Mean Monthly Soil Research Articles

Application of the ensemble of T&P models for estimating the respiration of forest soils in the zone of temperate continental climate

The aim of the study was by using an ensemble of T&P models, i.e. empirical models of soil respiration dependent on temperature, precipitation and other meteorological and soil parameters, to show the dependence of the choice of optimal empirical models of soil respiration on the soil types in forest ecosystems, in this case Entic Podzol and Haplic Luvisol, as well as on options for parameterizing models using soil or air temperatures, precipitation and soil organic carbon stock. Location and time of the study. Temperate continental climate zone of the Central Russia: mixed forest in the north shore of Oka River and deciduous forest on the south shore of Oka River. The data were collected in 1998–2022. Methods. An ensemble of empirical models of soil respiration was used, linking soil respiration to monthly mean soil or air temperatures and precipitation and soil organic carbon stock. At the same time, a method for determining soil respiration at zero degrees was proposed based on the results of a comparative analysis of simulated data with field measurements. Results. For the forest Entic Podzol, i.e. the well-drained soil poor in organic carbon, the model that relates soil respiration to soil temperature, precipitation and organic carbon storage was the best, whereas for Haplic Luvisol, i.e. the soil with good water retention capacity, the Reich-Hashtmoto model with a quadratic dependence on temperature at an exponent point was the best model. Conclusions. When choosing optimal empirical models of soil respiration, it is important to take into account such soil parameters as organic carbon stock and the ability to retain water.

The Estimation of Monthly Mean Soil Temperature at Different Depths in Sivas Province, Turkey by Artificial Neural Networks

ABSTRACT In this study, soil temperature of Sivas province was estimated by the artificial neural networks (ANNs) method using data obtained from five different meteorological measurement stations situated in provincial borders. Nineteen years of (2000–2018) monthly mean air temperature data obtained from five different soil depths (5, 10, 20, 50 and 100 cm) was used for ANN analysis. Predicted and measured soil temperatures were strongly correlated with determination coefficient (R2) values ranging between 0.9767 and 0.9941. Mean Absolute Error (MAE) ranged from 0.532°C to 1.381°C, while Mean Absolute Percentage Error (MAPE) ranged from 5.692% to 16.263% and Root Mean Squared Error (RMSE) ranged between 0.694°C and 1.666°C. It was found that the predicted values are in good agreement with the measured data. However, there was a tendency to underestimate the soil temperature.

Grid-based simulation of soil moisture in the UK: future changes in extremes and wetting and drying dates

Soil moisture, typically defined as the amount of water in the unsaturated soil layer, is a central component of the hydrological cycle. The potential impacts of climate change on soil moisture have been less specifically studied than those on river flows, despite soil moisture deficits/excesses being a factor in a range of natural hazards, as well as having obvious importance for agriculture. Here, 1 km grids of monthly mean soil moisture content are simulated using a national-scale grid-based hydrological model, more typically applied to look at changes in river flows across Britain. A comparison of the soil moisture estimates from an observation-based simulation, with soil moisture deficit data from an operational system developed by the UK Met Office (Meteorological Office Rainfall and Evaporation Calculation System; MORECS), shows relatively good correspondence in soil drying and wetting dates, and in the month when soils are driest. The UK Climate Projections 2018 Regional projections are then used to drive the hydrological model, to investigate changes in occurrence of indicative soil moisture extremes and changes in typical wetting and drying dates of soils across the country. Analyses comparing baseline (December 1981–November 2011) and future (December 2050–November 2080) time-slices suggest large increases in the spatial occurrence of low soil moisture levels, along with later soil wetting dates, although changes to soil drying dates are less clear. Such information on potential future changes in soil moisture is important to enable the development of appropriate adaptation strategies for a range of sectors vulnerable to soil moisture levels.

Evaluating the most effective climatic parameters affecting the monthly mean soil temperature estimates using the PLS method

Evaluating the most effective climatic parameters affecting the monthly mean soil temperature estimates using the PLS method

One third of the abiotically-absorbed atmospheric CO2 by the loess soil is conserved in the solid phase

It has frequently been noticed that alkaline soils in arid and semiarid areas can absorb atmospheric CO2 abiotically. However, the fate of the absorbed CO2 is largely unknown, limiting our ability to accurately assess the contribution of abiotic CO2 absorption to carbon sequestration. The hypothesis that some abiotically-absorbed carbon could be fixed in the soil solid phase is yet to be explicitly tested. From April to November 2016, we added 13CO2 to the natural alkaline loess soil at a depth of 0–17 cm and quantified the proportion of 13CO2 conserved in the soil solid phase on the central Loess Plateau of China. The results showed that natural surface soil absorbed 13CO2 at a rate of 475.9 mg m−2 d−1. Of the absorbed 13CO2, 33.2% was conserved in the soil solid phase. The rate of added 13CO2 conserved in the solid phase was positively correlated with mean monthly soil water content but negatively correlated with mean monthly soil temperature. Our results indicated that, loess soil can absorb CO2 from the atmosphere through abiotic processes, and part of the abiotically-absorbed CO2 is stably fixed in the soil solid phase. Soil with a higher water content and lower temperature may promote the abiotic CO2 fixation. The rate of CO2 fixation through abiotic processes at the surface soil accounted for approximately 10%-20% of the reported local annual net ecosystem exchange, implying that the abiotic CO2 uptake by loess soil may play an important role in assessing the capacity of CO2 sequestration in these areas.

Bias-adjusted seasonal forecasts of soil moisture for forestry applications in Finland

Abstract. Seasonal forecasts for forestry have been developed in the Finnish Meteorological Institute in cooperation with Finnish end-users. Such forecasts could help forest companies in preparing for adverse conditions of timber harvesting operations. Bearing capacity for harvesting operations is dependent on soil moisture, and skillful forecasts have potentially large economic value. Using the ECMWF seasonal forecasts, we evaluated the monthly mean soil moisture forecasts for four different start months, with lead times from 0 to 2 months. Forecasts were bias adjusted, and showed skill in the first month for all four months. After the first lead month, winter months fared a bit better than summer months.

Response of Soil Respiration and Its Components to Nitrogen and Phosphorus Addition in Farming-Withdrawn Grassland in the Semiarid Loess Hilly-Gully Region

Understanding the soil respiration characteristics in response to nitrogen and phosphorus addition in farming-withdrawn grasslands within semi-arid loess hilly-gully regions is of great importance for providing a theoretical basis for evaluating the effects of artificial regulation approaches on carbon cycling. We report on a field experiment that was undertaken from May to September 2018 in a farming-withdrawn grassland ecosystem in China, which is dominated by Stipa bungeana and Lespedeza davurica. Three different levels of nitrogen and phosphorus additions were used, including three main plots of N[0, 50, and 100 kg·(hm2·a)-1] and three subplots of P (P2O5)[0,40, and 80 kg·(hm2·a)-1]. The soil respiration rate, heterotrophic respiration rate, soil temperature, and soil moisture were measured monthly in each treatment. Results showed that N and P addition had no effect on soil temperature or moisture content (P>0.05). The soil respiration rate showed an obvious monthly variation and peaked in July. In the treatment without fertilizer addition, the monthly mean soil respiration rate, heterotrophic respiration rate, and autotrophic respiration rate were 0.69, 0.39, and 0.29 g·(m2·h)-1, respectively. P addition had no significant effect on the soil respiration rate and its components without N addition (P>0.05). Under conditions of N addition, P addition significantly increased the soil respiration rate and its component (P<0.05). The monthly mean soil respiration rate, heterotrophic respiration rate, and autotrophic respiration rate were 0.93, 0.50, and 0.47 g·(m2·h)-1, respectively. The Q10 (i.e., temperature sensitivity) values for soil respiration, heterotrophic respiration, and autotrophic respiration in unfertilized soil were 1.86, 2.36, and 2.24, respectively. The addition of N and P reduced the Q10 value of soil respiration and its components. Our findings suggest that the response of soil respiration and its two components to N and P addition in studied farming-withdrawn grassland in the semiarid loess hilly-gully region were closely related to their addition amounts.

Intensified Precipitation Seasonality Reduces Soil Inorganic N Content in a Subtropical Forest: Greater Contribution of Leaching Loss Than N2O Emissions

AbstractSoil nitrogen (N) loss has been predicted to intensify with increased global precipitation changes. However, the relative contributions of leaching and gaseous N emissions to intensified N losses are largely unknown. Thus, we simulated intensified precipitation seasonality in a subtropical forest by extending the dry season via rainfall exclusion and increasing the wet‐season storms via irrigation without changing the total annual precipitation. Extending the dry season length increased the monthly mean soil NO3− content by 25%–64%, net N mineralization rate by 32%–40%, and net nitrification rate by 25%–28%. After adding water in the wet season, the monthly NO3− leaching was enhanced by 43% in the relatively dry year (2013, 2,094‐mm annual rainfall), but reduced by 51% in the relatively wet year (2014, 1,551 mm). In contrast, the monthly mean N2O emissions were reduced by 24% in 2013 but increased by 78% in 2014. Overall, the annual inorganic N content was decreased significantly by the precipitation changes. Decrease of soil inorganic N might be linked to the enhanced NO3− leaching in 2013, and be linked to the increased N2O emissions in 2014. However, in both years the annual total amount of N lost through leaching was significantly greater than that through N2O emissions. The enhanced N2O emissions driven by wet‐season storms were correlated with an increase in nirS abundance. Our results suggest that increased frequency of droughts and storms will decrease soil inorganic N content in warm and humid subtropical forests mainly through enhanced leaching losses.

Analysis of greengram genotypes based on morpho-physiological, biochemical attributes and seed yield in relation to growing season

The study was conducted during kharif and summer seasons of 2013-14 and 2014-15 with twenty genotypes of greengram. The mean monthly soil moisture content was 23.46 per cent for kharif season and 12.95 per cent for summer season. Significant variations in morpho-physiological, biochemical attributes and seed yield were recorded in all the genotypes. The genotype Pusa Baisakhi was found to be the highest seed yielder during kharif season which was followed by Pant Moong 4, Pratap, SGC 25 and SGC 20. The genotype Pusa Baisakhi showed the highest value for leaf area per plant, in vivo leaf nitrate reductase activity, leaf photosynthetic rate, total dry matter content per plant and number of pods per plant. On the other hand, during summer season the genotype SGC 25 was found to be the highest seed yielder followed by SGC 20, Pusa Baisakhi, Pant Moong 4 and Pratap. The genotype SGC 25 was found to record highest value for number of branches per plant, total leaf chlorophyll content, stomatal conductance, leaf photosynthetic rate and number of pods per plant. On an average during kharif season 27.21 per cent higher seed yield could be obtained compared to that of summer season.

Effects of soil moisture on dust emission from 2011 to 2015 observed over the Horqin Sandy Land area, China

Abstract Using the observational data of dust concentrations and meteorological parameters from 2011 to 2015, the effects of soil moisture and air humidity on dust emission were studied at long (monthly) and short (several days or hours) time scales over the Horqin Sandy Land area, Inner Mongolia of China. The results show that the monthly mean dust concentrations and dust fluxes within the near-surface layer had no obvious relationship with the monthly mean soil moisture content but had a slightly negative correlation with monthly mean air relative humidity from 2011 to 2015. The daily mean soil moisture exhibited a significantly negative correlation with the daily mean dust concentrations and dust fluxes, as soil moisture changed obviously. However, such negative correlation between soil moisture and dust emission disappeared on dust blowing days. Additionally, the effect of soil moisture on an important parameter for dust emission, the threshold friction velocity (u∗t), was investigated during several saltation-bombardment and/or aggregation-disintegration dust emission (SADE) events. Under dry soil conditions, the values of u∗t were not influenced by soil moisture content; however, when the soil moisture content was high, the values of u∗t increased with increasing soil moisture content.

Evaluating the performance of artificial intelligence methods for estimation of monthly mean soil temperature without using meteorological data

Soil temperature has an important role in agricultural, hydrological, meteorological and climatological studies. In the present research, monthly mean soil temperature at four different depths (5, 10, 50 and 100 cm) was estimated using artificial neural networks (ANN), adaptive neuro-fuzzy inference system (ANFIS) and gene expression programming (GEP). The monthly mean soil temperature data of 31 stations over Iran were employed. In this process, the data of 21 and 10 stations were used for training and testing stages of used models, respectively. Furthermore, the geographical information including latitude, longitude and altitude as well as periodicity component (the number of months) was considered as inputs in the mentioned intelligent models. The results demonstrated that the ANN and ANFIS models had good performance in comparison with the GEP model. Nevertheless, the ANFIS generally performed better than ANN model.

Environmental controls of evapotranspiration in a mixed plantation in North China.

The mixed plantation plays an important role in the water cycle in the hilly area of North China. To evaluate the effect of afforestation on the water balance in this region, the temporal variation of evapotranspiration (ET) and environmental controls were investigated based on the eddy flux measurement of water vapor in a 31-year-old mixed plantation from 2006 to 2010. During 5years, annual ET ranged from 513 to 680mm, with an average of 579mm. Growing season ET accounted for 72-82% of annual ET during the 5-year period and its interannual variation was determined by the number of rainy days. In the non-growing and growing seasons, monthly ET was primarily dependent on monthly mean soil water content and monthly mean net radiation, respectively. Annual mean Priestley-Taylor coefficient (α) was 0.64, and the decoupling factor (Ω) was 0.48. High values of α and Ω implied that ET was energy limited in the growing seasons of 2006-2010. The mean annual ratio of ET to precipitation (ET/P) was 1.10. The density of the mixed plantation was around 50% higher than the optimal value determined by local water capacity, leading to a large ET/P ratio. The dense plantation needs to be thinned to prevent excessive water loss in the hilly area of North China.

Wind erosion control utilizing standing corn residue in Northeast China

Soil wind erosion is a serious concern in agricultural regions. Wind erosion is of particular concern in Northeast China where a north continental monsoon climate is prevalent and land is prepared for seeding using an ancient ridge culture technique. Cultural reluctance to adopting a cropping strategy that leaves residues is also based on local population use of corn stalks as animal fodder and fuel. In order to evaluate the conservation effects of standing residue on controlling soil wind erosion, a 4-year study (2011–2014) was conducted near Changchun city in Northeast China. Four experimental treatments were used: un-fixed corn residue coverage (shattering/cutting the corn stalks into small sections and spreading them on the soil surface) and three treatments with the standing corn residue of different height for each treatment; 30-, 40- and 50-cm.11The treatment with soil surface covered with small pieces of un-fixed, loose corn residue is designated as PA. The 30-cm high standing corn residue treatment is designated as PB; 40-cm treatment as PC; and 50-cm treatment as PD. Saltation probability is designated as Pi. The corn stalk residue above that which remained in each treatment was removed from the field as much as practical. The standing residue treatments also resulted in some soil coverage by fugitive leaves and small stalk pieces. The experimental design was four treatments replicated four times, with years as replicates. Soil loss from the un-fixed corn residue coverage treatment and soil sediment from the standing residue coverage treatments was measured. Standing residue with the heights of 30-, 40- and 50-cm increased mean aerodynamic roughness length (equivalent to the height at which the wind speed theoretically becomes zero) by 19.87, 43.77 and 61.62, respectively, and increased mean threshold wind speed by 11, 25 and 33%, respectively. Mean monthly soil loss mass balance for un-fixed corn residue was 1.27Mgha−1, and the mean monthly values for soil sediment mass balance were 0.725, 1.088 and 1.967Mgha−1 for 30-, 40- and 50-cm standing residue treatments, respectively. These experiments indicate that standing residue conservation management can act as an effective way to control soil wind erosion, while providing a portion of corn stalks for the local population to continue using as animal fodder and fuel.

海南西部桉树人工林土壤水分变化特征及其对林龄的响应

PDF HTML阅读 XML下载 导出引用 引用提醒 海南西部桉树人工林土壤水分变化特征及其对林龄的响应 DOI: 10.5846/stxb201305301229 作者: 作者单位: 海南师范大学 地理与旅游学院,海南师范大学 生命科学学院,北京师范大学 地表过程与资源生态国家重点实验室,海南师范大学 地理与旅游学院,海南师范大学 地理与旅游学院,海南师范大学 地理与旅游学院 作者简介: 通讯作者: 中图分类号: 基金项目: 国家自然科学基金项目(40961033,41361006);国家重点基础研究项目(2007CB106807);国家科技支撑计划(2012BAC18B04) Variation of soil moisture content for Eucalyptus forests and its response to stand ages in Western Hainan Author: Affiliation: Hainan Normal University,,Beijing Normal 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:在海南西部儋州林场选取空间相邻、自然环境相似、不同林龄与连栽代次的桉树林样地和椰树林对照样地,通过2010-2012年连续3a定点取样,研究桉树林土壤水分变化特征及其对林龄的响应,分析桉树林种植对林地土壤水分的影响。结果表明:(1)1-4月土壤含水量持续减少,5-6月波动较大,7-10月增加到年内极大值,11-12月降低,但处于年内较高水平。(2)短伐桉树林(二代5年桉树林、三代1年桉树林、三代4年桉树林)、20a桉树林以及10a椰树林5个样地的月均土壤含水量存在显著或极显著差异。二代5年桉树林与三代1年桉树林之间以及20a桉树林与10a椰树林之间的土壤含水量差异均不显著;其余各林地之间土壤含水量差异显著或极显著。(3)随着土壤深度增加,短伐桉树林与20a桉树林、10a椰树林之间的土壤含水量差异增大。表层0-30 cm短伐桉树林年均土壤含水量为6.08%,20a桉树林为7.53%,10a椰树林为6.93%;80 cm以下则分别为8.10%、11.72%和11.95%。与10a椰树林、20a桉树林相比,短伐桉树林对土壤深层水分有较大负面影响。(4)短伐桉树林、20a桉树林和10a椰树林土壤含水量的变异系数由表层到深层逐渐递减,其中林龄较大的短伐桉树林变异系数较大,且变异系数较大的土层也较深厚。与20a桉树林、10a椰树林相比,林龄较大的短伐桉树林对深层土壤水分的消耗较多。(5)连栽代次愈多,林龄越大,土壤含水量愈少;采伐之后1a桉树林的土壤含水量明显增加,有利于桉树后期生长。 Abstract:Danzhou, which lies in western Hainan and where large-scale Eucalyptus plantations are present, was chosen as the target study area. We selected 1-to-5-year-old short-rotation Eucalyptus trees, 20-year-old Eucalyptus trees and 10-year-old Cocos trees with adjacent space and similar natural conditions as our experimental plots. After 3 years of continuous sampling, from 2010 to 2012, in fixed sites, we analyzed the variation of soil moisture content for Eucalyptus forests and its response to plantation ages. The results showed that: (1) Soil moisture content decreased continuously from January to April, fluctuated in May and June, increased to the annual maximum between July and October, and descended slightly during the remaining months. (2) There were significant or highly significant differences in mean monthly soil moisture content among the short-rotation Eucalyptus plantations (including a second-generation 5-year-old short-rotation Eucalyptus plantation, a third-generation 1-year-old short-rotation Eucalyptus plantation and a third-generation 4-year-old short-rotation Eucalyptus plantation), 20-year-old Eucalyptus plantation and 10-year-old Cocos plantation, except between the second-generation 5-year-old short-rotation Eucalyptus plantation and the third-generation 1-year-old short-rotation Eucalyptus plantation and between the 20-year-old Eucalyptus plantation and the 10-year-old Cocos plantation. (3) Differences in soil moisture content increased with soil depth between the short-rotation Eucalyptus plantations and 20-year-old Eucalyptus plantation, 10-year-old Cocos plantation. In the 0-30 cm soil layer, the average moisture contents for the short-rotation Eucalyptus plantations, non-short-rotation Eucalyptus plantation and Cocos plantation were 6.08%, 7.53% and 6.93%, respectively, while, in soil layers deeper than 80 cm, values were 8.10%, 11.72% and 11.95%, respectively. The phenomenon that increases in soil depth enlarge differences in soil moisture content reveals that short-rotation Eucalyptus forests consumed more water in the deep soil, compared with the Cocos forest and non-short-rotation Eucalyptus forest. (4) The variation coefficient of soil moisture content gradually declined from top to deep soil layers for the short-rotation Eucalyptus plantations, 20-year-old Eucalyptus plantation and 10-year-old Cocos plantation. In addition, the coefficient was larger for the elder short-rotation Eucalyptus forests and under deeper soil layers, which indicated that compared to the Cocos forest and non-short-rotation Eucalyptus forest, the elder short-rotation Eucalyptus forests consumed more deep soil water. (5) More continuous planting and greater stand age minified soil moisture content. The soil moisture of the 1-year-old Eucalyptus plantation was in a recovery phase and exhibited a higher content, which would improve the soil water environment and the growth of Eucalyptus trees. 参考文献 相似文献 引证文献

Vegetation Types Alter Soil Respiration and Its Temperature Sensitivity at the Field Scale in an Estuary Wetland

Vegetation type plays an important role in regulating the temporal and spatial variation of soil respiration. Therefore, vegetation patchiness may cause high uncertainties in the estimates of soil respiration for scaling field measurements to ecosystem level. Few studies provide insights regarding the influence of vegetation types on soil respiration and its temperature sensitivity in an estuary wetland. In order to enhance the understanding of this issue, we focused on the growing season and investigated how the soil respiration and its temperature sensitivity are affected by the different vegetation (Phragmites australis, Suaeda salsa and bare soil) in the Yellow River Estuary. During the growing season, there were significant linear relationships between soil respiration rates and shoot and root biomass, respectively. On the diurnal timescale, daytime soil respiration was more dependent on net photosynthesis. A positive correlation between soil respiration and net photosynthesis at the Phragmites australis site was found. There were exponential correlations between soil respiration and soil temperature, and the fitted Q 10 values varied among different vegetation types (1.81, 2.15 and 3.43 for Phragmites australis, Suaeda salsa and bare soil sites, respectively). During the growing season, the mean soil respiration was consistently higher at the Phragmites australis site (1.11 µmol CO2 m−2 s−1), followed by the Suaeda salsa site (0.77 µmol CO2 m−2 s−1) and the bare soil site (0.41 µmol CO2 m−2 s−1). The mean monthly soil respiration was positively correlated with shoot and root biomass, total C, and total N among the three vegetation patches. Our results suggest that vegetation patchiness at a field scale might have a large impact on ecosystem-scale soil respiration. Therefore, it is necessary to consider the differences in vegetation types when using models to evaluate soil respiration in an estuary wetland.

Evaluation of multi-model simulated soil moisture in NLDAS-2

Summary The North American Land Data Assimilation System (NLDAS) phase 2 (NLDAS-2) has generated 31-years (1979–2008) of water and energy products from four state-of-the-art land surface models (Noah, Mosaic, SAC, VIC). The soil moisture data from these models have been used for operational drought monitoring activities, but so far have not yet been comprehensively evaluated. In this study, three available in situ soil moisture observation data sets in the United States were used to evaluate the model-simulated soil moisture for different time scales varying from daily to annual. First, we used the observed multiple layer monthly and annual mean soil moisture from the Illinois Climate Network to evaluate 20-years (January 1985–December 2004) of model-simulated soil moisture in terms of skill and analysis of error statistics. Second, we utilized 6-years (1 January 1997–31 December 2002) of daily soil moisture observed from 72 sites over the Oklahoma Mesonet network to assess daily and monthly simulation skill and errors for 3 model soil layers (0–10 cm, 10–40 cm, 40–100 cm). Third, we extended the daily assessment to sites over the continental United States using 8-years (1 January 2002–31 December 2009) of observations for 121 sites from the Soil Climate Analysis Network (SCAN). Overall, all models are able to capture wet and dry events and show high skill (in most cases, anomaly correlation is larger than 0.7), but display large biases when compared to in situ observations. These errors may come from model errors (i.e., model structure error, model parameter error), forcing data errors, and in situ soil moisture measurement errors. For example, all models simulate less soil moisture due to lack of modeled irrigation and ground water processes in Illinois, Oklahoma, and the other Midwest states.

Soil moisture retrieved from microwave satellite data and its relationship with the Asian dust (Hwangsa) frequency in East Asia during the period from 2003 to 2010

A soil moisture retrieval algorithm using AMSR-E microwave satellite data has been developed by the National Institute of Meteorological Research (NIMR). This algorithm is based on a simple inversion method that does not require a prior soil texture data. In this study, the relationship between soil moisture retrieved from the NIMR algorithm and the occurrence of Asian dust (Hwangsa) is statistically analyzed. The frequency of occurrence of Asian dust events was recorded at 410 sites in China from 2003–2010 in three regions; the Gobi desert, Inner Mongolia and Northeast China. Results showed low soil moisture values of around 0.1 g cm−3 in the Gobi desert and Inner Mongolia-lowest in summer and a little higher in winter. Soil moisture values in Northeast China were marginally higher than in other regions, but lowest in winter and higher in summer. About 55% of Asian dust in the Gobi desert occurred when the monthly mean soil moisture was less than the monthly mean soil moisture for eight years. Approximately 75% of Asian dust in Northeast China occurred when soil moisture was the same as the monthly mean soil moisture for eight years. While soil moisture in the Gobi desert and Inner Mongolia declined in spring, it increased in Northeast of China.

Vegetation patches improve the establishment of Salvia mexicana seedlings by modifying microclimatic conditions

Human disturbance has disrupted the dynamics of plant communities. To restore these dynamics, we could take advantage of the microclimatic conditions generated by remaining patches of vegetation and plastic mulch. These microclimatic conditions might have great importance in restoring disturbed lava fields located south of Mexico City, where the rock is exposed and the soil is shallow. We evaluated the effects of both the shade projected by vegetation patches and plastic mulch on the mean monthly soil surface temperature (Tss) and photosynthetic photon flux density (PPFD) and on the survival and growth of Salvia mexicana throughout the year. This species was used as a phytometer of microsite quality. Shade reduced the T ss to a greater extent than mulch did. Both survival and growth were enhanced by shade and mulch, and the PPFD was related with seedling growth. During the dry season, plant biomass was lost, and there was a negative effect of PPFD on plant growth. At micro-meteorological scales, the use of shade projected by patches of vegetation and mulch significantly reduced the mortality of S. mexicana and enhanced its growth. Survival and growth of this plant depended on the environmental quality of microsites on a small scale, which was determined by the environmental heterogeneity of the patches and the landscape. For plant restoration, microsite quality must be evaluated on small scales, but on a large scale it may be enough to take advantage of landscape shade dynamics and the use of mulch to increase plant survival and growth.

Concentration of Radiocarbon in Soil-Respired CO2 Flux: Data-Model Comparison for Three Different Ecosystems in Southern Poland

We report and compare the results of long-term observations (1998–2006) of monthly mean soil CO2 fluxes and their carbon isotope composition, carried out at 3 sites with contrasting characteristics: 1) a grassland site located in the urban area of Krakow, southern Poland, which was exposed to anthropogenic impact for more than a century; 2) a mixed forest site; and 3) cultivated agricultural field site. A closed-chamber, dynamic sampling system was used to collect monthly cumulative samples of soil-respired CO2. The CO2 collected at the mixed forest site was enriched in 14C with respect to European free-atmosphere continental 14CO2 background (high-altitude station Jungfraujoch in Swiss Alps) by approximately 40%, while the urban site revealed 14C depletion by ∼30% against the same reference. The Δ14C values observed at the agricultural site were lying in between, clustering along the regional reference atmospheric Δ14CO2 trend curve. The Δ14C values of soil-respired CO2 at the urban site turned out to be indistinguishable from the Δ14CO2 values in the local atmosphere. For the estimation of mean turnover time of soil carbon for each of the monitored sites, we used a multicompartment model (MCM) accounting for input of carbon to the soil profile via deposition of fresh organic matter, as well as 3 different sources of CO2 in the soil profile: 1) root respiration; 2) “fast”; and 3) “slow” pools of soil carbon. The estimated mean turnover time of carbon in the “fast” carbon pool was ∼14 yr for both urban grassland and mixed forest sites, and ∼22 yr for the cultivated agricultural field. From the observed differences in Δ14C values of the measured fluxes of soil-respired CO2, we conclude that 14C content of the biogenic component in the local atmospheric CO2 is site-specific and may differ significantly from the regional atmospheric background Δ14CO2 value. Therefore, the assumption widely used in 14C-based assessments of the fossil-fuel contribution local atmospheric CO2 load, stating that 14C concentration in the biogenic CO2 component is equal to that of regional atmospheric reference value, needs to be carefully evaluated on a case-by-case basis.

Seasonal hydrologic prediction in the United States: understanding the role of initial hydrologic conditions and seasonal climate forecast skill

Abstract. Seasonal hydrologic forecasts derive their skill from knowledge of initial hydrologic conditions and climate forecast skill associated with seasonal climate outlooks. Depending on the type of hydrological regime and the season, the relative contributions of initial hydrologic conditions and climate forecast skill to seasonal hydrologic forecast skill vary. We seek to quantify these contributions on a relative basis across the Conterminous United States. We constructed two experiments – Ensemble Streamflow Prediction and reverse-Ensemble Streamflow Prediction – to partition the contributions of the initial hydrologic conditions and climate forecast skill to overall forecast skill. In ensemble streamflow prediction (first experiment) hydrologic forecast skill is derived solely from knowledge of initial hydrologic conditions, whereas in reverse-ensemble streamflow prediction (second experiment), it is derived solely from atmospheric forcings (i.e. perfect climate forecast skill). Using the ratios of root mean square error in predicting cumulative runoff and mean monthly soil moisture of each experiment, we identify the variability of the relative contributions of the initial hydrologic conditions and climate forecast skill spatially throughout the year. We conclude that the initial hydrologic conditions generally have the strongest influence on the prediction of cumulative runoff and soil moisture at lead-1 (first month of the forecast period), beyond which climate forecast skill starts to have greater influence. Improvement in climate forecast skill alone will lead to better seasonal hydrologic forecast skill in most parts of the Northeastern and Southeastern US throughout the year and in the Western US mainly during fall and winter months; whereas improvement in knowledge of the initial hydrologic conditions can potentially improve skill most in the Western US during spring and summer months. We also observed that at a short lead time (i.e. lead-1) contribution of the initial hydrologic conditions in soil moisture forecasts is more extensive than in cumulative runoff forecasts across the Conterminous US.