Spatial Distribution Of Tree Species Research Articles

Comparison of Algorithms and Optimal Feature Combinations for Identifying Forest Type in Subtropical Forests Using GF-2 and UAV Multispectral Images

The composition and spatial distribution of tree species are pivotal for biodiversity conservation, ecosystem productivity, and carbon sequestration. However, the accurate classification of tree species in subtropical forests remains a formidable challenge due to their complex canopy structures and dense vegetation. This study addresses these challenges within the Jiangxi Lushan National Nature Reserve by leveraging high-resolution GF-2 remote sensing imagery and UAV multispectral images collected in 2018 and 2022. We extracted spectral, texture, vegetation indices, geometric, and topographic features to devise 12 classification schemes. Utilizing an object-oriented approach, we employed three machine learning algorithms—Random Forest (RF), k-Nearest Neighbor (KNN), and Classification and Regression Tree (CART)—to identify 12 forest types in these regions. Our findings indicate that all three algorithms were effective in identifying forest type in subtropical forests, and the optimal overall accuracy (OA) was more than 72%; RF outperformed KNN and CART; S12 based on feature selection was the optimal feature combination scheme; and the combination of RF and Scheme S12 (S12) yielded the highest classification accuracy, with OA and Kappa coefficients for 2018-RF-S12 of 90.33% and 0.82 and OA and Kappa coefficients for 2022-RF-S12 of 89.59% and 0.81. This study underscores the utility of combining multiple feature types and feature selection for enhanced forest type recognition, noting that topographic features significantly improved accuracy, whereas geometric features detracted from it. Altitude emerged as the most influential characteristic, alongside significant variables such as the Normalized Difference Greenness Index (NDVI) and the mean value of reflectance in the blue band of the GF-2 image (Mean_B). Species such as Masson pine, shrub, and moso bamboo were accurately classified, with the optimal F1-Scores surpassing 89.50%. Notably, a shift from single-species to mixed-species stands was observed over the study period, enhancing ecological diversity and stability. These results highlight the effectiveness of GF-2 imagery for refined, large-scale forest-type identification and dynamic diversity monitoring in complex subtropical forests.

Different phosphorus preferences among arbuscular and ectomycorrhizal trees in a subtropical forest

Phosphorus (P) is one of the most limiting elements for efficient plant growth and regeneration, coexisting plants are found to be able to partition soil P components through different types of mycorrhizal symbiosis. However, previous evidences were mostly based on artificial addition of different forms of P chemicals, there is still a lack of observational and experimental verifications on how tree species respond to soil P heterogeneity in natural soils. Herein, we conducted a field survey to investigate how spatial distribution of tree species with different types of mycorrhizal associations are related with soil P compositions. We found that arbuscular mycorrhizal (AM) trees tend to distribute in soils rich in inorganic P, while ectomycorrhizal (ECM) trees distribute in habitats with low inorganic P. We further established a shade-house experiment to evaluate how P availability of field soils affects seedling performance of AM and ECM trees. Biomass of AM seedlings was highest when grew in soil with the medium level of inorganic P, while ECM seedlings grown best in soil with the lowest inorganic P level. Seedling survival and mycorrhizal colonisation rates decreased, while specific root length and specific area of seedling roots increased, with increasing inorganic P concentrations. Using field soil with natural composition of P-forms and spatial heterogeneity, our findings confirmed the hypothesis that AM trees prefer inorganic P while ECM trees are able to utilise organic P in a more realistic setting, which regulated spatial distributions and promoted coexistence of subtropical tree species at local scale.

Assessing the impact of climate warming on tree species composition and distribution in the forest region of Northeast China.

Global climate change has markedly influenced the structure and distribution of mid-high-latitude forests. In the forest region of Northeast China, the magnitude of climate warming surpasses the global average, which presents immense challenges to the survival and habitat sustainability of dominant tree species. We predicted the potential changes in aboveground biomass, dominant tree species composition, and distribution in the forest region of Northeast China over the next century under different climatic conditions encompassing the current scenario and future scenarios (RCP2.6, RCP4.5, and RCP8.5). Forest ecosystem process model LINKAGES 3.0 was used to simulate dynamic changes in species-level aboveground biomass under four climate scenarios at the homogeneous land-type unit level. The potential spatial distribution of tree species was investigated based on three indicators: extinction, colonization, and persistence. The results showed that LINKAGES 3.0 model effectively simulated the aboveground biomass of 17 dominant tree species in the forest region of Northeast China, achieving a high accuracy with R² = 0.88. Under the current, RCP2.6, and RCP4.5 climate scenarios, the dominant tree species presented gradual increases in aboveground biomass, whereas under RCP8.5, an initial increase and subsequent decline were observed. With increasing warming magnitude, cold-temperate coniferous tree species will gradually be replaced by other temperate broad-leaved tree species. Furthermore, a large temperature increase under RCP8.5 will likely produce a significant contraction in the potential distribution range of tree species like Larch, Scotch pine, Ribbed birch, Spruce and Fir, while most temperate broad-leaved tree species and Korean pine are expected to demonstrate a northward migration. These findings provide guidance for enhancing the adaptability and resilience of forest ecosystems in middle and high latitudes and addressing the threats posed by climate warming.

Evaluation and optimization of ecological landscape pattern for urban agglomeration in the Pearl River Delta, China.

The evaluation and optimization of landscape ecological pattern has important implications for the accurate improvement of forest quality and high-quality urban development in the Pearl River Delta urban agglomeration. Based on the "one map" data and digital elevation model data of forest resource management in 2021, we evaluated and optimized landscape ecological pattern of the Pearl River Delta urban agglomeration by morphological spatial pattern analysis and minimum cumulative resistance model. The results showed that there were 435861 patches in the Pearl River Delta urban agglomeration that could be used as ecological source area, covering an area of 7346.60 km2 and accounting for 13.4% of the Pearl River Delta area. Thirty patches were selected as the ecological source area of the study area by using the area and patch importance index, covering an area of 2792.59 km2 and accounting for 5.1% of the Pearl River Delta area. The overall natural environment of the Pearl River Delta urban agglomeration was excellent. The ecological resistance level was small. The peripheral ecological resistance was low. The core ecological resistance was high. There was still a large room for adjustment of stand types and landscape patterns, which should be optimized by adjusting the composition and spatial distribution of tree species. The ecological network of the Pearl River Delta urban agglomeration was optimized with 30 ecological sources, 103 key ecological corridors, and 95 ecological nodes. The improvement rates of the optimized probability of connectivity index and integral index of connectivity index were 297.5% and 695.1%, respectively. The optimization results could effectively connect the ecological sources and spread the ecological service functions of ecological sources.

Evaluation of urban forest spatial distribution characteristics in Guangdong - Hong Kong - Macao Greater Bay Area

To understand the health and ecological benefits of scenic recreational forests, we elucidated their spatial distribution characteristics, which can be used to create guidelines and reveal strategic issues regarding the spatial distribution of tree species. We randomly set up 900 m2 quadrats in scenic recreational forest communities in Guangzhou, Foshan, and Zhuhai, and surveyed each tree using LiDAR. We then calculated the living vegetation volume (LVV) and amount of recreational space on the forest floor (RSFF), and analyzed the differences in spatial distribution characteristics across cities, locations, and forest types. The spatial distribution characteristics of trees differed between different cities, but were similar among different locations and forest types. Urban scenic recreational forest areas are thus configured based on aesthetics, recreational functions, and the spatial distribution characteristics of different tree species. Additionally, the relationship between the tree crown LVV and the RSFF was generally synergistic, yet contradictory. Although an increase in LVV can effectively improve ecological benefits, it may also reduce RSFF and other benefits provided by tree crowns to urban residents.

Tree species on environmental gradients in subtropical forest of northwest Belize, in the Maya Lowlands

We studied species composition and spatial distributions of tree species, and the underlying topography and soil, in subtropical forests of northwest Belize, a region in the Maya Lowlands. Our goal was to learn how much the spatial distributions of species vary and are predictable over the landscape. The study was done in old-growth, subtropical moist forest on limestone-derived topography and soil. We identified to species all trees ≥10 cm DBH in 209 400-m2 plots. For each plot, we characterized topographic setting and analyzed soil nutrients and texture. We recorded 3,984 individual trees of ∼140 tree species and used the 3,775 individuals of the 69 species occurring in ≥5 plots in multivariate analyses, including Nonmetric Multidimensional Scaling (NMS). NMS showed that 73% of the variation in species composition per plot was associated with the first three ordination axes. Sixteen out of the 34 quantitative variables we measured were correlated at R 2 > 10% with the axes. Of the categorical variables, Topographic Class was strongly associated with species composition, and USDA Texture Class less so. Of the 69 focal tree species, the abundances of 21 were correlated at R 2 > 10% with one or more axes of the NMS ordination. Importantly, these 21 species accounted for 68% of all individual trees sampled in the 209 plots. Twenty-three species were indicators of particular topographic and soil classes. We conclude that patterns of tree species distribution are strongly and predictably associated with different topographic and soil conditions in this landscape. In the past, the ancient Maya could have used this type of predictable plant–soil relationship to optimize their agriculture. In the future, our results are a basis for predicting local shifts in tree species distributions due to climate change.

Population Structure and Spatial Distribution of Tree Species in Lower Montane Forest, Doi Suthep-Pui National Park, Northern Thailand

Plant diversity is important for sustainable development, particularly in watershed areas. This study explored tree population and diversity in a lower montane forest (LMF). A 16-ha permanent plot was established in LMF at Huai Kogma sub-watershed, northern Thailand. All trees with a diameter at breast height ≥ 2 cm were tagged, measured, identified, and their coordinates were mapped. The results showed that 220 species in 139 genera from 63 plant families were found. The dominant families based on species numbers and tree density were Fagaceae, Lauraceae, and Theaceae. The most dominant species were Castanopsis acuminatissima, Schima wallichii, Castanopsis armata, and Styrax benzoides. Diameter classes for climax species frequently followed negative exponential distributions, indicating their populations could be maintained into the future. By contrast, pioneer species, such as Macaranga indica, Morus macroura, and Rhus javanica, had discontinuous distribution, and were mostly found in gap areas, indicating successful regeneration may require high light intensity. Spatial distribution patterns based on Morisita’s index showed that most of the selected species had clumped patterns, particularly those in the Fagaceae family, which were predominantly distributed along the mountain ridge. Tree distribution patterns can affect ecological dynamics, thus reinforcing patterns dependent on local interactions such as the abundance of and distance to available resources. Our finding can aid evaluations of forest sustainability, and support the biodiversity conservation plans. In particular, the selection of suitable species for LMF restoration programs where mixed plantings of pioneer and climax species are planned.

Exploring the Optimal Feature Combination of Tree Species Classification by Fusing Multi-Feature and Multi-Temporal Sentinel-2 Data in Changbai Mountain

Tree species classification is crucial for forest resource investigation and management. Remote sensing images can provide monitoring information on the spatial distribution of tree species and multi-feature fusion can improve the classification accuracy of tree species. However, different features will play their own unique role. Therefore, considering various related factors about the growth of tree species such as spectrum information, texture structure, vegetation phenology, and topography environment, we fused multi-feature and multi-temporal Sentinel-2 data, which combines spectral features with three other types of features. We combined different feature-combinations with the random forest method to classify Changbai Mountain tree species. Results indicate that topographic features participate in tree species classification with higher accuracy and more efficiency than phenological features and texture features, and the elevation factor possesses the highest importance through the Mean Decrease in Gini (MDG) method. Finally, we estimated the area of the target tree species and analyzed the spatial distribution characteristics by overlay analysis of the Classification 3 result and topographic features (elevation, slope, and aspect). Our findings emphasize that topographic factors have a great influence on the distribution of forest resources and provide the basis for forest resource investigation.

Spatial Distribution and Species Association of Dominant Tree Species in Huangguan Plot of Qinling Mountains, China

The spatial distribution pattern and population structure of trees are shaped by multiple processes, such as species characteristics, environmental factors, and intraspecific and interspecific interactions. Studying the spatial distribution patterns of species, species associations, and their relationships with environmental factors is conducive to uncovering the mechanisms of biodiversity maintenance and exploring the underlying ecological processes of community stability and succession. This study was conducted in a 25-ha Qinling Huangguan forest (warm-temperate, deciduous, broad-leaved) dynamic monitoring plot. We used univariate and bivariate g(r) functions of the point pattern analysis method to evaluate the spatial distribution patterns of dominant tree species within the community, and the intra- and interspecific associations among different life-history stages. Complete spatial randomness and heterogeneous Poisson were used to reveal the potential process of community construction. We also used Berman’s test to determine the effect of three topographic variables on the distribution of dominant species. The results indicated that all dominant species in this community showed small-scale aggregation distribution. When we excluded the influence of environmental heterogeneity, the degree of aggregation distribution of each dominant species tended to decrease, and the trees mainly showed random or uniform distribution. This showed that environmental heterogeneity significantly affects the spatial distribution of tree species. Dominant species mainly showed positive associations with one another among different life-history stages, while negative associations prevailed among different tree species. Furthermore, we found that the associations between species were characterized by interspecific competition. Berman’s test results under the assumption of complete spatial randomness showed that the distribution of each dominant species was mainly affected by slope and convexity.

Fine-scale topographic influence on the spatial distribution of tree species diameter in old-growth beech (Fagus orientalis Lipsky.) forests, northern Iran

The Hyrcanian forest in northern Iran is threatened by human use and encroachment and has suffered degradation in some areas. The forest has been declared a World Heritage Site and management in the region is shifting from timber production to conservation. There is considerable interest in developing a greater understanding of these diverse forest communities to inform forest management and multiple use plans to maintain the diversity and resilience of these forests. The Hyrcanian forest is characterized by a complex topography of catenas ranging up mountain slopes. Topographic gradients greatly influence microhabitat conditions which in turn impact tree distribution. To date there has been limited research on the impacts of this diverse topography on the spatial distribution of tree species and tree diameters in Hyrcanian forests. Such information is necessary to better understand the regional traits of tree diameters in these natural mixed temperate forests before forest management occurs. We examined the influence of the area’s catena topography on the spatial pattern of tree species and on species stand structure in terms of tree diameter distribution. To quantify these dynamics, we conducted a complete enumeration inventory of all trees with dbh >12 cm within a 7.947 ha study area that included three C-shaped (concave) and three V-shaped (convex) catenas. Geostatistical variogram analysis and Clark and Evans aggregation index were utilized to study the spatial distribution of tree diameters. Beech, alder, hornbeam, linden and Persian maple exhibited clustered patterns, and sour cherry, ash, and oak exhibited random patterns. Geostatistical analysis clearly revealed the substantial influence of catena topography on the diameter distributions of alder and linden, more subtle influence on the diameter distributions of beech, and a possible influence on Persian maple, providing valuable insight into stand structure over neighborhood-based indices alone. Alder and linden both exhibited strong spatial structure in their diameter distributions (56% and 86%, respectively) where their diameter was strongly correlated with trees within 108 m and 83 m, respectively, sharing more similar diameters to each other than trees beyond that distance. Beech, maple, and hornbeam exhibited very weak if any spatial structure over short distances. These findings can be used to support the alignment of forest management practices in managed Hyrcanian forests with goals of protecting and maintaining biodiversity and sustainable forest ecosystems, and to inform geospatial modeling of species diameter distributions in areas where a complete stem-map is not feasible.

Effects of forest stand structure on population of endangered orchid species Cypripedium calceolus L.

Lady’s slipper orchid (Cypripedium calceolus L.) has suffered a dramatic decline and is one of the most endangered orchid species in Europe. It grows mainly on calcareous soils in deciduous and mixed forests. Although numerous studies have contributed to our understanding of the causes of C. calceolus decline, surprisingly, little is known about the effects of the forest stand structure on the spatial distribution and morphometric characteristics of C. calceolus ramets. In this study, we analyzed how the spatial distribution of tree species and several structural characteristics of the forest stand affect the distribution and morphology of ramets of C. calceolus. For this, we used a remnant population of this species located in extensively managed forests in the Krowiarki Range (the Sudetes, SW Poland). The alarming decline in C. calceolus in this region over the last century is commonly attributed to forest management and land-use changes (abandonment of pastoralism in forests). We analyzed the morphometric characteristics and spatial distribution of C. calceolus ramets in this population in relation to the spatial distributions of trees, canopy gaps, saplings and structural characteristics of the forest stand. For this, we combined precise measurements of the forest stand structure, spatial analyzes in GIS and multivariate logistic regression modeling.The probability of the occurrence of C. calceolus was best predicted by its proximity to silver fir trees. We attributed this mainly to a positive effect by silver fir on the topsoil moisture, which can be especially beneficial to C. calceolus as this species is sensitive to drought. The occurrence of C. calceolus ramets was negatively affected by the basal area and positively affected by the diameter at the breast height of trees growing in a 5 m buffer zone. The structural attributes of the forest stand structure also affected the orchid’s morphology. Ramets growing close to beech or sycamore had lower leaf dimensions than ramets close to fir, and a pattern of decreasing leaf size with proximity to beech or sycamore was visible.This study spotlights the relationship between forest stand structure and the population of the endangered orchid C. calceolus. Based on the results of this and previous research, we have formulated several recommendations for the protection of the remnant population of this species in managed forests. These include maintaining mixed beech-fir forests rather than pure beech forest stands, supporting forest regeneration by species other than European beech, cutting young beech trees to prevent overgrowing the orchid ramets, fencing remnant populations of C. calceolus to exclude browsing pressure and maintaining spatial heterogeneity to support wild pollinators.

Tree crown segmentation and species classification in a wet eucalypt forest from airborne hyperspectral and LiDAR data

ABSTRACT To sustainably manage forest biodiversity and monitor changes in species patterning, mapping the spatial distribution of tree species is indispensable. Remote sensing can provide powerful tools for mapping species, but this task is complex in areas with high plant diversity and multi-layered canopies. This paper addresses the issue of classifying wet eucalypt forest plants by examining tree crown segmentation and species classification using different combinations of remote sensing datasets against mapped tree locations. This study explores optimal segmentation parameters for tree crown delineation compared to manually digitized tree crowns. The best segmentation accuracy of 88.71%, resulted from segmenting a combined Minimum Noise Fraction (MNF) dataset derived from hyperspectral imagery (HSI) and a LiDAR-derived Canopy Height Model (CHM). Object-based classification of tree species was performed using a random forest classifier. The fused dataset of MNF and CHM produced the highest overall accuracy of 78.26% for four vegetation classes, while the fused HSI, indices, and CHM performed best (66.67%) with five vegetation classes. However, both approaches had a high overall performance. The CHM contributed to tree crown segmentation and species classification accuracy, and fused datasets were more robust to spatially discriminate wet eucalypt forest species compared to a single dataset. Eucalyptus obliqua was classified with the highest accuracy of 90.86% for four classes using the fused MNF and CHM dataset, and 86.11% for five classes using the fused HSI, indices, and CHM dataset. An important understorey species – the tree fern (Dicksonia antarctica) – was classified with the highest accuracy of 83.54% for four classes using HSI. Therefore, fusing hyperspectral and LiDAR data could classify both the overstorey and dominant understorey species, and thus play a crucial role in identifying forest biological diversity. This approach will be useful for forest managers and ecologists to plan sustainable management of eucalypt forest biodiversity and produce maps for monitoring species of interest.

Predicting potential suitable habitats of Chinese fir under current and future climatic scenarios based on Maxent model

The continuous global climate change has affected the living habits, morphological characteristics and spatial distribution of tree species. Chinese fir (C. lanceolata (Lamb.) Hook) is one of the most important conifer tree species in China, which plays a major role in terms of timber supplies and environment protection. Predict the potential suitable habitats of Chinese fir under different climatic scenarios, can not only provide scientific theoretical basis for the planning and planting of Chinese fir, but also have great significance for maintaining the stability of the plantation ecosystem. Here, we used the maximum entropy (Maxent) model which optimized by the ENMeval package, to predicted the potential suitable habitats for Chinese fir under current climatic conditions and two climatic scenarios in 2070s. Our results showed that the complexity of the model was relative low, when the regularization multiplier (RM) was 0.5 and feature combination (FC) was linear (L) and quadratic (Q). Under this parameter setting, the high and moderate suitable habitat area of Chinese fir were 83.90 × 104 km2 and 97.62 × 104 km2, respectively, which suggested we can carry out Chinese fir planting activities with different cultivation purposes. The minimum temperature of the coldest month, annual precipitation, annual mean temperature and mean temperature of warmest quarter were identified as the essential factors shaping habitat suitability for Chinese fir. Under future climate scenarios, the high suitable habitat was reduced and the degree of fragmentation was increased, and the total potential suitable habitat of Chinese fir had the tendency to migrate to high-altitude regions. Managers should be cautious about the cultivation area selection of Chinese fir plantation as the potential suitable habitat changed under the global climate change continuously. It is therefore imperative to adjust the long-term management and protection strategy of Chinese fir plantation.

Species composition and community structure of warm temperate deciduous broadleaved forests in Huangguan of Qinling Mountains, China

The Qinling Mountain is a natural boundary between warm temperate zone and subtropical zone. While the China Forest Biodiversity Monitoring Network (CForBio) have basically covered most of the climate regions in China, few plots were located in the climate transition zone. Following the field protocol of CForBio and the Center for Tropical Forest Science (CTFS), a 25 hm2(500 m×500 m) forest plot was established in Huangguan Nature Reserve in Shaanxi Province, China, in 2019. In this study, we analyzed species composition, flora characteristics, diameter class structure, and spatial distribution patterns of dominant tree species based on the data of all woody species with a diameter at breast height (DBH) ≥1 cm. The results showed that there were 75137 woody individuals with DBH ≥1 cm in the plot (95679 when including branching individuals), belonging to 121 species, 83 genera and 44 families. The flora type at the genera level was mainly temperate, accounting for 71.1% of the total genera, and mixed with some tropical components. The dominant species in the community were obvious, with the number of individuals in the top 5 species exceeding 40% of the total number of individuals, the number of individuals in the top 50 species accounting for 95% of the total number of individuals, and the number of individuals in the remaining 61 species being less than 5% of the total. The diameter distribution of all woody indivi-duals in the plot was inverted 'J' type. Spatial distribution patterns varied across the four most abundant species with importance value >5. The degree of aggregation within species decreased with the increases of scales, while the spatial distribution of different species was affected by environmental heterogeneity. Warm-temperate deciduous broadleaved forest in Qinling Mountains had abundant species, stable community structure and good regeneration, reflecting the typical characteristics of the transition from warm temperate zone to subtropical zone. Environmental heterogeneity might be an important factor affecting the spatial distribution of tree species in the plot.

Mapping the spatial distribution of tree species selected by elephants (Loxodonta africana) in Venetia-Limpopo Nature Reserve using Sentinel-2 imagery

Mapping the spatial distribution of tree species selected by elephants (Loxodonta africana) in Venetia-Limpopo Nature Reserve using Sentinel-2 imagery

Fine‐scale tree spatial patterns are shaped by dispersal limitation which correlates with functional traits in a natural temperate forest

AbstractQuestionsStudying the spatial distribution of tree species is fundamental to understanding the ecological processes governing forest dynamics. Habitat filtering and dispersal limitation are two key processes in the emergence of intraspecific aggregation in natural forest communities. The contributions of these ecological processes vary among species, communities, ontogenetic stages (i.e. juveniles and adults) and spatial scales. In this study, we investigated the ecological processes underlying species spatial distributions in two ontogenetic stages and determined how these processes are linked to species functional traits.LocationA naturally established 2.4‐ha temperate forest located on a limestone hill in SW Belgium.MethodsTrees ≥1.3 m were exhaustively censused and mapped, and environmental variables and functional traits were collected. We applied spatial point pattern modelling to explore the processes underlying species distributions. First, point process models simulating complete spatial randomness, habitat filtering and non‐habitat clustering processes were fitted to observed species point patterns. The analyses were conducted for juveniles and adults both separately and together. The most parsimonious model for each species/ontogenetic stage was selected based on three summary statistics. Secondly, we investigated the links between functional traits and the parameters of the spatial models.Results(a) Dispersal limitation plays a central role in the formation of intraspecific aggregation in this forest, alone or in combination with habitat filtering. (b) Distributions of juveniles are less influenced by habitat filtering than distributions of adults. (c) Dispersal differ substantially among species and interspecific differences in clustering characteristics are explained by seed mass, wood density and maximum height.ConclusionsDispersal limitation can be of major importance in shaping temperate forests. Coupling spatial point pattern modelling and functional traits is an efficient way to understand mechanisms of species assemblages at fine spatial scales in temperate forests.

Storm legacies shaping post-windthrow forest regeneration: learnings from spatial indices in unmanaged Norway spruce stands

The anticipated increase in extreme disturbance events due to climate change is likely to expose Norway spruce (Picea abies (L.) Karst.) dominated forests in northern Europe to new conditions. Empirical data on the resilience of such natural (unmanaged) forests to disturbance and the long-term patterns of regeneration in its aftermath are currently scarce. We performed a quantitative assessment of natural forest stands in north–western Latvia to identify and characterise the patterns of stand structure 44 years after a stand-replacing disturbance and investigated the effects of legacies on regeneration. The spatial distribution of tree species and their dimensions were assessed in 71 circular sample plots (500 m2 each) in natural forest areas, where Norway spruce dominated prior to the windthrow and salvage logging was not carried out. Spatial indices (species mingling index, size differentiation index, and aggregation index) were used to characterise stand structure and diversity. The different initial states (age and coverage of surviving trees) of stands affected eventual tree species dominance, size differentiation, degree of mingling and aggregation. Our results demonstrate a close relationship between disturbance legacies and spatial indices. The pre-storm understory and canopy survivors decreased species mingling, whereas survivors increased size differentiation. The size differentiation increased also with a higher degree of species mingling. Leaving differential post-storm legacies untouched promotes a higher structural and species diversity and therefore supports the management approach of preserving canopy survivors.

THERMAL INVERSIONS IDENTIFICATION THROUGH THE ANALYSIS OF THE VEGETATION INVERSIONS OCCURRED IN THE FOREST ECOSYSTEMS FROM THE EASTERN CARPATHIANS

The earth’s climate has a direct impact on the spatial distribution of the vegetation cover. Forests are one of the most prevalent ecosystems on earth. The forest’s structure, if unaltered, can be an indicator of some climate patterns. This paper proposes an algorithm for identifying vegetation inversions within mountain forest ecosystems in the eastern Carpathians of Romania, using freely available GIS and remote sensing data. Air temperature has a direct impact on the spatial distribution of tree species. Therefore, temperature-inversion spatial patterns can be estimated.

Spatial distribution of tree species in mountain national parks depends on geomorphology and climate

During changing climates, tree species distribution and productivity are subject of dynamic changes. However, two other factors can play a role in forest development: human impact and terrain properties. Furthermore, terrain properties can frequently modify climatic limitation of tree species growth both positively and negatively. Here, we chose to study five national parks in southern Poland. We tested the impact of climate, soil type and geomorphic indices on the occurrence and biomass of tree species using random forest models. We assumed that despite the presence of human impact, fundamental relationships between landscape properties and climate were still detectable in the selected parks. Elevation and valley depth were the most important individual predictors of tree species distribution; site-specificity was an additional important factor. In addition to the strong age-dependency of aboveground biomass (mainly for Norway spruce Picea abies (L.) Karst and European beech Fagus sylvatica L.), elevation negatively impacted the productivity of all tree species. Additionally, the topographic wetness index negatively affected the biomass of F. sylvatica, while the slope positively influenced its biomass. Using partial dependence plots, we described how geomorphic variables modify climate-dependent elevational patterns of species studied distributions and biomass. Due to protection and preservation of these sites as provided by the national park system, we could separate the effects of particular variables on tree species studied. Our results broaden understanding of the influence of geomorphological variability on species distributions under similar climatic and soil conditions. This allows for predicting sites with a higher probability of species persistence under changing climates. Therefore, our results might be used to identify sites less vulnerable to climate change, therefore important for conservation prioritization.

Remote sensing and GIS-based forest fire risk zone mapping: The case of Manisa, Turkey

The aim of this research is to map the potential forest fire risk zones using various landscape analysis techniques in Manisa province, Turkey. Forest fire, which is defined as an ecological disaster caused by natural processes or as a result of human activities, causes environmental degradation and fragmentation of the landscape. Therefore, it is very important to produce a fire risk zone map that can be used to minimize the frequency of fire, to prevent damage, to provide a prediction for the problems that may cause fire and to form a decision mechanism for the solution methods. This research utilized CORINE 2018 produced under the framework of the Copernicus Program which is the European Union's Earth Observation Programme coordinated and managed by the European Commission, ASTER Global DEM digital elevation model data obtained from the website of NASA Earthdata, fire archive records based on MODIS satellite images, digital stand map displaying the spatial distribution of tree species, and the OpenStreetMap (OSM) which were used for mapping the existing road network. Vegetation cover, slope, aspect, elevation, distance to settlement, and distance to road variables were used to determine risk zones. The specific weights were assigned to each thematic map layer according to their capacity on fire ignition. The slope, aspect, and elevation maps were generated from the digital elevation model. The distance to settlement map was generated from the CORINE database while the distance to road map was produced from OSM. The Fire Risk Zone Index (FRZI) was utilized to determine forest fire risk zones. According to the generated final fire risk map, almost 25.8% of the study area was predicted to be under very high and highrisk zones. The final forest fire risk model was validated with past fire incidents data that was acquired from MODIS images as fire points. The result of this research showed that out of 149 fire incidents in Manisa between 2001 and 2018, 97 incidents had occurred in very high and highrisk areas. This finding supports that the presented methodology based on RS and GIS techniques is reliable and can be effectively used in the process of delineation of the forest fire risk zones.