Major Forest Types Research Articles

Tree species composition and diversity in natural temperate forests of the North-Western Himalayas

The present study was undertaken in the natural temperate Himalayan forests of Himachal Pradesh, India, to assess the tree species composition and diversity. For this purpose, six major forest types (FT) viz., FT1- Upper Himalayan Pinus roxburghii forest, FT2- Quercus leucotrichophora forest, FT3- Low-level P. wallichiana forest, FT4- Moist C. deodara forest, FT5- Western Mixed Coniferous Forest, FT6- Pinus gerardiana forest were selected. Detailed sampling was carried out in these forest types, and the sample plots in each forest type were laid out using the stratified random approach. Tree stem density varied from 191.11 N ha−1 (FT6) to 441.11 N ha−1 (FT2), whereas the tree total basal cover varied from 20.01 m2 ha−1 (FT6) to 47.59 m2 ha−1 (FT5). The diversity indices reflected that a total of 21 tree species (16 genera, 11 families) were identified, with tree species richness ranging from 3 (FT6) to 9 (FT1 & FT5). The forest type FT5 recorded the maximum Shannon index of diversity (2.36), Simpson Index of diversity (0.75), Margalef's Index of richness (1.37), pielou equitability (0.74), menheink index of species richness (0.49), whereas the highest Shannon Index of diversity (0.73) and species heterogeneity (0.85) in FT6 forest type. Furthermore, dominance-diversity (d-d) curves drawn that all the six forest types showed geometric curves reveals that one or two tree species are dominant in a particular forest type. Simultaneously, the research area's species diversity, tree stem density, and tree total basal cover were equivalent to those seen in other sections of Western Himalayas.

Stand Volume Growth Modeling with Mixed-Effects Models and Quantile Regressions for Major Forest Types in the Eastern Daxing’an Mountains, Northeast China

The relative growth rate (RGRnv) is the standardized measurement of forest growth, whereby excluding the size differences between individuals allows their performance to be compared equally. The RGRnv model was developed using the National Forest Inventory (NFI) data on the Daxing’an Mountains, in Northeast China, which contain Dahurian larch (Larix gmelinii Rupr.), white birch (Betula platyphylla Suk.), and mixed coniferous–broadleaf forests. Four predictor variables—i.e., quadratic mean diameter (Dq), stand basal area (G), average tree height (Ha), and altitude (A)—and four different methods—i.e., the nonlinear mixed-effects models (NLME), three nonlinear quantile regression (NQR3), five nonlinear quantile regression (NQR5), and nine nonlinear quantile regression (NQR9) models—were used in this study. All the models were validated using the leave-one-out method. The results showed that (1) the mixed coniferous–broadleaf forest presented the highest RGRnv; (2) the RGRnv was negatively correlated with the four predictors, and the heteroscedasticity reduced significantly after the weighting function was integrated into the models; and (3) the quantile regression models performed better than NLME, and NQR9 outperformed both NQR3 and NQR5. To make more accurate predictions, parameters of the adjusted mixed-effects and quantile regression models should be recalculated and localized using sampled RGRnv in each region and then applied to predict all the other RGRnv of plots. MAPE% indicates the mean absolute percentage error. The values were stable when the sample numbers were greater than or equal to six across the three forest types, which showed relatively accurate and lowest-cost prediction results.

Spatial forest vulnerability profile of major forest types in Indian Western Himalaya

Forest vulnerability assessment with ground realities/ data has great implications for adaptation and management planning at local and regional scale. However, such assessments are still limited across globe including the Himalaya. In view of this, present study derived a spatial map of inherent forest vulnerability using ground based observation and information in the western Himalaya. Based on literature and data availability, we selected nine forest vulnerability indicators under four domains i.e., ecological (species richness, and NDVI), climate (temperature, rainfall), topographic (slope, aspect, elevation), disturbances (forest fragmentation) and social (population density). Analytic Hierarchy Process (AHP), which is a multi-criteria decision method, was used for weighting the vulnerability indicators. Based on AHP, forest vulnerability index (FVI) was developed using general linear model approach. The FVI index was further classified into four different categories i.e., low, medium, high and very high. The results revealed maximum (37%) forest grids under medium vulnerable profile followed by 31% (high) and 21% (low) vulnerable grids. In general, temperate and mixed forests show higher forest vulnerability in the region, whereas subtropical pine, broadleaf and subalpine forests falls under lesser vulnerable forest grids. These results exhibited that elevation (15.4%), population density (15.1%), slope (14.5%), rainfall (13.7%), forest fragmentation (12.9%), temperature (12.3), and aspect (11.4%) are the major drivers of forest vulnerability, particularly for the Himalayan region. To validate the results, we compared the developed FVI in present study with ground based FVI already generated in previous studies from the region, and found higher similarity in the assessments. The spatial forest vulnerability maps generated in the present study provides a realistic profile of vulnerable forests in Indian western Himalaya, which can be used for developing adaptation measure and management planning.

Tree species mixing causes a shift in fine‐root soil exploitation strategies across European forests

Abstract Mixed‐species forests have often been shown to enhance above‐ground ecosystem properties and processes. Despite the significance of fine roots for tree and ecosystem functioning, the role of tree species diversity for below‐ground processes driven by fine roots remains largely unknown. Previously, an underyielding of fine‐root biomass (FRB) in tree mixtures across four major European forest types has been reported. To explain this phenomenon, we tested here the effect of tree species mixing on fine‐root traits related to soil exploitation efficiency, including biotic feedbacks from ectomycorrhizal fungi (EcM), and assessed the role of root trait dissimilarity. We analysed morphological and chemical traits as well as ectomycorrhizal colonisation intensity of absorptive fine roots (i.e. first three most distal orders) in soil samples from 315 mixed and mono‐specific tree neighbourhoods in mainly mature, semi‐natural forest stands across Europe. Additionally, we quantified mycorrhizal abundance and diversity in soil samples from the same stands. At the community level, fine roots in tree mixtures were characterised by higher specific root lengths and root nitrogen concentrations, lower diameters and root tissue densities indicating a faster resource acquisition strategy compared to mono‐specific stands. The higher root EcM colonisation intensity and soil EcM diversity in mixtures compared to mono‐specific stands may further provide evidence for positive biotic feedbacks. Moreover, the diversity of fine‐root traits influenced FRB, as mixtures characterised by a higher trait dissimilarity were linked to a lower reduction in FRB. At the level of phylogenetic groups, thin‐rooted angiosperm species showed stronger responses to mixing than thick‐rooted gymnosperms, especially in terms of root morphology and EcM colonisation, indicating different strategies of response to tree mixing. Our results indicate that a lower FRB can reflect a shift in soil resource acquisition strategies, rather than a lower performance of trees in mixtures. They show that several non‐exclusive mechanisms can simultaneously explain negative net effects of mixing on FRB. This study sheds new light on the importance of using integrative approaches including both above‐ and below‐ground biomass and traits to study diversity effects on plant productivity. A free Plain Language Summary can be found within the Supporting Information of this article.

Spatial patterns and associations of tree species at different developmental stages in a montane secondary temperate forest of northeastern China.

BackgroundSecondary forests have become the major forest type worldwide. Research on spatial patterns and associations of tree species at different developmental stages may be informative in understanding the structure and dynamic processes of secondary forests.MethodsIn this study, we used point pattern analysis to analyze the spatial patterns and associations of tree species at seedling, sapling and adult stages in a 4ha plot in the montane secondary temperate forest of northeastern China.ResultsWe found that species showed similar patterns at seedling, sapling and adult stages, and aggregation was the dominant pattern. The spatial patterns of tree species were mainly affected by habitat heterogeneity. In addition, the strength of positive or negative associated pattern among tree species would decrease with developmental stages, which attributed to neighborhood competition and plant size increasing.ConclusionsOur results indicated that the spatial patterns and associations of tree species at seedling and sapling stages partly reflected that at adult stage; habitat heterogeneity and neighborhood competition jointly contributed to species coexistence in this secondary forest.

Diversity, regeneration, and anthropogenic disturbance in major Indian Central Himalayan forest types: implications for conservation

Diversity, regeneration, and anthropogenic disturbance in major Indian Central Himalayan forest types: implications for conservation

Developing stand volume, biomass and carbon stock models for ten major forest types in forest region of northeastern China

Developing stand volume, biomass and carbon stock models for ten major forest types in forest region of northeastern China

Post-Glacial Climate–Fire Interactions Control Tree Composition of Mesic Temperate Forests in Eastern North America

Stand-scale gap-phase dynamics is generally viewed as the main driver of development in mesic deciduous forests of the temperate biome. Soil charcoal of temperate forests in eastern North America are unnoticed in most surveys, thus explaining why fire is undervalued as a driver of forest succession. The extent to which gap-phase, fire, or other processes are responsible for the regeneration and maintenance of mesic deciduous forests is unknown because paleoecological evidence is lacking. We tested the fire-driven succession hypothesis on the development of this major forest type. Based on charcoal 14C dates of two sites, 44 and 55 fires occurred since early Holocene, with a mean interval of 170 to 215 years. The vegetation of both sites followed comparable post-glacial trajectories consisting of three distinct periods. Conifers dominated the two first periods during 5200–6000 years and were replaced by hardwoods–conifers over the last 3500 years. The first period was represented by boreal conifers, whereas the second period, dominated by white pine (Pinus strobus) forests, persisted during 3000–4300 years. The third period marked the development of hardwood (sugar maple, Acer saccharum) forests. Fires occurred continuously on the sites since early Holocene likely under dry conditions during the conifer periods and cooler and moister conditions during the hardwood–conifer period. Recurrent fires appear with climate as key drivers of the long-term dynamics of several temperate forests in eastern North America. Similar studies on other temperate forests should be pursued to test the hypothesis of climate–fire interactions influencing tree composition change.

The role of hunting on Sapajus xanthosternos' landscape of fear in the Atlantic Forest, Brazil.

Habitats with spatial variation in food availability, predation risk, and hunting pressure allow us to study how animals resolve the trade-off between food searching and predator avoidance. We investigated the influence of food availability, predation risk, and the perceived predation risk on habitat use by a primate living under high hunting pressure, the yellow-breasted capuchin monkeys, Sapajus xanthosternos, at Una Biological Reserve (ReBio Una). We hypothesized that the hunting pressure occurring in the capuchins' home range would favor predator avoidance to the detriment of searching for food. We characterized a set of covariates related to resource availability (fruit and invertebrate biomasses, feeding on dispersed and clumped food items, sleeping sites), perceived predation risk (alarm calls given to terrestrial and aerial predators, silent group movement, and vigilance behavior), and actual predation risk (evidence of hunting) and estimated their effects on how one group of capuchin monkeys uses its habitat. The group divides its time among three major forest types within their home range: agroforest, mature, and secondary. Our results suggest that the actual and perceived risk of hunting by humans, as well as the perceived predation risk by both terrestrial and aerial predators, were significant determinants of capuchin monkeys' space use. Yellow-breasted capuchin monkeys' space use was negatively related to the risk of hunting by humans (actual evidence and silent behavior), the perceived risk of predation by both aerial and terrestrial predators, and the presence of sleeping sites. Capuchin monkeys' use of space was not related to the biomass of fruits in the habitat, and the biomass of invertebrates had a very low positive effect. We confirmed our prediction that in a habitat with high hunting pressure, the risk of predation, both perceived and actual, had a more significant impact on how yellow-breasted capuchins used space than did food availability.

Global patterns of forest autotrophic carbon fluxes

Carbon (C) fixation, allocation, and metabolism by trees set the basis for energy and material flows in forest ecosystems and define their interactions with Earth's changing climate. However, while many studies have considered variation in productivity with latitude and climate, we lack a cohesive synthesis on how forest carbon fluxes vary globally with respect to climate and one another. Here, we draw upon 1,319 records from the Global Forest Carbon Database, representing all major forest types and the nine most significant autotrophic carbon fluxes, to comprehensively review how annual C cycling in mature, undisturbed forests varies with latitude and climate on a global scale. Across all flux variables analyzed, rates of C cycling decreased continuously with absolute latitude-a finding that confirms multiple previous studies and contradicts the idea that net primary productivity of temperate forests rivals that of tropical forests. C flux variables generally displayed similar trends across latitude and multiple climate variables, with no differences in allocation detected at this global scale. Temperature variables in general, and mean annual temperature or temperature seasonality in particular, were the best single predictors of C flux, explaining 19%-71% of variation in the C fluxes analyzed. The effects of temperature were modified by moisture availability, with C flux reduced under hot and dry conditions and sometimes under very high precipitation. Annual C fluxes increased with growing season length and were also influenced by growing season climate. These findings clarify how forest C flux varies with latitude and climate on a global scale. In an era when forests will play a critical yet uncertain role in shaping Earth's rapidly changing climate, our synthesis provides a foundation for understanding global patterns in forest C cycling.

Stand structure and species diversity regulate biomass carbon stock under major Central Himalayan forest types of India

BackgroundData on the impact of species diversity on biomass in the Central Himalayas, along with stand structural attributes is sparse and inconsistent. Moreover, few studies in the region have related population structure and the influence of large trees on biomass. Such data is crucial for maintaining Himalayan biodiversity and carbon stock. Therefore, we investigated these relationships in major Central Himalayan forest types using non-destructive methodologies to determine key factors and underlying mechanisms.ResultsTropical Shorea robusta dominant forest has the highest total biomass density (1280.79 Mg ha−1) and total carbon density (577.77 Mg C ha−1) along with the highest total species richness (21 species). The stem density ranged between 153 and 457 trees ha−1 with large trees (> 70 cm diameter) contributing 0–22%. Conifer dominant forest types had higher median diameter and Cedrus deodara forest had the highest growing stock (718.87 m3 ha−1); furthermore, C. deodara contributed maximally toward total carbon density (14.6%) among all the 53 species combined. Quercus semecarpifolia–Rhododendron arboreum association forest had the highest total basal area (94.75 m2 ha−1). We found large trees to contribute up to 65% of the growing stock. Nine percent of the species contributed more than 50% of the carbon stock. Species dominance regulated the growing stock significantly (R2 = 0.707, p < 0.001). Temperate forest types had heterogeneous biomass distribution within the forest stands. We found total basal area, large tree density, maximum diameter, species richness, and species diversity as the predominant variables with a significant positive influence on biomass carbon stock. Both structural attributes and diversity influenced the ordination of study sites under PCA analysis. Elevation showed no significant correlation with either biomass or species diversity components.ConclusionsThe results suggest biomass hyperdominance with both selection effects and niche complementarity to play a complex mechanism in enhancing Central Himalayan biomass carbon stock. Major climax forests are in an alarming state regarding future carbon security. Large trees and selective species act as key regulators of biomass stocks; however, species diversity also has a positive influence and should also reflect under management implications.

ForestGEO: Understanding forest diversity and dynamics through a global observatory network

ForestGEO is a network of scientists and long-term forest dynamics plots (FDPs) spanning the Earth's major forest types. ForestGEO's mission is to advance understanding of the diversity and dynamics of forests and to strengthen global capacity for forest science research. ForestGEO is unique among forest plot networks in its large-scale plot dimensions, censusing of all stems ≥1 cm in diameter, inclusion of tropical, temperate and boreal forests, and investigation of additional biotic (e.g., arthropods) and abiotic (e.g., soils) drivers, which together provide a holistic view of forest functioning. The 71 FDPs in 27 countries include approximately 7.33 million living trees and about 12,000 species, representing 20% of the world's known tree diversity. With >1300 published papers, ForestGEO researchers have made significant contributions in two fundamental areas: species coexistence and diversity, and ecosystem functioning. Specifically, defining the major biotic and abiotic controls on the distribution and coexistence of species and functional types and on variation in species' demography has led to improved understanding of how the multiple dimensions of forest diversity are structured across space and time and how this diversity relates to the processes controlling the role of forests in the Earth system. Nevertheless, knowledge gaps remain that impede our ability to predict how forest diversity and function will respond to climate change and other stressors. Meeting these global research challenges requires major advances in standardizing taxonomy of tropical species, resolving the main drivers of forest dynamics, and integrating plot-based ground and remote sensing observations to scale up estimates of forest diversity and function, coupled with improved predictive models. However, they cannot be met without greater financial commitment to sustain the long-term research of ForestGEO and other forest plot networks, greatly expanded scientific capacity across the world's forested nations, and increased collaboration and integration among research networks and disciplines addressing forest science.

Tree biomass distribution patterns with a forest succession in subtropical China

AbstractTo better understand the effect of forest succession on biomass sequestration, we investigated biomass stock and allocation of evergreen broadleaf forest, a major zonal forest type in subtropical China. To analyze the biomass patterns and dynamics with forest succession, three forest types, pine (Pinus massoniana Lamb.) forest (PF), pine and broadleaf mixed forest (MF) and evergreen broadleaf forest (BF), were selected and their tree biomasses were investigated. The results showed that the biomass of the arbor layer was the highest in BF, which was 292.51 t/hm2, followed by MF and PF with 206.87 and 171.76 t/hm2, respectively. It indicated that tree biomass increased with the forest succession. The biomass patterns in arbor layer were similar during the forest succession, in which the biomass of trunks accounted for the largest proportion in the total biomass decreased with the forest succession, but the proportion of the biomass of roots increased with the forest succession. The biomass of the diameter class above 20 cm in PF, MF and BF contributed to a large proportion of the total biomass. With the succession, the increase of tree species diversity has a positive effect on the increase of tree biomass. Our results indicated that forest succession can sequestrate biomass carbon and alleviate the global climate change.

Low root functional dispersion enhances functionality of plant growth by influencing bacterial activities in European forest soils.

Current studies show that multispecies forests are beneficial regarding biodiversity and ecosystem functionality. However, there are only little efforts to understand the ecological mechanisms behind these advantages of multispecies forests. Bacteria are among the key plant growth-promoting microorganisms that support tree growth and fitness. Thus, we investigated links between bacterial communities, their functionality and root trait dispersion within four major European forest types comprising multispecies and monospecific plots. Bacterial diversity revealed no major changes across the root functional dispersion gradient. In contrast, predicted gene profiles linked to plant growth activities suggest an increasing bacterial functionality from monospecific to multispecies forest. In multispecies forest plots, the bacterial functionality linked to plant growth activities declined with the increasing functional dispersion of the roots. Our findings indicate that enriched abundant bacterial operational taxonomic units are decoupled from bacterial functionality. We also found direct effects of tree species identity on bacterial community composition but no significant relations with root functional dispersion. Additionally, bacterial network analyses indicated that multispecies forests have a higher complexity in their bacterial communities, which points towards more stable forest systems with greater functionality. We identified a potential of root dispersion to facilitate bacterial interactions and consequently, plant growth activities.

A Multi Sensor Approach to Forest Type Mapping for Advancing Monitoring of Sustainable Development Goals (SDG) in Myanmar

Monitoring forests is important for measuring overall success of the 2030 Agenda because forests play an essential role in meeting many Sustainable Development Goals (SDG), especially SDG 15. Our study evaluates the contribution of three satellite data sources (Landsat-8, Sentinel-2 and Sentinel-1) for mapping diverse forest types in Myanmar. This assessment is especially important because Myanmar is currently revising its classification system for forests and it is critical that these new forest types can be accurately mapped and monitored over time using satellite imagery. Our results show that using a combination of Sentinel-1 and Sentinel-2 yields the highest accuracy (89.6% ± 0.16 percentage point(pp)), followed by Sentinel-2 alone (87.97% ± 0.11 pp) and Landsat-8 (82.68% ± 0.13 pp). The higher spatial resolution of Sentinel-2 Blue, Green, Red, Narrow Near Infrared and Short Wave Infrared bands enhances accuracy by 4.83% compared to Landsat-8. The addition of the Sentinel-2 Near Infrared and three Vegetation Red Edge bands further improve accuracy by 0.46% compared to using only Sentinel-2 Blue, Green, Red, Narrow Near Infrared and Short Wave Infrared bands. Adding the radar information from Sentinel-1 further increases the accuracy by 1.63%. We were able to map the two major forest types, Upper Moist and Upper Dry Mixed Deciduous Forest, which comprise 90% of our study area. Accuracies for these forest types ranged from 77 to 96% depending on the sensors used, demonstrating the feasibility of using satellite data to map forest categories from a newly revised classification system. Our results advance the ongoing development of the National Forest Monitoring System (NFMS) by the Myanmar Forest Department and United Nations-Food and Agriculture Organization (UN-FAO) and facilitates future monitoring of progress towards the SDGs.

The Influence of Environmental Variation on the Genetic Structure of a Poison Frog Distributed Across Continuous Amazonian Rainforest.

Biogeographic barriers such as rivers have been shown to shape spatial patterns of biodiversity in the Amazon basin, yet relatively little is known about the distribution of genetic variation across continuous rainforest. Here, we characterize the genetic structure of the brilliant-thighed poison frog (Allobates femoralis) across an 880-km-long transect along the Purus-Madeira interfluve south of the Amazon river, based on 64 individuals genotyped at 7609 single-nucleotide polymorphism (SNP) loci. A population tree and clustering analyses revealed 4 distinct genetic groups, one of which was strongly divergent. These genetic groups were concomitant with femoral spot coloration differences, which was intermediate within a zone of admixture between two of the groups. The location of these genetic groups did not consistently correspond to current ecological transitions between major forest types. A multimodel approach to quantify the relative influence of isolation-by-geographic distance (IBD) and isolation-by-environmental resistance (IBR) nevertheless revealed that, in addition to a strong signal of IBD, spatial genetic differentiation was explained by IBR primarily linked to dry season intensity (r2 = 8.4%) and canopy cover (r2 = 6.4%). We show significant phylogenetic divergence in the absence of obvious biogeographical barriers and that finer-scaled measures of genetic structure are associated with environmental variables also known to predict the density of A. femoralis.

Ecosystem-level carbon storage and its links to diversity, structural and environmental drivers in tropical forests of Western Ghats, India

Tropical forests are rich in biodiversity with great potential for carbon (C) storage. We estimated ecosystem-level C stock using data from 70 forest plots in three major forest types: tropical dry deciduous (TDD I and TDD II), tropical semi-evergreen (TSE I and TSE II) and tropical evergreen forests (TEF I, TEF II and TEF III) of Kanyakumari Wildlife Sanctuary, Western Ghats, India. The average C stock in these forests was 336.8 Mg C/ha, of which 231.3, 3.0, 2.4, 15.2 and 84.9 Mg C/ha were stored in woody vegetation, understorey, litter, deadwood and soil respectively. The live vegetation, detritus and soil contributed 65.5%, 5.5% and 29% respectively to the total ecosystem-level C stock and distributed in forest types in the order: TEF III > TEF II > TEF I > TSE I > TDD II > TSE II > TDD I. The plant diversity, structural attributes and environmental factors showed significant positive correlations with C stocks and accounted for 6.7, 77.2 and 16% of variance. These findings indicate that the tropical forests in the Western Ghats store large amount of C, and resulting data are invaluable for planning and monitoring forest conservation and management programs to enhance C storage in tropical forests.

Assessing the Vulnerability of Military Installations in the Coterminous United States to Potential Biome Shifts Resulting from Rapid Climate Change.

Climate-change impacts to Department of Defense (DoD) installations will challenge military mission and natural resource stewardship efforts by increasing vulnerability to flooding, drought, altered fire regimes, and invasive species. We developed biome classifications based on current climate for the coterminous United States using the Holdridge Life Zone system to assess potential change on DoD lands. We validated classifications using comparisons to existing ecoregional classifications, the distribution of major forest types, and tree species in eastern North America. We projected future life zones for mid- and late-century time periods under three greenhouse gas emission scenarios (low-B1, moderate-A1B, and high-A2) using an ensemble of global climate models. To assess installation vulnerability (n = 529), we analyzed biome shifts using spatial cluster analysis to characterize interregional variation, and identified representative installations for subsequent landscape-level analyses. Although mean annual temperatures are expected to increase, installations located in the Northeast, Lake States, and western Great Plains are likely to experience the largest proportional increases in temperature. Accordingly, forest and grassland communities at these installations managed to support a wide range of training, and environmental objectives may be adversely affected by altered disturbance regimes, heat, and moisture stress. However, precipitation is projected to increase in the Northeast and Lake States mitigating some effects of increased temperatures on biological communities. Given the uncertain response to climate change in different ecoregions, additional environmental and stewardship attributes are needed within a decision-support framework to understand vulnerabilities and provide appropriate responses.

Soil solution in Swiss forest stands: A 20 year's time series.

Soil solution chemistry is influenced by atmospheric deposition of air pollutants, exchange processes with the soil matrix and soil-rhizosphere-plant interactions. In this study we present the results of the long-term Intercantonal Forest Observation Program in Switzerland with soil solution measurements since 1998 on a current total of 47 plots. The forest sites comprise two major forest types of Switzerland including a wide range of ecological gradients such as different nitrogen (N) deposition and soil conditions. The long-term data set of 20 years of soil solution measurements revealed an ongoing, but site-specific soil acidification. In strongly acidified soils (soil pH below 4.2), acidification indicators changed only slowly over the measured period, possibly due to high buffering capacity of the aluminum buffer (pH 4.2-3.8). In contrast, in less acidified sites we observed an increasing acidification rate over time, reflected, for example, by the continuous decrease in the ratio of base cations to aluminum (BC/Al ratio). Nowadays, the main driver of soil acidification is the high rate of N deposition, causing cation losses and hampering sustainable nutrient balances for tree nutrition. Mean nitrate leaching rates for the years 2005-2017 were 9.4 kg N ha-1 yr-1, ranging from 0.04 to 53 kg N ha-1 yr-1. Three plots with high N input had a remarkable low nitrate leaching. Both N deposition and nitrate leaching have decreased since 2000. However, the latter trend may be partly explained due to increased drought in recent years. Nonetheless, those high N depositions are still affecting the majority of the forest sites. Taken together, this study gives evidence of anthropogenic soil acidification in Swiss forest stands. The underlying long-term measurements of soil solution provides important information on nutrient leaching losses and the impact climate change effects such as droughts. Furthermore, this study improves the understanding of forest management and tree mortality regarding varying nitrate leaching rates.

Predicting Vegetation Carbon Density Distribution in different Terrains in Subtropical Forests in China

ABSTRACT 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.