## 5 Discussion and Conclusions  
The ignition risk model generated in this work makes it possible to identify those sectors of the wildland urban interface zones with a higher probability of forest fire ignition. In turn, it tells us what characteristics of the study area make it more prone to ignition. Depending on their predictive capacity, two groups of variables allow us to understand why ignition is more probable in these sectors. The group of variables with the most significant predictive capacity includes the crop proportion, the distance to the nearest road, and the distance to the nearest city. These are variables of anthropogenic origin if we consider that they are associated with productive activities (crops) and urban characteristics (roads and cities). The second group of variables has a medium ability to predict ignition. Among these, we find variables of anthropogenic origin, such as the proportion of forest plantations and population density, and variables of natural origin, such as grasslands, scrubs, and exposure. The results coincide with previous studies that have verified the coincidence between forest fires' risk and high proportions of land use destined for crops [26]. In this regard, particular importance has been assigned to forest crops in the ignition of fires [22]. It has been shown that the uncontrolled growth of forest species increases the combustible material and the ignition risk [16; 22; 77; 78; 79]. On the other hand, it has been pointed out that replacing the native forest with homogeneous pine and eucalyptus plantations in the central-southern zone of Chile has led to a greater production of large-scale wildland fires [56]. Our results help confirm the strong influence of human activities on forest fire ignition [4; 10; 20; 24; 40]. As in our work, the proximity of ignition points to roads and human settlements are factors that previous studies highlight as risk factors [3]. The analysis of the WUI satellite images indicates that the territory's characteristics changed due to the scar from the 2017 megafire. The density of forest plantations is the most evident change. The images show that forest plantations are in the process of recovery. On the other hand, the urban infrastructure has recovered rapidly. This maintains the high levels of risk associated with the distance from roads and cities and population density. In particular, Santa Olga town reconstruction shows that the repair process focuses on restoring the urban infrastructure and improving the living conditions of the people affected by the fires. However, integrating the ignition risk prevalent in the Maule region into decisions is not evident. It is feasible to interpret that the lower number of ignitions observed in the 2019-2020 season is a consequence of the megafire scar. Variables associated with crops, scrubs, and grasslands decrease their influence on ignition, given that such combustible materials are less dense. However, it is crucial to remember that the risk of ignition will grow as forest crops recover. This information must be incorporated into the decisions adopted for the prevention and preparation of forest fires. Along with this, the authorities and communities must integrate into their decisions how climate change contributes to ignition probability. The decrease in rainfall, soil degradation, and heat waves are impacts of climate change related to the variables that the ignition risk model classifies with a strong and medium influence. Previous studies have confirmed that these impacts of climate change affect soil humidity, creating conditions for high flammability of combustible materials [4; 10; 11; 56]. The exposure of the land to sunlight is another climate change variable that our model associates with the ignition risk. According to [PERSON] (2021), in areas more exposed to sunlight, the vegetation loses humidity and becomes more flammable. The Maule region has been highly impacted by climate change. This condition is not expected to vary, at least in the short and medium term [60; 61; 80].