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. 2022 Sep 21;8(38):eabm5952. doi: 10.1126/sciadv.abm5952

Table 2. Comparison of the stiffest eigenparameters θ^1, θ^2, and θ^3 (associated with the largest eigenvalues λ1, λ2, and λ3) considering a multivariate log-normal prior distribution for the parameters to fit the ecosystem model (table S1) to data (Fig. 3B).

Each θ^1, θ^2, and θ^3 is identified via Eq. 8 after obtaining eigenvalues (fig. S6) and eigenvectors from matrices H (or L), P, and G. Stiff eigenparameters from matrix H (or L) are obtained at two sets of best-fit parameter values θ1 and θ2 (fig. S5). Matrix H (or L) returns different stiff eigenparameters when evaluated at two distinct sets of best-fit parameter values, while matrices P and G return different stiff eigenparameters because the prior influences the model-data fit.

Eigenparameter θ^i Sensitivity matrices
H or L evaluated at P G
θ1 θ2
1 (cN/aN)(aM/cM)0.4 (cM/aM)(aN/cN)0.9 aP0.9/cP (cM/aM)(aN/cN)0.9
2 (cM/aM)(cN/aN)0.4 (cN/aN)(cM/aM)0.9 cN/aN (cN/aN)(cM/aM)0.9
3 cP/(aP0.9dN0.4) cP/aP0.9 cM/aM cP/aP0.9