Mountain Forest Area Research Articles

Population status of Saurauia spp. in Slamet Mountain, Central Java

Saurauia is belong to Actinidiaceae family. Saurauia spreading naturally in several highlands in Indonesia including Slamet Mountain. Some species of Saurauia had been used as traditional medicines for diabetes, cancer, and cholesterol. The population of Saurauia in Indonesia has been greatly reduced. This study aims to determine its distribution, population size and population structure of Saurauia in Slamet Mountain forest area. It was conducted in 4 locations forest which are on different slopes on Slamet Mountain. Retrieval of population data by following existing track using a purposive sampling method. A measuring plot of 20x20 m2 was made at the location in which Saurauia spp. discovered. The result of this research found 636 individuals in 103 measuring plots. Which consists of 4 species of Saurauia i.e. S. nudiflora DC. (90 individuals), S. pendula Blume (382), S. microphylla de Vriese (145) and S. bracteosa DC. (19). S. microphylla and S. bracteosa are species included in IUCN red list with vulnerable status. Both species require more conservation efforts. The population structure of Saurauia found was dominated by the seedling phase around 45.91%, mature phase 36.01% and juvenile phase 18.08% with varying height and diameter.

Landslide detection in mountainous forest areas using polarimetry and interferometric coherence

The cloud-free, wide-swath, day-and-night observation capability of synthetic aperture radar (SAR) has an important role in rapid landslide monitoring to reduce economic and human losses. Although interferometric SAR (InSAR) analysis is widely used to monitor landslides, it is difficult to use that for rapid landslide detection in mountainous forest areas because of significant decorrelation. We combined polarimetric SAR (PolSAR), InSAR, and digital elevation model (DEM) analysis to detect landslides induced by the July 2017 Heavy Rain in Northern Kyushu and by the 2018 Hokkaido Eastern Iburi Earthquake. This study uses fully polarimetric L-band SAR data from the ALOS-2 PALSAR-2 satellite. The simple thresholding of polarimetric parameters (alpha angle and Pauli components) was found to be effective. The study also found that supervised classification using PolSAR, InSAR, and DEM parameters provided high accuracy, although this method should be used carefully because its accuracy depends on the geological characteristics of the training data. Regarding polarimetric configurations, at least dual-polarimetry (e.g., HH and HV) is required for landslide detection, and quad-polarimetry is recommended. These results demonstrate the feasibility of rapid landslide detection using L-band SAR images.

Estimations and uncertainty of biogenic volatile organic compound emission inventory in China for 2008–2018

Accurate biogenic volatile organic compound (BVOC) emission estimations are essential for developing effective air pollution control measures. Chinese BVOC emissions were calculated at a spatial resolution of 36 km × 36 km for 2008–2018 using the Model of Emissions of Gases and Aerosols from Nature. A statistical method was developed to obtain more accurate emission rates based on large numbers of observations from China and other countries. The most detailed and accurate vegetation investigations at high resolutions were used to determine the distributions of leaf biomass and coverage for 82 vegetation species and types. The results show that the national BVOCs emissions in China in 2018 were large, 58.89 Tg, with isoprene, monoterpene, sesquiterpene, and other VOCs accounting for 63.60%, 11.35%, 2.18%, and 22.87% of the emissions, respectively. Broadleaf trees exhibited the largest isoprene and total BVOC emissions. The biogenic emissions and compositions displayed strong seasonal variations, and isoprene was significantly more sensitive to seasonality. The emissions were concentrated in the Greater Khingan Mountain, Changbai Mountain, Qinling Mountain, southeast and southwest forest areas, and Hainan Province because of their larger distributions of broadleaf trees with higher emission potentials. During 2008–2018, BVOC emissions increased by 20.18% at an annual rate of 2.03%, and isoprene exhibited the greatest enhancement of 32.67%, which was primarily due to the increase in leaf biomass. The regions with the largest growth were distributed in the Greater Khingan and Changbai Mountains, and the Sichuan, Hunan, and Hubei Provinces, which was primarily the result of the substantial increase in volumes of trees with higher emission rates. The uncertainty of our estimates was evaluated by comparing the applied basal emission factors, vegetation coverages, meteorological data, and emission algorithms from previous studies, and it was estimated to be approximately −36.5–4.6%.

Regional Forest Mapping over Mountainous Areas in Northeast China Using Newly Identified Critical Temporal Features of Sentinel-1 Backscattering

Sentinel-1 provides an extraordinary opportunity to explore the temporal behavior of backscattering of C-band synthetic aperture radar (SAR) due to its unique capability of successive observations every 12 days. This study reported new findings on the critical temporal features of Sentinel-1 backscattering over mountainous forested areas in northeast China and their application in regional forest mapping. Two interesting phenomena were discovered through the analysis of 450 scenes of images acquired by Sentinel-1A or Sentinel-1B over an area of 318,898.62 km2. The first phenomenon was that the dates of the largest drops of backscattering coefficients over forest and non-forest plots were different during the transition from autumn to winter. The largest drop of non-forest plots occurred around the date of the minimum temperature decreasing below 0 °C, while that of forest plots occurred around the date of the maximum temperature decreasing below 0 °C. The second phenomenon was that at the dates where these two drops occurred, the magnitude of the drop was negatively correlated with the forest canopy coverage for the first date and positively correlated for the second date. Based on these two phenomena, two methods for the forest mapping, referred to as the direct method and the indirect method, were proposed using only three dates of Sentinel-1 images, i.e., Date1: before the minimum temperature decreased below 0 °C, Date2: after the minimum temperature decreased below 0 °C but before the maximum temperature decreased below 0 °C, and Date3: after the maximum temperature decreased below 0 °C. The results showed that the overall accuracy of the forest map produced by the direct method was 93.60%, while that by the indirect method was 93.80%. Their accuracies were comparable with those of forest maps derived from publicly released land cover maps, which was approximately 94.42% for the best one. This study proposed a new way to do large-scale forest mapping in annually frozen regions using as few Sentinel-1 SAR images as possible.

A framework for the predictive mapping of forest soil properties in mountain areas

The modelling of forest ecosystems is a broad scientific field, encompassing species distribution, dynamic forest succession, growth and disturbance, and biogeochemical cycles. Soil information is frequently required for a holistic and spatially explicit modelling approach. Information on soil properties at sufficient resolution to be incorporated in spatially distributed models is rare however, in particular for mountain forest areas that are poorly accessible and where the required sampling effort is high. In order to bridge this gap, we aim to develop a concept for predicting spatially continuous forest soil properties in mountain areas and substantiate it by comparing different statistical approaches to digital soil mapping, namely Random Forests and Generalized Additive Models. Therefore, we used field descriptions of 1653 legacy soil profiles from a forest area of 5130 km2 in Tyrol and modelled a variety of soil properties that are essential for the characterisation of forest sites with respect to tree growth. A set of 23 spatially explicit predictor variables, grouped according to geological substrate information, topography, climate, biotic variables, and time–space, were included in the concept and tested. There was a special focus on the predictive relevance of the newly developed geological substrate information, which includes lithogenetic units, lithological composition, and the multilayering of sediments. As a physical soil property, it was possible to predict the plant-available water storage capacity with a significant degree of accuracy, with r2 = 0.49–0.56, while for the biologically driven state variable organic humus layer thickness, r2 = 0.22–0.27 was achieved. For describing soil reaction, Ellenberg’s indicator value of vegetation turned out to be a suitable proxy for soil pH value, and was modelled with a high degree of predictive power with r2 = 0.75–0.77. All model results were verified by different evaluation methods, ranging from cross-validation to comparison with independent datasets, tests for spatial autocorrelation, and considering ecological soundness in variable selection. We were able to show that in addition to variables derived from Digital Terrain Models and climate information, the new type of detailed geological substrate information is the most relevant predictor and is promising for digital soil mapping in mountain areas. This finding was independent of the applied statistical approaches and both Generalized Additive Models and Random Forests showed comparable accuracy and proved to be appropriate for these tasks. In addition, we were able to support the modelling results by interpreting the predictors’ mode of action with regard to the underlying processes controlling soil properties.

The status of southern white-cheeked gibbon<i> (Nomascus siki) </i> in Truong Son key biodiversity area

The Southern white-cheeked crested gibbon, Nomascus siki, is an endemic primate to Vietnam and Laos, and has been identified as a nationally and globally endangered species (EN). However, little information is known on the status of the species in Vietnam generally and in the Truong Son key biodiversity area (Truong Son KBA) particularly. In order to explore the current status of the species in the Truong Son KBA, we conducted field surveys in 2018 and 2019. Analysis of the survey data shows 149 groups of gibbon in the 4 study areas. Combined with results of similar-techniqued survey in 2016 on the same species in Khe Nuoc Trong forest, we identified at least 252 gibbon groups and estimated 425 gibbon groups in the entire Truong Son KBA. These gibbon groups are mainly distributed in medium-rich evergreen closed forests in mountainous areas of the west Truong Son KBA, adjacent to the Vietnam-Laos border.

Assessing transformation scenarios from pure Norway spruce to mixed uneven-aged forests in mountain areas

Mixed mountain forests, primarily made up of Norway spruce (Picea abies (L.) Karst.), silver fir (Abies alba Mill.) and European beech (Fagus sylvatica L.), cover about 10 × 106 ha of submontane–subalpine altitudes in Europe. They provide invaluable ecosystem services, e.g. protection against avalanches, landslides or rockfall. However, pure Norway spruce stands have, since mediaeval times, been heavily promoted as productive stand types for salt works at sites naturally supporting mixed mountain forests. Damage to these secondary pure spruce stands has been steadily increasing in recent decades. Furthermore, due to their previous limitation due to low temperatures and a short growing season, forest ecosystems in higher elevations are expected to be strongly affected by climate warming. To address these problems, alternative management concepts are being intensively discussed. A possible option to improve the stability and resilience of the stand is the transformation from pure Norway spruce stands into site-appropriate, sustainable and stable mixed mountain forests. In this study, we have tested seven different transformation scenarios (e.g. slit, shelterwood and gap-coupes, strip clear-cutting, do-nothing) and their impact on five evaluation criteria (forest growth, economics, carbon sequestration, (stand) stability and biodiversity). As there are hardly any practical examples for some of the transformation scenarios available, we have used the forest growth simulator SILVA to assess whether the tested transformation scenarios differ in transformation success and to observe trade-offs between the criteria of evaluation. Of the investigated scenarios, we consider the ones with gap or slit-coupes with the most beneficial overall utility values for the portfolio of the five evaluation criteria. However, we showed with our results that it is possible, by means of several trajectories, to return destabilised forests to sustainable and stable systems. We showed that a transformation is realistic, even if sophisticated silvicultural concepts are not strictly pursued.

Fogwater deposition of radiocesium in the forested mountains of East Japan during the Fukushima Daiichi Nuclear Power Plant accident: A key process in regional radioactive contamination

Because of limited environmental monitoring data, the regional-scale impact of the deposition of fogwater radiologically contaminated by the Fukushima Daiichi Nuclear Power Plant (F1NPP) accident remains unclear. To redress this situation, we present an observational report of the radiocesium concentration in fogwater and its deposition in a Japanese forest during the early stages of the F1NPP accident (March 2011). The data were acquired by using a passive collector to capture fogwater above the forest canopy on a monthly basis. In addition, the radiocesium concentrations in monthly throughfall and stemflow were measured under the canopies of four tree species. The 137Cs activity concentration in fogwater during the observational period was 45.8 Bq L−1, which was twice as high as that present in bulk precipitation. The ratio of 137Cs in throughfall to that in bulk precipitation (TF/BP ratio) ranged from 1.0 to 2.5. The high TF/BP ratios may have been caused by the high radiocesium concentration in fogwater deposition. Based on this assumption, we assessed the TF/BP ratio according to the 137Cs activity concentrations of throughfall and bulk precipitation measured in various mountainous regions in East Japan. Our results reveal that the TF/BP ratio is high at some sites and that it increases with elevation. Sites with a high TF/BP ratio were almost entirely situated in areas of fogwater deposition, as predicted by an atmospheric dispersion model. In addition, sites with a high TF/BP ratio were above the cloud base at the time when plumes with high atmospheric 137Cs activity concentrations passed through the areas. Thus, these measurements of radiocesium in fogwater during the early stages of the F1NPP accident provide evidence that fogwater with high radioactive contamination was deposited in the forested mountain areas of East Japan. Given the major impact of fogwater deposition of radiocesium, its role should be considered carefully to better understand radiocesium cycling in forest ecosystems.

ANALYSING THE GROWTH CONDITION OF HAZEL MUSHROOM BASE ON THE DATE OF LANDSAT 8 AND THE PLATFORM OF ENVI

Abstract. Armillariella mellea mainly distributes in Changbai Mountain forest area, which is one of the few edible fungi that can be cultured artificially. It contains a variety of essential amino acids and vitamins for human body. Frequent consumption can strengthen the body immunity. It is of great significance to analyze the growth environment of Armillariella mellea by remote sensing technology for its growth prediction and artificial cultivation research. Based on ENVI software and Landsat 8 image, the surface temperature and soil moisture in Xiao Hinggan Mountains in August 2014 were retrieved by the method of atmospheric correction and TVDI, and the optimum growth environment of Armillariella mellea was analyzed. The results are as follows: 1) The optimum growth temperature of Armillariella mellea is 25–30 °C, and the soil moisture condition is 0.4–0.6. The Armillariella mellea mainly distributes in the north-central part of the study area. Combined with other growth environment information, the study area is generally suitable for the growth of Armillariella mellea; 2) we found the Armillariella mellea around the area of 83 samples of 100 samples which were choose to analyse. The accuracy is higher; 3) It is feasible to obtain the optimum growth environment of Hazelnut mushroom by remote sensing technology.

The main characteristics of slope and river runoff transformations under the conditions of degradation of natural complexes on the catchment

The article shows that conducting hydrological calculations in the basins of very small and small rivers and their catchments is associated with significant errors, which is accounted for not only by the drastic limitations of the observational materials, but is also due to significant slope and river runoff transformations depending on the impact of natural complexes degradation (plant communities, soil cover, etc.). In the meantime, it should be noted that the emergence of a number of adverse processes, such as the propagation of erosion and channel processes, floods, environmental and economic damage inflicted on natural and economic systems, etc. is largely associated with the slope and river runoff transformations. This predetermines the necessity of investigating the processes in question. Given the above-mentioned, the article serves to reflect the results of research conducted within the mountain forest area of the Southern Urals and the Cis-Urals by the academic staff of the Department of hydrometeorology and geoecology of the Bashkir state university from 1955 to 2012. The main factors contributing to the increased maximum water discharge during the spring flood are confined to an increase in the modules of runoff coefficients as the scale of anthropogenic load on natural complexes increases, and, consequently, to a decrease in the natural water-regulating capacity of the catchments. The above-mentioned processes have resulted in the increasing maximum values of slope and river runoff and account for the adverse effects observed in the natural, economic and ecological systems.

Eigenvalue-Based Approaches for Solving an Ill-Posed Problem Arising in Sensor Orientation

Sensor orientation is an essential step for georeferencing of images, establishing the coordinate transformation between the image and ground spaces. This orientation is mainly carried out by the sensor dependent or independent models, and the desired georeferencing accuracy is achieved with the adjusted orientation elements using ancillary data. Independently of the orientation model, an ill-posed problem is occurred in the adjustment process, caused by the ill-conditioned Jacobian matrix which is differentiated through the orientation elements. However, this challenge is mitigated by various approaches such as regularization, matrix inversion, or elimination methods. In this work, three different types of orientation models were exposed on Zonguldak test site characterizing mountainous urban and dense forest areas: 1) sensor-dependent orientation model for handling of SPOT 5 HRG panchromatic stereo images and 2) sensor-dependent and 3) sensor-independent rational function model (RFM) for Pleiades 1A and SPOT 6 panchromatic mono images. The main finding of this work is that eigenvalue-based approaches, i.e., Tikhonov regularization using eigenvalue and Moore–Penrose (pseudo) inversing, provide the best numerical solutions among the approaches initially investigated by the authors. The novelty of this article is that two eigenvalue-based approaches investigated in this article are never preferred to solve ill-posed problem in different sensor orientation cases.

Determinants of the beta diversity of tree species in tropical forests: Implications for biodiversity conservation

The mapping of earth’s biodiversity has advanced our theoretical and empirical understanding of biodiversity and has thus guided conservation efforts. Yet, early biodiversity maps often relied on alpha diversity indices, while beta diversity has rarely been used for practical conservation actions. We used generalized dissimilarity modelling (GDM) and variance partitioning to map beta diversity patterns of Hainan Island, China, and explore its underlying factors based on a large dataset of 248,538 individual trees belonging to 1,016 species in 902 forest plots. We used principal component analysis and hierarchical clustering to visualize community similarity, and spatial overlap analysis to assess the ability of the current protected areas (PAs) to encompass beta diversity. The GDMs explained 27.65% and 26.58% of the variation in beta diversity at the genus and species levels, respectively. The community composition of tree species in Hainan presented a general east-to-west gradient, and three floristic regions were delineated. This biogeographical pattern is predominantly structured by mean annual precipitation. Environmental variables, rather than geographical distance, were the most important factors determining present beta diversity patterns. Currently, PAs of Hainan Island are concentrated on mountain forest areas, while the lowland forest has largely been ignored. Thus, we suggest that biodiversity mapping based only on alpha diversity is not enough to identify conservation gaps, and the inclusion of beta diversity in such maps constitutes a promising tool to maximize the biodiversity coverage of PAs. Our study provides empirical evidence that a spatially explicit analysis of beta diversity in a specific region can be used for conservation planning.

Prediction of Competition Indices in a Norway Spruce and Silver Fir-Dominated Forest Using Lidar Data

Competitive interactions are important predictors of tree growth. Spatial and temporal changes in resource availability, and variation in species and spatial patterning of trees alter competitive interactions, thus affecting tree growth and, hence, biomass. Competition indices are used to quantify the level of competition among trees. As these indices are normally computed only over small areas, where field measurements are done, it would be useful to have a tool to predict them over large areas. On this regard, remote sensing, and in particular light detection and ranging (lidar) data, could be the perfect tool. The objective of this study was to use lidar metrics to predict competition (on the basis of distance-dependent competition indices) of individual trees and to relate them with tree aboveground biomass (AGB). The selected study area was a mountain forest area located in the Italian Alps. The analyses focused on the two dominant species of the area: Silver fir (Abies alba Mill.) and Norway spruce (Picea abies (L.) H. Karst). The results showed that lidar metrics could be used to predict competition indices of individual trees (R2 above 0.66). Moreover, AGB decreased as competition increased, suggesting that variations in the availability of resources in the soil, and the ability of plants to withstand competition for light may influence the partitioning of biomass.

Bird eye analysis of skyline views from an elevated recreation trail—The case of the Fu Forest Trail, Fuzhou, China

The Fu Forest Trail in the Chinese city of Fuzhou, completed in 2018, is a new pedestrian recreational system in an urban mountain forest area. Construction of the walkway was guided by identification of key sightlines between the mountains and the city. These sightlines controlled the interaction with the skylines around the walkway, building height, volume and density, and while also assisting with coordinated development of mountain forest area and surrounding urban areas. In the present study, a three-dimensional (3D) city model of the urban area with Fu Forest Trail was developed based on Geographic Information System (GIS). Combined with the principle of the real vision of human eyes, we obtained six skylines correspond to three observation areas from viewpoints along the forest trail. At the same time, the three indicators on the skyline aesthetic evaluation of silhouette complexity, layering equilibrium degree, and fractal dimension have been evaluated. Analysis led to the identification of several problems in the skyline around Fu Forest Trail: the outline is too flat, the proportion of layers is unbalanced, and there is a lack of satisfactory fluctuations and influential high-rise buildings. During the past 20 years, high-intensity development of real estate projects had resulted in a disproportionate share of excessively high, very large, and homogeneous residential buildings around the mountainous area. Buildings almost fully surround the mountain, which also explains the latter problem. We suggest that the government takes zonal control measures to restrict the development of the surrounding mountains in different gradients according to the distance from the mountains. Our findings can provide support for further study and governmental decision-making, while also providing inspiration for similar projects in China and elsewhere.

The Growth of Mountain Tourism in a Traditional Forest Area of Greece

The recreational value of forests in mountain areas creates significant potential for local growth. Indeed, in recent decades, it has been noted that there has been an increase in the popularity of forests recognized as tourism destinations with a strong recreational importance. In the forest area of Metsovo, the locals are aware of the role of tourism in local growth, and it is considered, along with forestry and livestock farming, as the major critical advantage for sustainable development. Research Highlights: Although the locals are satisfied with the quality of their lives, they consider that mountain tourism should be enhanced with certain prerequisites, such as forest infrastructure and improvement of the road network. Background and Objectives: The case study aims to examine and interpret the locals’ views in the mountain area of Metsovo on different factors that are able to support and encourage the growth of mountain tourism. Materials and Methods: Simple random sampling was applied, and data collection took place in 2018. In order to analyze and synthesize the locals’ views, reliability, factor, and hierarchical cluster analyses were used. Results: The main findings of the survey indicate that according to the locals’ views, there is a need for strategic organization addressing primarily forest recreation infrastructures from the Forest Service. Conclusions: The locals’ views are focused on mountain tourism-related exploitation with the aim of forest recreation infrastructures. Indeed, the locals acknowledge the important role of the forest service in conservation schemes, but they also identify that there are forest recreational potentials in their area that need to be enhanced by the central administration and locally by the Forest Service.

Assessment of causes and future deforestation in the mountainous tropical forest of Timor Island, Indonesia

The Mutis-Timau Forest Complex, one of the remaining mountainous tropical forest areas in Timor Island, eastern Indonesia that covers an area of 31,984 ha, tends to decrease gradually. Efforts to secure mountain forest functions and counteract the negative impact of declining forest areas are often constrained by data uncertainty on factors contributing to deforestation. For this reason, this study attempts to develop models of deforestation and predict future deforestation in the Mutis-Timau Forest Complex. We constructed models of deforestation that describe the relationship between deforestation and factors contributing to deforestation using spatial statistical models. In this model, we used the deforestation data for the 1987–2017 period obtained from a previous study as dependent variables and the potential causes of deforestation generated from Geographic Information System spatial analysis as independent variables. Using the probability of deforestation derived from the model, we predicted future deforestation under two different scenarios, namely, business-as-usual (as the reference scenario) and reducing emission from deforestation and forest degradation. Our findings showed that a positive relationship exists between probability of deforestation, distance to the settlement, and population density variables, whereas a negative relationship exists between likelihood of deforestation, elevation, slope, distance to the road, distance to the savanna, and forest management unit variables. During the 2017–2030 period, under the business-as-usual scenario, the Mutis-Timau Forest Complex will lose 1327.65 ha in forest area with an annual deforestation rate of 0.54%. Meanwhile, under the reducing emission from deforestation and forest degradation scenario, the overall forest loss was estimated to be 1237.11 ha with an annual deforestation rate of 0.50%. The predicted area of avoided deforestation in 2017–2030 under the reducing emission from deforestation and forest degradation scenario was 90.54 ha. Such data and information are important for the Mutis-Timau Forest Complex authority in prioritizing actions for combating deforestation and designing appropriate forest-related policies and supporting data for reducing emission from deforestation and forest degradation programme or other incentive schemes in reducing deforestation.

Adapting the planning and management of Norway spruce forests in mountain areas of Romania to environmental conditions including climate change

In Romania, natural Norway spruce forests are spread across upper mountain slopes (1300–1800 m). They perform multiple functions, being especially recognised for their economic value. However, where planted forests extend beyond the spruce's naturally occurring areas, they are frequently exposed to deleterious environmental factors. In Romania, forest planning is based on typological studies that were carried out between 1950 and 1970, and the regulations are applied in a somewhat flexible manner. In the context of the potential threats from climate change that could amplify induced destabilising phenomena, the risks to which these forests are becoming exposed can only be mediated through flexible management and the permanent adaptation of forest planning. For this reason, the purpose of this study was to develop a strategy for adapting forest management plan guidelines, with a view to improving ecosystem stability. A Norway spruce forest was chosen from the south-eastern Carpathians, which is included in the Natura 2000 Fagaras Mountains site. The models on which we based our current stand compositions resulted from long-term monitoring and analysis of species and stand structures. Stand structure - and forest structure, in general - is key to the continuous existence of stand functions and ecosystem services. Through design decisions, we promote biodiversity and the natural, better adapted, regeneration of local provenances. We highlight the rationale behind forest management planning and its regulations, with respect to the sustainable management of Norway spruce forests, which are vulnerable to potential changes in their structure as a result of climate change. Based on our findings, we propose the adaptation of measures used in forest management planning for Norway spruce forests to include protective functions that can be applied to all man-made Norway spruce forests introduced in former beech forest regions, and mixed coniferous/beech forests, that are vulnerable to changing environmental factors.

What Are the Principal Factors Affecting Ambient Ozone Concentrations in Czech Mountain Forests?

The aim of our study was to identify the factors substantially affecting day-to-day variability in O3 concentrations in Czech mountain forests. We examined the effects of meteorology and ambient NOx recorded in regular long-term continuous monitoring at five mountain forest sites representing different regions, covering both polluted and relatively unpolluted areas over the time period of 1992–2018. To investigate the association between ambient O3 concentrations on one hand, and precursor NOx concentrations and meteorology on the other hand, we used a generalized additive model, GAM, with semiparametric (penalized-spline-based) components to capture properly the possible departures from linearity. Our results revealed that the O3 concentrations showed significant associations with all selected explanatory variables, i.e. air temperature, global solar radiation (GLRD), relative humidity, and NOx. Apparently, both meteorology and air pollution are highly important for day-to-day O3 concentrations, and this finding is consistent for all five rural sites, representing middle-elevated forested mountain areas in Central Europe. In addition to individual variables, we were able to detect interactions between three pairs of explanatory variables, namely temperature*GLRD, temperature*relative humidity, and GLRD*relative humidity. Moreover, we confirmed non-linear O3 behavior towards individual explanatory variables.

Assessment of landslide hazard from tree-ring eccentricity and from compression wood – a comparison

We have compared maps of landslide activity and hazard, developed with the use of two different dendrochronological indicators: tree-ring eccentricity and reaction (compression) wood. The maps were prepared based on 125 Norway spruce ( Picea abies L. Karst.) trees growing at 44 sampling points, distributed over an area of 3.75 km 2 . In general, the two maps show similar patterns of landslide activity. However, tree-ring eccentricity yielded a greater number of dated events (246) compared to compression wood (129). Besides the differences in the absolute values of dating results, the general landslide activity and hazard zonation based on both disturbances are similar. Both growth disturbances develop as a result of stem tilting. Eccentricity develops after slight tilting, while compression wood is developed when tilting is more significant. Because of the differences in the strength of disturbing factors, which cause the development of compression wood and growth eccentricity, the best approach would be to combine the results of dating obtained from the two methods. The dendrochronological analysis of tree growth disturbances (eccentric growth and compression wood) is a promising approach for determining landslide hazards in forested mountain areas and can be applied in spatial management.

Vegetation pattern of Northeast China during the special periods since the Last Glacial Maximum

Since the Last Glacial Maximum (LGM), the global climate has experienced several stages, such as cold and warming events, which provide an ideal model for evaluating climate change in the future. Based on the pollen records in Northeast (NE) China, the vegetation pattern during special periods since the LGM was reconstructed in this work. During the LGM (approximately 18,000 cal yr BP), the steppes expanded rapidly in NE China, and a cold-dry meadow-steppe developed on the Songnen Plain. The Liaohe Plain and the Hulun Buir Plateau were occupied by a steppe-desert, with forest-steppe vegetation grown in the central and southern plains; there were cold-dry coniferous forests and mixed conifer-broadleaf forests in mountainous areas. In the early Holocene (10,000–9,000 cal yr BP), Changbai mountain (CBM) forests thrived in the eastern hilly area and the Sanjiang Plain, while the central region was dominated by steppes, and warm-temperate broadleaf forests developed northward. During the Holocene warm period (approximately 6,000 cal yr BP), CBM forests and cold-temperate coniferous forests developed in the north, while spruce-fir forests developed in the eastern Xiao Hinggan Mountains and the Sanjiang Plain. The distribution centre of deciduous broadleaf forests migrated to the south of the Changbai Mountains and the Liaodong Peninsula. The isolated woodlands increased on the Songnen Plain and the meadow-steppes expanded to the Liaohe Plain. Therefore, the increase in temperature leads to the increase of monsoon precipitation in NE China, which is beneficial to the development of warm-temperate forest vegetation. The increase of summer monsoons and precipitation caused by climate warming may be the main reason for the improved plant load.