In recent years, forest fires have become an important issue in Central Europe. To model the probability of the occurrence of forest fires in the Lower Silesian Voivodeship of Poland, historical fire data and several types of predictors were collected or generated, including topographic, vegetation, climatic, and anthropogenic features. The main objectives of this study were to determine the importance of the predictors of forest fire occurrence and to map the probability of forest fire occurrence. The H2O driverless artificial intelligence (DAI) cloud platform was used to model forest fire probability. The gradient boosted machine (GBM) and random forest (RF) methods were applied to assess the probability of forest fire occurrence. Evaluation the importance of the variables was performed using the H2O platform permutation method. The most important variables were the presence of coniferous forest and the distance to agricultural land according to the GBM and RF methods, respectively. Model validation was conducted using receiver operating characteristic (ROC) analysis. The areas under the curve (AUCs) of the ROC plots from the GBM and RF models were 83.3% and 81.3%, respectively. Based on the results obtained, the GBM model can be recommended for the mapping of forest fire occurrence in the study area.

Differing levels of humidity, sunlight exposure or temperature in different areas of mountain ranges are fundamental to the existence of particular vegetation types. A better understanding of even local variability of trees may bring significant benefits, not only economic, but most of all, nature-related. The main focus of this study was the analysis of relationships between increment in stand height, age and the natural topography in the examined area. Among others, the following were examined with regard to their influence on the growing process: age, altitude above sea level (m a.s.l.), aspect and slope, topographic wetness index (TWI), and topographic position index (TPI) generated from an airborne laser scanning (ALS)-derived elevation model. To precisely calculate forest growth dynamics in mountain conditions for different spruce stands, repeated airborne lidar measurements from 2007 and 2012 were used (with resolution respectively 4 and 6 pts./m²). Detailed information on every stand including species composition, share of individual species, as well as their age, were acquired from the State Forests IT System (SILP). It was proven in this study, that environmental and topographic variables may have an impact on forest growth dynamics on even closely located areas. Apart from the age, the greatest influence on tree growth has an altitude above sea level, aspect and slope. The highest height increment of spruce was observed in the stands of up to 30 years old, those that had grown at an altitude under 850 m a.s.l., on the slopes up to 15 degrees or on those which were on the northeastern exposure. The results obtained show that the physiology of species, even those that are well known, largely depends on local topographic conditions. The proven impact of different topography factors on the growth of spruce may be used while planning economic activities in precision forestry. Additional research with using multiple laser scanning in the context of other regions or other species may bring us better recognition of local growth conditions and in consequence, significantly better planning and higher revenues obtained from the sale of trees.

Mountain forests constitute one of the most diverse ecosystems, not only in Europe but also all over the world. Mountain ranges, which frequently encompass multiple countries, constitute a unique link between various natural areas, which are very often completely different from the historical point, or which are characterized by different use and management types. Although the role of mountain forests is relatively well recognized nowadays, in the distant past, these areas were poorly penetrated, mainly due to the unfavourable climate and natural topography, which discouraged not only from settling down but also from moving around. Despite the fact that mountains had been the object of interest of mining, weaving, and glassmaking industries for hundreds of years, dramatic changes in the stands in these areas were sealed by the industrial revolution in the 18th and 19th centuries. The purpose of this paper is the analysis of forest dieback process in the mountain ranges of Sudetes and Western Carpathians placed in Poland. Stress factors have been divided into three main groups, however, it should be remembered that it is a very simplified division and some factors could be partially found in the anthropogenic, as well as biotic, and even abiotic factor groups. Neither the beginning nor the end of deforestation process was defined precisely in the study, which was deliberate in taking into account constant changes in the ecosystems. Generally, three periods may be distinguished here, regarding the spruce forests dieback process. Typically anthropogenic deforestation, caused by the industrialization of the areas during the industrial revolution and earlier, deforestation in the years 1970–1980 and partially before the year 2000 (Western Carpathians) caused by a set of various stress factors and the latest period, that is, generally understood climate change. The last several years have particularly contributed to the expansion of detailed knowledge about the dependencies and the influence of abiotic, biotic, and anthropogenic factors on the health condition of spruce trees. Although models have already been developed, which describe the course of insect outbreaks, the growth and health condition of spruces, or climate factors, no model has been developed so far that would allow to depict the process of hitherto deforestation, and to enable modelling the forthcoming changes. It seems that the development of such tool, not only from the forest management point of view, would constitute a milestone on the way to precision forestry.

Spruce stands in the mountains of Central Europe are particularly valuable, not only because of their natural and scenic values but also because of their role in the protection of watersheds and soil. Over the past decades, these stands were frequently exposed to massive deforestation caused by various biotic, abiotic and anthropogenic factors. The current health condition of spruce stands in the Eastern Sudetes shows that the next phase of deterioration of these stands has begun. Bearing in mind past experiences and the current situation in these mountain areas, it is particularly important to understand the processes and factors that may short-term (2012–2016) spruce health analyses based on the normalized difference red-edge index and RapidEye satellite imagery, which is being delivered annually. Aided by remote sensing data and Boosted Regression Trees, it was possible to determine the topographic and tree stand features having the greatest impact on the vitality of spruce in all analyzed areas during 2012–2016. As the results show, the highest impact on the value of the normalized difference red-edge index indicator comes from a height above sea level, age of stands, terrain slopes, and exposure. In various areas, these factors may affect the vitality of spruce to varying degrees but not always in the same way. Our models accurately explained 74–81% of the randomly selected input data (predicted 72–80% of the excluded data) for site A, 50–58% for site B (48–57% for tested data) and 54–70% for site C (52–69% for excluded data).

The increase in the deer population observed in recent decades has strongly impacted forest regeneration and the forest itself. The reduction in the quality of raw wood material, as a consequence of deer-mediated damage, constitutes a significant burden on forest owners. The basis for the commencement of preventive actions in this setting is the understanding of the populations and behaviors of deer in their natural environment. Although multiple studies have been carried out regarding this subject, only a few suggested topography as an important factor that may influence the distribution and intensity of deer-mediated damage. The detailed terrain models based on LiDAR data as well as the data on damage caused by deer from the State Forests database enabled thorough analyses of the distribution and intensity of damage in relation to land form in this study. These analyses were performed on three mountain regions in Poland: the Western Sudety Mountains, the Eastern Sudety Mountains, and the Beskidy Mountains. Even though these three regions are located several dozen to several hundred kilometers apart from each other, not all evaluated factors appeared common among them, and therefore, these regions have been analyzed separately. The obtained results indicated that the forest damage caused by deer increased with increasing altitude above 1000 m ASL. However, much larger areas of damage by deer were observed at elevations ranging from 401 to 1000 m ASL than at elevations below 400 m ASL. Moreover, the locations of damage (forest thickets and old stands) indicated that red deer is the species that exerts the strongest pressure on forest ecosystems. Our results show the importance of deer foraging behavior to the structure of the environment.

In the 1980s, the Western Sudety Mountains were affected by a forest dieback process, resulting in large-scale deforestation covering an area of about 15,000 ha. A similar phenomenon is presently being observed in the Western Beskidy and Eastern Sudety Mountains, where the course of the process and the final effects are similar. The presented study analyzed the relationships between forest dieback processes today and in the past. Among others, the impact of the following factors was examined: exposure, slope, altitude, and topographic index, which was generated based on the airborne LIDAR (also airborne laser scanning abbreviated as ALS) data. The identification of forest dieback areas in the past was carried out based on the archived Landsat satellite imagery, as well as data obtained from the Polish State Forests. The identification of forest dieback areas at present was carried out based on the ALS data (single-tree detection approach) and color infrared aerial images. In the study, inter-dependencies between forest dieback today and in the past were compared. The performed analyses show significant differences between forests’ dieback specifics in all three areas. The process first occurred at 800–900 m a.s.l., and afterwards at over 900 m. Mortality was especially intensive on the western and southwestern slopes. Below 700 m a.s.l., forests survived quite well. In the 1980s, significantly higher concentrations of hazardous chemical compounds were noted, which resulted in respectively greater deforestations on aspects open to the operation of prevailing winds (mainly west). Nowadays, a proportionately higher number of trees die on the southern aspects, which is particularly visible in the Western Sudety Mountains.