3.4.2. Models’ outputs and performance evaluation
The environmental predictive models displayed high predictive power
according to the AUC values of 0.86, 0.93 and 0.84 for the species, Pop1
and Pop2, respectively (Table 3). These results suggest that the
predictions effectively captured relationships between environmental
variables and locations points of Pop1 comparing to Pop2 and the
species.
Based on the Minimum training presence (MTP), suitable areas for
Kersting’s groundnut and population groups were defined. We found that
current distributions were significantly different between populations
and species. The Maxent model for the species predicted a large area of
cultivable conditions across the three agroclimatic zones, Southern
Sudanian (SS), Northern Sudanian (NS) and Northern-Guinean (NG) (Fig.
6a1). The SS an NG zones were the areas forecasted to have high suitable
climatic conditions for the species production. For the Pop1, the areas
predicted to have high likely cultivability conditions were concentrated
in NG zone of Benin, but very less and sparsely distributed in SS zone
(Fig6b1). The Pop2 was projected across the three studied agroclimatic
zones of the four countries with highest cultivable areas in SS and NS
zones (Fig6c1).
Furthermore, the potential distribution maps under future (in 2055)
climatic conditions revealed varied patterns in KG and genetic
populations cultivable areas (Fig 6 and Fig 7, see supplemental
Figures).
Under the two future climatic scenarios RCP4.5 and RCP8.5, an increase
in the species cultivable areas for about 2.75%, were observed due to
the decrease of the non-suitable areas (Fig 6a2, a3, Fig 7). This areas
expansion was observed mainly in the NG zone of Southern Benin, also in
SS and NS zones of Burkina Faso, Ghana and Togo. Similarly, an increase
of the cultivability areas of Kersting’s groundnut was observed in the
SS zone of the Northern Benin. On the other hand, the SS zone of Central
Benin became climatically unsuitable to the crop production. The Pop1
showed to be more vulnerable to future scenarios as the suitable areas
slightly decreased (0.504 % under RCP4.5 and 0.779 % under RCP8.5),
while the unsuitable ranges increased (Fig 6b2, b3, Fig 7). The model of
this genetic group predicted an increase in the suitable areas of NG
zone of Benin, Ghana and Togo while a decrease was observed in the NS
and SS zone of the four countries. The potential cultivable areas of the
Pop2 (Fig 6c2, c3, Fig 7) slightly decreased by 0.322% under RCP4.5
while increased with extreme conditions of RCP8.5 (0.519%). The future
climatic conditions of the SS zone of Central Benin would constitute
constraints to this population cultivation. In contrast, the NG zone of
Southern Benin and Togo and the SS zone gained in cultivable areas for
Pop2.