Table 1.
Predictors used in regression tree and random forest model building.
Figure 1.
Log-log plots of cumulative distribution of links per species.
(a) Oritani Marsh (unrestored), (b) Secaucus Marsh (0 year), (c) Harrier Marsh (10 year), and (d) Mill Creek Marsh. Cross marks represent observational data lines, and r2 values represent the fit to the data of the best simple models: power-law distribution (straight line), truncated power-law distribution (downward curved dashed line), or exponential distribution (downward curved solid line).
Table 2.
Summary of food web metrics for each of the estuarine food webs.
Figure 2.
The structure of the food web at Secaucus High School Marsh.
The marsh food web (a) without grouping, and (b) with species sorted according to their group affinity. The lines connect a consumer with a consumed species; the nodes represent species identified in Table S1. The grouping configuration is determined by [60], assessed using AIC, a configuration containing 15 groups was the best fit of the data. The grouping algorithm, seeks to partition the species into groups that make the density of connections within each sub-matrix maximal/minimal. Alternate group configurations are presented in Table S3.
Table 3.
Regression tree and random forest model results.