Nitrogen deposition and increased precipitation interact to affect fine root production and biomass in a temperate forest: Implications for carbon cycling

Different responses of canopy and shrub leaves to canopy nitrogen and water addition in warm temperate forest

Introduction

Understanding the effects of nitrogen deposition and increased rainfall on plants is critical for maintaining forest ecosystem services. Although previous studies primarily examined the effects of environmental changes on leaf functional traits, the underlying physiological and metabolic processes associated with these traits remain poorly understood and warrant further investigation.

Methods

To address this knowledge gap, we evaluated the influence of canopy nitrogen (25 kg ha-1 yr-1) and water (30% of the local precipitation) addition on leaf functional traits, diversity, and associated physiological and metabolic processes in the dominant species of tree and shrub layers.

Results

Only the interaction between nitrogen and water significantly reduced the functional richness (FRic) of the community. The other treatments had no notable effects on functional diversity. Importantly, the physiological processes of trees and shrubs showed different regulatory strategies. In addition, there were significant changes in 29 metabolic pathways of the tree, whereas only 18 metabolic pathways were significantly altered in shrub. Among the identified metabolic pathways, four were annotated multiple times, with amino acid metabolism being the most active.

Discussion

These regulatory processes enable the leaves to withstand external disturbances and maintain their relative stability under changing environmental conditions. The study findings underscore the limitations of previous research, which often relied on the direct application of treatments to the understory and so failed to accurately assess the effects of nitrogen and water on leaf functional traits. Future studies should adopt canopy-level nitrogen and water addition to better simulate the impacts of global environmental change.

Additive Effects of Multiple Global Change Drivers on Terrestrial Nitrogen Cycling Worldwide

Global change has dramatically altered the Earth's biogeochemical cycles. However, the interactive effects of multiple global change factors (GCFs) on terrestrial nitrogen (N) cycling worldwide remain unclear, limiting the ability to predict how future global change will affect the global N cycle. We conducted a meta-analysis of 108 published articles to evaluate the main and interactive effects of elevated CO2, N addition, warming, and altered precipitation on soil N pools (NH4 +, NO3 -, and organic N) and transformation rates (N mineralization, nitrification, and denitrification) across terrestrial ecosystems. Results showed that single GCFs impacted the soil N cycle in different directions and magnitudes, with N addition and increased precipitation having the strongest positive effects on N pools and transformation rates, respectively. Moreover, the positive effects of N addition on the soil N cycle were generally enhanced when combined with other GCFs. Although the interactions of multiple GCFs were commonly additive (66.2%-83.3%), both synergistic (10.5%-15.1%) and antagonistic (2.8%-18.9%) effects were also observed. The types of treatment and ecosystem, geographic location, and climate all regulated the responses of soil N pools to GCFs to some degree, while only the types of treatment and ecosystem significantly affected the response of soil transformation rates to GCFs. These findings emphasize the importance of considering interactive effects among GCFs on terrestrial N cycling and highlight the necessity of incorporating these interactions into Earth system models for accurate predictions of N cycling responses to global changes.

Dynamics of soil carbon stock in response to land use conversion in European woodland and shrubland in the last decade

Soil carbon sequestration and its monitoring is important to improve climate resilience and mitigate global warming. According to the European Environment Agency (EEA), soils in Europe are losing carbon that could hamper achieving the EU climate targets. Hence, it is necessary to explore the dynamics of soil organic carbon (SOC) storage in different ecosystems so that the EU policymakers can observe the progress towards achieving EU Green Deal objectives. The aim of this research was to quantify the ΔSOC-S in woodland and shrubland in the last decade (2009-2018) and to study the ΔSOC-S due to the land use conversion. In this regard, revisited sampling points between 2009 and 2018 from the topsoil (0-20 cm) of woodland and shrubland of the EU + UK soil database named Land Use/Land Cover Area Frame Survey (LUCAS) was used. The analysis revealed that broadleaved-woodland to coniferous- or mixed-woodland conversion in 2018, and shrubland to woodland conversion in 2015 increased SOC-S. Overall, we found a net accumulation of SOC-S in woodland (2184.08 ton ha-1) and shrubland (302.78 ton ha-1) soil with 7.78% increment in woodland and 12.56% in shrubland between 2009/12 and 2018. Also, in central Europe, mean annual temperature (MAT) increased and precipitation (MAP) decreased between the study periods. The relationship between precipitation and temperature showed that precipitation and SOC-S in woodland had no relationship, but with the rising temperature, SOC-S in both land types significantly decreased revealing warming can significantly affect SOC-S.

Response of Root Respiration to Warming and Nitrogen Addition Depends on Tree Species

Roots contribute a large fraction of CO2 efflux from soils, yet the extent to which global change factors affect root-derived fluxes is poorly understood. We investigated how red maple (Acer rubrum) and red oak (Quercus rubra) root biomass and respiration respond to long-term (15 years) soil warming, nitrogen addition, or their combination in a temperate forest. We found that ecosystem root respiration was decreased by 40% under both single-factor treatments (nitrogen addition or warming) but not under their combination (heated × nitrogen). This response was driven by the reduction of mass-specific root respiration under warming and a reduction in maple root biomass in both single-factor treatments. Mass-specific root respiration rates for both species acclimated to soil warming, resulting in a 43% reduction, but were not affected by N addition or the combined heated × N treatment. Notably, the addition of nitrogen to warmed soils alleviated thermal acclimation and returned mass-specific respiration rates to control levels. Oak roots contributed disproportionately to ecosystem root respiration despite the decrease in respiration rates as their biomass was maintained or enhanced under warming and nitrogen addition. In contrast, maple root respiration rates were consistently higher than oak, and this difference became critical in the heated × nitrogen treatment, where maple root biomass increased, contributing significantly more CO2 relative to single-factor treatments. Our findings highlight the importance of accounting for the root component of respiration when assessing soil carbon loss in response to global change and demonstrate that combining warming and N addition produces effects that cannot be predicted by studying these factors in isolation.

A meta-analysis reveals increases in soil organic carbon following the restoration and recovery of croplands in Southwest China

In China, the Grain for Green Program (GGP) is an ambitious project to convert croplands into natural vegetation, but exactly how changes in vegetation translate into changes in soil organic carbon remains less clear. Here we conducted a meta-analysis using 734 observations to explore the effects of land recovery on soil organic carbon and nutrients in four provinces in Southwest China. Following GGP, the soil organic carbon content (SOCc) and soil organic carbon stock (SOCs) increased by 33.73% and 22.39%, respectively, compared with the surrounding croplands. Similarly, soil nitrogen increased, while phosphorus decreased. Outcomes were heterogeneous, but depended on variations in soil and environmental characteristics. Both the regional land use and cover change indicated by the landscape type transfer matrix and net primary production from 2000 to 2020 further confirmed that the GGP promoted the forest area and regional mean net primary production. Our findings suggest that the GGP could enhance soil and vegetation carbon sequestration in Southwest China and help to develop a carbon-neutral strategy.

Influence of nitrogen water interaction on leaf functional traits of dominant species in warm temperate forest

Plant functional traits are indicative of plant responses to environmental changes, influencing ecosystem functions. Leaves, as a key focus in studying plant functional traits, present an area where the impact of nitrogen deposition and altered rainfall patterns on functional diversity remains ambiguous. To elucidate plant response mechanisms to environmental factors, we employed a canopy-based platform to add nitrogen, water, and their combination. We assessed the functional traits and community-weighted mean of the leaves of three dominant trees and three dominant shrubs. The results showed that nitrogen addition to the canopy significantly increased the leaf dry matter content of the Celtis sinensis Pers, but markedly decreased the specific leaf area of the Liquidambar formosana Hance. The nitrogen-water interaction did not notably affect the specific leaf area and equivalent water thickness of leaves. Canopy addition of nitrogen, water, and their combined interaction substantially lowered leaf nitrogen content and markedly increased leaf C/N. The structural equation model demonstrated a significant negative correlation between leaf dry matter content, equivalent water thickness, and leaf nitrogen content, as well as between equivalent water thickness and leaf phosphorus content. Our results provide evidence for the adaptation of plants to the environment and different strategies for resource and energy utilization.

Depth-dependent responses of soil organic carbon under nitrogen deposition

Emerging evidence points out that the responses of soil organic carbon (SOC) to nitrogen (N) addition differ along the soil profile, highlighting the importance of synthesizing results from different soil layers. Here, using a global meta-analysis, we found that N addition significantly enhanced topsoil (0-30 cm) SOC by 3.7% (±1.4%) in forests and grasslands. In contrast, SOC in the subsoil (30-100 cm) initially increased with N addition but decreased over time. The model selection analysis revealed that experimental duration and vegetation type are among the most important predictors across a wide range of climatic, environmental, and edaphic variables. The contrasting responses of SOC to N addition indicate the importance of considering deep soil layers, particularly for long-term continuous N deposition. Finally, the lack of depth-dependent SOC responses to N addition in experimental and modeling frameworks has likely resulted in the overestimation of changes in SOC storage under enhanced N deposition.

Precipitation change affects forest soil carbon inputs and pools: A global meta-analysis

The impacts of precipitation change on forest carbon (C) storage will have global consequences, as forests play a major role in sequestering anthropogenic CO2. Although forest soils are one of the largest terrestrial C pools, there is great uncertainty around the response of forest soil organic carbon (SOC) to precipitation change, which limits our ability to predict future forest C storage. To address this, we conducted a meta-analysis to determine the effect of drought and irrigation experiments on SOC pools, plant C inputs and the soil environment based on 161 studies across 139 forest sites worldwide. Overall, forest SOC content was not affected by precipitation change, but both drought and irrigation altered plant C inputs and soil properties associated with SOC formation and storage. Drought may enhance SOC stability by altering soil aggregate fractions, but the effect of irrigation on SOC fractions remains unexplored. The apparent insensitivity of SOC to precipitation change can be explained by the short duration of most experiments and by biome-specific responses of C inputs and pools to drought or irrigation. Importantly, we demonstrate that SOC content is more likely to decline under irrigation at drier temperate sites, but that dry forests are currently underrepresented across experimental studies. Thus, our meta-analysis advances research into the impacts of precipitation change in forests by revealing important differences among forest biomes, which are likely linked to plant adaptation to extant conditions. We further demonstrate important knowledge gaps around how precipitation change will affect SOC stability, as too few studies currently consider distinct soil C pools. To accurately predict future SOC storage in forests, there is an urgent need for coordinated studies of different soil C pools and fractions across existing sites, as well as new experiments in underrepresented forest types.

Fine root biomass and morphology in a temperate forest are influenced more by canopy water addition than by canopy nitrogen addition

Introduction

Increasing atmospheric N deposition and changes in precipitation patterns could profoundly impact forest community structure and ecosystem functions. However, most N and water (W) addition experiments have focused on direct N application to leaf litter or soil, neglecting canopy processes such as leaf evaporation and absorption.

Methods

In this study, we aimed to assess the effects of atmospheric N deposition and increased precipitation on the fine root biomass and morphology of plants in a temperate deciduous forest. To achieve this, we applied N and W above the forest canopy and quantified the seasonal dynamics (January, July, and October) of fine root biomass and morphology.

Results

Our results revealed that only canopy W addition significantly increased the biomass of fine roots in January compared to that in other seasons (p < 0.05). We observed no significant interaction effect of N and W on fine root biomass. However, we found that the different growth seasons had a significant impact on the fine root biomass (p < 0.001). The combined application of N and W significantly affected the root tip density (p = 0.002). Although canopy N addition was significantly positively correlated with available soil N (p < 0.05), we detected no significant association with fine root biomass or morphology.

Discussion

The findings of this study indicated that fine root biomass and morphology, are affected to a greater extent by the provision of W than by N application. These findings provide a new perspective and a more precise understanding of the effects of the actual N deposition and precipitation on the dynamics of plant fine roots in forest ecosystems.

Significant effects of precipitation frequency on soil respiration and its components-A global synthesis

Global warming intensifies the hydrological cycle, which results in changes in precipitation regime (frequency and amount), and will likely have significant impacts on soil respiration (R_s ). Although the responses of R_s to changes in precipitation amount have been extensively studied, there is little consensus on how R_s will be affected by changes in precipitation frequency (PF) across the globe. Here, we synthesized the field observations from 296 published papers to quantify the effects of PF on R_s and its components using meta-analysis. Our results indicated that the effects of PF on R_s decreased with an increase in background mean annual precipitation. When the data were grouped by climate conditions, increased PF showed positive effects on R_s under the arid condition but not under the semi-humid or humid conditions, whereas decreased PF suppressed R_s across all the climate conditions. The positive effects of increased PF mainly resulted from the positive response of heterotrophic respiration under the arid condition while the negative effects of decreased PF were mainly attributed to the reductions in root biomass and respiration. Overall, our global synthesis provided for the first time a comprehensive analysis of the divergent effects of PF on R_s and its components across climate regions. This study also provided a framework for understanding and modeling responses of ecosystem carbon cycling to global precipitation change.

Enhanced cadmium phytoremediation capacity of poplar is associated with increased biomass and Cd accumulation under nitrogen deposition conditions

Nitrogen (N) deposition plays a significant role in soil cadmium (Cd) phytoremediation, and poplar has been considered for the remediation of contaminated soil because of its enormous biomass and strong Cd resistance. To reveal the underlying physiological and root phenotypic mechanisms of N deposition affecting Cd phytoextraction in poplar, we assessed root phenotypic characteristics, Cd absorption and translocation, chlorophyll fluorescence performance, and antioxidant enzyme activities of a clone of Populus deltoides × P. nigra through combined greenhouse Cd and N experiments. Our results showed that Cd significantly changed the root phenotype by reducing root length, tip number, and diameter. Cd also caused the peroxidation of lipids, damaged the photosystem II (PSII) reaction centre, and reduced photosynthetic capacity, resulting in a decrease in biomass accumulation in poplar. The N60 (60 kg N·ha^-1·yr^-1) and N90 (90 kg N·ha^-1·yr^-1) treatments promoted the net photosynthetic rate of poplar by increasing the activity of antioxidant enzymes and proline content and repairing the PSII reaction centre, thus increasing the biomass accumulation of poplar exposed to Cd stress. Simultaneously, the N60 and N90 treatments might have increased Cd uptake from the soil by upregulating total root length, root tips, and fine root length. Cd mainly accumulated in roots and stems but not in leaves. The N30 (30 kg N·ha^-1·yr^-1) treatment had no obvious effects on these parameters compared with the single Cd treatment. Consequently, our study suggested that adequate N can improve biomass and Cd accumulation to enhance the phytoremediation capacity of poplar for Cd, which might be related to the improvement of leaf physiological defence and the change in root phenotypic characteristics.

Fine-root functional trait response to nitrogen deposition across forest ecosystems: A meta-analysis

Nitrogen (N) deposition has complex effects on vegetation dynamics and nutrient cycling in terrestrial ecosystems. However, how N deposition alters fine root traits remains unclear in forest ecosystems. Here, we carried out a synthesis based on 890 paired observations of 14 fine root traits from 79 articles to assess the effects of N deposition on fine root traits. The results showed that N deposition mainly affected root nutrient content and stoichiometry. Specifically, N deposition increased the root N content, root carbon: phosphorus (C:P) and root nitrogen: phosphorus (N:P) ratio, but decreased the root P content and root C:N ratio. Moreover, N deposition increased fine root respiration, but had no significant effect on other root morphological and physiological traits. N deposition effects on fine root biomass, root tissue density and fungal colonization decreased with N deposition duration. Compared to fine root P content, N deposition effects on fine root C content and C:P ratio increased with N deposition level. Moreover, the interaction between N deposition level and duration significantly affected fine root biomass. N deposition effects on fine-root biomass decreased with greater N deposition duration, especially in high N deposition experiments. Moreover, the effect of N deposition on root diameter decreased with mean annual temperature and mean annual precipitation. N form, forest type and soil depth significantly affect the effect of N deposition on fine root C:P. Therefore, the effects of N deposition on fine root traits were not only determined by N deposition level, duration and their interactions, but also regulated by abiotic factors. These findings highlight the diverse responses of fine root traits to N deposition have strong implications for forest ecosystems soil carbon stocks in a world of increasing N deposition associated with decreased root-derived carbon inputs and increases in fine-root respiration.

Asymmetric nexus between technological innovation and environmental degradation in Sweden: an aggregated and disaggregated analysis

The number of studies on the relationship between technological innovation and CO₂ emissions has gradually increased in recent years, although there is no clear agreement in the literature. Previous research has revealed both positive and negative consequences of technological innovation on the environment. Moreover, most researchers have used linear approaches to explore this connection, which can result in spurious outcomes when nonlinearities exist in the data. According to this background, this research utilizes asymmetric ARDL and spectral causality approaches to assess the asymmetric connection between technological innovation and CO₂ emissions in Sweden utilizing data from 1980 to 2018. In addition, the disaggregated asymmetric effects of technological innovation (patent resident and patent nonresident) on CO₂ are also captured in this study. The Nonlinear Autoregressive Distributed lag (NARDL) results showed that positive (negative) shocks in economic growth enhance environmental quality in Sweden. Furthermore, a positive (negative) shock in technological innovation causes a decrease (increase) in CO₂. Similarly, a positive (negative) shock in patent nonresident and residents leads to a decrease (increase) in CO₂ emissions in Sweden. The outcomes from the spectral causality revealed that in the medium and long term, aggregate and disaggregate technological innovation can predict CO₂ emissions in Sweden. This study has significant policy implications for policymakers and the government in Sweden. Based on these findings, the study suggests that the government of Sweden should investment in technological innovation since it plays a vital role in curbing environmental degradation.

The spillover of tourism development on CO2 emissions: a spatial econometric analysis

Climate change and tourism's interaction and vulnerability have been among the most hotly debated topics recently. In this context, the study focuses on how CO2 emissions, the primary cause of global warming and climate change, respond to changes in tourism development. In order to do so, the impact of tourism development on CO2 emissions in the most visited countries is investigated. A panel data from 2000 to 2017 for top 70 tourist countries are analysed using a spatial econometric method to investigate the spatial effect of tourism on environmental pollution. The direct, indirect, and overall impact of tourism on CO2 emissions are estimated using the most appropriate generalized nested spatial econometric (GNS) method. The findings reveal that tourism has a positive direct effect and a negative indirect effect; both are significant at the 1% level. The negative indirect effect of tourism is greater than its direct positive effect, implying an overall significantly negative impact. Further, the outcome of financial development and CO2 emissions have an inverted U-shaped and U-shaped relationship in direct and indirect impacts. Population density, trade openness, and economic growth significantly influence environmental pollution. In addition, education expenditure and infrastructure play a significant moderating role among tourism and environmental pollution. The results have important policy implications as they establish an inverted-U-shaped relationship among tourism and CO2 emissions and indicate that while a country's emissions initially rise with the tourism industry's growth, it begins declining after a limit.

The dynamics of public spending on sustainable green economy: role of technological innovation and industrial structure effects

In order to achieve the goal of sustainable green economic development, it is necessary to conduct a comprehensive assessment of the efficiency of the green economy and compare it with emission reductions. The green economy idea is a much-discussed solution to economic growth. Therefore, this study investigated the impact of government spending on the performance of the green economy of various countries under the "Belt and Road" (BRI) initiative project. The data were analyzed using the BRI economy panel data from 2008 to 2018. The generalized method of moments (GMM) was used to estimate the effect of government expenditures on education and research and development (R&D) on green economic performance index (GEE) in BRI countries. The results reveal that during the study period, BRI countries have experienced an upward transition towards green development, except for Pakistan and Bangladesh; their GEE decreased gradually from 2010 to 2018. Further, the findings of the system GMM revealed that both education and R&D have a positive impact on the green economy. Moreover, the compositional and technological effects of the overall sample were verified with the GMM process. Nevertheless, the sub-sample results revealed a heterogeneous impact on countries with a high per capita GDP. Following the results, useful policy measures for promoting sustainable green economic development have been proposed.

A novel approach for DDoS attacks detection in COVID-19 scenario for small entrepreneurs

The current COVID-19 issue has altered the way of doing business. Now that most customers prefer to do business online, many companies are shifting their business models, which attracts cyber attackers to launch several kinds of cyberattacks against commercial companies simultaneously. The most common and lethal DDoS attack disables the victim's online resources. While large businesses can afford defensive measures against DDoS assaults, the situation is different for new entrepreneurs. Their lack of security resources restricts their ability to ward off DDoS attacks. Here, we aim to highlight the problems that prospective entrepreneurs should be aware of before joining the business, followed by a filtering mechanism that efficiently identifies DDoS assaults in the COVID-19 scenario, which is the subject of our research. The suggested approach employs statistical and machine learning techniques to discriminate between DDoS attack data and regular communication. Our suggested framework is cost-effective and identifies DDoS attack traffic with a 92.8% accuracy rate.

Classification of catchments for nitrogen using Artificial Neural Network Pattern Recognition and spatial data

In hydrological modelling, classification of catchments is a fundamental task for overcoming deficits in observational datasets. Most attention on this issue has focussed on identifying the catchments with similar hydrological responses for streamflow. Yet, effective methods for catchment classification are currently lacking in respect to Dissolved Inorganic Nitrogen (DIN), a water quality constituent that, at increasing concentrations, is threatening nutrient sensitive environments. Pattern recognition, using standard Artificial Neural Network algorithm is applied, as a novel approach to classify datasets that are considered to be suitable proxies for biological and anthropogenic drivers of observed DIN releases. Eleven gauged Great Barrier Reef (GBR) catchments within Queensland Australia are classified using spatial datasets extracted from ecosystem (e.g. original ecosystem responses to biogeographic, land zone, land form, and soil type attributes) and land use maps. To evaluate the performance of the examined spatial datasets as a proxy for deductive classification, the classification process is repeated inductively, using observed DIN and streamflow data from gauging stations. The ANN-PR method is seen to generate the same classification score format for the differing dataset types, and this facilitates a direct comparison for model output for observed data corroborations. The Kruskal-Wallis test for independence, at p > 0.05, identifies the deductive classification approach as a predictor for classification using DIN observations, which lacks an independence from each other at a p value of 0.01 and 0.02. This study concludes that an ANN-PR method can integrate the ecosystem and land use mapping data to deductively classify the GBR catchments into four regions that also have similar patterns of DIN concentrations. Due to the uniform availability of the mapping data, the findings provide a sound basis for further investigations into the transposing of knowledge from gauged catchments to ungauged areas.

Is there a tradeoff between financial globalization, economic growth, and environmental sustainability? An advanced panel analysis

In recent years, many empirical studies investigated the effects of globalization on the ecological footprint (EF). Most of these studies relied on the KOF index of globalization and studied the effects of total globalization and disaggregated impacts of economic, social, and political globalization on the EF. However, less attention has been given to financial globalization which can also influence the EF. Hence, this study investigates the association between financial globalization (FG), economic growth (GDP), and EF controlling population density (PD) in the selected West Asian and the Middle East (WAME) nations from 1990 to 2017. The study relied upon second-generation methods for checking stationary properties and Westerlund and other techniques to scrutinize cointegration. The evidence showed cointegration in the model. The long-run approximations from continuously updated fully modified (CUP-FM) and continuously updated bias corrected (CUP-BC) tests divulge that financial globalization is an important factor to promote ecological sustainability in the sample countries because it decreases EF. Population density exacerbates EF and worsens environmental deterioration in sample countries. The study detected the environmental Kuznets curve (EKC) between EF and economic growth in the presence of financial globalization and population density. Besides, financial globalization Granger causes EF, while the feedback effect exists between EF and economic growth. Based on these results, WAME economies can accomplish ecological sustainability and sustainable development by enhancing their financial globalization levels.

The Influence of Climate Warming and Humidity on Plant Diversity and Soil Bacteria and Fungi Diversity in Desert Grassland

Our study, which was conducted in the desert grassland of Ningxia in China (E 107.285, N 37.763), involved an experiment with five levels of annual precipitation 33% (R33), 66% (R66), 100% (CK), 133% (R133), 166% (R166) and two temperature levels (inside Open-Top Chamber (OTC) and outside OTC). Our objective was to determine how plant, soil bacteria, and fungi diversity respond to climate change. Our study suggested that plant α-diversity in CK and TCK were significantly higher than that of other treatments. Increased precipitation promoted root biomass (RB) growth more than aboveground living biomass (ALB). R166 promoted the biomass of Agropyron mongolicum the most. In the fungi communities, temperature and precipitation interaction promoted α-diversity. In the fungi communities, the combination of increased temperature and natural precipitation (TCK) promoted β-diversity the most, whose distance was determined to be 25,124 according to PCA. In the bacteria communities, β-diversity in CK was significantly higher than in other treatments, and the distance was determined to be 3010 according to PCA. Soil bacteria and fungi α- and β-diversity, and ALB promoted plant diversity the most. The interactive effects of temperature and precipitation on C, N, and P contents of plants were larger than their independent effects.

A Combination of Biotic and Abiotic Factors and Diversity Determine Productivity in Natural Deciduous Forests

The relative importance of different biotic and abiotic variables for estimating forest productivity remains unclear for many forest ecosystems around the world, and it is hypothesized that forest productivity could also be estimated by local biodiversity factors. Using a large dataset from 258 forest monitoring permanent sample plots distributed across uneven-aged and mixed forests in northern Iran, we tested the relationship between tree species diversity and forest productivity and examined whether several factors (solar radiation, topographic wetness index, wind velocity, seasonal air temperature, basal area, tree density, basal area in largest trees) had an effect on productivity. In our study, productivity was defined as the mean annual increment of the stem volume of a forest stand in m3 ha−1 year−1. Plot estimates of tree volume growth were based on averaged plot measurements of volume increment over a 9-year growing period. We investigated relationships between productivity and tree species diversity using parametric models and two artificial neural network models, namely the multilayer perceptron (MLP) and radial basis function networks. The artificial neural network (ANN) of the MLP type had good ability in prediction and estimation of productivity in our forests. With respect to species richness, Model 4, which had 10 inputs, 6 hidden layers and 1 output, had the highest R2 (0.94) and the lowest RMSE (0.75) and was selected as the best species richness predictor model. With respect to forest productivity, MLP Model 2 with 10 inputs, 12 hidden layers and 1 output had R2 and RMSE of 0.34 and 0.42, respectively, representing the best model. Both of these used a logistic function. According to a sensitivity analysis, diversity had significant and positive effects on productivity in species-rich broadleaved forests (approximately 31%), and the effects of biotic and abiotic factors were also important (29% and 40%, respectively). The artificial neural network based on the MLP was found to be superior for modeling productivity–diversity relationships.

Alkoxysulfenylation of alkenes: development and recent advances

Among the wide variety of synthetic transformations of inexpensive and abundant feedstock alkenes, vicinal difunctionalization of carbon-carbon double bonds represent one of the most powerful and effective strategies for the introduction of two distinct functional groups into target compounds in a one-pot process. In this context, the direct alkoxysulfenylation of alkenes has emerged as an elegant method to construct valuable β-alkoxy sulfides in an atom- and pot-economic manner utilizing readily accessible starting materials. Here, we review the available literature on this appealing research topic by hoping that it will be beneficial for eliciting further research and thinking in this domain.

Canopy and understory nitrogen addition have different effects on fine root dynamics in a temperate forest: implications for soil carbon storage

Elucidating the effects of atmospheric nitrogen (N) deposition on fine root dynamics and the potential underlying mechanisms is required to understand the changes in belowground and aboveground carbon storage. However, research on these effects in forests has mostly involved direct understory addition of N and has ignored canopy interception and processing of N. Here, we conducted a field experiment comparing the effects of canopy addition of N (CAN) with those of understory addition of N (UAN) at three N-addition rates (0, 25 and 50 kg N ha^-1  yr^-1 ) on fine root dynamics in a temperate deciduous forest. Fine root production and biomass were significantly higher with CAN than with UAN. At the same N-addition rate, increases in fine root production with CAN were at least two-fold greater than with UAN. At the high N-addition rate and relative to the control, fine root biomass was significantly increased by CAN (by 23.5%) but was significantly decreased by UAN (by 12.2%). Our results indicate that traditional UAN may underestimate the responses of fine root dynamics to atmospheric N deposition in forest ecosystems. Canopy N processes should be considered for more realistic assessments of the effects of atmospheric N deposition in forests.