Bodensystematik und Bodenklassifikation Teil I: Grundbegriffe

Soil systematics and classification systems Part I: Fundamentals Soil‐ordering systems are primarily based and developed on one of two underlying principles: They are either categorized according to soil‐forming processes, or the formation of categories develops by chosen parameters. This perspective has already been established in the literature, though it is often confusing as many terms are defined and applied differently. In this contribution, the various definitions of systematics, classification, taxonomy, and identification will be clearly differentiated and summarized. The core of our work is to clearly define and contrast three terms: systematics, classification, and identification. Systematics is the fundamental scientific and deductive ordering of objects into systematic units. The purpose of this approach is to organize the entire spectrum of knowledge within a discipline into a transparent and manageable form. Classification, in direct contrast to systematics, is goal‐oriented and an inductive ordering of objects. Thus, the ordering scheme consists of classes which are clearly parameterized. Identification is the ordering of new objects into an already existing systematics or classification system. Close attention is paid to both the differences and the similarities between a systematics and a classification system, especially pertaining to their practical applications. The identification requires that the category‐forming characteristics can be measured (e.g., for soil systematics, these are the soil‐forming processes and factors). Currently, it is unfortunately not feasible to objectively quantify most soil‐forming processes. Thus, most attempts at categorizing soils by systematics are hypothetical and highly subjective in nature. The resulting identification derived from the soil systematics approach is open to questions and contestable, since a graded measuring system does not yet exist to verify these determinations. In contrast, a soil‐classification system does allow an objective soil‐profile identification, although such systems are conceived pragmatically and designed for a practical purpose (e.g., not scientifically based on process intensities). Unfortunately, such a classification system cannot be applied as a universal scientific categorization system due to this method of conception. Both categorization approaches are required in soil science in order to satisfy both the practical and the scientific aspects of the field. However, substantial research must be done to complete and verify systematics. The only viable short‐term solution is through the development of a graded classification system where the categories of the system are directly derived from the current systematics approach. In the long run both the exact investigation and the detailed modeling of the soil‐forming processes are inevitable.     

Gonadotropin‐Releasing Hormone Administration to Dairy Cows without a Corpus Luteum 4 Weeks after Calving Increases Reproductive Performance

This field study investigated whether the administration of a single dose of gonadotropin‐releasing hormone (GnRH) to dairy cows without a corpus luteum (CL) 4 weeks after calving can improve reproductive performance. Holstein dairy cows underwent ultrasonography to assess the presence of ovarian structures at 29.2 ± 5.2 days post‐partum, and cows were divided into two main groups based on the presence (CL group, n = 230) or absence (non‐CL group, n = 460) of a CL. The non‐CL group was further randomly divided into two subgroups based on the administration of GnRH (non‐CL GnRH group, n = 230) or no GnRH (non‐CL control group, n = 230). Subsets of cows from non‐CL control (n = 166) and non‐CL GnRH (n = 175) groups received a second ultrasonography at 44.5 ± 5.4 days post‐partum to assess CL formation. The percentage of cows with CL at the second ultrasonography was greater in the non‐CL GnRH group (70.9%) than in the non‐CL control group (53.0%, p = 0.0006). The hazard of the first post‐partum insemination by 150 days in milk (DIM) was higher in the CL group than in the non‐CL control group (hazard ratio [HR]: 1.36, p = 0.001). The probability of a pregnancy to the first insemination was higher in non‐CL GnRH (odds ratio [OR]: 1.50, p = 0.04) and CL groups (OR: 1.55, p = 0.03) compared to the non‐CL control group. Furthermore, the hazard of pregnancy by 210 DIM was higher in non‐CL GnRH (HR: 1.30, p = 0.01) and CL (HR: 1.51, p = 0.0001) groups than in the non‐CL control group. In conclusion, administration of GnRH to dairy cows without a CL 4 weeks after calving was associated with an increase in ovulation and improved reproductive performance.     

Investigating flow mechanisms in a forest soil by mixed‐effects modelling

Uniform and preferential flow produces typical infiltration patterns. We made three tracer experiments in a Norway spruce forest soil and qualitatively identified the dominant flow regime based on stained patterns. We analysed soil texture, fine root density and soil bulk density from preferential flow paths and the soil matrix by means of linear mixed‐effects models. These models can account for dependences in the data structure caused by hierarchical sampling and can deal with missing values. There were between 44% (topsoil) and 76% (subsoil) larger root densities in preferential flow paths than in the soil matrix. No significant differences in soil texture were detected. The bulk density was greater in the soil matrix by 0.12 g cm⁻³, which is probably because of a greater soil organic matter content of preferential flow paths. Using flow patterns and model results we identified the dominant flow mechanisms. At this study site, roots constituted the main preferential flow paths and induced macropore flow, especially in the topsoil. In the subsoil, root density decreased and inhomogeneous infiltration from preferential flow paths into the soil matrix caused unstable flow.     

Uncertainty in the spatial prediction of soil texture: Comparison of regression tree and Random Forest models

Within the southern Ecuadorian Andes, landslides have an impact on landscape development. Landslide risk estimation as well as hydrological modelling requires physical soil data. Statistical models were adapted to predict the spatial distribution of soil texture from terrain parameters. For this purpose, 56 soil profiles were analysed horizon-wise by pipette and laser method. Results by pipette compared to laser method showed the expected shift to higher silt and lower clay contents. Linear regression equations were adapted. The performance of regression tree (RT) and Random Forest (RF) models was compared by hundredfold model runs on random Jackknife partitions. Digital soil maps of sand, silt and clay percentage mean and standard deviation indicate model variability and prediction uncertainty.RF models performed better than RT models. All terrain factors considered in the analysis influenced soil texture of the surface horizon, but altitude a.s.l. was assigned the highest variable importance during model construction. Shallow subsurface flow is considered responsible for increasing sand/clay ratios with increasing altitude, on steep slopes and with overland flow distance to the channel network by removing clay particles downslope. Deeper soil layers are not influenced by this process and therefore, did not show the same texture properties. However, the influence of parent material and landslides on the spatial distribution of soil texture cannot be neglected. Model performance, most probably, could be improved by a bigger dataset.     

Natural abundance of 18O of sugar biomarkers in topsoils along a climate transect over the Central Scandinavian Mountains,Norway

Precipitation and topsoil samples from a climate transect over the Scandinavian Mountains, Norway, were analyzed for bulk and compound‐specific δ¹⁸O values. The natural abundance of ¹⁸O in the plant‐derived hemicellulose biomarkers arabinose and xylose correlates positively with δ¹⁸O of bulk soil, but not with δ¹⁸O of precipitation. This suggests that other factors than δ¹⁸O_prec, such as evaporative ¹⁸O enrichment of leaf water, exert a strong influence on the natural abundance of ¹⁸O in soils.     

Response of Boar Sperm to the Treatment with Cholesterol‐Loaded Cyclodextrins Added Prior to Cryopreservation

Cryopreserved boar sperm is not used extensively for artificial insemination, owing to the poor fertility rates of the sperm after freezing and thawing. The sperm membrane is damaged as the cells are cooled from body temperature to 5°C (cold shock), as well as during the freeze–thaw process. Increasing the cholesterol content of boar sperm membranes could help them survive cryopreservation, similar to sperm from other species that are cold shock sensitive. The aim of this study was to determine the optimal cholesterol‐loaded cyclodextrin (CLC) concentration to use for boar sperm cryopreservation, and the influence of CLCs on the cryosurvival of sperm from boars classified as good or poor freezers. Treating boar sperm with 1 mg of CLC/120 × 10⁶ sperm slightly improved (p < 0.05) the percentage of viable sperm after freezing–thawing. On the other hand, sperm, from both good and poor freezers, responded similarly to CLC treatment. Nevertheless, additional studies will be needed to study the effect of this treatment on other parameters of sperm quality.     

Environmental mastitis in intensive high‐producing dairy herds in New South Wales

Objective To determine the prevalence of mastitis pathogens in high‐producing intensive dairy herds in New South Wales. Design Field survey. Procedure Milk samples from the mastitis‐affected quarter were collected from cows on five high‐producing dairy farms in NSW. The 820 samples were cultured using standard microbiological culture techniques. Results Bacteria or fungi were isolated from 83.3% of samples (683/820). More than two colony types were isolated from 16.7% of samples (137/820), two types from 6.6% (54/820), and one type from 52.3% (429/820). No bacteria were isolated from 24.4% (200/820) of the primary cultures, but enrichment cultures of these samples yielded single colony type bacterial isolates from 36.5% (73/200) of samples. Environmental pathogens, including coliforms, environmental Streptococcus and Staphylococcus spp., made up 91% (555/610) of isolates and accounted for 33.6% (205/610), 41.6% (254/610) and 15.7% (96/610), respectively, of isolates. Escherichia coli accounted for 76.1% (156/205) of the coliform isolates, Streptococcus uberis and Streptococcus dysgalactiae accounted for 32.3% (82/254) and 28.0% (71/254), respectively, of the environmental streptococcal isolates. Contagious pathogens were uncommon, comprising only 2.5% (15/610) of the total isolates. Conclusion The incidence and causes of mastitis are largely influenced by farm management. The relatively high prevalence of coliform mastitis in the intensive high‐producing herds in this survey contrasts with the low incidence reported in surveys of pasture‐based herds in Victoria. If the Australian dairy industry continues its current trend of intensification, coliform intra‐mammary infections may emerge as an increasingly important cause of mastitis.     

华北平原主要农作物灌溉需水量的估算

本文根据华北平原农田水分循环特点,建立了一个农田土壤水分平衡模型.利用研究区内30个气象台站20～40年的气象资料,模拟计算了华北平原主要农作物(冬小麦、夏玉米和棉花)的历年灌溉需水量.在模拟过程中,考虑到华北平原土壤质地层次排列复杂,土壤持水特性不一,将土壤的最大有效含水量划分了5个等级.根据统计排频分析,确定了在干旱年、中等年及湿润年型下冬小麦、夏玉米和棉花的灌溉需水量.并分析了华北平原的1m 土层土壤最大有效含水量为180～240mm 范围时,3种作物多年平均的及不同年型的灌溉需水量在华北平原的区域分布特征.