Soil property differences among high‐ and average‐yielding soya bean areas in Arkansas,USA

Soya bean [Glycine max (L.) Merr] yields >6719 kg/ha (100 bu/ac) have only recently and infrequently been achieved. Quantifying soil property differences between high‐ and average‐yielding areas can help to further identify non‐plant‐related properties contributing to soya bean yield potential. The objective of this study was to evaluate the effects of region and soil depth on soil property differences between high‐ and average‐yielding areas. In each of the seven regions of the ‘Grow for the Green’ yield contest in Arkansas, prior to or just after harvest in 2014 and 2015, soil samples were collected from the top 20 cm of one contest high‐yield (HY ) area that was in close proximity to an average‐yield (AY ) area. Across all regions and both years, soya bean yields differed (P  <  0.05) between yield areas, averaging 4701 and 5498 kg/ha in AY and HY areas, respectively. Averaged across soil depth and years, numerous soil properties differed (P  <  0.05) between HY and AY areas within at least one of seven regions. Total soil C content was at least 20.2% greater in the HY than in the AY area in three of seven regions. Extractable soil P content was, on average, 19.4 kg/ha greater in HY than in AY areas in three of the seven regions. Results from this study have the potential to help producers better understand soil properties that contribute to or hinder achieving ultra‐high (>6719 kg/ha) soya bean yields.     

Straw mulching with fertilizer nitrogen: An approach for improving crop yield,soil nutrients and enzyme activities

Field experiments were conducted to study soil properties, soil enzymes activities, water use efficiency (WUE) and crop productivity after six years of soya bean straw mulching in the semi‐arid conditions of China. The experiment included four treatments: CK (Control), N (240 kg N ha^‐1), H (soya bean straw mulching at half rate 700 kg ha^‐1 with 240 kg N ha^‐1) and F (soya bean straw mulching at full rate 1,400 kg ha^‐1 with 240 kg N ha^‐1). Soil organic carbon (SOC), soil labile organic carbon (LOC), soil available N (AN), available P (AP) and enzyme activities were analysed after wheat harvesting in 2016 and 2017. Results show that straw amounts had positive effects on the soil fertility indices being higher for treatment F. The SOC, LOC, AN, AP and enzyme activities (i.e. saccharase, urease and alkaline phosphatase) were in the order of F > H > N > CK. High wheat grain yield and WUE were observed for F treatment. A total of six years mulching along with 240 kg ha^‐1 nitrogen fertilizer application is sufficient for wheat yield stability and improving soil properties except urease activities in the semi‐arid condition of China. However, the straw mulching amount should be further studied with minimum nitrogen fertilizer for an environment‐friendly and effective approach for improving the soil biological properties with adequate crop production on a sustainable basis in the semi‐arid region of China.     

Time‐lapse monitoring of soil water content using electromagnetic conductivity imaging

The volumetric soil water content (θ) is fundamental to agriculture because its spatiotemporal variation in soil affects the growth of plants. Unfortunately, the universally accepted thermogravimetric method for estimating volumetric soil water content is very labour intensive and time‐consuming for use in field‐scale monitoring. Electromagnetic (EM) induction instruments have proven to be useful in mapping the spatiotemporal variation of θ. However, depth‐specific variation in θ, which is important for irrigation management, has been little explored. The objective of this study was to develop a relationship between θ and estimates of true electrical conductivity (σ) and to use this relationship to develop time‐lapse images of soil θ beneath a centre‐pivot irrigated alfalfa (Medicago sativa L.) crop in San Jacinto, California, USA. We first measured the bulk apparent electrical conductivity (EC_a – mS/m) using a DUALEM‐421 over a period of 12 days after an irrigation event (i.e. days 1, 2, 3, 4, 6, 8 and 12). We used EM4Soil to generate EM conductivity images (EMCIs). We used a physical model to estimate θ from σ, accounting for soil tortuosity and pore water salinity, with a cross‐validation RMSE of 0.04 cm³/cm³. Testing the scenario where no soil information is available, we used a three‐parameter exponential model to relate θ to σ and then to map θ along the transect on different days. The results allowed us to monitor the spatiotemporal variations of θ across the surveyed area, over the 12‐day period. In this regard, we were able to map the soil close to field capacity (0.27 cm³/cm³) and approaching permanent wilting point (0.03 cm³/cm³). The time‐lapse θ monitoring approach, developed using EMCI, has implications for soil and water use and management and will potentially allow farmers and consultants to identify inefficiencies in water application rates and use. It can also be used as a research tool to potentially assist precision irrigation practices and to test the efficacy of different methods of irrigation in terms of water delivery and efficiency in water use in near real time.     

Textural Comparisons of Gluten‐Free and Wheat‐Based Doughs,Batters, and Breads

Studies were conducted with two newly developed gluten‐free bread recipes. One was based on corn starch (relative amount 54), brown rice (25), soya (12.5), and buckwheat flour (8.5), while the other contained brown rice flour (50), skim milk powder (37.5), whole egg (30), potato (25), and corn starch (12.5), and soya flour (12.5). The hydrocolloids used were xanthan gum (1.25) and xanthan (0.9) plus konjac gum (1.5), respectively. Wheat bread and gluten‐free bread made from commercial flour mix were included for comparison. Baking tests showed that wheat and the bread made from the commercial flour mix yielded significantly higher loaf volumes (P < 0.01). All the gluten‐free breads were brittle after two days of storage, detectable by the occurrence of fracture, and the decrease in springiness (P < 0.01), cohesiveness (P < 0.01), and resilience (P < 0.01) derived from texture profile analysis. However, these changes were generally less pronounced for the dairy‐based gluten‐free bread, indicating a better keeping quality. Confocal laser‐scanning microscopy showed that the dairy‐based gluten‐free bread crumb contained network‐like structures resembling the gluten network in wheat bread crumb. It was concluded that the formation of a continuous protein phase is critical for an improved keeping quality of gluten‐free bread.     

Integrating socio‐economic and biophysical assessments using a land use allocation model

This work is devoted to bridging the gap between large‐area, economically driven macromodels such as the Canadian Regional Agriculture Model (CRAM) and small‐area biophysically based process models used in environmental assessments through the development of a Land Use Allocation Model (LUAM). LUAM is designed to enable environmental assessments of economic scenarios to be conducted by allocating crop area changes predicted for large areas by CRAM to much smaller Soil Landscapes of Canada (SLC) polygons through an optimization method based on land capability, relative crop productivity and current land use. To develop the procedures, we used linear programming to optimize crop production for large areas under current commodity prices and land productivity ratings and then allocated the results to much smaller soil‐landscape polygons based on land capability. To assess the validity of our prototype LUAM, we compared the predicted crop areas with actual crop data from the Census of Agriculture using the method of cumulative residuals (MCR). We concluded that this version of the LUAM model can predict the location of land use to some extent, but requires further refinement. The potential for further development of LUAM using the Land Suitability Rating System (LSRS) is discussed.     

Change in soil organic carbon following the ‘Grain‐for‐Green’ programme in China

Agricultural soils are considered to have great potential for carbon sequestration through land‐use change. In this paper, we compiled data from the literatures and studied the change in soil organic carbon (SOC) following the ‘Grain‐for‐Green’ Programme (GGP, i.e., conversion from farmland to plantation, secondary forests and grasslands) in China. The results showed that SOC stocks accumulated at an average rate of 36·67 g m⁻² y⁻¹ in the top 20 cm with large variation. The current SOC storage could be estimated using the initial SOC stock and year since land use transformation (Adjusted R² = 0·805, p = 0·000). After land use change, SOC stocks decreased during the initial 4–5 years, followed by an increase after above ground vegetation restoration. Annual average precipitation and initial SOC stocks had a significant effect (p < 0·05) on the rate of change in SOC, while no significant effects were observed between plantation and natural regeneration (p > 0·05). The ongoing ‘Grain‐for‐Green’ project might make significant contribution to China's carbon sequestration. Copyright © 2009 John Wiley & Sons, Ltd.     

Soil organic carbon in cropping sequences with predominance of soya bean in the argentinean humid Pampas

Soya bean (Glycine max (L.) Merr.) monoculture can lead to a decrease in labile fractions of soil organic carbon (SOC). This study sought to evaluate the effects of cover crops (CC), application of fertilizer, and crop rotation on SOC, particulate organic carbon (POC), and soil carbon input in soya bean-based crop sequences under a no-till cropping system in the Argentinean Humid Pampas. Five crop sequences at two sites differing in initial SOC were evaluated: continuous soya bean (Sb), continuous soya bean fertilized with phosphorus (P) and sulphur (S) (Sbf), grass CC / PS-fertilized soya bean (CC/Sbf), nitrogen (N)-fertilized CC / PS-fertilized soya bean (CCf/Sbf) and NPS-fertilized crop rotation with high intensification sequence index (ISI) (Rot). At 0–5 cm, SOC and POC were higher (p < .05) in the sequences with higher residue-C supply (CC/Sbf; CCf/Sbf and Rot) at both sites. Changes in SOC at 0–20 cm simulated by AMG model closely tracked measured results at 0–20 cm. Findings from this study suggest that the inclusion of CC or crop rotation with high ISI improved C balance in soils under crop sequences with soya bean predominance.     

Potential to predict depth‐specific soil–water content beneath an olive tree using electromagnetic conductivity imaging

Efficient monitoring of soil moisture is becoming increasingly important. To understand soil–plant–water dynamics, we evaluate the potential of using a multiple‐coil‐array electromagnetic induction instrument and inversion software to map soil moisture beneath an olive tree. On twelve different days, we collected apparent electrical conductivity (EC _a) data using a DUALEM ‐21S and the volumetric soil moisture (θ ) using a bank of soil moisture sensors on opposite sides of the tree. Using EM 4Soil, we inverted the EC _a data on five of the days and established a site‐specific calibration between estimates of true electrical conductivity (σ ) and θ . The strongest calibration relationship between σ and θ (R ² = 0.65) was obtained for a full‐solution, S2 algorithm and damping factor of 1.2. A leave one out cross‐validation (LOOCV ) showed the calibration was robust, with a root mean square error (RMSE ) of 0.046 m³/m³, a mean error (ME ) of 0.001 m³/m³ and a Lin's concordance of 0.72. We subsequently evaluated the calibration relationship on the seven remaining days and over a drying period of 120 days. This approach provides information about the temporal evolution of θ by a LOOCV of validation with a RMSE of 0.037, ME of −0.003 and a Lin's concordance of 0.54. Improvement could be achieved by aligning the DUALEM ‐21S in the same orientation as the sensors, with time‐lapse inversion also being advantageous.     

Phosphorus use efficiency of improved faba bean (Vicia faba) varieties in low‐input agro‐ecosystems

The use of phosphorus (P)‐efficient legumes is a prerequisite for sustainable intensification of low‐input agro‐ecosystems. A study was undertaken in a farmer's field in the tropical highlands of Ethiopia to assess the agronomic performance, P acquisition efficiency (PAE), and P utilization efficiency (PUE) of six improved faba bean varieties (Vicia faba L. var. CS‐20DK, Degaga, Gebelcho, Moti, Obse, Walki) without and with P application. Varieties showed significant variations in PUE, but P application had no significant effect on PUE. Variety Moti demonstrated highest PUE of 272 kg grain kg^?1 P, which was 1.6‐fold higher than the lowest PUE (164 kg grain kg^?1 P) of Gebelcho. PUE was significantly and positively correlated with grain yield (r = 0.542) and negatively correlated with shoot PAE (r = –0.541), indicating that PUE is important for grain yield. The results demonstrate that variations in grain and biomass yield of faba beans were largely due to differences in PUE and not due to PAE. Therefore, we argue that genetic resources of faba bean varieties showing optimal agronomic performance and high PUE in low‐input agro‐ecosystems should be better explored. Introduction of such varieties in low‐input cereal‐based cropping systems could improve and enhance P use efficiency at the system level.     

Laboratory Measurement of Yield and Composition of Dry‐Milled Corn Fractions Using a Shortened,Single‐Stage Tempering Procedure

The objective was to describe a laboratory‐scale dry‐milling procedure that used single‐stage tempering and determine the effect of hybrid on yields and fraction compositions in milled corn. Samples of 11 commercially available hybrids were processed through a laboratory dry‐milling procedure that used 1 kg samples of corn to produce milling fractions of large grits, small grits, fines, germ, and pericarp. Compositions of milling fractions (protein, neutral detergent fiber, ash, and crude fat) were determined. The procedure used a single‐stage tempering step that increased corn moisture from 15 to 23.5% wb during an 18‐min tempering period. Germ were separated from endosperm particles using a roller mill followed by screening over a sieve with 1.68‐mm openings. Coefficients of variability were small, indicating acceptable repeatability. Overall yield means were 39.2, 25.3, 13.8, 78.2, 14.3, and 6.8 g/100 g (db) for large grits, small grits, fines, total endosperm, germ, and pericarp, respectively. There were effects due to hybrid (P < 0.05) on fraction yields and compositions of milling fractions. Correlations (r) among endosperm fractions (large grits, small grits, and fines) ranged from 0.54 to |–0.92|. Correlations among endosperm fractions and germ and pericarp were <0.68. The developed dry‐milling method estimated milling yields among hybrids with low standard deviations relative to the means and should be a useful tool for research and industry in measuring dry‐milling characteristics.     

Evaluating a low‐cost portable NIR spectrometer for the prediction of soil organic and total carbon using different calibration models

This study aims to assess the performance of a low‐cost, micro‐electromechanical system‐based, near infrared spectrometer for soil organic carbon (OC) and total carbon (TC) estimation. TC was measured on 151 soil profiles up to the depth of 1 m in NSW, Australia, and from which a subset of 24 soil profiles were measured for OC. Two commercial spectrometers including the AgriSpec^TM (ASD) and NeoSpectra^TM (Neospectra) with spectral wavelength ranges of 350–2,500 and 1,300–2,500 nm, respectively, were used to scan the soil samples, according to the standard contact probe protocol. Savitzky–Golay smoothing filter and standard normal variate (SNV) transformation were performed on the spectral data for noise reduction and baseline correction. Three calibration models, including Cubist tree model, partial least squares regression (PLSR) and support vector machine (SVM), were assessed for the prediction of soil OC and TC using spectral data. A 10‐fold cross‐validation analysis was performed for evaluation of the models and devices accuracies. Results showed that Cubist model predicts OC and TC more accurately than PLSR and SVM. For OC prediction, Cubist showed R² = 0.89 (RMSE = 0.12%) and R² = 0.78 (RMSE = 0.16%) using ASD and NeoSpectra, respectively. For TC prediction, Cubist produced R² = 0.75 (RMSE = 0.45%) and R² = 0.70 (RMSE = 0.50%) using ASD and NeoSpectra, respectively. ASD performed better than NeoSpectra. However, the low‐cost NeoSpectra predictions were comparable to the ASD. These finding can be helpful for more efficient future spectroscopic prediction of soil OC and TC with less costly devices.     

Estimating Sediment Delivery Ratios for Grassed Waterways using WEPP

Grassed waterways (GWWs) transport sediment and nutrients from upland source areas to receiving waters. Watershed planners have a critical need to understand GWW sediment delivery to optimally target source area management practices. Better physically based tools are needed to estimate sediment delivery by GWWs. This study developed several distributed sediment delivery ratio (SDR) regressions for GWWs using the process‐based Water Erosion Prediction Project (WEPP) model to provide simple equations to estimate sediment delivery for planning applications. Water Erosion Prediction Project was calibrated and validated for runoff and sediment yield for large 30.2‐ha and smaller 5·7‐ha nested watersheds with terraces and a common GWW outlet. A crop rotation of corn, oat and alfalfa and fall tillage using chisel plow were used in the nested watersheds. A hypothetical management case without terraces using corn, oat and alfalfa rotation with chisel plow as fall tillage was also evaluated for the 5·7‐ha watershed and the GWW. The length, slope, Manning's roughness coefficient and infiltration rate for the GWW were varied and SDRs calculated for 30 representative (in terms of daily rainfall) days over a 20‐year period of simulated climate. Regressions were developed for the existing (terraced) and hypothetical (non‐terraced) management scenarios for early (April–July), late (August–October) and full (April–October) growing seasons. Equations developed for the non‐terrace watershed had higher R ² values compared to the terraced watershed suggesting that channel and rainfall parameters were better able to explain the variation in SDR for the non‐terraced watershed. Manning's roughness coefficient was the most significant parameter for predicting SDR for both the terraced and non‐terraced watersheds. The equations developed here can be used to estimate SDRs for watersheds that are drained via GWWs having similar physical characteristics: slope (1–5%), Mannings's roughness coefficient (0·1–0·3), length (0·15–1 km) and infiltration rate (0·025–25 mm h⁻¹). The SDRs can be used to estimate sediment yield, which is an essential element for making land management decisions but is rarely measured. Copyright © 2017 John Wiley & Sons, Ltd.     

Can tropical grasses grown as cover crops improve soil phosphorus availability?

Tropical grasses grown as cover crops can mobilize phosphorus (P) in soil and have been suggested as a tool to increase soil P cycling and bioavailability. The objective of this study was to evaluate the effect of tropical grasses on soil P dynamics, lability, desorption kinetics and bioavailability to soya bean, specifically to test the hypothesis that introducing grass species in the cropping system may affect soil P availability and soya bean development according to soil P concentration. Three grass species, ruzi grass (Urochloa ruziziensis ), palisade grass (Urochloa brizantha ) and Guinea grass (Megathyrsus maximus ), were grown in soils with contrasting P status. Soya bean was grown after grasses to assess soil P bioavailability. Hedley P fractionation, microbial biomass P, phytase‐labile P and the diffusive gradient in thin films were determined, before and after cultivation. It was found that grasses remobilized soil P, reducing the concentration of recalcitrant P forms. The effect of grasses on changing the P desorption kinetics parameters did not directly explain the observed variation on P bioavailability to soya bean. Grasses and microorganisms solubilize recalcitrant organic P (P_o) forms and tropical grasses grown as cover crops increased P bioavailability to soya bean mainly due to the supply of P by decomposition of grass residues in low‐P soil. However, no clear advantages in soya bean P nutrition were observed when in rotation with these grasses in high‐P soil. This study indicates that further advantages in soya bean P nutrition after tropical grasses may be impeded by phytate, which is not readily available to plants.     

Field‐scale potassium and phosphorus fluxes in the bioenergy crop switchgrass: Theoretical energy yields and management implications

Our understanding of how mineral nutrition affects productivity and composition of bioenergy crops grown on marginal lands remains fragmented and incomplete despite world‐wide interest in using herbaceous biomass as an energy feedstock. Our aim was to determine switchgrass (Panicum virgatum L.) biomass production and maize (Zea mays L.) grain yield on marginal soils used previously to evaluate the effect of soil phosphorus (P) and potassium (K) fertility on alfalfa (Medicago sativa L.) forage production. Grain yield of maize was reduced on P‐ and/or K‐limited plots that also impaired alfalfa forage yield, whereas switchgrass biomass yields were high even in plots possessing very low available P (4 mg kg^–1) and K (< 70 mg kg^–1) levels. Linear‐plateau regression models effectively described the relationship of soil test P and K to tissue P and K concentrations, and tissue P and K concentrations accurately predicted removal of P and K in harvest biomass. However, neither soil‐test P and K, nor tissue P and K concentrations were effective as diagnostics for predicting switchgrass biomass yield nor could soil tests and their change with cropping predict nutrient removal. Concentrations of cellulose, hemicellulose, lignin, and ash were not influenced by P and K nutrition. Predicted bio‐ethanol production was closely associated with biomass yield whereas high biomass K concentrations reduced estimated bio‐oil production per hectare by as much as 50%. Additional research is needed to identify diagnostics and managements to meet the bioenergy production co‐objectives of having high yield of biomass with very low mineral nutrient concentrations (especially K) while sustaining and improving the fertility of marginal soils.     

Multi‐factorial causes of land‐use change: land‐use dynamics in the agropastoral village of Im Mial,northwestern Syria

Land‐use dynamics in drylands are complex processes. In the context of a typical agropastoral village in northwestern Syria Im Mial, the effects of demographic and social changes, reduced soil productivity, changes in agricultural technologies and historical events on land use and land productivity are examined. Decreasing yields, mainly the result of reduced fallow periods and low investments in the land, and the deterioration of the grazing resources are the two main signs of the loss of land productivity in the area. The growing population forces the villagers to practise continuous rainfed barley cultivation with no or only occasional fallow, and without any application of plant nutrients. Also, technological changes, from the use of donkey ploughs and hand harvesting to less labour‐intensive and time‐consuming cultivation practices with tractors and combine harvesters, and the increased importance of stubble in the livestock diet have contributed to the reduction of the fallow periods. The villagers attribute the yield decreases mainly to the low rainfall in the area. The high rainfall variability discourages the fallowing of fields because continuous cultivation maximizes the chances for good harvests in years with high rainfall. There is also an expansion of cultivation into the less fertile and sloping traditional grazing areas. Population growth, increased numbers of livestock and the expansion of cultivated land into grazing areas has also put pressure on the grazing resources of the village. The possession of livestock is seen as a sign of wealth and the villagers aim to have large flocks of animals. For them, livestock is also an important means for investment of cash earned from off‐farm work, which is the main source of income for most of the households in the village. There is a recent trend of increasing levels of crop‐livestock integration with less free grazing that produces higher return to the land users. This may also have a positive effect on the restoration and conservation of the degraded natural traditional grazing grounds. The stabilization and productive use of the land resources in this dry environment requires the combined and interdisciplinary effort from both the land‐users and the policy‐makers. Copyright © 2001 John Wiley & Sons, Ltd.     

Land‐use change in subalpine grassland soils: Effect on particulate organic carbon fractions and aggregation

Abandonment of mountain grassland often changes vegetation composition and litter quantity and quality, but related effects on labile soil organic matter (SOM) are largely unknown. The aim of this study was to investigate the impacts of grassland management and abandonment on soil carbon distribution in light (< 1.6 g cm^–3) particulate organic matter (POM) and aggregation along a gradient of management intensity including hay meadows, pastures, and abandoned grasslands. The reduction of management intensity is an interregional phenomenon throughout the European Alps. We therefore selected sites from two typical climate regions, namely at Stubai Valley, Austria (MAT: 3°C, MAP: 1097 mm) and Matsch Valley, Italy (MAT: 6.6°C, MAP: 527 mm), to evaluate effects of land‐use change in relation to climate. Free water‐floatable and free POM (wPOM, fPOM), and an occluded POM fraction (oPOM), were isolated from three water‐stable aggregate size classes (2–6.3 mm, 0.25–2 mm, < 0.25 mm) using density fractionation. Aggregate mean weight diameter slightly decreased with decreasing management intensity. In contrast to absolute POM‐C, fPOM‐C increased in aggregates at both sites with abandonment. Because the oPOM‐C was less affected by abandonment, the ratio of oPOM‐C : fPOM‐C shifted from > 1 to < 1 from meadow to abandoned grassland in aggregates at both sites and thus independent of climate. This suggests that in differently managed mountain grasslands free and occluded POM are functionally different SOM fractions. In bulk soil, the oPOM‐C : fPOM‐C ratio is better suited as an indicator for the response of SOM to management reduction in subalpine grasslands than the total soil C, absolute or relative POM‐C content.     

Cesium‐137‐based erosion‐rate determination of a steep mountainous region

Data on quantification of erosion rates in alpine grasslands remain scarce but are urgently needed to estimate soil degradation. We determined soil‐erosion rates based on ¹³⁷Cs in situ measurements. The method integrates soil erosion over the last 22 y (time after the Chernobyl accident). Measured erosion rates were compared with erosion rates modeled with the Universal Soil Loss Equation (USLE). The comparison was done in order to find out if the USLE is a useful tool for erosion prediction in steep mountainous grassland systems. Three different land‐use types were investigated: hayfields, pasture with dwarf shrubs, and pasture without dwarf shrubs. Our test plots are situated in the Urseren Valley (Central Switzerland) with a mean slope steepness of 37°. Mean annual soil‐erosion rates determined with ¹³⁷Cs of the investigated sites ranged between the minimum of 4.7 t ha^–1 y^–1 for pastures with dwarf shrubs to >30 t ha^–1 y^–1 at hayfields and pastures without dwarf shrubs. The determined erosion rates are 10 to 20 times higher compared to previous measurements in alpine regions. Our measurements integrated over the last 22 y, including extreme rainfall events as well as winter processes, whereas previous studies mostly reported erosion rates based on summer time and short‐term rainfall simulation experiments. These results lead to the assumption that heavy‐rainfall events as well as erosion processes during winter time and early spring do have a considerable influence on the high erosion amounts that were measured. The latter can be confirmed by photographs of damaged plots after snowmelt. Erosion rates based on the USLE are in the same order of magnitude compared to ¹³⁷Cs‐based results for the land‐use type “pasture with dwarf shrubs”. However, erosion amounts on hayfields and pasture without dwarf shrubs are underestimated by the USLE compared to ¹³⁷Cs‐based erosion rates. We assume that the underestimation is due to winter processes that cause soil erosion on sites without dwarf shrubs that is not considered by the USLE. Dwarf shrubs may possibly prevent from damage of soil erosion through winter processes. The USLE is not able to perform well on the affected sites. Thus, a first attempt was done to create an alpine factor for the USLE based on the measured data.     

Glycosidases in soils as affected by cropping systems

Glycosidases are a group of soil enzymes that play a major role in degradation of carbohydrates. This study was conducted to assess the impact of crop rotation and N fertilization on the activities of α‐ and β‐glucosidases and α‐ and β‐galactosidases in plots of two long‐term field experiments at the Clarion‐Webster Research Center (CWRC) and Northeast Research Center (NERC) in Iowa. Surface‐soil (0–15 cm) samples were taken in 1996 and 1997 in corn (Zea mays L.), soybean (Glycine max (L.) Merr.), oats (Avena sativa L.), or meadow (alfalfa) (Medicago sativa L.) plots that received 0 or 180 kg N ha^–1, applied as urea before corn, and an annual application of 20 kg P ha^–1 and 56 kg K ha^–1. Activities of the four glycosidases were significantly affected by crop rotations in both years at the two sites but not by nitrogen application. In general, higher activities were observed in plots under meadow or oat and the lowest in continuous corn (CWRC) and soybean (NERC). Four‐year rotation showed the highest activity, followed by 2‐year rotation and monocropping systems. Linear‐regression analyses indicated that, in general, the activities of the glycosidases were significantly correlated with microbial‐biomass C (r > 0.302, p ≤ 0.05) and microbial‐biomass N (r > 0.321, p ≤ 0.05), organic‐C (r > 0.332, p ≤ 0.05) and organic‐N (r > 0.399, p ≤ 0.01) contents of the soils. Results of this work suggest that multicropping stimulated the activities of the glycosidases. The specific activities of the glycosidases in soils of the two sites studied, expressed as g p‐nitrophenol released per kg of organic C, differed among the four enzymes. The lowest values were obtained for β‐galactosidase and α‐glucosidase, followed by α‐galactosidase and β‐glucosidase.     

Rainforest litter quality and chemical controls on leaf decomposition with near‐infrared spectrometry

Plant‐litter chemical quality is an important driver of many ecosystem processes, however, what actually constitutes high‐ or low‐quality litter (chemical potential for fast and slow decomposition, respectively) is often interpreted by the indices available. Here, near‐infrared spectroscopy (NIRS) was used to explore leaf‐litter chemical quality and the controls on decomposition in the tropical rainforest region of north Queensland Australia. Leaf‐litter samples from litterfall collections and litterbag studies were used. NIRS was used to calibrate the chemical compositions of the material (N, P, C, Mg, Ca, acid detergent fiber, acid detergent lignin, α‐cellulose, and total phenolics) from a smaller sample set covering the spectral range in the full set of samples. Calibrations were compared for both separate (local) and combined models, for litterbags, and litterfall. Coefficients of determination (r²) in the local models ranged from 0.88 (litterbag Mg) to 0.99 (litterfall N), with residual prediction deviation ratios > 3 for all constituents except Mg (≈ 2.5). Mass loss in the litterbags was strongly related to the NIR spectra, with model r²'s of 0.75 (in situ leaves) and 0.76 (common control leaf). In situ decomposability was determined from modeling the initial NIR spectra prior to decomposition with litterbag exponential‐decay rates (model r² of 0.81, n = 85 initial samples). A best subset model including litter‐quality, climate, and soil variables predicted decay better than the NIR decomposability model (r² = 0.87). For litter quality alone the NIR model predicted decay rate better than all of the best predictive litter–chemical quality indices. The decomposability model was used to predict in situ decomposability in the litterfall samples. The chemical variables explaining NIR decomposability for litterfall were initial P, C, and phenolics (linear model r² = 0.80, n = 2471). NIRS is a holistic technique that is just as, if not more accurate, than litter–chemical quality indices, when predicting decomposition and decomposability, shown here in a regional field study.     

Biophysical and socio‐economic causes for increasing fallow land in Tamil Nadu

The question of increasing fallow land assumes significance at national and international levels due to the decline in net cultivated area and increasing population. Biophysical characteristics of farmland and socio‐economic conditions of farmers are responsible for the increasing fallow. This study was carried out to assess the extent of permanent fallow and identify causes for its increase. High‐resolution remote sensing data were used to identify fallow land in two identified blocks of south India, viz. Nanguneri and Kangeyam. The land resources were characterized, and the specific biophysical and socio‐economic factors responsible for the increasing fallow land were assessed. Multiple regression analysis was carried out to identify the factors responsible for increasing fallows. Soil parameters such as erosion, soil texture, soil depth and available nitrogen contributed significantly (P > 0.05) to the increase in fallow land. The size of farm holding, number of farm fragments, distance from the road in Nanguneri and farm size and the distance to the nearest town in Kangeyam were socio‐economic factors that had a strong effect (P > 0.01) on increasing the fallow land. Variable importance rankings in random forest analysis indicated that soil erosion and soil pH had the largest impact on the decision to fallow land in Nanguneri and Kangeyam blocks, respectively. Based on biophysical and socio‐economic constraints, the land resources of fallow land were evaluated for other alternate land use options and policy measures were suggested.