Search Results

You are looking at 1 - 2 of 2 items for

  • Author or Editor: A. F. Navia x
  • All content x
Clear All Modify Search
Community Ecology
Authors: V. H. Cruz-Escalona, A. F. Navia, P. A. Mejia-Falla, M. V. Morales-Zárate, and C. A. Salinas-Zavala

In this paper, we used two methodological approaches to analyze the structure and function of a trophic web in the temperate coastal lagoon of Bahía Magdalena, Baja California Sur, Mexico, which represents the largest wetland ecosystem along the west coast of the Baja California peninsula. Ecosystem structure was studied using a topological approach, while ecosystem functioning was analyzed using a biomass balance model. Connectance values indicated a low number of functional group interactions, consistent with the range proposed for similar marine trophic webs. This pattern may reflect incorporation of a few functional groups clustered along the trophic web. Results would vary if the model included more functional groups or different levels of aggregation, since aggregation and diversity strongly influence the base of the food web. Topological results suggest that trophic web structure depends primarily on lower and intermediate trophic level organisms like macrobenthic invertebrates, penaeid shrimp and marine turtles. Balance biomass model results suggest that trophic groups positioned on the first level most strongly support Bahía Magdalena trophic web functioning. In particular, the pelagic red crab (Pleurocondes planipes) transfers energy between basal and upper levels of the food web (a wasp-waist energy control). When compared to ecosystems at different latitudes, the results indicate that the Bahía Magdalena ecosystem is still in a developmental phase, wherein trophic web functioning depends largely on the balance between energy flows originating from primary producers and those originating from detrital pathways. While these results are preliminary, they demonstrate the potential of combined topological and biomass approaches in analyzing highly organized ecosystems. The combined approach can make both theoretical and empirical predictions about the functional response of real systems to structural changes, thus enhancing evidence-based methods for ecosystem management.

Restricted access
Community Ecology
Authors: R. Olmo Gilabert, A. F. Navia, G. De La Cruz-Agüero, J. C. Molinero, U. Sommer, and M. Scotti


Anthropic activities impact ecosystems worldwide thus contributing to the rapid erosion of biodiversity. The failure of traditional strategies targeting single species highlighted ecosystems as the most suitable scale to plan biodiversity management. Network analysis represents an ideal tool to model interactions in ecosystems and centrality indices have been extensively applied to quantify the structural and functional importance of species in food webs. However, many network studies fail in deciphering the ecological mechanisms that lead some species to occupy the most central positions in food webs. To address this question, we built a high-resolution food web of the Gulf of California and quantified species position using 15 centrality indices and the trophic level. We then modelled the values of each index as a function of traits and other attributes (e.g., habitat). We found that body size and mobility are the best predictors of indices that characterize species importance at local, meso- and global scale, especially in presence of data accounting for energy direction. This result extends previous findings that illustrated how a restricted set of traitaxes can predict whether two species interact in food webs. In particular, we show that traits can also help understanding the way species are affected by and mediate indirect effects. The traits allow focusing on the processes that shape the food web, rather than providing case-specific indications as the taxonomy-based approach. We suggest that future network studies should consider the traits to explicitly identify the causal relationships that link anthropic impacts to role changes of species in food webs.

Open access