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. Author manuscript; available in PMC: 2019 Mar 1.
Published in final edited form as: Mar Environ Res. 2018 Jan 8;134:109–120. doi: 10.1016/j.marenvres.2018.01.003

Table 2.

Relationship between predictors and chemical indicators modeled using PLS regression.

Chemical Indicator r2 p Relationship(s)
Soil δ15N 0.80 <0.0001 More urban ~ high δ15N
Soil δ13C 0.37 <0.0001 More urban ~ more negative δ13C
Soil C:N ratio 0.44 <0.0001 No individual correlations p>0.10
Soil C:P ratio 0.29 <0.0001 Western Long Island ~ low CP ratios
Soil N:P ratio 0.32 <0.0001 No individual correlations p>0.10
Macrophyte δ15N 0.61 <0.0001 More urban ~ high δ15N
Macrophyte δ13C 0.56 <0.0001 More urban ~ more negative δ13C
Macrophyte C:N ratio 0.39 <0.0001 More urban ~ low CN ratio
Macrophyte C:P ratio 0.41 <0.0001 High barren land cover ~ high CP ratios Sewage inputs ~ low CP ratios
Macrophyte N:P ratio 0.27 0.0003 High shrub cover ~ high NP ratios Western Long Island ~ low NP ratios
Snail δ15N 0.62 <0.0001 More urban ~ high δ15N
Snail δ13C 0.36 <0.0001 High forest cover ~ more negative δ13C Low salinity ~ more negative δ13C
Fish δ15N 0.57 <0.0001 More urban ~ high δ15N
Fish δ13C 0.49 <0.0001 Low salinity ~ more negative δ13C