Table A1 Population dynamics models fitted to time series of C. venustus (1990-2007).
Estimated parameters 2 Log Models for Calomys venustus R AICc ΔAICc Likelihood wi wi/wj k (likelihood) a b c d f
A Rt=b-exp(a×Cvt-1+c)+d×mediaspr 0.11 1.7 1.80** 0.337. 0.63 33.543 0.000 1.000 0.189 1.000 -13.608 4
B Rt=b-exp(a×Cvt-1+c+d×sumRain)+f×mediaspr 0.11. 1.7 1.90** -0.0003 0.34 0.71 33.565 0.021 0.989 0.187 1.011 -9.060 5
C Rt=b-exp(a×Cvt-1+c)+d×sumRain 0.46** 1.7 -0.36 0.0027. 0.61 34.503 0.960 0.619 0.117 1.616 -11.587 4
D Rt=b-exp(a×Cvt-1+c) 0.63** 1.7 -1.28* 0.49 35.506 1.963 0.375 0.071 2.668 -13.833 3
E Rt=b-exp(a×Cvt-1+c+d×(sprRain+sumRain)+f×mediaspr) 0.55** 1.7 4.42. -0.0011117. -0.24* 0.68 35.585 2.041 0.360 0.068 2.775 -10.063 5
F Rt=b-exp(a×Cvt-1+c)+d×(sprRain+sumRain) 0.41* 1.7 -0.13 0.0016 0.58 35.703 2.160 0.340 0.064 2.945 -12.186 4
G Rt=b-exp(a×Cvt-1+c+d×NDVIminanual)+f×mediaspr 0.11 1.7 2.01** -0.352 0.369. 0.65 36.681 3.138 0.208 0.039 4.801 -10.613 5
H Rt=b-exp(a×Cvt-1+c+d×sumRain) 0.68** 1.7 -1.03 -0.0012 0.56 36.793 3.250 0.197 0.037 5.078 -12.732 4
I Rt=b-exp(a×Cvt-1+c+d×sumRain+f×mediaspr) 0.59** 1.7 3.16 -0.0013497 -0.197. 0.65 36.875 3.331 0.189 0.036 5.289 -10.711 5
J Rt=b-exp(a×Cvt-1+c+d×sprRain)+f×mediaspr 0.09 1.7 1.95** -0.0001 0.36. 0.65 36.985 3.441 0.179 0.034 5.588 -10.768 5
K Rt=b-exp(a×Cvt-1+c+d×(sprRain+sumRain)) 0.65** 1.7 -0.87 -0.00069 0.54 37.423 3.880 0.144 0.027 6.959 -13.043 4
L Rt=b-exp(a×Cvt-1+c)+d×sprRain+f×sumRain 0.43* 1.7 -0.21 0.00053 0.00269 0.61 38.445 4.901 0.086 0.016 11.595 -11.499 5
M Rt=b-exp(a×Cvt-1+c+d×sprRain)+f×sumRain 0.46** 1.7 -0.3 -0.00016 0.0027 0.61 38.535 4.991 0.082 0.016 12.129 -11.540 5
N Rt=b-exp(a×Cvt-1+c)+d×winTmin 0.71* 1.7 -1.62 0.047 0.51 38.553 5.010 0.082 0.015 12.244 -13.608 4
O Rt=b-exp(a×Cvt-1+c)+d×sprRain 0.55* 1.7 -0.89 0.0008 0.5 38.643 5.100 0.078 0.015 12.807 -13.656 4
P Rt=b-exp(a×Cvt-1+c+d×sprRain+f×mediaspr) 0.50* 1.7 3.95 -0.001096 -0.229. 0.61 38.765 5.221 0.073 0.014 13.607 -11.657 5
Q Rt=b-exp(a×Cvt-1+c+d×sprRain) 0.62** 1.7 -1.16 -0.0003 0.5 38.873 5.330 0.070 0.013 14.368 -13.772 4
R Rt=b-exp(a×Cvt-1+c+d×NDVIminanual+f×mediaspr) 0.54* 1.7 3.81 -2.141 -0.211 0.60 39.046 5.502 0.064 0.012 15.660 -11.796 5
S Rt=b-exp(a×Cvt-1+c+d×NDVIminanual+f×sumRain) 0.69** 1.7 -0.62 -1.394 -0.001 0.57 40.431 6.888 0.032 0.006 31.312 -12.488 5
T Rt=b-exp(a×Cvt-1+c+d×sumRain)+f×sprRain 0.58* 1.7 -0.63 -0.00103 0.00084 0.57 40.465 6.921 0.031 0.006 31.836 -12.504 5
U Rt=b-exp(a×Cvt-1+c+d×sumRain+f×winTmin) 0.68** 1.7 -1.14 -0.0011 -0.0224 0.57 40.475 6.931 0.031 0.006 31.996 -12.513 5
V Rt=b-exp(a×Cvt-1+c+d×sumRain)+f×winTmin 0.72* 1.7 -1.19 -0.00116 0.0247 0.56 40.775 7.231 0.027 0.005 37.174 -12.663 5
W Rt=b-exp(a×Cvt-1+c+d×sprRain+f×sumRain) 0.67** 1.7 -0.98 -0.00013 -0.0011 0.56 40.885 7.341 0.025 0.005 39.276 -12.718 5 a non-linearity coefficient, b maximum finite reproductive rate, c equilibrium point, d, e and f coefficients for different effects, R2 coefficient of determination, AICc Akaike information criterion corrected for small sample bias, ΔAICc differences in AICc, likelihood exp(-ΔAICc/2), wi
Akaike weights, wi/wj evidence ratios, k number of estimated parameters, Rt = ln(Nt) - ln(Nt-1) realized logarithmic per-capita population growth rate, Cvt-1 logarithmic abundance of C. venustus in t-1, sum summer, spr spring, win winter, Tmin minimum temperature, media mean temperature, NDVIminannual minimum annual NDVI, ** P <0.01, *P < 0.05, P < 0.1 Table A2 Population dynamics models fitted to A. azarae time series (1990-2007).
Estimated parameters 2 Log Models for Akodon azarae R AICc ΔAICc Likelihood wi wi/wj k ( likelihood) a b c d f
A.1 Rt=b-exp(a×Aat-1+c)+d×NDVIminanual 2.3772. -1.5827* -8.6174. 6.7000** 0.76 10.535 0.000 1.000 0.646 1.000 2.460 5
B.1 Rt=b-exp(a×Aat-1+c+d×sprRain+sumRain))+f×NDVIminanual 1.7018 -1.3565* -5.4979 -0.0009 6.3833** 0.78 13.970 3.435 0.180 0.116 5.570 3.215 6
C.1 Rt=b-exp(a×Aat-1+c+d×NDVIminanual) 1.1071 0.9340 -1.7532 -6.2628 0.69 14.537 4.001 0.135 0.087 7.394 0.459 5
D.1 Rt=b-exp(a×Aat-1+c+d×sprRain+sumRain)+f×NDVIminanual) 0.3928 2.2411 0.6540 -0.0005 -2.5964 0.76 15.070 4.535 0.104 0.067 9.655 2.665 6
E.1 Rt=b-exp(a×Aat-1+c+d×sprRain)+f×NDVIminanual 2.3867. -1.5405* -8.5781 -0.0003 6.5527** 0.76 15.389 4.853 0.088 0.057 11.321 2.506 6
F.1 Rt=b-exp(a×Aat-1+c) 3.6090 0.3079 -13.4200 0.47 19.844 9.308 0.010 0.006 105.016 -4.255 4
G.1 Rt=b-exp(a×Aat-1+c)+d×sprRain+sumRain) 3.1849 -0.4130 -11.9529 0.0011 0.57 20.420 9.884 0.007 0.005 140.061 -2.483 5
H.1 Rt=b-exp(a×Aat-1+c)+d×NDVImedanual 5.6775 -2.3810 -21.1665 5.2198 0.55 21.197 10.662 0.005 0.003 206.625 -2.871 5
I.1 Rt=b-exp(a×Aat-1+c)+d×sprRain 4.5052 -0.1736 -16.7778 0.0013 0.54 21.331 10.795 0.005 0.003 220.900 -2.938 5
J.1 Rt=b-exp(a×Aat-1+c)+d×mediaspr 6.7987 3.2789 -25.1549 -0.1552 0.52 22.148 11.612 0.003 0.002 332.336 -3.347 5
K.1 Rt=b-exp(a×Aat-1+c+d×sprRain) 3.2057 0.3360 -11.2707 -0.0021 0.51 22.608 12.072 0.002 0.002 418.257 -3.577 5
L.1 Rt=b-exp(a×Aat-1+c+d×NDVImedanual) 2.8365 0.3637 -8.1409 -4.9337 0.50 22.745 12.209 0.002 0.001 447.926 -3.645 5
M.1 Rt=b-exp(a×Aat-1+c)+d×sumRain 2.8489 0.0792 -10.6405 0.0008 0.49 23.066 12.531 0.002 0.001 526.000 -3.806 5
N.1 Rt=b-exp(a×Aat-1+c)+d×winTmin 4.0558 0.4053 -15.1443 0.0350 0.49 23.292 12.757 0.002 0.001 588.968 -3.919 5
O.1 Rt=b-exp(a×Aat-1+c+d×sumRain) 3.9025 0.2937 -14.6197 0.0004 0.47 23.953 13.417 0.001 0.001 819.538 -4.249 5
P.1 Rt=b-exp(a×Aat-1+c)+d×sprRain+f×sumRain 3.7447 -0.4378 -14.0249 0.0014 0.0008 0.57 25.146 14.611 0.001 0.000 1488.230 -2.373 6
Q.1 Rt=b-exp(a×Aat-1+c+d×sprRain)+e×mediaspr 7.0751 3.5131 -25.3443 -0.0027 -0.1672 0.56 25.531 14.995 0.001 0.000 1803.788 -2.565 6
R.1 Rt=b-exp(a×Aat-1+c+d×sprRain)+f×sumRain 2.2208 0.0639 -7.5940 -0.0023 0.0011 0.55 25.900 15.365 0.000 0.000 2169.778 -2.750 6
S.1 Rt=b-exp(a×Aat-1+c+d×sumRain)+f×sprRain 3.8267 -0.1953 -13.8526 -0.0015 0.0015 0.55 26.066 15.531 0.000 0.000 2357.668 -2.833 6
T.1 Rt=b-exp(a×Aat-1+c+d×sumRain)+f×mediaspr 8.6368 3.8129 -33.0079 0.0038 -0.1831 0.54 26.477 15.942 0.000 0.000 2895.591 -3.039 6
U.1 Rt=b-exp(a×Aat-1+c+d×sprRain+f×mediaspr) 3.4601 0.3413 -16.0979 -0.0020 0.1994 0.53 26.794 16.259 0.000 0.000 3392.293 -3.197 6
V.1 Rt=b-exp(a×Aat-1+c+d×sprRain)+f×winTmin 3.2974 0.4426 -11.6106 -0.0024 0.0334 0.53 26.879 16.343 0.000 0.000 3538.940 -3.239 6
W.1 Rt=b-exp(a×Aat-1+c+d×sprRain+f×sumRain) 2.3809 0.4084 -7.8384 -0.0021 -0.0013 0.52 27.283 16.747 0.000 0.000 4331.144 -3.441 6
X.1 Rt=b-exp(a×Aat-1+c+d×sprRain+f×winTmin) 3.9403 0.3003 -13.5902 -0.0022 0.0783 0.51 27.377 16.842 0.000 0.000 4540.682 -3.489 6 a non-linearity coefficient, b maximum finite reproductive rate, c equilibrium point, d and f coefficients for different effects, R2 coefficient of
determination, AICc Akaike information criterion corrected for small sample bias, ΔAICc differences in AICc, likelihood exp(-ΔAICc/2), wi Akaike weights, wi/wj evidence ratios, k number of estimated parameters, Rt = ln(Nt) - ln(Nt-1) realized logarithmic per-capita population growth rate, Aat-1 logarithmic abundance of A. azarae in t-1, sum summer, spr spring, win winter, Tmin minimum temperature, media mean temperature,
NDVIminannual minimum annual NDVI, NDVImedannual mean annual NDVI, ** P < 0.01, *P < 0.05, P < 0.1 Table A3 Population dynamics models fitted to A. azarae time series (1990-2007, 4 points removed).
Estimated parameters 2 Log Models for Akodon azarae R AICc ΔAICc Likelihood wi wi/wj k a b c d f ( likelihood) A.2 Rt =b-exp(a×Aat-1+c) 2.98 * 0.63 ** -10.77 * 0.87 1.63 0 1 0.273 1 5.68643 4 B.2 Rt=b-exp(a×Aat-1+c+d×sprRain) 3.05** 0.62** -10.64* -0.0013 0.91 2.411 0.7814 0.6765734 0.185 1.478 8.082232 5
C.2 Rt=b-exp(a×Aat-1+c)+d×sprRain 3.64 * 0.21 -13.28* 0.000988. 0.91 2.611 0.9814 0.612189 0.167 1.6335 7.982075 5 D.2 Rt=b-exp(a×Aat-1+c+d×(sprRain+sumRain)) 2.96* 0.61** -9.93* -0.0013 0.9 3.311 1.6814 0.4314023 0.118 2.318 7.632407 5
E.2 Rt=b-exp(a×Aat-1)+c+d×(sprRain+sumRain) 3.50* 0.054 -12.83* 0.0007 0.9 3.711 2.0814 0.3532023 0.096 2.8312 7.430642 5
F.2 Rt=b-exp(a×Aat-1+c)+d×mediaspr 3.42* 2.09 -12.40* -0.076 0.88 5.691 4.0614 0.1312417 0.036 7.6195 6.442932 5
G.2 Rt=b-exp(a×Aat-1+c+d×sprRain)+e×mediaspr 3.59** 2.33. -12.59* -0.0014. -0.089 0.93 6.75 5.12 0.0773047 0.021 12.936 9.625613 6
H.2 Rt=b-exp(a×Aat-1+c+d×sumRain) 3.29* 0.61** -12.15* 0.000737 0.87 6.751 5.1214 0.0772495 0.021 12.945 5.909759 5
I.2 Rt=b-exp(a×Aat-1+c)+d×winTmin 2.83* 0.62* -10.16. -0.01 0.87 7.081 5.4514 0.0654994 0.018 15.267 5.748096 5
J.2 Rt=b-exp(a×Aat-1+c)+d×sumRain 2.98 * 0.57 -10.79 * 0.000151 0.87 7.131 5.5014 0.0638822 0.017 15.654 5.722554 5
K.2 Rt=b-exp(a×Aat-1+c+d×sprRain+e×mediaspr) 3.55* 0.58** -14.61* -0.0014. 0.1 0.92 7.71 6.08 0.0478349 0.013 20.905 9.147052 6
L.2 Rt=b-exp(a×Aat-1+c+d×sprRain+e×winTmin) 3.25* 0.61** -11.14* -0.00137 0.047 0.91 8.88 7.25 0.0266491 0.007 37.525 8.560116 6
M.2 Rt=b-exp(a×Aat-1+c+d×sprRain)+e×sumRain 3.11* 0.44 -10.85* -0.0015 0.00043 0.91 9 7.37 0.0250972 0.007 39.845 8.503316 6
N.2 Rt=b-exp(a×Aat-1+c+d×sprRain)+e×winTmin 2.90* 0.60** -10.08* -0.001 -0.016 0.91 9.56 7.93 0.018968 0.005 52.72 8.223262 6
O.2 Rt=b-exp(a×Aat-1+c+d×sprRain+e×sumRain) 2.98* 0.62** -10.26* -0.0014 0.00042 0.91 9.66 8.03 0.018043 0.005 55.423 8.172857 6
P.2 Rt=b-exp(a×Aat-1+c)+d×sprRain+e×sumRain 3.69* 0.085 -13.51* 0.0010. 0.00028 0.91 9.68 8.05 0.0178634 0.005 55.98 8.164143 6
Q.2 Rt=b-exp(a×Aat-1+c+d×sumRain)+e×sprRain 3.62* 0.2 -13.20* -0.0001 0.001 0.91 10.03 8.4 0.0149956 0.004 66.686 7.98643 6
R.2 Rt=b-exp(a×Aat-1+c+d×sumRain)+e×mediaspr 4.08* 2.38 -15.22* 0.0012 -0.093 0.89 12.04 10.41 0.0054891 0.001 182.18 6.984965 6 a non-linearity coefficient, b maximum finite reproductive rate, c equilibrium point, d and f coefficients for different effects, R2 coefficient of determination, AICc Akaike information criterion corrected for small sample bias, ΔAICc differences in AICc, likelihood exp(-ΔAICc/2), wi
Akaike weights, wi/wj evidence ratios, k number of estimated parameters, Rt=ln(Nt)-ln(Nt-1) realized logarithmic per-capita population growth rate, Aat-1 logarithmic abundance of A. azarae in t-1, sum summer, spr spring, win winter, Tmin minimum temperature, media mean temperature,
** P<0.01, *P< 0.05, P<0.1