position, and results of MANOVA.

<p>Values are means ± SD.</p>*<p>Raw δ¹⁵N values are presented as reference, but statistics are not calculated for this value as it was not incorporated in whole MANOVA model.</p>†<p>“δ¹⁵N above soil” refers to the increase in gecko δ¹⁵N values over soil δ¹⁵N values at the same site.</p

Mean number (A) and dry biomass (B) of invertebrate consumers (+SE) found in pitfall traps placed on coast and interior of 4 islets of each forest type: dicot (black fill) and palm (no fill).

<p>Each sample is the average of three collections of an individual trap over 1 month; each collection was from a continuous 48 hour period.</p

Differences in leaf, soil, and gecko (both <i>Lepidodactylus lugubris</i> and <i>Lepidodactylus</i> sp. nov.) stable isotope values (means ±1 SD) measured in dicot forests (grey and black symbols) and palm forests (open symbols).

<p>Tissues from <i>R. rattus</i> in both forest types are shown as a reference (denoted with a *). Prey items (small circles) are shown without SD for visual clarity (SD values are included in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0041364#pone.0041364.s001" target="_blank">Table S1</a>). Significantly enriched δ¹⁵N values in dicot forests suggest allochthonous subsidies from seabird guano are incorporated in all organisms. Extreme elevation of δ¹⁵N of both gecko species suggests changes in diet of these species across forest types, or larger changes in food web. Values of δ¹³C in geckos suggest allochthonous marine food sources are important in diets of both gecko species, but are significantly more important for <i>L.</i> sp. nov.</p

Stomach contents of two species of gecko (<i>Lepidodactylus lugubris</i> and <i>Lepidodactylus</i> sp. nov.) across forest types.

<p>Diet diversity, as estimated by Shannon diversity index, is indicated by forest type. Indices with different letters indicate significant differences based on comparisons with Hutchenson's test; indices that share the same letters are not significantly different from each other.</p

Significant predictors of gecko trophic position, body size (SVL), and body condition from a multiple stepwise regression.

<p>Predictor variables included: available soil nitrogen, mean stem size, mean stand basal area, and islet perimeter to area ratio. After each significant predictor we indicate direction of the correlation as positive (+) or negative (−). As there was no interaction in response between forest type and species, data for both species of <i>Lepidodactylus</i> are pooled for this analysis.</p

Habitat preference modulates transoceanic dispersal in a terrestrial vertebrate

The importance of long-distance dispersal (LDD) in shaping geographical distributions has been debated since the nineteenth century. In terrestrial vertebrates, LDD events across large water bodies are considered highly improbable, but organismal traits affecting dispersal capacity are generally not taken into account. Here, we focus on a recent lizard radiation and combine a summary-coalescent species tree based on 1225 exons with a probabilistic model that links dispersal capacity to an evolving trait, to investigate whether ecological specialization has influenced the probability of trans-oceanic dispersal. Cryptoblepharus species that occur in coastal habitats have on average dispersed 13 to 14 times more frequently than non-coastal species and coastal specialization has, therefore, led to an extraordinarily widespread distribution that includes multiple continents and distant island archipelagoes. Furthermore, their presence across the Pacific substantially predates the age of human colonization and we can explicitly reject the possibility that these patterns are solely shaped by human-mediated dispersal. Overall, by combining new analytical methods with a comprehensive phylogenomic dataset, we use a quantitative framework to show how coastal specialization can influence dispersal capacity and eventually shape geographical distributions at a macroevolutionary scale

Prioritizing conserved areas threatened by wildfire and fragmentation for monitoring and management.

In many parts of the world, the combined effects of habitat fragmentation and altered disturbance regimes pose a significant threat to biodiversity. This is particularly true in Mediterranean-type ecosystems (MTEs), which tend to be fire-prone, species rich, and heavily impacted by human land use. Given the spatial complexity of overlapping threats and species' vulnerability along with limited conservation budgets, methods are needed for prioritizing areas for monitoring and management in these regions. We developed a multi-criteria Pareto ranking methodology for prioritizing spatial units for conservation and applied it to fire threat, habitat fragmentation threat, species richness, and genetic biodiversity criteria in San Diego County, California, USA. We summarized the criteria and Pareto ranking results (from west to east) within the maritime, coastal, transitional, inland climate zones within San Diego County. Fire threat increased from the maritime zone eastward to the transitional zone, then decreased in the mountainous inland climate zone. Number of fires and fire return interval departure were strongly negatively correlated. Fragmentation threats, particularly road density and development density, were highest in the maritime climate zone, declined towards the east, and were positively correlated. Species richness criteria showed distributions among climate zones similar to those of the fire threat variables. When using species richness and fire threat criteria, most lower-ranked (higher conservation priority) units occurred in the coastal and transitional zones. When considering genetic biodiversity, lower-ranked units occurred more often in the mountainous inland zone. With Pareto ranking, there is no need to select criteria weights as part of the decision-making process. However, negative correlations and larger numbers of criteria can result in more units assigned to the same rank. Pareto ranking is broadly applicable and can be used as a standalone decision analysis method or in conjunction with other methods