Data from: Ecological network inference from long-term presence-absence data
Ecological communities are characterized by complex networks of trophic and nontrophic interactions, which shape the dy-namics of the community. Machine learning and correlational methods are increasingly popular for inferring networks from co-occurrence and time series data, particularly in microbi...
| Main Authors: | , , |
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| Format: | Dataset |
| Language: | English |
| Published: |
Dryad
2018
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| Subjects: | |
| Online Access: | https://dx.doi.org/10.5061/dryad.8m11n http://datadryad.org/stash/dataset/doi:10.5061/dryad.8m11n |
| Summary: | Ecological communities are characterized by complex networks of trophic and nontrophic interactions, which shape the dy-namics of the community. Machine learning and correlational methods are increasingly popular for inferring networks from co-occurrence and time series data, particularly in microbial systems. In this study, we test the suitability of these methods for inferring ecological interactions by constructing networks using Dynamic Bayesian Networks, Lasso regression, and Pear-son’s correlation coefficient, then comparing the model networks to empirical trophic and nontrophic webs in two ecological systems. We find that although each model significantly replicates the structure of at least one empirical network, no model significantly predicts network structure in both systems, and no model is clearly superior to the others. We also find that networks inferred for the Tatoosh intertidal match the nontrophic network much more closely than the trophic one, possibly due to the challenges of identifying trophic interactions from presence-absence data. Our findings suggest that although these methods hold some promise for ecological network inference, presence-absence data does not provide enough signal for models to consistently identify interactions, and networks inferred from these data should be interpreted with caution. : Food web adjacency list for France river datasetAdjacency list representing all feeding interactions for the France river dataset, as identified by a literature review of gut content analyses. 'Parent' column represents the source of the interaction. 'Child' column represents the target of the interaction. 'Sign' represents the effect of the Parent species on the Child species. Since feeding interactions are +/-, each predator-prey pair will be represented by two rows: one for the negative effect of predator on prey, and one for the positive effect of prey on predator.Comte-adjlist.csvList of species for the France river network datasetComteSpNames-final.txtList of species for the Tatoosh middle intertidal datasettatoosh-control-exp-cv-spnames.txtPresence-Absence data for Tatoosh middle intertidalPresence-absence data for species in the Tatoosh middle intertidal (space-separated data frame). First column is a site identifier, second column is the census year, and all other columns are presence/absence for a species in a given site-year. Data for different sites are separated with a row of NAs.tatoosh-site-year-all.txtTrophic interaction adjacency list for Tatoosh data setOrganized as for the France adjacency list, but with trophic (feeding) interactions for the Tatoosh data set.tatoosh-trophic-adjlist.csvNontrophic interaction adjacency list for Tatoosh data setOrganized identically to the France adjacency list, but contains nontrophic (non-feeding) interactions for the Tatoosh data set.tatoosh-nontrophic-adjlist.csv |
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