Topological and biomass balance approaches to analyzing food webs of Bahía Magdalena, Baja California Sur, Mexico

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.