## 4 Discussion
### RS Variables Across Sampled Sites  
The set of remote sensing variables selected through Variance Inflation Factor (VIF) analysis serves as reliable surrogates for key ecological aspects in subtropical semi-arid ecosystems. The Brightness Index (BI\({}_{2}\)), a strong proxy for bare soil (Escafadal), can indicate varying levels of forest cover and degradation [83]. The Modified Chlorophylll Absorption in Reflectance Index (MCARI\({}_{\text{Sent}}\); [84]), which reflects leaf chlorophyll content, may help distinguish herbaceous vegetation--characterized by short-term productivity peaks during the vegetative period--from woody vegetation, which retains its leaves for longer periods [85; 86]. The Normalized Difference Water Index (NDWI\({}_{\text{Gao}}\); Gao), an indicator of leaf water content, can capture the seasonal behavior of species with different drought adaptations [37; 40]. The effectiveness of each ecological spectral index (BI\({}_{2}\), MCARI\({}_{\text{Sent}}\), and NDWI\({}_{\text{Gao}}\)) in differentiating various forest conservation and management categories in the Arid Chaco region varies across temporal periods and months (Figure 4). Our results underscore the effectiveness of the Brightness Index (BI\({}_{2}\)) in capturing vegetation phenology differences among forest classes with varying levels of resource utilization and extraction. In particular, BI\({}_{2}\) proved highly effective in differentiating savannas (CL 7) and grasslands with trees (CL 8), primarily used for intensified livestock raising, from formations with greater woody cover. Open formations, almost exclusively used for pastoral activities, exhibited significantly higher BI\({}_{2}\) values throughout the year, reflecting the prominence of bare soil surfaces. In contrast, natural formations with higher woody plant cover, such as mature forests on foothills and plains (CL 1-2), high forests (CL 3-4), and low forests and scrollands, all managed for multifunctional purposes such as timber extraction, grazing, aromatic herb collection, natural medicine production, and nature-based tourism [46], displayed significantly lower BI\({}_{2}\) values. These findings align with previous research conducted in the Chaco region and other semi-arid areas [37; 83; 87; 88]. Although the application of the BI\({}_{2}\) index may have limitations in densely vegetated areas with closed canopies due to reduced bare soil visibility [37], it remains a valuable tool for monitoring dry forest lands, which cover over 10% of the world's forest area [89]. Despite these challenges, integrating the Brightness Index (BI\({}_{2}\)) with other remote sensing variables has proven to be a reliable approach for distinguishing vegetation formations with different structures and levels of use in arid and semi-arid regions. Indeed, areas with high BI\({}_{2}\) values correspond to forests that have undergone significant modifications in structure and species composition. This observation is corroborated by the Structural Alteration Index (_SAI_) calculated for the analyzed sites, particularly in areas subjected to intensive livestock use (e.g., CL 6-8, Table 1). The Modified Chlorophylll Absorption in Reflectance Index (MCARI\({}_{\text{Sent}}\)), which reflects leaf chlorophyll content, effectively differentiates vegetation formations with varying  
Figure 4: Temporal variability in the effectiveness of spectral indices (BI\({}_{2}\), MCARI\({}_{\text{Sent}}\), NDWI\({}_{\text{Gao}}\)) in differentiating conservation and management categories of forests in the Arid Chaco. Wet (<70 mm) and dry (>70 mm) months, along with temperature levels (high: >25 \({}^{\circ}\)C, intermediate: 15–25 \({}^{\circ}\)C, low: <15 \({}^{\circ}\)C), are reported to capture seasonal forest dynamics. management regimes and conservation statuses (CL in Table 1). MCARI\({}_{\text{sent}}\) values were significantly higher in savannas (CL 7) and grasslands with trees (CL 8), which are characterized by leaf renewal and productivity peaks during the summer.