Evironmental indicators are the elements required to plan sustainable forest management practices. This assessment was carried out based on indicators that are sensitive to management and changes in the soil, climate, and associated functions. This study aims at determining soil quality and climate that affect the production of signalgrass silvopasture system in mountain ecosystems. The survey-based study was conducted during dry and wet seasons in 2017-2018. We used stratified random sampling method. Stratification was based on site (agroforestry phase) and environment (season and year). Site nested on environment. Agroforestry phases consisted of initial phase (<50% of the shade intensity of the sun), intermediate phase (50-70% of the shade intensity of the sun), and advanced phase (>70% of the shade intensity of the sun). Seasons were divided into two, dry season (rainfall < 60 mm.month-1) and wet season (rainfall > 100 mm.month-1) and years were limited from 2017 to 2018. The observation was conducted on 30 environmental parameters and signalgrass productions. The data was analyzed using linear mixed models, analysis of variance (ANOVA), structural equation modelling (SEM), and stepwise regression. The study results indicate that the highest signalgrass production at the initial agroforestry phase was 4.50 tons.ha-1. There is a very significant decrease in signalgrass production at the intermediate agroforestry phase by 36.64 % and at the advanced agroforestry phase by 280.80 %, compared to the initial agroforestry phase. The signalgrass production was increased very significantly influenced by the increase in cation exchange capacity (CEC), soil organic carbon (SOC), air temperature (Tair), and wind speed (U2). In addition, it was also significantly influenced by available nitrate (NO3-). Signalgrass production can be improved by the assessment tools by improving CEC, NO3-, SOC, U2 , and Tair with routine organic matters application and annual pruning.