Search

A new species of Cuphophyllus (Hygrophoraceae, Agaricales) was discovered in mixed coniferous and broad-leaved forests (Pinaceae and Fagaceae) and grassland margins in Lijiang, North-west Yunnan, and South-west China. The species is described using morphological and molecular methods. Based on on-site habitat observation data and a literature review, the novel species is best described as a saprobic macrofungus that thrives in soil humus within mixed pine forests or grasslands. The basidiomata of the novel species exhibit macroscopic similarities to C. virgineus; however, C. lijiangensis sp. nov. differs primarily in having a smaller pileus, shorter stipe, larger basidiospores, and an intricate trichoderm pileipellis. Phylogenetic analysis, based on the combined rDNA internal transcribed spacer (ITS), nuc28S rDNA (28S), and RNA polymerase II subunit 2 (rpb2) genes, places C. lijiangensis in a clade with C. virgineus, C. borealis, C. yacurensis, and C. russocoriaceus. Both morphological characteristics and phylogenetic data support C. lijiangensis as a distinct new species within Cuphophyllus. This study provides a comprehensive description of the new species, colour photographs of basidiomata, micromorphological structures, and a phylogenetic tree to show the position of the new species. [ABSTRACT FROM AUTHOR]

The oribatid mite family Achipteriidae is recorded in the Dominican Republic for the first time. A new species of the genus Achipteria—A. (Izuachipteria) dominicanensis sp. nov.—is described, based on adults collected from leaf litter in a mixed forest. The species is characterized by the morphology of the lamella (triangular distally, without strong lateral tooth), the location of the lamellar seta (on ventral side of the lamella), the length of the bothridial seta (long), the ornamentation and morphology of the pteromorph (partially striate, with lateral tooth), the number of the leg claws (one), and the absence of the notogastral saccules. The taxonomic status of the subgenera Achipteria (Cubachipteria), A. (Hokkachipteria), and A. (Izuachipteria) is discussed. An identification key, distribution, and habitat of the known representatives of Achipteria (Izuachipteria) are presented. [ABSTRACT FROM AUTHOR]

Copyright of Canadian Water Resources Journal / Revue Canadienne des Ressources Hydriques is the property of Taylor & Francis Ltd and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The present study is based on oribatid mite material collected from litter of the riparian mixed forest in the Hicacos Peninsula, northern Cuba. A list of 26 species, belonging to 23 genera and 15 families, is presented; of these, one genus and three species are reported for the first time for Cuban fauna. Two new species – Eremulus hicacosensis sp. nov. (Eremulidae) and Suctobelbella (Flagrosuctobelba) matanzasensis sp. nov. (Suctobelbidae) – are described. Identification keys to the known species of Eremulus and Suctobelbella (Flagrosuctobelba) from the Neotropical region are provided.http://www.zoobank.org/urn:lsid:zoobank.org:pub:2F4E8CE0-49AE-400B-BF0E-E9640C521E3E [ABSTRACT FROM AUTHOR]

Accurate knowledge of site conditions and their effects on regeneration establishment is important for selecting the most appropriate tree species and regeneration methods for a given regeneration site. This study examined the response of the first-year field performance of Scots pine (Pinus sylvestris L.), Norway spruce (Picea abies (L.) Karst.) and silver birch (Betula pendula Roth.) seedlings in boreal forests to variables available in open forest and natural resources datasets. Survival, height increment and damage of planted tree seedlings and the success of direct seeding of pine were analysed on a total of 284 plots (1000 m2) in 18 regeneration experiments established in 2020–2022 in southern and central Finland. The height increment of silver birch was higher than that of conifers, while the lowest mortality rate was found for spruce. In the generalised linear mixed models, topographic wetness index, soil texture, site type and growing stock at clearcut explained the species-specific survival and height increment of planted seedlings and the success of pine seeding. Low-cost, open geospatial data effectively provide useful details on the site conditions suitable for diversifying tree species composition in boreal forests instead of monocultures. [ABSTRACT FROM AUTHOR]

This study was conducted to explore measures taken by private forest owners in a region of southern Sweden to adapt forestry to climate change and the motivations behind these measures. Additionally, measures undertaken were compared with policy goals of the Swedish Forest Agency. Data were gathered through a questionnaire and interviews. The most common measure, mentioned by 72% (64) of respondents, is the choice of tree species, usually involving the replacement of Norway spruce (Picea abies (L.) H. Karst) with Scots pine (Pinus sylvestris L.) or deciduous tree species. Other significant measures are creating mixed forests and shortened rotation periods for Norway spruce. While forest owners have adopted several policy-aligned measures, they have not yet prioritized measures pertaining to forest roads, or specific social and environmental concerns such as avoiding clear-cutting in erosion-prone areas or creating dying trees. The most common motive for adapting forestry is to reduce the risk of damage. Communication activities of authorities and forestry advisors that start from forest owners' multifunctional views and multiple motives for taking action could promote the development of climate-adapted forests. Highlighting the additional environmental and social values that are served by climate adaptation measures may further motivate forest owners. [ABSTRACT FROM AUTHOR]

A GIS-based approach was used in this study to assess 10 years of land-use change in the lower Shivalik landscape of the Western Himalayas, India. The landscape encompasses two major protected areas which are home to a thriving population of large mammals. The main objective was to identify the changes in the land use pattern, specifically after forming a new tiger reserve in the landscape. Landsat 8 and 4 imagery were used for the time series analysis for the years 2018, 2013, and 2008, respectively. The change was calculated using nine land use classes, with mixed forest showing the highest change value, followed by agriculture, grassland, and scrub. The dense forest area increased immensely after the formation of the new tiger reserve. The results for dense and mixed forest classes also identified less fragmentation in the number of patches during the same time. Even though most of the landscape is within the boundaries of a protected area, the change in land use forms is noticeable. As development activities continue to expand, this region will face increased strain, which will impact the area's natural biodiversity. To protect that, a long-term conservation management effort is required. [ABSTRACT FROM AUTHOR]

The genus Laccaria (Hydnangiaceae, Agaricales) is an important ectomycorrhizal symbiont of a broad range of host plants. Laccaria guizhouensis was collected from a subtropical mixed forest dominated by Fagaceae in Southwest China and described based on morphological characteristics and molecular data. Laccaria guizhouensis is characterised by its medium-sized basidiocarps and strong striate or sulcatus, flesh-coloured to brown pileus, flesh-coloured to brown lamellae, 2- to 4-spored basidia, globose to obellipsoid, hyaline, moderately echinulate basidiospores, and 1–1.5 μm-long echinulate. Phylogenetic analyses based on ITS sequences (HMAS352265 and HMAS352266) indicated that L. guizhouensis represented a new species separated from all other Laccaria species. [ABSTRACT FROM AUTHOR]

The article discusses recent advances in fungal taxonomy and phylogeny, highlighting the vast diversity of fungi in the world. It emphasizes the need for a polyphasic approach to accurately identify and characterize fungi, which includes techniques such as micro- and macromorphology, biochemical analyses, and molecular biology. The article also mentions several research studies that have contributed to the understanding of fungal identification and classification. Overall, the article provides valuable insights into the field of mycology and its potential impact on our understanding of fungi. [Extracted from the article]

Pine wilt disease (PWD), caused by pine wood nematodes, has brought a great loss in ecology and economy all over the world. In China, the forest health status is also significantly affected by PWD since 1980, especially in coniferous forests and mixed forest regions. The PWD spreads very fast and can cause a healthy pine wood tree to die within a very short time. An effective way to protect other healthy pine wood trees is to discover PWD trees early. Using unmanned aerial vehicle (UAV) images can help people discover the PWD tree quickly and accurately, and a few automatical methods have been developed to monitor PWD trees including the deep learning methods. Because of the robust spatial-temporal transferability, deep learning methods have become the mainstream algorithms to monitor PWD trees. As we know, the training dataset is the most important material to train a deep learning model. However, there is still a lack of a PWD segmentation dataset so far. To fill this gap, in this paper, we have generated the first open-sourced PWD segmentation dataset based on very high-resolution UAV images to help the community conduct PWD monitor research conveniently. This dataset has 994 training samples, and each sample has visible bands with 512 × 512 pixels, and the spatial resolution of this dataset is 0.05 m. In order to train an advanced segmentation model, we have designed a lightweight deep-learning model for mobile devices or edge devices in this manuscript, named MobileSeg. The main feature of MobileSeg is its decoupling, which uses the re-parameterization technology to improve the model performance. Finally, a large-scale real-world scenario experiment with very high-resolution UAV images was utilized to validate the performance of MobileSeg, the experiment result indicated that MobileSeg has achieved the best performance compared with the recent lightweight segmentation models, and the experiment also proved the effectiveness of the proposed PWD dataset. [ABSTRACT FROM AUTHOR]

Copyright of Ecoscience (Ecoscience) is the property of Taylor & Francis Ltd and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

A mechanized1 harvesting system combined with whole-tree chipping was investigated on two harvesting sites in central and eastern Ohio, USA. Production and machine rate data of the operations were collected through time-motion studies, with chipping sub-tasks (elements) defined as: feeding, chipping, and loading. Chipping cycles averaged 21.5 min to produce 13.3 dry (21.3 green) tonnes per truckload, providing an hourly rate of 37.3 dry tonnes per productive machine hour (PMH), excluding delays. Total cycle time including truck delivery averaged 183 min, resulting in an hourly production rate of 4.4 dry tonnes/PMH delivered. The complete harvesting system included one feller-buncher, two grapple skidders, and a chipper. Harvesting cost ranged from (USD) $22.2 to $27.8/dry tonne, at the landing. Trucking cost was $0.48/dry tonne/km for the average hauling distance of 78 km. The total delivered cost amounted to $59.9–$65.5 per dry tonne. Chips were sampled from the operations and characterized to evaluate their quality as a bioenergy fuel, according to ANSI Standard AD17225–4:2014 Solid Biofuels. Results of chip properties indicated 37.5% green moisture (i.e. water mass fraction), 0.212 g/cm3 bulk density, 10.5% bark content, 0.49% ash, and 18.59 MJ/Kg calorific heating value. Size distribution of wood chips was categorized into small (3–<16 mm) 46%, medium (16–<45 mm) 45%, and large (45–63 mm) 3%, respectively. Fines (<3 mm) composed less than 1% while 4.5% were oversize (>63 mm). These whole-tree chips were found to meet the requirements of the highest grade (A1) of the U.S. wood chip fuel quality standard for bioenergy applications. [ABSTRACT FROM AUTHOR]

This study's objectives were to suggest harmonised criteria for the definition of mixed forests for two Nordic countries, describe their principal mixture types, and provide an overview of their current extent. We used national forest inventory data compiled in Finland and Sweden, considering the forest available for wood supply (FAWS), excluding seedling and sapling plots before canopy closure. The definition of the mixed forest was based on the threshold criteria, which indicate the basal area proportion of the dominant tree species of the total in a stand. The proportion of mixed forests increased with higher threshold criteria: 21% to 42% in Finland and 24% to 49% in Sweden, as the threshold criterion was changed from 65% to 85%. With a threshold criterion of 75%, the area of mixed FAWS was 5.6 million ha (31% of FAWS) in Finland and 6.5 million ha (36%) in Sweden. The dominant mixture type was the pine-spruce-birches mixture (31%) in Finland and the pine-spruce mixture (29%) in Sweden. The proportion of peatland forest of mixed forests was similar in the countries: 9-10%. The mixed forests proportion increased from north boreal to hemiboreal, increasing with more mature development classes. [ABSTRACT FROM AUTHOR]

Boreal mixed forests of trembling aspen (Populus tremuloides) and white spruce (Picea glauca) can provide higher outputs of many ecosystem goods and services, combined with resilience for changing environmental conditions. In this study, we examine the growth of white spruce and aspen over a range of stand compositions created by spot and broadcast treatments of broadleaves using manual and chemical means, aspen spacing, and untreated control. Twenty-two growing seasons postharvest, treatment responses created a range of broadleaf densities and spatial arrangements, reflected in significant differences in heights and diameters of the spruce mixedwood component. At this early seral stage, treatments have generated diversity in both tree species composition and stand structure. Modeling of the stand structures created by the different treatments provided outcomes ranging from pure conifer to broadleaf dominated when assessed by merchantable volumes. Broadleaf manipulations changed the relative proportion of spruce and broadleaf species in a mixture, achieving a variety of potential landscape and stand-level goals. Treatment differences were often not statistically significant until at least 16 years after stand initiation. Monitoring the achievement of mixedwood management goals will require longer time periods than currently employed for broadleaf or conifer monocultures. [ABSTRACT FROM AUTHOR]

This study aimed to (1) investigate the long-term results of Cedrus libani + Pinus nigra mixed afforestation and (2) compare it with pure P. nigra afforestation in terms of wood production, economic return, and carbon (C) sequestration. The study was conducted in Elazığ-Sivrice, southeastern Turkey. Data were collected from six sample plots, and stem analysis for each species in the mixed stand was performed to reveal the growth and development of the basal-area-averaged trees. Statistical analyses showed that the pure P. nigra stands were superior to the mixed stands in terms of wood production (236 m3 ha−1 vs. 150 m3 ha−1), wood economic value ($19,551 ha−1 vs. $11,483 ha−1), and C sequestration (93 t ha−1 vs. 64 t C ha−1) at 54 years old. The lower values calculated for the mixed stand may have been due to the incompatible growth curves of the two species. These results imply that if the aim is to obtain wood products, pure P. nigra stands may be more advantageous than mixtures of C. libani and P. nigra for afforestation. [ABSTRACT FROM AUTHOR]

Plant functional traits (e.g. leaf pigment and water contents, specific leaf area) serve as important indicators of plant condition, both within a given vegetation season and between years. Remote sensing-based methods allow for non-destructive and repeatable monitoring of the Earth's surface and thus offer an efficient way to map and monitor these traits. In our study, we used a large database of ground survey data sampled at several contrasting phenological phases of vegetation to develop and compare different machine learning models trained to estimate selected plant functional traits at two different sites: mixed floodplain forest at Lanžhot and beech forest at Štítná, both in the Czech Republic. Empirical models were trained as predictors using 1) Sentinel-2 satellite data (a data set with higher spatial and spectral resolution), and 2) Harmonized Landsat Sentinel-2 (HLS) product (a data set with higher temporal resolution). The most successfully retrieved traits were chlorophyll and carotenoid content (R2 = 0.78 and 0.65, respectively). Although models trained with Sentinel-2 predictors proved to be slightly better in terms of validation statistics compared to HLS predictors, the HLS product may be preferable for some applications requiring analysis at a high frequency. The best-performing machine learning algorithm, canonical correlation forest, was then applied per pixel to all cloud-free images from the HLS product at both study sites for the years 2019–2021. This allowed us to create a time series of plant functional traits useful for observing differences between the two sites, as well as between growing seasons, and also to observe patterns of spatial behaviour using map outputs. [ABSTRACT FROM AUTHOR]

Recently, many freeze/thaw (FT) products have been developed using spaceborne microwave measurements. In this letter, we compared the newest FT products, SMAP36 (36 km resolution) and SMAP09 (9 km resolution) provided by the Soil Moisture Active Passive (SMAP) mission and one product, AMSR2 FT, generated by the Advanced Microwave Scanning Radiometer 2 (AMSR2) against surface soil temperature measurements across Russia using a total of 494 stations. The results indicate that AMSR2 FT has a better performance in Russia than the SMAP products, which is more pronounced in the AM (descending orbit) value of overall accuracy (OA) than in the PM (ascending orbit). It is challenging to distinguish FT states in the transition periods between warm and cold seasons, but AMSR2 FT performs better than SMAP products. AMSR2 FT has a high OA in inland areas but a low OA along coastal zones because pixels may contain a water body or lake ice. The poorest SMAP results are mainly distributed in mixed forest areas, indicating that the algorithm should be improved to solve the wet snow problem in these areas. The results of this study could help improve FT products in Russia and provide application instructions for FT product users. [ABSTRACT FROM AUTHOR]

Studying individual trees is a common way that scientists employ to study forests and estimate forest parameters. In this study, a graph-based approach was developed for detecting individual trees in a broadleaf, complex forest region based on UAV-derived point cloud data. Horizontal cross-sections at different heights were applied to the Canopy Height Model (CHM) to extract initial candidates for graph nodes. The graph was processed in multiple steps, and individual treetop locations were detected based on graph nodes' properties. The impact of various parameters, such as minimum area of connected components and minimum tree heights, on the performance of the developed method was investigated. The evaluation step demonstrated the potential of the proposed graph-based method for individual tree detection in a complex forest region in Mazandaran, Iran. In particular, the graph-based method obtained Precision, Recall, and F1-score values of 0.64, 0.73, and 0.68, respectively. Furthermore, the intercomparison with the well-known and most used Local Maximum (LM) suggested the applicability of the proposed method. After point cloud generation, the proposed method was implemented entirely in Python using open-source packages, which increases its applicability for other scholars and managers. The source code of the proposed algorithm can be found at . [ABSTRACT FROM AUTHOR]

Ethiopian mixed forests have multipurpose benefits and services. However, there is a gap of information in the entire Ethiopian highlands on forest growth needed for implementation of sustainable forest management and provision of ecosystem services. Therefore, main aim of this study was to identify main factors deriving tree growth in forest and woodland in Amhara Regional State of Ethiopia and to provide an individual tree basal area increment (BAI) model based on increment cores. The data came from 170 sampling plots in study area and cover 51 tree species. For each tree species, diameter at breast height (DBH), height, increment core measurement, tree location, and distance from subject tree measurements were recorded. Because of large number of trees species, it is difficult to develop growth functions for each individual tree species. Thus, classification of species groups provided a framework to organize information that differs between vegetation types. Our classification resulted in three groups. For each tree species group, an individual tree BAI model was calibrated. The tree species group of BAI differs by DBH class. The response to BAI depends on competitive condition of a tree. This growth model can be used to predict tree growth for Ethiopian mixed-species forests. [ABSTRACT FROM AUTHOR]

Copyright of Ecoscience (Ecoscience) is the property of Taylor & Francis Ltd and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Finer spatial resolution (roughly 1 km) of terrestrial rainfall is necessary for urban hydrology and microscale agriculture demands but still limited in various 'top-down' satellite rainfall products (SRPs). This study aims to evaluate the potential application of an emerged 'bottom-up' approach, the parameterized SM2RAIN model, to the C-band Synthetic Aperture Radar Sentinel-1 (S1) satellites for a high-spatial-resolution SRP (SM2RAIN-S1, 0.01º/6-day) over Central South Korea. By comparing its performance with the Integrated Multi-satellitE Retrieval for Global Precipitation Measurement (IMERG) Early Run product at a similar resolution against a common reanalysis rainfall product and rain gauges network during a 1-year period, we explore whether this novel bottom-up SRP can add improvements to the conventional top-down SRP regarding differences in climate areas (coast and inland), vegetation covers (cropland and mixed forest), and seasonality (rainy and non-rainy seasons). The SM2RAIN-S1 demonstrates its feasibility in capturing general spatiotemporal rainfall patterns in the study area compared to other rainfall products; however, noises associated with the S1 images still occurred. For the comparison over climate-vegetation areas, the extended triple collocation revealed that the SM2RAIN-S1 is relatively superior to the IMERG mainly over inland and forest regions, suggesting the suitability of 6-day SM2RAIN-S1 data to the stable and lower temporal rainfall variation in such regions, where the IMERG data are limited. The comparison against rain gauge data over rainfall seasons indicated that the SM2RAIN-S1 generally outperformed IMERG for bias and Root-Mean-Square Error, particularly during the rainy season. Moreover, the SM2RAIN-S1 shows its feasibility for moderate and heavy rain detection, while it is less effective in detecting light rain events compared to the IMERG. This study encourages the potential use of the bottom-up SM2RAIN-S1 rainfall product to complement, downscale, and correct the biases in top-down SRPs; together with supporting their integration for improving high spatio-temporal resolution rainfall products. [ABSTRACT FROM AUTHOR]

North American ash species (Fraxinus spp.) are under dire threat from the invasive pest, emerald ash borer (Agrilus planipennis, EAB), and mapping ash trees is of utmost significance for conservation and prevention efforts. We developed remote sensing techniques to identify ash trees at the individual tree level in a mixed-species forest in Maine, USA, using hyperspectral bands combined with derived spectral vegetation indices (SVIs), texture metrics using Random Forest (RF) and Support Vector Machine (SVM) algorithms. The pixel-based SVM-Optimized model proved to be the most accurate classification method with the lowest number of input variables including six Minimum Noise Fraction (MNF)-reduced bands, four SVIs and two texture variables, achieving 78.2% overall accuracy and 81.0% ash Producer's Accuracy. The technique presented in this study could be used to map ash trees throughout Maine and other states with similar forest types for future preservation efforts. [ABSTRACT FROM AUTHOR]

The oribatid mite family Oppiidae is highly diverse in the northern hemisphere, but in Korea it is represented by only 16 species. Herein, we propose three new species, Moritzoppia coreanasp. nov., Medioxyoppia brevisetosasp. nov. and Medioxyoppia claviacuminatasp. nov., and provide a supplementary description of a little known species, Oxybrachioppia ctenifera, which is newly reported from Korea. All species are inhabitants of the litter and soil of mixed forests, and following the descriptions and comparisons, we discuss aspects of the distribution, diversity of each genus, and habitat ecology of species reported herein. [ABSTRACT FROM AUTHOR]

A new species of the genus Gymnodamaeus (Oribatida, Gymnodamaeidae) is described from litter with needles in mixed forest (spruce-birch-cedar) of Western Siberia, Russia, based on adult and juvenile instars. The adult instar of Gymnodamaeus uslaminorumsp. nov. is characterized by the tuberculate cerotegument on the body; short, spiniform interlamellar seta inserted on cylindrical tubercle; long bothridial seta with a flattened head; dorsosejugal region with one pair of large tubercles; anterodorsal notogastral part with slight ridges forming П-like structure; six/seven pairs of setiform notogastral setae; parastigmatic tubercle Sp; one pair of anogenital concavities; and the absence of discidium and parastigmatic tubercle Sa. The identification keys to known larvae and nymphs of Gymnodamaeus are presented. . [ABSTRACT FROM AUTHOR]

Crown variables are used in growth and production models to increase the accuracy of estimates. These variables are costly and difficult to measure, mainly in dense native forests such as mixed ombrophilous forests (MOF), where Araucaria angustifolia is the predominant species. Thus, this study aimed to evaluate the effect of qualitative and quantitative variables to describe the vigour of the crown, competition and growth of A. angustifolia in Southern Brazil MOF. We selected trees in the MOF area and measured circumference at breast height (CBH) and total height (h). For the crowns, a ranking of values was established in the variables: Crown Shape (CS), Vertical crown Shape (VS), Distance between Branches (DB), Sociological Position (SP), percentage of Green Leaves (GL) and Crown Size (CZ). Periodic Annual Increment in basal area (PAIg) and a Competition Index (CI) were calculated. We used principal component analysis (PCA) and Hierarchical Cluster Analysis (HCA) to describe and classify the sampled trees. Two groups were generated: i) dominant and codominant trees, with higher growth, better vigour and better crown quality; and ii) suppressed trees with low vigour, consequently low increment and worse crown quality. The CI, when based only on diameter information, was inadequate to describe the competitive status of the trees, so information about crowns was necessary. Qualitative crowns variables are important to classify the vigour, current level of competition and to understand the different trends in A. angustifolia growth. [ABSTRACT FROM AUTHOR]

Resilient ecosystems provide natural insurance value, or resilience value, to the landowner and to society at large. In response to global calls for integrating biodiversity in sector policy and planning, we analysed the specified resilience value by simulating three storm regimes and five management scenarios: Business As Usual/BAU (spruce-dominance), Spruce Monoculture, More Broadleaves, Continuous Cover Forestry (CCF), and No Thinnings. The forest decision support system Heureka RegWise was used to simulate the effects of storms on forest dynamics and Net Present Value (NPV). No Thinnings, CCF and More Broadleaves were more resilient to storms (reduced damage cost) compared to BAU. BAU had the highest NPV only if storms are ignored, a common assumption in today's forest planning. Given storms, No Thinnings maximises NPV on landscape level. On the 20% most vulnerable plots the NPV was much higher for No Thinnings and slightly higher for CCF and More Broadleaves, compared to BAU. CCF and More Broadleaves also provide nature-based solutions (co-benefits) including public goods. However, forestry adaptations to storms are slow in Sweden, in contrast to e.g. German state forestry which emphasises maximising tree growth and resilience to several stresses and disturbances rather than NPV optimisation. [ABSTRACT FROM AUTHOR]

The different geographical origins of Baltic, Bitterfeld and Ukrainian ambers may be reflected in differences in their preserved fungal spores and plant pollen. In this study, over 573 palynomorphs were isolated through solvent extraction and the differences in their morphological characteristics examined using conventional transmitted light microscopy to explore this hypothesis. The spore spectra in the Baltic, Bitterfeld and Ukrainian samples differed considerably whereas the pollen spectra differed only marginally. In the Ukrainian ambers, the isolated fungal spores were primarily basidiomycetes (mostly Coprinus s.l., Strophariaceae and similar taxa with thick-walled, melanised spores), indicative of a moist environment rich in decaying plant debris. The first amber-based evidence for Ilex was found in the Bitterfeld samples and for members of the Juglandaceae in those from the Baltic. Overall, the pollen spectra were consistent with earlier findings on Eocene-Oligocene vegetation and climate. The mixed forests of those geological epochs are the hallmark of a habitat containing multifaceted niches for animals and obviously fungi. [ABSTRACT FROM AUTHOR]

Revealing the dynamics of soil organic carbon (Corg) and nutrients at aggregate scales is essential for improving our understanding of soil Corg mitigation and nutrient restitution in the Cunninghamia lanceolata plantations. In this study, soil Corg, total nitrogen (Ntot), available phosphorus (Pava), and exchangeable cations (including calcium (Ca2+), magnesium (Mg2+), potassium (K+), and sodium (Na+)) received the analysis in aggregate fractions acquired from 0 to 10 cm and 10–20 cm depths in the three different stand types, namely mixed stands of Cunninghamia lanceolata and Michelia macclurei (stand A), Cunninghamia lanceolata and Mytilaria laosensis (stand B), and pure stand of Cunninghamia lanceolata (stand C). Soil aggregates were classified into macro-aggregates (>2 mm), meso-aggregates (2–0.25 mm), and micro-aggregates (<0.25 mm) by the dry-sieving process. The two mixed stands displayed higher level of soil aggregate stability than the pure stand. Moreover, micro-aggregates acted as the main fractions that carried soil Corg, Ntot, and Pava, and both micro-aggregates and macro-aggregates referred to the main fractions that carried exchangeable cations. As for the soil nutrient stocks, only the exchangeable K+ stock of the pure stand dominated among the Corg and nutrient stocks, in addition, the rest of the other nutrient stocks of the mixed forests (stands A and B) took an advantage over the pure stand. Moreover, the Corg and nutrient stocks in stands A and B were reflected in the macro-aggregates, differently, those of stand C were mainly reflected in the micro-aggregates. Thus, selecting suitable broadleaf tree species mixed with Cunninghamia lanceolata can alleviate the reduction of soil aggregate stability and the loss of soil nutrients, thus promoting soil resources to be sustainably utilized and protecting soil quality and health in southern Guangxi of China. [ABSTRACT FROM AUTHOR]

Through large-scale afforestation and reforestation, China has increased its forest area and improved forest quality, making considerable contributions to carbon stocks of the world's forests. As one of the important indicators of forest quality and carbon potential, vegetation carbon density (VCD) is affected by different factors at different scales, but little is known about the effect of topographic factors on the VCD of subtropical forests in the southeast of China, especially at a large regional scale. Based on the national forest continuous inventory protocols, more than 2000 permanent samples (2061 samples in 2009, 2115 samples in 2014, and 2132 samples in 2016) of major forest types (Bamboo forests (BB), broad-leaved forests (BF), mixed forests (MF), coniferous forests (CF)) were grouped by topographic factors to compare the distribution of VCD in Zhejiang Province of China. The four topographic factors (altitude, slope gradient, aspect, and slope position) explained 16.2%~28.4% of the variance in different forest types in the random forest model and the importance order of the four terrain variables is basically corresponding to the significance in the radar charts. The VCD of each forest type varies significantly at different altitudes (p <.05, except for the BB samples in 2009). In general, VCD tends to be higher at high altitudes. The VCD in BB and BF varies significantly with slope gradient (p <.05, the largest on the steep slope and the smallest on the gentle slope); however, the VCD of CF and MF showed almost no difference in different slope gradients. We found significant differences in VCD between the eight aspects in the mixed forest (p <.05, the largest in the S and SW aspects), but not in the other three forest types. As for different slope positions, the VCD of ridges is relatively large, and the VCD of the upslope is generally larger than that of the downslope (more pronounced in BB and BF, all p <.05). This study made a detailed analysis of the greening distribution in different topographic factors, and the research conclusion could provide a scientific basis for the selection of afforestation location and forest scientific management, and contribute to the improvement of the capability of coping with climate change in subtropical forests. [ABSTRACT FROM AUTHOR]

Highly accurate and detailed information on land cover products is crucial in studying global climate change and sustainable development. GlobeLand30 is the first global 30 m resolution Land cover (LC) product based on remote sensing data developed by Chinese scientists. GlobeLand30 has 10 first-level classes of products. However, no second-level classification products have been released. This study presents an integration method based on fuzzy theory and combines three 30 m resolution LC products, namely, National Land Cover Database 2011 (NLCD 2011), Fine Resolution Observation and Monitoring of Global Land Cover Segmentation 2010 (FROM-GLC-Seg) and global forest cover data (treecover2010) products, using the European Environment Information and Observation Network Action Group on Land Monitoring in the European (EAGLE) system of semantic translation. The conterminous United States region is adopted as the research area, and the GlobeLand30 (2010) forest class is subdivided into coniferous, broadleaf and mixed forests. Three different weighted voting methods are applied. The difference is whether the user or local accuracy of the source product is considered. The result shows that the respective accuracies of broadleaf, coniferous, and mixed forests are approximately 65.8%, 57.0%, and 40.9% of the weighted voting method without considering any product's accuracy; 79.3%, 65.9%, and 58.4% of the weighted voting method considering the user accuracy; and 79.9%, 69.9%, and 59.3% of the weighted voting method considering the local accuracy of each product, respectively. The proposed method for refining the GlobeLand30 first class forest can be applied to other classes and land cover products. [ABSTRACT FROM AUTHOR]

The Araucaria Mixed Forests (AMF) are subtropical conifer-hardwood mixed forests that are part of the Atlantic forest floristic dominion in Brazil and Argentina. The AMF is dominated by the conifer Araucaria angustifolia (hereafter araucaria), accompanied by a diversity of angiosperms. Its distribution largely corresponds to the 13°C isotherm and is associated with overall lower temperature, frost-prone, and wetter climates than neighboring vegetation types. Palynological research and bioclimatic modelling have yielded somewhat conflicting results but suggest intense forest-grassland dynamics, with grasslands possibly dominating the landscape during the drier and colder last glacial maximum. Araucaria is a cultural keystone species whose distribution has been greatly fostered by Amerindian activity in the last few millennia. Angiosperms form a lower layer beneath araucaria canopies, and they seem to be geographically structured into a wetter and colder eastern and a drier and hotter western portion. Araucaria attain large sizes and high longevity but is unable to regenerate under the shade cast by angiosperm canopies and need large-scale disturbances for successfully complete their life-cycles. This cycle has been synthesised in the non-equilibrium Lozenge model of forest dynamics. Regeneration opportunities arise from the frequent multiple treefall gaps produced by the tornado and windstorm-prone climate of subtropical South America and by the grazing-, fire-, and nurse-plant successional dynamics of the forest-grassland mosaic. Dispersal is mediated by a complex web of interactions with birds and mammals. A review of the dynamics of southern Oceanic Temperate Forests indicates that the dynamics of the AMF fits a prevailing pattern in these forests that corresponds to the Lozenge model. Deforestation and degradation by logging and cattle grazing have impacted most of the AMF original range. Similarly to what happened to Agathis australis in New Zealand, the establishment of commercial plantations still need incentives and research to thrive and produce large-scale environmental benefits. [ABSTRACT FROM AUTHOR]

Grasses and fire pose a major challenge for forest restoration. Here we evaluate a case study of reforestation in an area invaded by the tall invasive grass Saccharum spontaneum in the Panama Canal Watershed. The project objectives were to (1) replace Saccharum with a forest, (2) restore a stratified mixed species forest and (3) sequester carbon. We aimed to compare the practice of forest restoration with a treatment grounded in theory. Therefore, the first species selection method followed business-as-usual: contractors planted any combination of 130 prescribed species. The second method followed the framework species approach, a mixture of 22 species was planted to ensure early shade, create a stratified forest over time, attract seed dispersers, and for their potential to fix N2. Both treatments showed successful restoration trajectories 8.5 years after planting, they did not differ in structural characteristics (stem density, basal area, aboveground biomass, height, and amount of Saccharum). However, based on the species present, the framework approach shows more potential to become a stratified forest. As the framework approach also withstood fires much better than the business-as-usual approach, we conclude that it improves restoration success in this human-dominated landscape. [ABSTRACT FROM AUTHOR]

Assessment of vegetation biochemical and biophysical variables is useful when developing indicators for biodiversity monitoring and climate change studies. Here, we compared a radiative transfer model (RTM) inversion by merit function and five machine learning algorithms trained on an RTM simulated dataset predicting the three plant traits leaf chlorophyll content (LCC), canopy chlorophyll content (CCC), and leaf area index (LAI), in a mixed temperate forest. The accuracy of the retrieval methods in predicting these three plant traits with spectral data from Sentinel-2 acquired on 13 July 2017 over Bavarian Forest National Park, Germany, was evaluated using in situ measurements collected contemporaneously. The RTM inversion using merit function resulted in estimations of LCC (R2 = 0.26, RMSE = 3.9 µg/cm2), CCC (R2 = 0.65, RMSE = 0.33 g/m2), and LAI (R2 = 0.47, RMSE = 0.73 m2/m2), comparable to the estimations based on the machine learning method Random forest regression of LCC (R2 = 0.34, RMSE = 4.06 µg/cm2), CCC (R2 = 0.65, RMSE = 0.34 g/m2), and LAI (R2 = 0.47, RMSE = 0.75 m2/m2). Several of the machine learning algorithms also yielded accuracies and robustness similar to the RTM inversion using merit function. The performance of regression methods trained on synthetic datasets showed promise for fast and accurate mapping of plant traits accross different plant functional types from remote sensing data. [ABSTRACT FROM AUTHOR]

The effect of site preparation (mixed mounding and removal of the humus layer) under a shelterwood of mixed boreal forest along a forest interior-edge gradient on Norway spruce (Picea abies) seedlings was studied two years after planting. Mounds had a positive effect on root development, ectomycorrhiza formation and the absorption of nitrogen (N) and phosphorus (P) in the seedlings, and augmented their survival, growth and biomass. Humus removal had an adverse effect on the root biomass and ectomycorrhiza formation. A decreased soil fertility after the removal of humus led to a low N and P content in the seedlings. Two years after planting, humus removal had not affected the growth of the seedlings, but reduced their biomass. The influence of the forest edge, compared to the interior plot, was mostly associated with a decrease in the stand density, reduced amount of litter and increased light availability for the seedlings. [ABSTRACT FROM AUTHOR]

The aim of this study is to produce updated forest map of the Bogdkhan Mountain, Mongolia using multitemporal Sentinel-2A images. The target area has highly mixed forest types and it is very difficult to differentiate the fuzzy boundaries among different forest types. To extract the forest class information, an object-based classification technique is applied and a rule-base to separate the mixed classes is developed. The rule-base uses a hierarchy of rules describing different conditions under which the actual classification has to be performed. To compare the result of the developed method with a result of a pixel-based approach, a Bayesian maximum likelihood classification is applied. The final result indicates overall accuracy of 90.87% for the object-based classification, while for the pixel-based approach it is 79.89%. Overall, the research indicates that the object-based method that uses a thoroughly defined segmentation and a well-constructed rule-base can significantly improve the classification of mixed forest types and produce of a reliable forest map. [ABSTRACT FROM AUTHOR]

Understanding the spatial distribution of dead pine trees (DPTs) in mountainous areas is vital for diseased wood cleanup and the prediction of pine wilt disease. The study induced a deep learning (DL) model of convolutional neural networks (CNNs) for the DPT detection using unmanned aerial vehicle images. Two thousand manually labelled DPT and Non-DPT samples were collected to train (80%) and optimize (20%) the CNNs of AlexNet and GoogLeNet, and 768 samples from other three areas were used to predict the categories in Jinjiang, Fujian, southeastern China. The same dataset was used to compare the classification accuracy between CNNs and the traditional template matching (TM) method. In addition, the potential factors influencing the overall accuracy of the DL model for DPT detection were evaluated. Training results of AlexNet and GoogLeNet showed an accuracy of over 93.30% and 97.38% respectively for the top-1 test after the final training iteration. For the DPT classification in the prediction areas of pure forests, the TM method showed the 56–65% of overall accuracy while CNNs showed 65–80%. CNNs-based DPT detection was more accurate than the traditional TM method. Terrains and red broadleaf trees influence the CNNs-based DPT detection from aerial visible-images in mixed artificial forest and peaks areas. [ABSTRACT FROM AUTHOR]

Effects of species composition on the growth of Norway spruce – Scots pine mixtures had earlier only been studied in unthinned stands. Individual-tree thinning responses in mixed stands were studied to test for the presence of mixture effects in more open stands. Data were collected from 28 temporary sample plots with varying species proportions in 7 thinned spruce-pine stands on medium fertile sites in Eastern Norway. Effects of neighborhood species composition on the individual-tree basal area growth before and after thinning were tested for to detect mixture effects. Spatially-explicit competition indices were used to describe release during thinning in the growth models. Neighborhood species composition only had a minor effect on the thinning response of spruce. Growth before thinning of both species and the thinning response of pine were not affected by species composition. Release had a strong effect on the thinning response of both species. Low density of the studied stands and the more dominant position of pine compared to spruce in mixture, even after the thinning from below, explained some of the observed effects. [ABSTRACT FROM AUTHOR]

Regeneration plays an essential role in the restructuring of plant communities, with seedlings and sprouts representing two different regeneration strategies. As an important timber species, Cunninghamia lanceolata is widely distributed throughout southern and eastern China. However, the morphology and growth of its sprouts and seedlings under natural environments have not been examined in detail. Our study quantified the morphology and growth of Cunninghamia lanceolata during its early regeneration phase. We selected a secondary mixed coniferous forest in the Huangshan region of China as the research location, and examined sapling height, basal stem diameter, lateral branch length, as well as the relationships between main stem and lateral branch elongation, and between sapling basal stem diameter and height. The results showed that high light intensity promoted the extension growth of main stems and the elongation of lateral branches of seedlings. Meanwhile, sprouts generally had shorter height growth than seedlings with the same basal stem diameter, and the growth allocation of seedlings was generally more dependent on light intensity. Our findings suggest that the morphology and growth of C. lanceolata might vary depending on the interaction of regeneration mode (plants originating from sprouts or seedlings) and light intensity. [ABSTRACT FROM AUTHOR]

Radiation detected by sensors can reveal information regarding canopy structure and leaf surface properties. It has been shown that the scattering coefficient (Wλ), a 'pure' spectrum obtained after correction for the effect of canopy structure on the bidirectional reflectance factor (BRF), can provide information about biochemical composition; e.g. nitrogen content, more objectively. However, specular radiation reflected from leaf surface (without any information from the leaf interior) has a potential influence on Wλ and thus consequently affects the estimation of canopy nitrogen content (CNC). The so-called specular reflection influence has rarely been studied. Polarized reflectance (Rp), as part of the specular reflectance, was used to assess this kind of influence. To model the accurate Rp within the study area, six bidirectional polarization distribution function (BPDF) models were intercompared, using the existing POLDER/PARASOL Rp database, to produce Rp for three vegetation types: needleleaf, broadleaf, and mixed forest. Then, correction for polarized reflection and canopy structure was made to yield a more reasonable and accurate Wλ. An efficient interval partial least-squares regression (iPLSR) method for CNC estimation was used to analyse the impact of polarized reflection on both the 400 nm–2,500-nm canopy Wλ and CNC estimation. The results showed that the contribution of polarization was greater in the strong-absorption spectral region, with an influence on Wλ estimation of up to 25% and 28% in the visible and short-wave infrared regions, respectively. Also, improvements of 0.93% in average regarding the relative mean square error of cross-validation (RMSECV) were seen in CNC estimation accuracy. Moreover, sensitivity analyses of BPDF model parameters, and of the fixed total number of intervals in the iPLSR were also conducted. Improvements with an average of 1.19% regarding the RMSECV was consistently seen in the accuracy of CNC regression after polarization correction, no matter how many fixed intervals were. The results also gave guides on the selection of spectral regions used to estimate forest CNC. [ABSTRACT FROM AUTHOR]

The forestry industry in the Basque Country has experienced an abandonment of small-sized forests in which native and introduced species tend to regrow if unattended; thus, requiring an intervention under which proper forest management is implemented. This paper evaluates the potential fractionation of lignin and cellulose from six tree species coming from such mixed forests as a value-added use of wood discarded by logging within the frame of sustainable forest management. The species used were Northern red oak, common oak, common ash, Iberian white birch, sweet chestnut, and black locust. The different wood samples were treated with an Organosolv treatment and elemental chlorine-free bleaching to fractionate them to their main components, recovering the cellulose and the lignin. Cellulose was defibrillated via high-pressure homogenization to obtain cellulose nanofibers. The resulting lignin and cellulose nanofibers were analyzed. The results support the idea that this process offers the opportunity to treat different raw materials in the same process, with corresponding possible economic benefits. [ABSTRACT FROM AUTHOR]

The palynological sequence in core QZMS from Qizimei Mountain, central China, reflects the vegetation and climate dynamics since 12,900 calibrated years before present (cal yr BP). A palynological analysis demonstrated that the temperate deciduous broadleaved and coniferous mixed forest that was present from 12,900 to 10,600 cal yr BP changed to a deciduous broadleaved and coniferous mixed forest from 10,600 to 10,300 cal yr BP due to climate warming. From 10,300 to 7000 cal yr BP, a subtropical and temperate broadleaved and coniferous mixed forest was present. Then, the climate cooled from 7000 to 3000 cal yr BP. The variations in freshwater algae and Sphagnum (AS) and aquatic herbs (AH) indicate that rainfall increased from the early Holocene to 6890 cal yr BP and then gradually decreased. This change in rainfall coincided with changes in the Asian Summer Monsoon (ASM) and rainfall patterns in southern and northern China during different periods. The rainfall pattern was dominated by a shift in the summer rainbelt in the Chinese ASM region, which was mainly driven by orbitally forced changes in insolation and shifts in the El Nino/Southern Oscillation during the Holocene. [ABSTRACT FROM AUTHOR]

Variation in tree biomass and carbon (C) stocks in tropical dry forests is important at both regional and global scale to know their contribution in global C cycle. In Indian tropical forests, the information on variation in tree biomass and C stocks at forest type level is scarce and fragmented. In the present study, three tropical dry deciduous forest types: dry deciduous teak forest (DDTF), dry deciduous mixed forest (DDMF) and Boswellia forest (BF) have been selected in Madhya Pradesh, Central India, to assess the biomass and C stocks. The total tree biomass (aboveground + belowground) ranged from 70.4 (DDTF) to 296.6 (BF) Mg/ha with a mean of 184.1 Mg/ha, whereas the tree C ranged from 35.3 (DDTF) to 140.9 (BF) Mg C/ha with a mean value of 87.4 Mg C/ha. The greatest biomass (220.4 Mg/ha) and C stocks (104.7 Mg C/ha) have been observed in BF type, whereas the least biomass (160.9 Mg/ha) and C (76.4 Mg C/ha) have been observed in DDTF type, with the mean biomass and C stock values of 184.1 Mg/ha and 87.4 Mg C/ha, respectively. In both DDTF and DDMF types, Tectona grandis contributed 76.5 and 26.4% of C, whereas in BF type, Boswellia serrata contributed 73.6% of C to the total C stock. A significant positive (R2 = 0.951; p < 0.01) relationship has been observed between basal area and tree C stock. The present study would improve our understanding of C stocks present in these forest types and could be used to enhance the C sequestration potential through conservation, monitoring and management of such forests. [ABSTRACT FROM AUTHOR]

The Rio Maior deposits, part of the Tagus Basin located in western Portugal, are comprised of sediments from late Pliocene to earliest Gelasian age. Using combined light and scanning electron microscopy, we report, for the first time, nine important taxa in late Pliocene, Piacenzian sediments from south-western Europe. Eight pollen-taxa (Cercidiphyllum, Craigia, Mortoniodendron, Diplopanax, Zanthoxylum, Sapotaceae, Sideroxylon and Leitneria) belong to extant plant groups currently living in tropical to temperate areas. The record of Trigonobalanopsis represents an extinct genus in the oak family (Fagaceae). The records of these taxa indicate the presence of a warm-temperate mixed forest during most parts of the Piacenzian at this latitude. [ABSTRACT FROM AUTHOR]

Pleistocene cave deposits usually provide ideal materials for the study of mammals. Karst caves in Chongzuo, Guangxi Zhuang Autonomous Region of south China are famous for numerous studies on their abundant mammalian fossils and most importantly, Homo sapiens. Unfortunately, the environmental backgrounds, e.g. vegetation and climate, that governed these faunas, are usually lacking because there is no appropriate proxy. In this work, we analysed the palynological assemblages from seven well-dated karst caves in Chongzuo. The ages of these seven caves (2.0–0.11 Ma) cover almost the entire Pleistocene. Though the number of pollen and spores is comparatively low, as expected, we managed to reconstruct the principle vegetation types. The results show that the individual vegetations were mainly warm temperate to subtropical evergreen and deciduous broad-leaved mixed forests. The present study provides important background environmental information on the Pleistocene faunas and Homo sapiens in Guangxi, south China. [ABSTRACT FROM AUTHOR]

Forest canopy structure is an important parameter in multipurpose forest management. An understanding of forest structure plays a particularly important role in the management of uneven-aged forests. The identification of vertical and horizontal variations in forest canopy structure using a ground-based survey is resource intensive, hence often demands for alternative data sources. In this study, one of the advanced remote sensing (RS) techniques, i.e. digital aerial photogrammetry was used to characterize forest canopy structure in a mixed conifer–broadleaf forest. We used aerial imagery acquired with a fixed-wing unmanned aerial vehicle (UAV) platform to produce RS metrics that could be used to classify and map forest structure types at landscape scale. Our results demonstrated that few structural and spectral metrics derived from UAV photogrammetric data, e.g. mean height, standard deviation of height, canopy cover, and percentage broadleaf vegetation cover, could characterize the forest structure across landscapes, particularly at the forest management compartment level, in a limited amount of time. We used cluster analysis for classification of forest structure types and identified five forest structure classes with varying levels of forest canopy structural complexity: (1) short, open-canopy, conifer-dominated structure; (2) short, dense-canopy, broadleaf-dominated structure; (3) tall, closed-canopy, broadleaf-dominated structure; (4) very tall, closed-canopy, conifer-dominated structure with a relatively high degree of variation in canopy height; and (5) very tall, closed-canopy, conifer-dominated structure with a relatively low degree of variation in canopy height. These classes showed relationships with forest management activities (e.g. selection harvesting) and natural disturbances (e.g. typhoon damage). Spatial distribution of forest canopy structural complexity that was revealed in this study is capable of providing important information for forest management planning and habitat modelling. Further, the simple, and flexible data-driven method used in this study to characterize forest structure has the potential to be applied with necessary changes over larger landscapes and different forest types for characterizing and mapping forest structural complexity. [ABSTRACT FROM AUTHOR]

To overcome existing knowledge gaps regarding altering harvest activities in the mixed species and heavily forested USA state of Maine, we used continuous forest inventory data to develop statistical models that predict harvest probability of occurrence and intensity. Among the three modeling approaches examined, the first one directly predicted stand-level basal area removal as a percentage of initial total stand basal area. The second approach first predicted stand-level harvest probability and then the stand-level basal area removal of the harvested plots only. The third approach used the stand-level harvest probability equation of the second approach, while subsequently predicting individual tree harvest probability for only the harvested plots. Among the most influential stand-level attributes were quadratic mean diameter, stand density, elevation, and ownership type, while the most influential tree-level attributes were diameter at breast height, basal area in larger trees, and species. Differences in prediction accuracy between modeling approaches were small with the third approach performing slightly better. Our findings suggest that harvesting in Maine might be less opportunistic and short-term driven than generally perceived. Overall, the analysis highlights the complex array of factors that influence harvesting patterns and provides a framework for better representing contrasting harvest behavior in future wood supply projections. [ABSTRACT FROM AUTHOR]

Forest structure is largely determined by nearest neighbor interactions, and reveals detailed interpretations of the current situation and development potential of the stand. A structure-based method is needed to analyze the relationship of nearest neighbor tree groups and therefore to characterize the forest spatial heterogeneity in a comprehensively and systematically way. A natural mixed forest of Quercus aliena var. acutiserrata and Pinus tabulaeformis in the Xiaolong Mountains, China was taken as an example to demonstrate the telescope method (i.e. N-variate distributions). Each tree with DBH ≥ 5 cm was investigated and located, and the frequencies of N-variate distributions flexibly combined with four structure parameters, uniform angle index, mingling, dominance and crowding were calculated using Excel pivot tables and the Winkelmass software. The telescope method could systematically interpret the forest structural characteristics at different resolutions. Especially, the quadrivariate distribution provides the most detailed and comprehensive spatial structure information. Based on the vertical projection dimension reduction and marginal probability distribution function, the continuous recursive process well revealed the inherently quantitative relationships among different distributions. This could be conducive to flexibly optimizing and reconstructing forest structure, and effectively selecting the trees to be removed. [ABSTRACT FROM AUTHOR]

In this research, the integration of remotely sensed data and Cellular Automata-Markov model (CA-Markov) have been used to analyze the dynamics of land use change and its prediction for the next year. Training phase for the CA-Markov model has been created based on the input pair of land use, which is the result of land use mapping using Maximum Likelihood (ML) algorithm. Three-map comparison has been used to evaluate process accuracy assessment of the training phase for the CA-Markov model. Furthermore, the simulation phase for the CA-Markov model can be used to predict land use map for the next year. The analyze of the dynamics of land use change and its prediction during the period 1990 to 2050 can be obtained that the land serves as a water absorbent surfaces such as primary forest, secondary forest and the mixed garden area continued to decline. Meanwhile, on build land area that can lead to reduced surface water absorbing tends to increase from year to year. The results of this research can be used as input for the next research, which aims to determine the impact of land use changes in hydrological conditions against flooding in the research area. [ABSTRACT FROM AUTHOR]

The expansion of spruce-dominated forestry in Southern Sweden during the twentieth century has led to a considerable amount of oak (Quercus robur L.) woodlands being converted into stands dominated by planted spruce. The thinning of spruces around oak trees is currently done in Sweden to improve local diversity of insects, oak growing conditions and eventually decrease their mortality. To evaluate the effect of these treatments, we dendrochronologically studied growth of old (100-200 years old) oaks subjected to thinning of different intensity at nine locations in southern Sweden, and compared them to oaks located in nearby pastures. The overall pattern suggests that commonly adopted thinning intensities do not significantly affect oak growth. Oak growth was positively related to oak age and negatively to the amount of dead oak crown. Analyses of correlations between oak growth and summer drought conditions, as reflected by location-specific chronologies of the Monthly Drought Code (MDC), indicated that older trees exhibited generally negative correlations, whereas the correlation remained generally positive for the younger trees, both inside and outside forest stands. We propose that removal of spruces should be primarily done around older and healthier-looking trees. [ABSTRACT FROM AUTHOR]