PMC7416927_01
Multiple machine-learning regression workflow (see Materials and methods).. Regression 1 includes only isotope data, dietary choices, demographic variables (S1 Table); regression 2 includes isotope data, dietary choices, demographic variables, and latitude/longitude; and regression 3 includes isotope data, dietary choices, demographic variables, and environmental covariates (Table 1).
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A series of random forest regression models were developed for each isotopic system incrementally testing the potential of different predictors to explain isotopic variability (Fig 1). We then used the selected significant predictors and VSURF to develop a random forest regression model for each isotopic system (Regression 1 in Fig 1). Last, we used the selected significant geographic, dietary choices and demographics predictors within VSURF to develop a random forest regression model for each isotopic system (Regression 2 in Fig 1). Last, we used the selected significant environmental, geographic, dietary choice and demographics predictors within VSURF to develop a random forest regression model for each isotopic system (Regression 3 in Fig 1).
Pearson correlation coefficient between isotopic data in hair and the continuous dietary choice, geographic and environmental variables.. Red and blue squares indicate significant positive or negative correlation (p-value<0.01) whereas crosses indicate no significant correlation (p-value>0.01).
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We then tested if significant relationships existed between these environmental variables and each isotopic system (Fig 3).
Semivariograms.. A. delta15Nhair variations; B. delta13Chair variations; C. delta34Shair variations. The x-axis distance represents the distance between pairs of observations. The blue points represents the average value of semivariance between point pairs for each 500km distance bin. The red lines represent theoretical semivariograms. Note the nugget value is approximately equal to the analytical precision of 0.2%, 0.2%, and 0.4% for delta15Nhair, delta13Chair, and delta34Shair values, respectively.
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Prior to testing correlations, we tested the presence of spatial autocorrelation in each isotopic dataset by calculating semivariograms (Fig 4).