North-South Transect Of Eastern China Research Articles

The unimodal latitudinal pattern of K, Ca and Mg concentration and its potential drivers in forest foliage in eastern China

Potassium (K), calcium (Ca), and magnesium (Mg) are essential elements with important physiological functions in plants. Previous studies showed that leaf K, Ca, and Mg concentrations generally increase with increasing latitudes. However, recent meta-analyses suggested the possibility of a unimodal pattern in the concentrations of these elements along latitudinal gradients. The authenticity of this unimodal latitudinal pattern, however, requires validation through large-scale field experimental data, and exploration of the underlying mechanisms if the pattern is confirmed. Here, we collected leaves of common species of woody plants from 19 montane forests in the north-south transect of eastern China, including 322 species from 160 genera, 67 families; and then determined leaf K, Ca, and Mg concentrations to explore their latitudinal patterns and driving mechanisms. Our results support unimodal latitudinal patterns for all three elements in woody plants across eastern China, with peak values at latitude 36.5 ​± ​1.0° N. The shift of plant-functional-type compositions from evergreen broadleaves to deciduous broadleaves and to conifers along this latitudinal span was the key factor contributing to these patterns. Climatic factors, mainly temperature, and to a lesser extent solar radiation and precipitation, were the main environmental drivers. These factors, by altering the composition of plant communities and regulating plant physiological activities, influence the latitudinal patterns of plant nutrient concentrations. Our findings also suggest that high leaf K, Ca, and Mg concentrations may represent an adaptive strategy for plants to withstand water stress, which might be used to predict plant nutrient responses to climate changes at large scales, and broaden the understanding of biogeochemical cycling of K, Ca, and Mg.

Machine learning algorithms realized soil stoichiometry prediction and its driver identification in intensive agroecosystems across a north-south transect of eastern China

Soil carbon (C), nitrogen (N), and phosphorus (P) are required components to maintain ecosystem structure, function, and services. Accurate soil nutrient stoichiometry assessments are crucial for precisely managing agricultural and natural ecosystems. However, direct measurement and evaluation of soil characteristics can be costly and time-consuming. The development of statistical and machine learning-based methods for predicting soil C:N:P stoichiometry and microbial dynamics is of great significance. The objective of this study is to compare the performance of four machine learning models, i.e., support vector machine, random forest, extreme gradient boosting, and gradient boosting decision tree, in predicting soil C:N:P stoichiometry and net N mineralization rate and to evaluate their applicability to different agricultural land use types and climate zones. Our results showed that extreme gradient boosting (average R2 > 0.81, RMSE <16.39, RPD > 2.67) and gradient boosting decision tree (average R2 > 0.77, RMSE <16.40, RPD > 2.32) models performed the best in predicting C:N:P stoichiometry, demonstrating high accuracy and stability. Machine learning models produced higher accuracy in the vegetable field (except for C:N) than in the rice paddy field with average accuracy improvement of 42.9 %. The prediction performance in warm temperate and subtropical regions was inferior to cold regions. Feature importance assessment suggests that electrical conductivity, total N, and water-filled pore space may have significant predictive roles in the rice paddy field, while mean annual precipitation, total P, and silt content could be important factors in the vegetable field. When predicting the net N mineralization rate, soil texture may emerge as a crucial factor in the rice paddy field, whereas moisture content may play a key role in the vegetable field. Thus, machine learning models can be recommended to predict soil C:N:P stoichiometry and net N mineralization rate for precise agricultural practices.

A distinctive latitudinal trend of nitrogen isotope signature across urban forests in eastern China.

Rapid urbanization has greatly altered nitrogen (N) cycling from regional to global scales. Compared to natural forests, urban forests receive much more external N inputs with distinctive abundances of stable N isotope (δ15 N). However, the large-scale pattern of soil δ15 N and its imprint on plant δ15 N remain less well understood in urban forests. By collecting topsoil (0-20 cm) and leaf samples from urban forest patches in nine large cities across a north-south transect in eastern China, we analyzed the latitudinal trends of topsoil C:N ratio and δ15 N as well as the correlations between tree leaf δ15 N and topsoil δ15 N. We further explored the spatial variation of topsoil δ15 N explained by corresponding climatic, edaphic, vegetation-associated, and anthropogenic drivers. Our results showed a significant increase of topsoil C:N ratio towards higher latitudes, suggesting lower N availability at higher latitudes. Topsoil δ15 N also increased significantly at higher latitudes, being opposite to the latitudinal trend of soil N availability. The latitudinal trend of topsoil δ15 N was mainly explained by mean annual temperature, mean annual precipitation, and atmospheric deposition of both ammonium and nitrate. Consequently, tree leaf δ15 N showed significant positive correlations with topsoil δ15 N across all sampled plant species and functional types. Our findings reveal a distinctive latitudinal trend of δ15 N in urban forests and highlight an important role of anthropogenic N sources in shaping the large-scale pattern of urban forest 15 N signature.

Controls on soil dissolved organic carbon along the 4000 km North-South forest transect in Eastern China

Dissolved organic carbon (DOC) is both a potential source and stability indicator of soil organic carbon (SOC), and plays a pivotal role in global C cycling and sequestration. However, at a large scale, still not enough information is known about relations between DOC in soils and various controlling factors in natural forest ecosystems. We sampled 252 soil samples (6 replicates and 3 depths for each site) from four long-term forest ecosystem stations in Changbaishan, Beijng Donglingshan, Shennongjia and Dinghushan along a 4000 km North-South transect in Eastern China. We found that higher soil DOC concentrations were observed in subtropical forests over the North-South transect. The highest and lowest DOC concentrations in the upper 60 cm soil layer were found in monsoon evergreen broadleaved forest (DIII, 113.8 ± 1.4 mg C/L) and Yue spruce-fir forest (CIII, 57.6 ± 3.0 mg C/L), respectively. The Haplic ferralsol (DII-DIV, 89.7 mg C/L) and Haplic Andosol (CIII, 57.6 mg C/L) showed the highest and the lowest DOC concentrations in the upper 60 cm soil layer, respectively. The soil DOC concentrations generally decreased from surface soil to subsoil in the forests with mean annual precipitation (MAP) ≥ 1500 mm. The lower proportion of DOC accounting for SOC in the upper 20 cm soil layer in temperate forests, among which Yue spruce-fir forest (CIII, 3.2 %) presented the lowest ratio, indicated a larger long-term soil C sequestration potential. The DOC concentrations in the upper 60 cm soil layer significantly correlated with mean annual temperature (MAT) (R2 = 0.50) and MAP (R2 = 0.46). However, in the upper 20 cm soil layer, forest type (R2 = 0.48) was the most significant correlation factor to DOC concentration. We concluded that in the North-South transect of Eastern China, MAT, MAP and forest type are the most significant large-scale factors controlling soil DOC, with temperate forests (especially Yue spruce-fir forest) possessing the highest long-term soil C sequestration potential.

Differential responses of fungal and bacterial necromass accumulation in soil to nitrogen deposition in relation to deposition rate

Influenced by nitrogen (N) deposition, changes in soil organic carbon (SOC) sequestration in terrestrial ecosystems could provide strong feedback to climate change. Mounting evidence showed that microbial necromass contributes substantially to SOC sequestration; however, how N deposition influences microbial necromass accumulation in soils remains elusive. We investigated the impacts of N deposition on soil microbial necromass, assessed by amino sugars, at seven forest sites along a north-south transect in eastern China. We found that the responses of fungal and bacterial necromass accumulation to N deposition depended on the deposition rate, with high N deposition (>50 kg N ha−1 yr−1) stimulating fungal necromass accumulation from 29.1 % to 35.2 %, while low N deposition damaging the accumulation of bacterial necromass in soil by 12.1 %. On the whole, N deposition benefitted the dominance of fungal over bacterial necromass, with their ratio being significantly greater at high-N level. The accumulation of microbial necromass was primarily governed by soil properties, including nutrients stoichiometry, clay content and pH, while the composition of microbial necromass was conjointly affected by soil properties and microbial community structure. The latitudinal distribution of microbial necromass contributions to SOC pool was not altered by N deposition, and was firmly controlled by the climatic and edaphic factors. Collectively, our results reveal the impacts of N deposition on microbial necromass accumulation in soil and the geographical pattern across forest ecosystems in eastern China, providing implications for our accurate predictions of global change impacts on SOC sequestration.

Soil carbon quantity and form are controlled predominantly by mean annual temperature along 4000 km North-South transect of Eastern China

The forest ecosystem plays a key role in mitigating global climate change through carbon sequestration in its biomass and soils to limit the rising atmospheric concentration of CO2. However, the combined overall interaction of climate and forest type on the quantities and forms of soil carbon (organic vs. inorganic) has not yet been sufficiently investigated. In this study, the contents of soil total carbon (STC), soil organic carbon (SOC) and soil inorganic carbon (SIC) were measured along the 4000 km North-South Transect of Eastern China. We sampled 252 soil samples (6 replicates for each site, 3 depths for each site) from four long-term ecosystem experimental stations in Dinghushan, Shennongjia, Beijing and Changbaishan, along the transect from south to north, including 14 different forest types. The contents of STC, SOC, and SIC in the upper 60 cm soil layer varied in different types of forest with 34–107 g C kg−1, 31–104 g C kg−1, and 1.5–8 g C kg−1, respectively. The northern fir and birch forest, most notably in Changbaishan, had the highest STC and SOC contents. The higher SIC contents were found in the southern evergreen broad-leaved forests in Dinghushan and Shennongjia. The contents of STC, SOC and SIC differed significantly in terms of mean annual temperature (MAT), mean annual precipitation (MAP), forest type, and soil depth. In the upper 60 cm soil layer, the most significant correlations occurred between SOC (or STC) and MAT (R2SOC = −0.62, R2STC = −0.60) when compared with the correlation between SOC (or STC) and MAP (R2SOC = −0.45, R2STC = −0.45) or elevation (R2SOC = 0.48, R2STC = 0.48). The soil stratification ratio (SR) of STC and SOC were typically ∼2–3 in most forests and even reached 5– 7 in Changbaishan forest, indicating a well-functioning ecosystem overall. We concluded that on the near-continental scale (4000 km), forest soil carbon contents and forms (SOC, STC, SIC) were controlled most strongly by temperature (MAT). Therefore, an innovative selection of a specific forest type (fir or broad-leaved forest) within set temperature regimes can better contribute to maximizing soil carbon content and thus optimize its sequestration on the national to near-continental scale to mitigate climate change.

Variation in functional trait diversity from tropical to cold-temperate forests and linkage to productivity

Functional trait diversity is an integrative plant trait index that represents an emerging and promising approach for exploring gross primary productivity (GPP); however, it is necessary to determine how these indices vary at large scales in natural forests to establish their linkage to GPP. Here, we explored spatial variation in functional diversity and underlying linkages to GPP in the natural forests of China. Specifically, we consistently measured 10 leaf traits related to the GPP of 366 tree species in nine typical forests along the North-South Transect of Eastern China and calculated three functional diversity indices (functional richness, FRic; functional evenness, FEve; and functional divergence, FDiv) for each community. All three indices consistently varied in different directions along the transect, due to the impact of climate (temperature and precipitation). FRic increased with temperature and precipitation, whereas FDiv decreased. FRic and FDiv (but not FEve) were identified as important metrics influencing GPP at large scales. Functional diversity, climate, and soil combined explained 90.4% of total variation in GPP from cold-temperate to tropical forests. The results confirmed that there is spatial variation in functional trait diversity, and that functional diversity is important for determining spatial variation in GPP in natural forests at large scales and should be integrated into ecological models.

Root nutrient capture and leaf resorption efficiency modulated by different influential factors jointly alleviated P limitation in Quercus acutissima across the North-South Transect of Eastern China.

Soil and climatic conditions are known to have close associations with plant morphological and stoichiometric traits at a regional scale along latitudinal gradients; however, how latitude drives biotic and abiotic factors affecting plant nutrient acquisition to accommodate environmental nutrient deficiency remains unclear. We quantified soil, root, leaf, and leaf litter nitrogen (N) and phosphorus (P) concentrations to determine the potentially limiting nutrient and the simultaneous responses of root capture and leaf resorption to nutrient deficiency in seven Quercus acutissima forests across the North-South Transect of Eastern China. The results showed that the mean leaf and root N:P ratios in Q. acutissima were 21.58 and 20.23, respectively, which markedly exceeded the P limitation threshold of 16 for terrestrial plants. The mean leaf litter N and P were 10.63 mg/g and 0.51 mg/g, respectively, indicating that P resorption proficiency was relatively higher than N resorption proficiency. N displayed higher stoichiometric homeostasis than P in the leaf. The leaf and root N:P ratios showed a quadratic variation that first decreased and then increased as latitude increased, whereas the phosphorus resorption efficiency and root-soil accumulation factor of P displayed the opposite trend. Partial least square path modeling ( PLS-PM) analysis demonstrated that root nutrient capture and leaf nutrient resorption were regulated by different influential factors. Overall, these findings provide new insights into plant strategies to adapt to environmental nutrient deficiency, as well as the scientific basis for predicting the spatial and temporal patterns of nutrient acquisition in the context of climate change.

Soil microbial respiration in forest ecosystems along a north-south transect of eastern China: Evidence from laboratory experiments

Soil microbial respiration (MR) is a key process controlling the soil-atmosphere CO2 flux, and is widely studied at individual sites. Yet its spatial variation and underlying mechanism at larger spatial scales are still poorly understood, limiting our estimates of the carbon cycle in terrestrial ecosystems and its feedbacks to climate change. Here, a novel incubation experiment based on the mean annual temperature of soil origin sites along a 4,200 km north–south forest transect of eastern China was conducted to investigate the spatial variations in MR. MR showed a hump-shaped relationship with latitude and peaked around 32° N, which coincided exactly with the ecotone of subtropical and temperate forests. Climate, soil physicochemical and microbial traits explained 56.1% of the total variations in MR across the transect, whereas explained 77.4% and 34.6% in tropical and subtropical versus temperate region, respectively. Soil physicochemical properties were consistently more important in controlling the MR's variation than other variables. Specifically, soil organic carbon was the most important factor in regulating the MR's variation across the transect, whereas its significance decreased when scaling down to tropical and subtropical regions. The mean annual temperature turned into the best indicator of MR in tropical and subtropical forests, whereas the combination of soil organic carbon with total nitrogen concentrations primarily regulated the variations in MR in temperate region. Collectively, our study showed a non-linear latitudinal pattern of soil MR and revealed the diverged controlling factors and mechanisms of MR in different climatic regions. These findings can potentially improve our capacity to predict the soil CO2 flux in Earth system models and the feedbacks to climate change.

Potential gross nitrogen mineralization and its linkage with microbial respiration along a forest transect in eastern China

Nitrogen (N) mineralization in soils generally controls biological N availability in terrestrial ecosystems. As the pivotal first step in the overall N mineralization process, gross N mineralization (GNM, defined as the production of ammonium from microbial mineralization of organic N) is inherently coupled with microbial mineralization of soil organic carbon (C) which is commonly referred to as microbial respiration (MR), and that has often been used as a proxy of C availability. However, the pattern of GNM and its underlying mechanisms at a regional scale, and its linkage with MR remain unclear. By analyzing 100 soil samples collected across different forest types along a 3800 km long north-south transect in eastern China, we simultaneously measured the potential GNM using a 15N pool dilution method and MR using a dynamic CO2 trapping technique. We conducted a structural equation model (SEM) to examine the interactive effects of climate, soil pH, microbial substrate availability, and microbial biomass on potential GNM along the forest transect. Furthermore, we conducted a non-linear regression analysis between potential GNM and MR. We found that both potential GNM and MR varied largely, from 0.55 to 16.14 mg N kg−1 soil d−1 and from 3.64 to 24.30 mg C kg−1 soil d−1, respectively, but were not significantly affected by forest type. The SEM analysis showed that 51% of the variation in potential GNM was explained, with microbial substrate availability being the most important influencing factor. There was a positive non-linear relationship between potential GNM and MR (R2 = 0.52, P < 0.0001). Notably, MR alone exerted a comparable role in explaining the variation in potential GNM compared to the interactive effects between multiple factors used in the SEM. Our findings confirm the dominant control of C availability to microbes on potential GNM, and necessitate the incorporation of MR for better modeling GNM in forest soils.

Stable isotopic signatures of carbon and nitrogen in soil aggregates following the conversion of natural forests to managed plantations in eastern China

Land cover change (LCC) from natural forest (NF) to plantations (PF) has occurred worldwide over the past several decades. However, the different LCC effects on soil aggregate C and N turnover in various climatic zones remain uncertain. Soil samples were taken from both NF and PF at five sites along an approximately 4200 km north-south transect in eastern China. We measured soil aggregate C and N concentrations, and δ13C and δ15N. The soil aggregate distribution is similar between NF and PF, except that the mass proportion of microaggregate is lower in NF. The impacts of LCC on soil C and N concentrations, and δ13C and δ15N vary among five climate zones. The changes in soil aggregate C and N concentrations and δ15N induced by LCC show nonlinear relationships with climatic factors (i.e., MAT and MAP), and there is a linear relationship between soil aggregate Δδ13C (calculated by subtracting PF from NF) and MAT and MAP. The soil aggregate C and N concentrations, and δ13C and δ15N show clear trends along the climatic transect. In addition, the impacts of LCC are more obvious in topsoil than in subsoil. Our findings highlight that the impacts of LCC on soil C and N concentrations are related to climatic factors. Specifically, that the increased decomposition of soil C in PF than NF can be compensated by higher C inputs with increasing MAT and MAP.

Assessing the Impacts of Extreme Climate Events on Vegetation Activity in the North South Transect of Eastern China (NSTEC)

Extreme climate events frequently exert serious effects on terrestrial vegetation activity. However, these effects are still uncertain in widely distributed areas with different climate zones. Transect analysis is important to understand how terrestrial vegetation responds to climate change, especially extreme climate events, by substituting space for time. In this paper, seven extreme climate indices and the Normalized Difference Vegetation Index (NDVI) are employed to examine changes in the extreme climate events and vegetation activity. To reduce the uncertainty of the NDVI, two satellite-derived NDVI datasets, including the third generation Global Inventory Monitoring and Modeling System (GIMMS-3g) NDVI dataset and the NDVI from the National Oceanic and Atmospheric Administration (NOAA) satellites on Star Web Servers (SWS), were employed to capture changes in vegetation activity. The impacts of climate extremes on vegetation activity were then assessed over the period of 1982–2012 using the North–South Transect of Eastern China (NSTEC) as a case. The results show that vegetation activity was overall strengthened from 1982 to 2012 in the NSTEC. In addition, extreme high temperature events revealed an increased trend of approximately 5.15 days per decade, while a weakened trend (not significant) was found in extreme cold temperature events. The strengthened vegetation activities could be associated with enhanced extreme high temperature events and weakened extreme cold temperature events over the past decades in most of the NSTEC. Despite this, inversed changes were also found locally between vegetation activity and extreme climate events (e.g., in the Northeast Plain). These phenomena could be associated with differences in vegetation type, human activity, as well as the combined effects of the frequency and intensity of extreme climate events. This study highlights the importance of accounting for the vital roles of extreme climate effects on vegetation activity.

Plant functional traits determine latitudinal variations in soil microbial function: evidence from forests in China

Abstract. Plant functional traits have increasingly been studied as determinants of ecosystem properties, especially for soil biogeochemical processes. While the relationships between biological community structures and ecological functions are a central issue in ecological theory, these relationships remain poorly understood at the large scale. We selected nine forests along the North–South Transect of Eastern China (NSTEC) to determine how plant functional traits influence the latitudinal pattern of soil microbial functions and how soil microbial communities and functions are linked at the regional scale. We found that there was considerable latitudinal variation in the profiles of different substrate use along the NSTEC. Specifically, we found that the substrate use by microorganisms was highest in the temperate forest soils (soil microbial substrate use intensities of 10–12), followed by the subtropical forest soils (soil microbial substrate use intensities of 7–10), and was least in the coniferous forest soils (soil microbial substrate use intensities of 4–7). The latitudinal variation in soil microbial function was more closely related to plant functional traits (leaf dry matter content, leaf C concentrations, and leaf N concentrations, P=0.002) than climate (mean annual precipitation, P=0.022). The soil silt, leaf dry matter, and leaf C and N contents were the main controls on the biogeographical patterns of microbial substrate use in these forest soils. The soil microbial community structures and functions were significantly correlated along the NSTEC. Soil carbohydrate and polymer substrate use were mainly related to soil Gram-positive (G+) bacterial and actinomycic phospholipid fatty acids (PLFAs), while the use of amine and miscellaneous substrates were related to soil Gram-negative (G−) bacterial and fungal PLFAs. The enzyme production varied with changes in the soil microbial communities. The soil enzyme activities were positively correlated with the bacterial PLFAs but were not correlated with the fungal PLFAs. The soil organic matter (SOM) decomposition rates were significantly higher in the temperate forests than in the subtropical and tropical forests, emphasizing the rapid degradability of high-energy substrates such as soil microbial biomass carbon, carbohydrates, and amino acids. The SOM decomposition rates were significantly and negatively related to soil dissolved organic carbon concentrations, carboxylic acids, polymers, and miscellaneous substrate use. The relationships between soil PLFAs and microbial substrate use, enzyme activities, and SOM decomposition rate show that as the soil microbial community structure changes, soil biogeochemical processes also change.

Evaluation of future runoff variations in the north–south transect of eastern China: effects of CMIP5 models outputs uncertainty

AbstractRunoff is an important water flux that is difficult to simulate and predict due to lacking observation. Meteorological forcing data are a key factor in causing the uncertainty of predicted runoff. In this study, climate projections from ten general circulation models of the Coupled Model Intercomparison Project 5 (CMIP5) with high resolution under the Representative Concentration Pathway (RCP) 4.5 scenario are employed to estimate the future uncertainty range of predicted runoff in the North–South Transect of Eastern China (NSTEC) from 2011 to 2100. It is found that the range of future annual runoff is from 268.9 mm (Meteorological Research Institute coupled GCM, MRI-CGCM3) to 544.2 mm (Model for Interdisciplinary Research on Climate, MIROC5). The precipitation and the annual actual evapotranspiration are two key factors that affect the variation of runoff. The low annual runoff for the MRI-CGCM3 model may be caused by low precipitation and high annual actual evapotranspiration (466.9 mm). However, the high annual runoff for the MIROC5 may be caused by the high precipitation, although there is high annual actual evapotranspiration (544.2 mm). The above results imply that the forcing data and the model physics are important factors in the numerical simulation and prediction about runoff.

A dataset of forest soil properties in north-south transect of eastern China

A dataset of forest soil properties in north-south transect of eastern China

Microbial properties regulate spatial variation in the differences in heterotrophic respiration and its temperature sensitivity between primary and secondary forests from tropical to cold-temperate zones

Large quantities of forest products globally have been lumbered, resulting in widespread conversion from primary forests [PFs] to secondary forests [SFs]. This transformation has exerted important impacts on the global carbon [C] cycle. Therefore, it is essential to clarify how soil C, which is a vital component of the global C pool, responds to the converting of forests from PFs to SFs, in parallel to identifying the underlying mechanisms. Here, nine paired (PFs and SFs) soil samples (0–10 cm) were obtained from tropical to cold-temperate zones along the north-south transect of eastern China (NSTEC). The heterotrophic respiration rate [RH] as per soil organic C at a reference temperature of 20 °C [R20-C] and its temperature sensitivity [Q10] were measured and calculated through 14 d incubation experiments. Our results showed that most of R20-C and Q10 in SFs were greater than those in PFs. Strong spatial variation in the differences in R20-C and Q10 between PFs and SFs [△R20-C, △Q10] was observed along the NSTEC, with the greatest △R20-C, △Q10 being detected in the soils of mid-latitude forests. Overall, 83.2% of the spatial variation in △R20-C was explained by physical-chemical and microbial properties, which contributed 68.5% and 52.4% variation solely, respectively. Similarly, 79% of the variation in △Q10 between PFs and SFs was explained by microbial properties, physical-chemical properties, and dissolved organic C, which contributed 81.6%, 10.5%, and 9% variation solely, respectively. Overall, our findings demonstrate high spatial variation in △RH and △Q10 between PFs and SFs, which was mainly explained by microbial properties of soils.

Deforestation decreases spatial turnover and alters the network interactions in soil bacterial communities

Despite important progress in understanding the influence of deforestation on the bacterial α diversity and community structure at local scales, little is known about deforestation impacts in terms of spatial turnover and soil bacterial community network interactions, especially at regional or global scales. To address this research gap, we examined the bacterial spatial turnover rate and the species networks in paired primary and secondary forest soils along a 3700-km north-south transect in eastern China using high-throughput 16S rRNA gene sequencing. The spatial turnover rate of bacterial communities was higher in primary forests than in secondary, suggesting deforestation increased biotic homogenization at a large geographic scale. Multiple regression on matrices analysis revealed that both geographic distance and soil properties (especially soil pH and organic matter availability) strongly affected bacterial spatial turnover. Through the phylogenetic molecular ecological network approach, we demonstrate that the bacterial network of primary forests was more intricate than in secondary forests. This suggests that microbial species have greater niche-sharing and more interactions in primary forests as compared to secondary forests. On the other hand, the bacterial network in secondary forests was more modular, and the taxa tended to co-occur, with positive correlations accounting for 82% of all potential interactions. In conclusion, our findings demonstrate that anthropogenic deforestation has clear effects on bacterial spatial turnover and network interactions, with potential for serious consequences such as microbial diversity loss in primary forests.

Assessing the characteristics of net primary production due to future climate change and CO2 under RCP4.5 in China

In this study, the maximal extent of future net primary production (NPP) uncertainties are explored by employing the conditional nonlinear optimal perturbation related to parameters (CNOP-P) approach and the Lund-Potsdam-Jena (LPJ) model based on future climate change assessments, which are provided by 10 general circulation models (GCMs) of the Coupled Model Intercomparison Project 5 (CMIP5) under the Representative Concentration Pathway (RCP) 4.5 scenario at the North-South Transect of Eastern China (NSTEC). The CNOP-P approach produces a scenario of climate change within the feasible bounds that could cause maximal uncertainty of NPP. We find that the future NPP will increase due to changes in climate and atmospheric CO2; however, there is a difference in the extent of the variation resulting from the 10 GCMs and the CNOP-P approach. Future NPPs are estimated from 3.89 Gt C (MRI-CGCM3 model) to 4.51 Gt C (bcc-csm1-1 model) using the LPJ model driven by the outputs of 10 GCMs. The estimates of NPP with two CNOP-P-type climate change scenarios are 4.74 Gt C and 5.31 Gt C and are larger than estimates of NPP by the outputs of the 10 GCMs. The above results imply that the terrestrial ecosystem supplies possible conditions for future carbon sinks for all climate change scenarios, especially for the CNOP-P-type climate change scenarios, although the estimates remain uncertain. Stimulative photosynthesis due to high precipitation and restrained autotrophic respiration due to low temperatures may play important roles in the carbon sink due to the CNOP-P-type climate change and CO2 in all climate change scenarios. In addition, it is found that the combination of climate change and increasing CO2 is the main driver of the increase of NPP.

Divergence of dominant factors in soil microbial communities and functions in forest ecosystems along a climatic gradient

Abstract. Soil microorganisms play an important role in regulating nutrient cycling in terrestrial ecosystems. Most of the studies conducted thus far have been confined to a single forest biome or have focused on one or two controlling factors, and few have dealt with the integrated effects of climate, vegetation, and soil substrate availability on soil microbial communities and functions among different forests. In this study, we used phospholipid-derived fatty acid (PLFA) analysis to investigate soil microbial community structure and extracellular enzymatic activities to evaluate the functional potential of soil microbes of different types of forests in three different climatic zones along the north–south transect in eastern China (NSTEC). Both climate and forest type had significant effects on soil enzyme activities and microbial communities with considerable interactive effects. Except for soil acid phosphatase (AP), the other three enzyme activities were much higher in the warm temperate zone than in the temperate and the subtropical climate zones. The soil total PLFAs and bacteria were much higher in the temperate zone than in the warm temperate and the subtropical zones. The soil β-glucosidase (BG) and N-acetylglucosaminidase (NAG) activities were highest in the coniferous forest. Except for the soil fungi and fungi–bacteria (F/B), the different groups of microbial PLFAs were much higher in the conifer broad-leaved mixed forests than in the coniferous forests and the broad-leaved forests. In general, soil enzyme activities and microbial PLFAs were higher in primary forests than in secondary forests in temperate and warm temperate regions. In the subtropical region, soil enzyme activities were lower in the primary forests than in the secondary forests and microbial PLFAs did not differ significantly between primary and secondary forests. Different compositions of the tree species may cause variations in soil microbial communities and enzyme activities. Our results showed that the main controls on soil microbes and functions vary in different climatic zones and that the effects of soil moisture content, soil temperature, clay content, and the soil N ∕ P ratio were considerable. This information will add value to the modeling of microbial processes and will contribute to carbon cycling in large-scale carbon models.

阔叶红松林生态化学计量学特征及其对纬度梯度的响应

PDF HTML阅读 XML下载 导出引用 引用提醒 阔叶红松林生态化学计量学特征及其对纬度梯度的响应 DOI: 10.5846/stxb201704300790 作者: 作者单位: 沈阳农业大学 理学院,沈阳农业大学 林学院,辽宁辽河平原森林生态系统定位研究站,沈阳农业大学 林学院 作者简介: 通讯作者: 中图分类号: 基金项目: 林业公益性行业专项（201304216）；“十二五”农村领域国家科技支撑计划专题（2012BAD22B040206） Characteristics of ecological stoichiometry in broad-leaved and Korean pine mixed forest and its response to latitude gradient in Northeast China Author: Affiliation: College of Science,Shenyang Agricultural University,College of Forestry,Shenyang Agricultural University,Research Station of Liaohe River Plain Forest Ecosystem CFERN,College of Forestry,Shenyang Agricultural University Fund Project: 摘要 | 图/表 | 访问统计 | 参考文献 | 相似文献 | 引证文献 | 资源附件 | 文章评论 摘要:为研究红松叶片的养分及生态化学计量学特征的空间分布及其影响因素，依据我国温带阔叶红松林的分布特点，沿纬度梯度，选取长白山（42°27'N）、张广才岭（44°16'N）和小兴安岭（48°05'N）等3个地区的典型阔叶红松老龄林，测定红松叶片碳（C）、氮（N）、磷（P）含量，及表层土壤（0-15 cm）、中层土壤（15-30 cm）的有机碳（SOC）、全氮（TN）和全磷（TP）含量，分析了其分布特征及其相互关系。结果表明：1）红松叶片C、N、P含量显著高于土壤。表层土壤C、N、P含量变化范围分别为27.6-87.4，2.0-7.2 mg/g和0.26-0.92 mg/g；中层土壤为8.1-59.7，0.7-4.6 mg/g和0.2-0.82 mg/g；而叶片为495.5-507.4，12.7-172.5 mg/g和1.1-2.1 mg/g。2）土壤中的SOC、C/N、C/P均随纬度升高极显著增加，而叶片各元素计量特征随纬度的变化不显著。3）叶片N、P含量分别与土壤N、P含量显著正相关，同时，叶片N与土壤C/N、P与土壤N/P显著相关。相比较而言，红松叶片N、P含量较低，这可能说明阔叶红松林土壤N、P供应不足，而叶片N/P仅为9.9，说明东北阔叶红松林N限制更加明显。本研究为阐明东北温带阔叶红松林的养分供应状况和限制因素，为阔叶红松林区提高红松生产力的管理措施的提出奠定了基础。 Abstract:Aims of this study is to explore the spatial distribution of nutrients and the ecological stoichiometry in leaves of Korean pine (Pinus koraiensis Sieb. et Zucc.) and identify the driven factors. According to the distribution range of broad-leaved and Korean pine mixed forest (BKF) in Northeast China, this study sampled 3 sites in Changbai Mountain (42°27'N), Zhangguangcai Mountain (44°16'N) and Xiaoxing'anling Mountain (48°05'N), and measured carbon (C), nitrogen (N) and phosphorus (P) in top soil (0-15 cm), subsurface soil (15-30 cm) and Korean pine leaves, determined spatial variation of nutrient elements along a latitude gradient and the relationships between leaves and soil. The results showed that:1) the contents of C, N and P in leaves were significantly higher than those in soil. The range of C, N, and P in the top (0-15 cm) soil were 27.6-87.4, 0.26-0.92 mg/g, and 2.0-7.2 mg/g, respectively, in subsurface (15-30 cm) soil were 8.1-59.7 mg/g, 0.7-4.6 mg/g, and 0.2-0.82 mg/g, respectively. While, in leaves, were 12.7-172.5 mg/g, 1.1-2.1 mg/g, and 495.5-507.4 mg/g. 2) The organic carbon and C/P and C/N in soil significantly increased along a latitude gradient. The correlation between the elements in leaves and latitude was not significant. 3) Leaves N, P was significantly correlated with total N and P in top soil respectively, additionally, leaves N was significantly correlated with that C/N in top soil, leaves P with N/P in top soil. Comparatively, the contents of N, P in Korean pine leaves are lower than that in natural forest ecosystems along the North-South Transect of Eastern China, which might suggest nutrients supply is not enough to Korean pine growth. Furthermore, low leaves N/P (9.9) indicated N limit is stronger than P in BKF. The results clarify the nutrient supply conditions and their influence factors in BKF, and are helpful to put forward effectively management way to increase forest productivity. 参考文献 相似文献 引证文献