Morphophysiological adjustments and Antioxidant defense in main tree species of southern China to simulated acid deposition

Mapping temperate forest tree species using dense Sentinel-2 time series

BackgroundThe Norwegian forest resource map (SR16) maps forest attributes by combining national forest inventory (NFI), airborne laser scanning (ALS) and other remotely sensed data. While the ALS data were acquired over a time interval of 10 years using various sensors and settings, the NFI data are continuously collected. Aims of this study were to analyze the effects of stratification on models linking remotely sensed and field data, and assess the accuracy overall and at the ALS project level.Materials and methodsThe model dataset consisted of 9203 NFI field plots and data from 367 ALS projects, covering 17 Mha and 2/3 of the productive forest in Norway. Mixed-effects regression models were used to account for differences among ALS projects. Two types of stratification were used to fit models: 1) stratification by the three main tree species groups spruce, pine and deciduous resulted in species-specific models that can utilize a satellite-based species map for improving predictions, and 2) stratification by species and maturity class resulted in stratum-specific models that can be used in forest management inventories where each stand regularly is visually stratified accordingly. Stratified models were compared to general models that were fit without stratifying the data.ResultsThe species-specific models had relative root-mean-squared errors (RMSEs) of 35%, 34%, 31%, and 12% for volume, aboveground biomass, basal area, and Lorey’s height, respectively. These RMSEs were 2–7 percentage points (pp) smaller than those of general models. When validating using predicted species, RMSEs were 0–4 pp. smaller than those of general models. Models stratified by main species and maturity class further improved RMSEs compared to species-specific models by up to 1.8 pp. Using mixed-effects models over ordinary least squares models resulted in a decrease of RMSE for timber volume of 1.0–3.9 pp., depending on the main tree species. RMSEs for timber volume ranged between 19%–59% among individual ALS projects.ConclusionsThe stratification by tree species considerably improved models of forest structural variables. A further stratification by maturity class improved these models only moderately. The accuracy of the models utilized in SR16 were within the range reported from other ALS-based forest inventories, but local variations are apparent.

This research focused on the reconstruction of historical fire regimes, structure and dynamic patterns of different types of forests, specifically to examine present tree species composition, regeneration patterns, size distribution, radial growth patterns of trees, composition, and structure of downed logs within different types of forests in the north-west Khentey Mountains, Mongolia. The Pinus sibirica-Abies sibirica (PiSi-AbSi) forests and Picea obovata-Abies sibirica (PcOb-AbSi) dark taiga forests consisted of more diverse tree species and had different size structures leading to a higher stand complexity than the Larix sibirica-Betula platyphylla (LaSi-BePl) and Pinus sylvestris-Larix sibirica (PiSy-LaSi) light taiga forests. Overall, the main tree species which occurred in the research area were present in all forest types, but they differed by the proportion of their Importance Value (IV).The PiSi-AbSi forest had a high number of P. sibirica and A. sibirica saplings, indicating that a future canopy could remain dominated by these species. Other tree species, such as P. obovata and B. platyphylla, which constituted a rather small part of the canopy, were also underrepresented in the sapling composition. In PcOb-AbSi forest, P. obovata made up only 5.8% of the saplings, while A. sibirica saplings made up the highest percentage (53.3%) of the total saplings, followed by P. sibirica saplings (31.7%). Also, the percentage of B. platyphylla saplings was higher (9.2%) than P. obovata. In LaSi-BePl forests, L. sibirica made up 54.3% of the canopy trees, however in the sapling tally B. platyphylla was dominant (77.6%); also it was well distributed in the different height classes of saplings. L. sibirica saplings made up only 22.4% of the total saplings. PiSy-LaSi forests consist of a high number of P. sylvestris saplings, indicating that a future canopy could remain dominated by the species. However, B. platyphylla sapling numbers were slightly higher (15.4%) than L. sibirica (11.5%).The continuous and stable tree recruitment of the different tree species in the P. sibirica dominated forest suggested that this forest did not experience any large fires for more than 200 years. Due to the openness of the canopy, light penetrates and warms the forest floor, enhancing the conditions for species diversity in the area. As a response to this fact, the understory growth is stimulated and species with the ability to sprout start to colonize the area. The tree recruitment pattern in PcOb-AbSi forest confirms the explained reaction of vegetation. In LaSi-BePl forests, B. platyphylla is abundant only during the first seven to twelve decades. After its decline P. sylvestris and L. sibirica became the main species. The tree recruitment wave indicates that this forest experienced major disturbances (e.g., fire) every 40-60 years. In PiSy-LaSi forest, the tree recruitment was more or less restricted to P. sylvestris, which may be explained by dry site conditions. The tree recruitment pulse occurred every 20-40 years in this forest.The tree-ring chronologies were developed for each trees species in order to examine growth patterns. A strong radial growth decrease of P. sylvestris trees in single years greatly fits to the fire event years. Such years are; 1790, 1822, 1866, 1905, 1929, 1948, 1954, 1972, 1981, 1996 and 2009.The climate response of each population (P. sibirica, A. sibirica, P. obovata, L. sibirica and P. sylvestris trees) was determined by correlating the residual chronology against a 17-month climate window from prior April to August of the current growth year. Correlation analysis for the five tree species indicated very different responses to climatic variables likely related to differences in elevation, topography, and microclimate at the study sites. On the other hand a few climatic variables were found to be correlated with the growth of tree species (P. sibirica, A. sibirica, and P. obovata), which are found at the wetter sites perhaps due to a stronger relative influence of non-climatic factors, leading to more individualistic tree growth patterns. P. sylvestris showed high responses to precipitation, snow-melt water and drought indices. With regard to the analysis of tree growth in response to climate factors, L. sibirica and P. sylvestris could be suitable species for climate studies in this area.Mean fire intervals were clearly different between the dark and light taiga forest types. The mean fire interval of 46 years (range 17.4-62 years) in PiSi-AbSi forests, and 39 years (range 15.8-68.5 years) in PcOb-AbSi dark taiga forests indicate that fire-return intervals are longer than those in LaSi-BePl and PiSy-LaSi light taiga forests. The seasonality of fires was, for most periods, constant and did not change within each forest type.

Climate condition affects foliar nutrition in main European tree species

Forestland connectivity in Romania—Implications for policy and management

There are many land use types and tree species in urban forest parks in which the human disturbance is frequent. Using remote sensing images to estimate the main tree species may provide a scientific basis for the making of sustainable management measures for scenic forest. In this article, Zijin Mountain National Forest Park in Nanjing, China, was selected as the case study area, and WorldView-2 data in December 2011 was chosen as the main information sources. Three kinds of band combinations were compared by using index of classification accuracy. Then the optimal combination was used to do supervised classification through three classification methods of decision tree classifier, neural networks, and support vector machine classification to distinguish the land use and the main species in the study area. The results showed that:1)The classification accuracy of 8-band combination of WorldView-2 is the highest and the overall accuracy and Kappa coefficients are 80.81% and 0.77, respectively, followed by the new 4-band combination and the standard 4-band combination. 2) Using the 8-band combination, the performance of decision tree classification is the best with overall classification accuracy of 87.10% and Kappa coefficient of 0.85, while the performance of neural networks classification is the worst with overall classification accuracy of 73.85% and Kappa coefficient of 0.70. 3) When comparing the accuracy of different tree species using decision tree classification, classification accuracy of the major local species is high, while the accuracy of foreign pine and cypress is relatively low.

Landsat-8 OLI and Sentinel-2 MSI images from years 2015 and 2016, a 1:10,000 digital soil map and a large number of reference samples were used with a random forest machine learning implementation in GRASS GIS to construct a tree species map for the entire territory of Estonia (42,755 km2). Class probabilities for seven main tree species, an extra class for other species and probability of the forest cover not conforming to the forest definition were assigned for each pixel. Validation of dominant species distribution by area showed very strong correlation at county level both in state forests (R2 = 0.98) and in private forests (R2 = 0.93). Validation of tree species composition using harvester measurement data from 2,045 regeneration felling areas showed also very strong correlation (R2 = 0.75) with the measured values of the proportion of coniferous trees. There was some tendency to underestimate the proportion of more common species and overestimation was found for the species with smaller proportion in the mixture. The accuracy for the proportion of deciduous species that were present in a smaller number of reference observations was substantially smaller. Validation of the results by using data from 659 large sample plots from the database of the Estonian Network of Forest Research Plots and 3,002 small sample plots from the National Forest Inventory (NFI) data base confirmed the findings based on harvester data. The NFI data revealed also a decrease of estimation error with the increase of forest age. Cohen’s kappa index of agreement for main species for NFI sample plots with main species proportion equal to or greater than 75% decreased from 0.69 to 0.66 when observations with forests younger than 20 years were included in the comparison. Overall, the constructed map provides valuable data about tree species composition for the forests where no up to date inventory data are available or for the projects that require continuous cover of tree species data of known quality over the entire Estonia.

Dynamik von Phosphor im Boden und von Nährstoffen im Kronenraum von Buchenwäldern unterschiedlicher Baumartendiversität

We investigated the interspecific relationships of Ormosia microphylla community in geomantic forest of Gutian Meeting site. The results showed that the main tree species in the arbor layer included Neolitsea aurata, Schima superba, Castanopsis carlesii, etc. while that in the shrub layer included Dendropanax proteus, Castanopsis fargesii, Diplospora dubia, etc. In the arbor layer, the niche breadth of O. microphylla was 21.04, and its niche overlap with the main tree species was low. The variance ratio and statistics of the main tree species in arbor layer were 0.77 and 59.57, respectively, indicating no significant association in arbor layer. In the χ2 test, there were 101 pairs of non-significant species pairs, and the logarithm ratio of positive and negative association species was 1: 1.18, indicating that the interspecific association was weak. In the shrub layer, the niche breadth of O. microphylla was 21.60. There was a high niche overlap between the main tree species in the shrub layer. The variance ratio and statistics of the shrub layer main tree species were 1.80 and 138.68, respectively, indicating significantly positive overall association in shrub layer. In the χ2 test, there were 107 pairs of significant species pairs, and the logarithm ratio of positive and negative association species was 1:0.09, indicating that the interspecific competition was strong. The Euclidean distances for the arbor and shrub layers were 6.40 and 4.91, respectively, suggesting the shrub layer was more stable than the arbor layer. In the shrub layer, there was a close relationship between O. microphylla and other main tree species. Due to intense resource competition, especially among the dominant species in the community, O. microphylla failed to achieve a dominant position as it grew into a mature tree. Therefore, there was an urgent need to implement artificial intervention measures and in-situ conservation strategies.

In this work, it was studied the need to adapt the choice of main Finnish boreal tree species in forest regeneration under the projected climate change. The forest ecosystem model (SIMA) was used to simulate the volume growth of young Norway spruce, Scots pine and silver birch stands under the current and gradually changing climate throughout Finland on sites with fertility varying from low to high. Compared with the current climate, the growth of Scots pine and silver birch increased under the changing climate throughout Finland. The increase wasthe highest on fertile sites under the SRES A2 climate change scenario. The growth of Norwayspruce decreased in southern and central Finland under the SRES A1B and A2 climate change scenarios compared with the current climate, and especially on sites with low fertility. In northern Finland, the growth of Norway spruce was clearly higher under the changing climate similar to Scots pine and silver birch, regardless of site fertility and time span. Overall, the growth responses of different tree species differed from each other largelydepending on the geographical location and climate change scenario applied. Based on this work, we may need to adapt the choice of main Finnish boreal tree species in forest regeneration under the changing climate, to consider the uncertainties related to the projected climate change in different time spans.

For afforestation, it is necessary to consider habitat conditions and their impact on specific tree species, in order to enable the selection of appropriate species to improve forest productivity and stand stability. Based on the 2014 Beijing forest management inventory data, we evaluated site quality using theoretical growth equations and quantile regression; we analyzed the effects of climate, topography, and soil variables on the growth of six main tree species using random forest models optimized by a genetic algorithm; and we mapped the potential habitat of six main tree species in Beijing. The results showed that climatic factors were the most important factors affecting tree growth. The prediction models had good accuracy, with an AUC of 0.75–0.85. Among the six main tree species studied, Pinus tabulaeformis Carr. was suitable for all of Beijing’s forest land. Platycladus orientalis (Linn.) Franco, Robinia pseudoacacia Linn. and Salix matsudana Koidz. were suitable for the mountainous areas, while Sophora japonica Linn. and Populus tomentosa Carr. were suitable for planting in the plains area of southeast Beijing. The optimized random forest model applied in this study gives insight into the distribution suitability of the main tree species in Beijing, and could serve as a reference for afforestation design.

Liangshan Prefecture is one of the three major forest areas in Sichuan Province and one of the three major disaster areas of forest fire. We measured the physicochemical properties and combustion performances of different organs (leaves and branches) of 15 main economic tree species in Liangshan, and analyzed the bioecology characteristics, silviculture characteristics and value characteristics of different tree species. We investigated the fire resistance of different tree species to screen out fire-resistant species suitable for economic forest development in Liangshan Prefecture, and improve the biological fire prevention ability. The seven physicochemical properties and combustion performances indices of 15 tree species showed significant differences. Except for crude ash and lignin, the weights of moisture content, caloric value, ignition point, crude fat, and crude fibre of leaves were higher than those of branches. Crude fibre index of leaves (9.6%) and the crude ash index of branches (9.9%) were the highest weight indices of the two organs, respectively. Based on the fire resistance, we divided all the species into three classes, i.e., class Ⅰ (excellent fire-resistance trees) Juglans regia and Morus alba; class Ⅱ (better fire-resistant trees) Sapium sebiferum, Mangifera indica, Phyllanthus emblica, Eriobotrya japonica, Ligustrum lucidum, Castanea mollissima, and Punica granatum; class Ⅲ (poor fire-resistant trees) Pinus armandii, Illicium simonsii, Morella rubra, Sapindus mukorossi, Olea europaea and Camellia oleifera. J. regia and M. alba had fireproof solid performance and could be used as the preferred species for fireproof economic forest in Liangshan region. It was suggested that to use class Ⅰ to Ⅱ fire-resistant tree species built the main fireproof isolated forest belt, and pay attention to fire prevention after planting class Ⅲ tree species in a large area.

In this study,LI-6400XT portable photosynthesis test system was employed to observe physiological indicators of 8 widely used species of Sha river′s plant corridor in Chengdu.Furthermore,the carbon sequestration,oxygen release capacity,cooling and humidification effects were also evaluated.Our results indicated: The capacity of carbon sequestration,oxygen release,cooling and humidification effect per unit of leaf area was in the order of summer autumn spring.The order of daily carbon sequestration and oxygen release capability per unit of leaf area from strong to weak was O.fragrans,S.babylonica,C.camphora,F.virens,E.sylvestris,G.biloba,C.pedunculatum and M.glyptostroboides;and the order of annual carbon sequestration and oxygen release capability per unit of leaf area from strong to weak was S.babylonica,C.camphora,F.virens,G.biloba,O.fragrans,C.pedunculatum,M.glyptostroboides and E.sylvestris.The capabilities of daily cooling and humidification effect per unit leaf area of the trees pecies from strong to weak was S.babylonica,E.sylvestris,M.glyptostroboides,C.pedunculatum,F.virens,C.camphora,G.biloba and O.fragrans.It was estimated that the total amount of annual carbon sequestration of trees in Sha river was about 5.87×104 t and the oxygen release was about 4.27×104 t.Based on the above analysis of the main tree species,it was suggested that S.babylonica,O.fragrans,E.sylvestris,and C.camphora should be taken as the priority tree species.Due to the weak C sequestration oxygen release and cooling and humidification effect,G.biloba should not be virescenced in a large area,but could be used as a longevous and ornamental tree species.

The capability of species-related forest stand characteristics determination with the use of hyperspectral data

An observational field plot,covering an area of 60×60m,was established to analyze the spatial distributions and associations of the main tree species in a spruce-fir coniferous and broadleaved mixed forest in the Changbai Mountain area in northeastern China. The spatial coordinates,diameters at breast height( DBH),diameters at ground height( DGH) and heights( H) of all trees with a height exceeding 30 cm and a dbh less than 5 cm were measured. The univariate O-ring function was used to analyze the spatial distribution patterns of the main tree species while the bivariate O-ring function statistic was used to analyze intraspecific and interspecific relationships among different trees. The distribution of tree diameters at breast height( DBH) of the entire community and of individual tree species follows the shape of an inverse J,which is rather unexpected because the distribution of dbh's in these forests is usually bimodal. All the Abies nephrolepis and Acer mono trees show an aggregated spatial distribution at short distances and a random distribution at other scales while Picea koraiensis、Pinus koraiensis and Tilia amurensis are randomly distributed at all scales. At different growth stages,the main tree species have different spatial distributions. Seedlings and saplings of Abies nephrolepis and Acer mono are spatially aggregated at close ranges but show uniform or random distributions at large scales. Spatial associations between the seedlings,saplings and big trees were also studied. As expected,the intensity of the spatial aggregation is declining withincreasing dbh' s. With few exceptions,pairs of the five main tree species,show mostly positive association at short distances.