Land use change to perennial energy crops in Northern Italy: Effects on soil organic carbon sequestration and distribution, soil enzyme activities and microbial communities.

Studies on soil organic carbon (SOC) sequestration in perennial energy crops are available for North-Central Europe, while there is insufficient information for Southern Europe. This research was conducted in the Po Valley, a Mediterranean-temperate zone characterised by low SOC levels, due to intensive management. The aim was to assess the factors influencing SOC sequestration and its distribution through depth and within soil fractions, after a 9-year old conversion from two annual systems to Miscanthus (Miscanthus × giganteus) and giant reed (Arundo donax). The 13C natural abundance was used to evaluate the amount of SOC in annual and perennial species, and determine the percentage of carbon derived from perennial crops. SOC was significantly higher under perennial species, especially in the topsoil (0-0.15 m). After 9 years, the amount of C derived from Miscanthus was 18.7 Mg ha-1, mostly stored at 0-0.15 m, whereas the amount of C derived from giant reed was 34.7 Mg ha-1, evenly distributed through layers. Physical soil fractionation was combined with 13C abundance analysis. C derived from perennial crops was mainly found in macroaggregates. Under giant reed, more newly derived-carbon was stored in microaggregates and mineral fraction than under Miscanthus. A molecular approach based on denaturing gradient gel electrophoresis (DGGE) allowed to evaluate changes on microbial community, after the introduction of perennial crops. Functional aspects were investigated by determining relevant soil enzymes (β-glucosidase, urease, alkaline phosphatase). Perennial crops positively stimulated these enzymes, especially in the topsoil. DGGE profiles revealed that community richness was higher in perennial crops; Shannon index of diversity was influenced only by depth. In conclusion, Miscanthus and giant reed represent a sustainable choice for the recovery of soils exhausted by intensive management, also in Mediterranean conditions and this is relevant mainly because this geographical area is notoriously characterised by a rapid turnover of SOC.

Sleepless night, the moon is bright: longitudinal study of lunar phase and sleep

Popular belief holds that the lunar cycle affects human physiology, behaviour and health. We examined the influence of moon phase on sleep duration in a secondary analysis of a feasibility study of mobile telephone base stations and sleep quality. We studied 31 volunteers (18 women and 13 men, mean age 50 years) from a suburban area of Switzerland longitudinally over 6 weeks, including two full moons. Subjective sleep duration was calculated from sleep diary data. Data were analysed using multiple linear regression models with random effects. Mean sleep duration was 6 h 49 min. Subjective sleep duration varied with the lunar cycle, from 6 h 41 min at full moon to 7 h 00 min at new moon (P < 0.001). Average sleep duration was shortened by 68 min during the week compared with weekends (P < 0.001). Men slept 17 min longer than women (P < 0.001) and sleep duration decreased with age (P < 0.001). There was also evidence that rating of fatigue in the morning was associated with moon phase, with more tiredness (P = 0.027) at full moon. The study was designed for other purposes and the association between lunar cycle and sleep duration will need to be confirmed in further studies.

Effects of experimental freezing on soil nitrogen dynamics in soils from a net nitrification gradient in a nitrogen-saturated hardwood forest ecosystem

This study examined effects of soil freezing on N dynamics in soil along an N processing gradient within a mixed hardwood dominated watershed at Fernow Experimental Forest, West Virginia. Sites were designated as LN (low rates of N processing), ML (moderately low), MH (moderately high), and HN (high). Soils underwent three 7-day freezing treatments (0, –20, or –80 °C) in the laboratory. Responses varied between temperature treatments and along the gradient. Initial effects differed among freezing treatments for net N mineralization, but not nitrification, in soils across the gradient, generally maintained at LN < ML ≤ MH < HN for all treatments. Net N mineralization potential was higher following freezing at –20 and –80 °C than control; all were higher than at 0 °C. Net nitrification potential exhibited similar patterns. LN was an exception, with net nitrification low regardless of treatment. Freezing response of N mineralization differed greatly from that of nitrification, suggesting that soil freezing may decouple two processes of the soil N cycle that are otherwise tightly linked at our site. Results also suggest that soil freezing at temperatures commonly experienced at this site can further increase net nitrification in soils already exhibiting high nitrification from N saturation.

Prediction of soil organic carbon for Ethiopian highlands using soil spectroscopy

Soil spectroscopy was applied for predicting soil organic carbon (SOC) in the highlands of Ethiopia. Soil samples were acquired from Ethiopia’s National Soil Testing Centre and direct field sampling. The reflectance of samples was measured using a FieldSpec 3 diffuse reflectance spectrometer. Outliers and sample relation were evaluated using principal component analysis (PCA) and models were developed through partial least square regression (PLSR). For nine watersheds sampled, 20% of the samples were set aside to test prediction and 80% were used to develop calibration models. Depending on the number of samples per watershed, cross validation or independent validation were used.The stability of models was evaluated using coefficient of determination (R2), root mean square error (RMSE), and the ratio performance deviation (RPD). The R2 (%), RMSE (%), and RPD, respectively, for validation were Anjeni (88, 0.44, 3.05), Bale (86, 0.52, 2.7), Basketo (89, 0.57, 3.0), Benishangul (91, 0.30, 3.4), Kersa (82, 0.44, 2.4), Kola tembien (75, 0.44, 1.9),Maybar (84. 0.57, 2.5),Megech (85, 0.15, 2.6), andWondoGenet (86, 0.52, 2.7) indicating that themodels were stable. Models performed better for areas with high SOC values than areas with lower SOC values. Overall, soil spectroscopy performance ranged from very good to good.

Evidence from the real world: N-15 natural abundances reveal enhanced nitrogen use at high plant diversity in Central European grasslands

Complementarity that leads to more efficient resource use is presumed to be a key mechanism explaining positive biodiversity–productivity relationships but has been described solely for experimental set-ups with controlled environmental settings or for very short gradients of abiotic conditions, land-use intensity and biodiversity. Therefore, we analysed plant diversity effects on nitrogen dynamics across a broad range of Central European grasslands. The 15N natural abundance in soil and plant biomass reflects the net effect of processes affecting ecosystem N dynamics. This includes the mechanism of complementary resource utilization that causes a decrease in the 15N isotopic signal. We measured plant species richness, natural abundance of 15N in soil and plants, above-ground biomass of the community and three single species (an herb, grass and legume) and a variety of additional environmental variables in 150 grassland plots in three regions of Germany. To explore the drivers of the nitrogen dynamics, we performed several analyses of covariance treating the 15N isotopic signals as a function of plant diversity and a large set of covariates. Increasing plant diversity was consistently linked to decreased δ15N isotopic signals in soil, above-ground community biomass and the three single species. Even after accounting for multiple covariates, plant diversity remained the strongest predictor of δ15N isotopic signals suggesting that higher plant diversity leads to a more closed nitrogen cycle due to more efficient nitrogen use. Factors linked to increased δ15N values included the amount of nitrogen taken up, soil moisture and land-use intensity (particularly fertilization), all indicators of the openness of the nitrogen cycle due to enhanced N-turnover and subsequent losses. Study region was significantly related to the δ15N isotopic signals indicating that regional peculiarities such as former intensive land use could strongly affect nitrogen dynamics. Synthesis. Our results provide strong evidence that the mechanism of complementary resource utilization operates in real-world grasslands where multiple external factors affect nitrogen dynamics. Although single species may differ in effect size, actively increasing total plant diversity in grasslands could be an option to more effectively use nitrogen resources and to reduce the negative environmental impacts of nitrogen losses.

Anion exchange membrane soil nitrate predicts turfgrass color and yield.

Desirable nitrogen (N) management practices for turfgrass supply sufficient N for high quality turf while limiting excess soil N. Previous studies suggested the potential of anion exchange membranes (AEMs) for predicting turfgrass color, quality, or yield. However, these studies suggested a wide range of critical soil nitrate-nitrogen (NO3-N) values across sample dates. A field experiment, in randomized complete block design with treatments consisting of nine N application rates, was conducted on a mixed species cool-season turfgrass lawn across two growing seasons. Every 2 wk from May to October, turfgrass color was assessed with three different reflectance meters, and soil NO3-N was measured with in situ AEMs. Cate-Nelson models were developed comparing relative reflectance value and yield to AEM desorbed soil NO3-N pooled across all sample dates. These models predicted critical AEM soil NO3-N values from 0. 45 to 1.4 micro g cm-2 d-1. Turf had a low probability of further positive response to AEM soil NO3-N greater than these critical values. These results suggest that soil NO3-N critical values from AEMs may be applicable across sample dates and years and may serve to guide N fertilization to limit excess soil NO3-N.

Collection of data on particulate and dissolved soil phosphorus in the Jena Experiment (Main Experiment, time series since 2002)

This data set contains two time series of measurements of dissolved phosphorus (organic, inorganic and total with a biweekly resolution) and dissolved inorganic phosphorus with a seasonal resolution. In addition, data on phosphorus from soil samples measured in 2007 and fractionated by different acid-extrations (Hedley fractions) are provided. All data measured at the main experiment plots of a large grassland biodiversity experiment (the Jena Experiment; see further details below). In the main experiment, 82 grassland plots of 20 x 20 m were established from a pool of 60 species belonging to four functional groups (grasses, legumes, tall and small herbs). In May 2002, varying numbers of plant species from this species pool were sown into the plots to create a gradient of plant species richness (1, 2, 4, 8, 16 and 60 species) and functional richness (1, 2, 3, 4 functional groups). Plots were maintained by bi-annual weeding and mowing. 1. Dissolved phosphorus in soil solution: Suction plates installed on the field site in 10, 20, 30 and 60 cm depth were used to sample soil pore water. Cumulatively extracted soil solution was collected every two weeks from October 2002 to May 2006. The biweekly samples from 2002, 2003 and 2004 were analyzed for dissolved organic phosphorus (DOP), dissolved inorganic phosphorus (PO4P) and dissolved total phosphorus (TDP) by Continuous Flow Analyzer (CFA SAN ++, SKALAR [Breda, The Netherlands]). 2. Seasonal values of dissolved inorganic phosphorus in soil solution were calculated as volume-weighted mean values of the biweekly measurements (spring = March to May, summer = June to August, fall = September to November, winter = December to February). 3. Phosphorus fractions in soil: Five independent soil samples per plot were taken in a depth of 0-15 cm using a soil corer with an inner diameter of 1 cm. The five samples per plot were combined to one composite sample per plot. A four-step sequential P fractionation (Hedley fractions) was applied and concentrations of P fractions in soil were measured photometrically (molybdenum blue-reactive P) with a Continuous Flow Analyzer (Bran&Luebbe, Germany).

Mineral nitrogen from KCl extractions of soil from the Jena Experiment (Main Experiment up to 30cm depth, year 2002)

As an estimate of plant-available N, this data set contains measurements of inorganic nitrogen (NO3-N and NH4-N, the sum of which is termed mineral N or Nmin) determined by extraction with 1 M KCl solution of soil samples from the main experiment plots of a large grassland biodiversity experiment (the Jena Experiment; see further details below). In the main experiment, 82 grassland plots of 20 x 20 m were established from a pool of 60 species belonging to four functional groups (grasses, legumes, tall and small herbs). In May 2002, varying numbers of plant species from this species pool were sown into the plots to create a gradient of plant species richness (1, 2, 4, 8, 16 and 60 species) and functional richness (1, 2, 3, 4 functional groups). Plots were maintained by bi-annual weeding and mowing. Soil sampling and analysis: Five soil cores (diameter 0.01 m) were taken at a depth of 0 to 0.15 m and 0.15 to 0.3 m of the mineral soil from each of the experimental plots in September 2002. Samples of the soil cores per plot were pooled during each sampling campaign. NO3-N and NH4-N concentrations were determined by extraction of soil samples with 1 M KCl solution and were measured in the soil extract with a Continuous Flow Analyzer (CFA, Skalar, Breda, Netherlands).

Mineral nitrogen from KCl extractions of soil from the Jena Experiment (Main Experiment up to 30cm depth, year 2004)

As an estimate of plant-available N, this data set contains measurements of inorganic nitrogen (NO3-N and NH4-N, the sum of which is termed mineral N or Nmin) determined by extraction with 1 M KCl solution of soil samples from the main experiment plots of a large grassland biodiversity experiment (the Jena Experiment; see further details below). In the main experiment, 82 grassland plots of 20 x 20 m were established from a pool of 60 species belonging to four functional groups (grasses, legumes, tall and small herbs). In May 2002, varying numbers of plant species from this species pool were sown into the plots to create a gradient of plant species richness (1, 2, 4, 8, 16 and 60 species) and functional richness (1, 2, 3, 4 functional groups). Plots were maintained by bi-annual weeding and mowing. Soil sampling and analysis: Five soil cores (diameter 0.01 m) were taken at a depth of 0 to 0.15 m and 0.15 to 0.3 m of the mineral soil from each of the experimental plots in March and October 2004. Samples of the soil cores per plot were pooled during each sampling campaign. NO3-N and NH4-N concentrations were determined by extraction of soil samples with 1 M KCl solution and were measured in the soil extract with a Continuous Flow Analyzer (CFA, Skalar, Breda, Netherlands).