Finding NEMO: nestedness engendered by mutualistic organisation in anemonefish and their hosts

The interaction structure of mutualistic relationships, in terms of relative specialization of the partners, is important to understanding their ecology and evolution. Analyses of the mutualistic interaction between anemonefish and their host sea anemones show that the relationship is highly nested in structure, generalist species interacting with one another and specialist species interacting mainly with generalists. This supports the hypothesis that the configuration of mutualistic interactions will tend towards nestedness. In this case, the structure of the interaction is at a much larger scale than previously hypothesized, across more than 180° of longitude and some 60° of latitude, probably owing to the pelagic dispersal capabilities of these species in a marine environment. Additionally, we found weak support for the hypothesis that geographically widespread species should be more generalized in their interactions than species with small ranges. This study extends understanding of the structure of mutualistic relationships into previously unexplored taxonomic and physical realms, and suggests how nestedness analysis can be applied to the conservation of obligate species interactions

Modeling habitat distribution from organism occurrences and environmental data: case study using anemonefishes and their sea anemone hosts

We demonstrate the KGSMapper (Kansas Geological Survey Mapper), a straightforward, web-based biogeographic tool that uses environmental conditions of places where members\ud of a taxon are known to occur to find other places containing suitable habitat for them. Using occurrence data for anemonefishes or their host sea anemones, and data for environmental parameters, we generated maps of suitable habitat for the organisms. The fact that the fishes are obligate symbionts of the anemones allowed us to validate the KGSMapper output: we were able to compare the inferred\ud occurrence of the organism to that of the actual occurrence of its symbiont. Characterizing suitable habitat for these organisms in the Indo-West Pacific, the region where they naturally occur, can be used to guide conservation efforts, field work, etc.; defining suitable habitat for them in the Atlantic and eastern Pacific is relevant to identifying areas vulnerable to biological invasions. We advocate\ud distinguishing between these 2 sorts of model output, terming the former maps of realized habitat and the latter maps of potential habitat. Creation of a niche model requires adding biotic data to the environmental data used for habitat maps: we included data on fish occurrences to infer anemone distribution and vice versa. Altering the selection of environmental variables allowed us to investigate which variables may exert the most influence on organism distribution. Adding variables does not necessarily improve precision of the model output. KGSMapper output distinguishes areas that fall within 1 standard deviation (SD) of the mean environmental variable values for places where members of the taxon occur, within 2 SD, and within the entire range of values; eliminating outliers or data known to be imprecise or inaccurate improved output precision mainly in the 2 SD range and\ud beyond. Thus, KGSMapper is robust in the face of questionable data, offering the user a way to recognize\ud and clean such data. It also functions well with sparse datasets. These features make it useful for biogeographic meta-analyses with the diverse, distributed datasets that are typical for marine organisms lacking direct commercial value