Exclusion of livestock decouples the relationship between plant production and diversity, species richness on complex topography in typical steppe in the Loess Plateau, China.

Grazing is widely used in more than one-forth of global terrestrial ecosystems, with three quarters are distributed on complex topography. Grazing and topography have both resulted in degradation of approximately 49 % of natural grasslands. However, research on the interaction between topography and livestock exclusion on grassland characteristics is scarce. This study was carried out on a typical steppe to explore the effect of topography and enclosure year on vegetation characteristics. Aboveground biomass, and species richness were examined for three different enclosure years (0, 3, and 6 years), on four slopes (0°, 15°, 30°, and 45° slope), and three aspects (flat, shady and sunny). The results indicated that: The aboveground biomass on the 0° slope had a greater value after 6 years of the enclosure. Aboveground biomass increased with the increasing enclosure year, while it decreased with increasing slope except enclosure for 0 year on shady slope. Aboveground biomass on the shady slopes was greater than on the sunny slopes. Species richness of community and perennial plants increased with increasing slope and enclosure year. The annual plants richness inversely correlated with slope and enclosure year. All plant diversity indexes increased with increasing enclosure year. Margalef and Shannon-wiener indexes decreased with increasing slope, while Simpson and Pielou indexes increased. This paper demonstrates that aspect, slope and enclosure affect aboveground biomass by affecting other vegetation characteristics. In conclusion, grassland production can be improved with moderate livestock exclusion under different topography.

Can machine learning algorithms perform better than multiple linear regression in predicting nitrogen excretion from lactating dairy cows.

This study aims to compare the performance of multiple linear regression and machine learning algorithms for predicting manure nitrogen excretion in lactating dairy cows, and to develop new machine learning prediction models for MN excretion. Dataset used were collated from 43 total diet digestibility studies with 951 lactating dairy cows. Prediction models for MN were developed and evaluated using MLR technique and three machine learning algorithms, artificial neural networks, random forest regression and support vector regression. The ANN model produced a lower RMSE and a higher CCC, compared to the MLR, RFR and SVR model, in the tenfold cross validation. Meanwhile, a hybrid knowledge-based and data-driven approach was developed and implemented to selecting features in this study. Results showed that the performance of ANN models were greatly improved by the turning process of selection of features and learning algorithms. The proposed new ANN models for prediction of MN were developed using nitrogen intake as the primary predictor. Alternative models were also developed based on live weight and milk yield for use in the condition where nitrogen intake data are not available (e.g., in some commercial farms). These new models provide benchmark information for prediction and mitigation of nitrogen excretion under typical dairy production conditions managed within grassland-based dairy systems.

Litter decomposes slowly on shaded steep slope and sunny gentle slope in a typical steppe ecoregion.

Plant litter decomposition is mainly affected by litter properties and environmental factors, but the influence of terrain on litter decomposition is not well understood. We studied the effects of terrain on litter decomposition over a period of 12 months at six locations in a typical steppe ecoregion and measured the concomitant release of carbon (C), nitrogen (N), and phosphorus (P). The study site has two aspects, shaded and sunny, each aspect having three slopes: 15°, 30°, and 45°. The same mixed litter was used at each location to exclude the influence of litter quality variation. Results showed that soil temperature and moisture, solar radiation, and plant species diversity varied by terrain, which in turn, affected the k-value (standardized total effects, 0.78, 0.12, 0.92, 0.23, respectively) and the release of C (0.72, -0.25, 0.83, 0.24, respectively), N (0.89, -0.45, 0.76, 0.40, respectively) and P (0.88, 0.77, 0.58, 0.57, respectively). K-value and C release decreased with increasing slope on shaded aspect, while increased with increasing slope on sunny aspect. The release of N and P decreased with increasing slope on the shaded aspect. K-value and C, N, and P release were significantly higher on shaded than that on sunny aspect at 15° and 30°, while at 45°, it was higher on sunny than on shaded aspect. The litter mass loss was slower on shaded 45° and sunny 15°. So moderate grazing or mowing could be used to reduce litter accumulation and accelerate litter decomposition on these terrains. Structural equation modeling indicated that soil temperature and solar radiation had the greatest influence on k-value and C, N, and P release, and these two factors were directly related to soil moisture and plant species diversity. Overall, our results emphasize the need to consider terrain for litter decomposition in typical steppe ecoregions.

Growth Indicators of Main Species Predict Aboveground Biomass of Population and Community on a Typical Steppe.

The objective was to explore a fast, accurate, non-destructive, and less disturbance method for predicting the aboveground biomass (AGB) of the typical steppe, by using plant height and canopy diameter of the dominant species, Stipa bungeana, Artemisia capillaris, and Lespedeza davurica, data were observed from 165 quadrats during the peak plant growing season, and the product of plant height (PH) and canopy diameter (PC) were calculated for each species. AGB of population were predicted for the same species and other species through using 2/3 of the measured data, and the optimal predictive equation was linear in terms of determination coefficient. The other 1/3 of the data, which was measured from no grazing paddocks or rotational grazing paddocks, was substituted into the predictive equations for validation. Results showed that PC of one dominant species could be used to predict aboveground biomass (AGB) of the same species or other species well. The predicted and measured values were significantly correlative, and most of the predictive accuracy was above 80%, and not affected by the managements of grassland, grazing or no grazing. A combination of 3 to 6 representative species was used to predict AGB of the community, and the predictive equations with PC of six species as an independent variable were the most optimal because explaining 83.5% variation of AGB. The predictive methods cost 1/15, 1/9, and 1/51 of time, labor, and capital as much as the destructive sample method (quadrat sampling method), respectively, and thus improved the efficiency of field study and protecting the fragile study areas, especially the long-term study sites in grassland.

Modern Holstein-origin dairy cows within grassland-based systems partition more feed nitrogen into milk and excrete less in manure.

The objective was to determine whether modern Holstein-origin dairy cows, when managed within grassland-based systems, partitioned more feed nitrogen (N) into milk and excreted less in manure, in comparison to an earlier population of Holstein-origin dairy cows. Data used were collated from total diet digestibility studies undertaken in Northern Ireland from 1990 to 2002 (old dataset, n = 538) and from 2005 to 2019 (new dataset, n = 476), respectively. An analysis of variance indicated that cows in the new dataset partitioned a significantly higher proportion of consumed N into milk and excreted a lower proportion in urine and total manure, compared to cows in the old dataset. A second analysis using the linear regression revealed that in comparison to the old dataset, the new dataset had a lower slope in the relationship between N intake and N excretion in urine or total manure, while a higher slope in the relationship between N intake and milk N output. A third analysis used the combined data from both datasets to examine if there was a relationship between experimental year and N utilization efficiency. Across the period from 1990 to 2019, urine N/N intake and manure N/N intake significantly decreased, while milk N/N intake increased. These results indicate that modern Holstein-origin dairy cows utilize consumed N more efficiently than earlier populations. Thus, N excretion is likely to be overestimated if models developed from the old data are used to predict N excretion for modern dairy herds. Therefore, the final part of analysis involved using the new dataset to develop prediction models for N excretion based on N intake and farm level data (milk yield, live weight and dietary N concentration). These updated models can be used to estimate N excretion from modern Holstein-origin dairy cows within grassland-based dairy systems.

Optimizing alfalfa productivity and persistence versus greenhouse gases fluxes in a continental arid region.

Alfalfa in China is mostly planted in the semi-arid or arid Northwest inland regions due to its ability to take up water from deep in the soil and to fix atmospheric N2 which reduces N fertilizer application. However, perennial alfalfa may deplete soil water due to uptake and thus aggravate soil desiccation. The objectives of this study were (1) to determine the alfalfa forage yield, soil property (soil temperature (ST), soil water content (SWC), soil organic carbon (SOC) and soil total nitrogen (STN)) and greenhouse gas (GHG: methane (CH4), nitrous oxide (N2O), and carbon dioxide (CO2)) emissions affected by alfalfa stand age and growing season, (2) to investigate the effects of soil property on GHG emissions, and (3) to optimize the alfalfa stand age by integrating the two standard criteria, the forage yield and water use efficiency, and the total GHG efflux (CO2-eq). This study was performed in alfalfa fields of different ages (2, 3, 5 and 7 year old) during the growing season (from April to October) in a typical salinized meadow with temperate continental arid climate in the Northwest inland regions, China. Despite its higher total GHG efflux (CO2-eq), the greater forage yield and water use efficiency with lower GEIhay and high CH4 uptake in the 5-year alfalfa stand suggested an optimal alfalfa stand age of 5 years. Results show that ST, SOC and RBM alone had positive effects (except RBM had no significant effect on CH4 effluxes), but SWC and STN alone had negative effects on GHG fluxes. Furthermore, results demonstrate that in arid regions SWC superseded ST, SOC, STN and RBM as a key factor regulating GHG fluxes, and soil water stress may have led to a net uptake of CH4 by soils and a reduction of N2O and CO2 effluxes from alfalfa fields. Our study has provided insights into the determination of alfalfa stand age and the understanding of mechanisms regulating GHG fluxes in alfalfa fields in the continental arid regions. This knowledge is essential to decide the alfalfa retention time by considering the hay yield, water use efficiency as well as GHG emission.

Comparison of Two Sampling Techniques for Evaluating Ruminal Fermentation and Microbiota in the Planktonic Phase of Rumen Digesta in Dairy Cows.

The objective of this experiment was to compare ruminal fluid samples collected through rumen cannula (RC) or using an oral stomach tube (ST) for measurement of ruminal fermentation and microbiota variables. Six ruminally cannulated lactating Holstein cows fed a standard diet were used in the study. Rumen samples were collected at 0, 2, 4, 6, 8, and 12 h after the morning feeding on two consecutive days using both RC and ST techniques. Samples were filtered through two layers of cheesecloth and the filtered ruminal fluid was used for further analysis. Compared with RC, ST samples had 7% greater pH; however, the pattern in pH change after feeding was similar between sampling methods. Total volatile fatty acids (VFA), acetate and propionate concentrations in ruminal fluid were on average 23% lower for ST compared with RC. There were no differences between RC and ST in VFA molar proportions (except for isobutyrate), ammonia and dissolved hydrogen (dH2) concentrations, or total protozoa counts, and there were no interactions between sampling technique and time of sampling. Bacterial ASV richness was higher in ST compared with RC samples; however, no differences were observed for Shannon diversity. Based on Permanova analysis, bacterial community composition was influenced by sampling method and there was an interaction between sampling method and time of sampling. A core microbiota comprised of Prevotella, S24-7, unclassified Bacteroidales and unclassified Clostridiales, Butyrivibrio, unclassified Lachnospiraceae, unclassified Ruminococcaceae, Ruminococcus, and Sharpea was present in both ST and RC samples, although their relative abundance varied and was influenced by an interaction between sampling time and sampling method. Overall, our results suggest that ruminal fluid samples collected using ST (at 180 to 200 cm depth) are not representative of rumen pH, absolute values of VFA concentrations, or bacterial communities >2 h post-feeding when compared to samples of ruminal fluid collected using RC. However, ST can be a feasible sampling technique if the purpose is to study molar proportions of VFA, protozoa counts, dH2, and ammonia concentrations.

Appropriate level of alfalfa hay in diets for rearing Simmental crossbred calves in dryland China.

OBJECTIVE: In dryland areas of China, alfalfa hay (AH) is a possible substitute for concentrate feed for beef cattle. To evaluate the potential benefits of this substitution, we studied the effect of the ratio of AH intake to total dry matter (DM) intake on average daily body-weight gain (ADG), dietary energy utilization status, and economic benefit in Gansu province. METHODS: In each of two feeding trials in 2016 (trial 1 [T1], July 3 to 17; trial 2 [T2], August 15 to September 23), crossbred male Simmental calves were allocated to low AH (LA), medium AH (MA), and high AH (HA) feeding groups (n = 4 per group). The target ADG was set as 1 kg for both trials. In a one-way-layout design based on conventional feeding practices in the province, calves received diets containing the different AH amounts, with a constant ratio of corn stover:total DM and decreasing rations of concentrate feed proportional to the increase in AH. Calves in T1 received AH at 15% (T1-LA), 23% (T1-MA), or 31% (T1-HA) of their dietary DM allowances; those in T2 received 9% (T2-LA), 24% (T2-MA), or 34% (T2-HA) AH. RESULTS: Among the T1 groups, both ADG and economic benefit were highest in T1-LA; whereas in T2, they were higher in the T2-LA and T2-MA groups than in T2-HA. Energy digestibility did not significantly differ among the groups in either trial. The dietary AH inclusion ratios of 14% in the warm season and 8% to 21% in the cool season appeared to yield optimal ADG, metabolizable energy intake, and economic benefit. CONCLUSION: Low-level inclusion of AH, ranging from 8% to 21%, is a practical approach for beef cattle feeding. This modified feeding regimen likely will promote increased growth performance during the fattening stage of beef steers in dryland areas of Gansu province, China.

Relationship between chemical composition of native forage and nutrient digestibility by Tibetan sheep on the Qinghai-Tibetan Plateau.

To better utilize native pasture at the high altitude region, three-consecutive-year feeding experiments and a total of seven metabolism trials were conducted to evaluate the impact of three forage stages of maturity on the chemical composition, nutrient digestibility, and energy metabolism of native forage in Tibetan sheep on the Qinghai-Tibetan Plateau (QTP). Forages were harvested from June to July, August to October, and November to December of 2011 to 2013, corresponding to the vegetative, bloom, and senescent stages of the annual forages. Twenty male Tibetan sheep were selected for each study and fed native forage ad libitum. The digestibility of DM, OM, CP, NDF, ADF, DE, DE/GE, and ME/GE were greatest (P < 0.01) from the vegetative stage, intermediate (P < 0.01) from the bloom stage, and least (P < 0.01) from the senescent stage. Nutrient digestibility and energy parameters correlated positively (linear, 0.422 to 0.778; quadratic, 0.568 to 0.815; P < 0.01) with the CP content of forage but correlated negatively with the content of NDF (linear, 0.343 to 0.689; quadratic, 0.444 to 0.777; P ≤ 0.02), ADF (linear, 0.563 to 0.766; quadratic, 0.582 to 0.770; P < 0.01), and ether extract (EE, linear, 0.283 to 0.574; quadratic, 0.366 to 0.718; P ≤ 0.04) of forage. For each predicted variable, the prediction of DMI expressed as grams per kilogram of BW (g/kg BW·d) yielded a greater R2 value (0.677 to 0.761 vs. 0.616 to 0.711) compared with the equations of DMI expressed as g/kg metabolic BW by step-wise regression. The results suggest that parameters of forage CP, NDF, and ADF content were most closely related to nutrient digestibility. Contrary to previous studies, in this study, ADF content had a greater linear relationship (0.766 vs. 0.563 to 0.732) with OM digestibility than the other parameters of nutrient digestibility. The quadratic relationship between forage CP content and CP digestibility indicates that when forage CP content exceeds the peak point (9.7% DM in the present study), increasing forage CP content could decrease CP digestibility when Tibetan sheep were offered native forage alone on the QTP. Additionally, using the forage CP, EE, NDF, and ADF content to predict DMI (g/kg BW·d) yielded the best fit equation for Tibetan sheep living in the northeast portion of the QTP.

Bacterial and Fungal Community Structures in Loess Plateau Grasslands with Different Grazing Intensities.

The Loess Plateau of China is one of the most fragile ecosystems worldwide; thus, human production activities need to be conducted very cautiously. In this study, MiSeq high-throughput sequencing was applied to assess the relationship between bacterial and fungal community structures and changes in vegetation and soil physical and chemical properties induced by grazing, in four grasslands with different levels of grazing intensity (0, 2.67, 5.33, and 8.67 sheep/ha) in the semiarid region of the Loess Plateau. The relative abundances of the bacterial community in the grasslands with 2.67 and 5.33 sheep/ha were significantly higher than those in grasslands with 0 and 8.67 sheep/ha, and the fungal diversity was significantly lower for grasslands with 2.67 sheep/ha than for the other grasslands. Redundancy analysis (RDA) showed that plant biomass, nitrate, and total nitrogen have significant effects on bacterial community structure, whereas nitrate and total nitrogen also significantly affect fungal community structure. Variation partitioning showed that soil and plant characteristics influence the bacterial and fungal community structures; these characteristics explained 51.9 and 52.9% of the variation, respectively. Thus, bacterial and fungal community structures are very sensitive to grazing activity and change to different extents with different grazing intensities. Based on our findings, a grazing intensity of about 2.67 sheep/ha is considered the most appropriate in semiarid grassland of the Loess Plateau.

Effects of stocking rates on functional group diversity and forage quality in rangeland of Qilian Mountain, China.

The present study aimed at investigating a balance between environment and livestock grazing, through identifying appropriate stocking rate in rangeland with highest biodiversity and forage quality. The experiment was carried out to determine the effects of six stocking rates on Shannon Weiner index of functional group diversity and nutritive value and relationship between them in the edge of the Tibetan plateau of China. The results showed that abundance of functional group diversity indices were significantly influenced by stocking rates (p < 0.05) and the highest appeared in 2.5 and 2.6 animal month unit (AMU) ha(-1)'. There were significant differences in forage content of nitrogen (N), water-soluble carbohydrate (WSC), neutral detergent fiber (NDF) and acid detergent fiber (ADF) under stocking rates (p<0.05). There were higher N and WSC content but lower NDF and ADF content under 2.5 and 2.6 AMU ha(-1) than other stocking rates. Positive relationship was found between all functional group diversity indices and N and WSC content of community but negative relationship between all functional group diversity indices and NDF and ADF content of community. All the results represented that moderate control of stocking rates was an effective management measure to protect functional diversity, improve forage quality and sustain rangeland health.

Prediction of metabolisable energy concentrations of fresh-cut grass using digestibility data measured with non-pregnant non-lactating cows.

Pasture-based ruminant production systems are common in certain areas of the world, but energy evaluation in grazing cattle is performed with equations developed, in their majority, with sheep or cattle fed total mixed rations. The aim of the current study was to develop predictions of metabolisable energy (ME) concentrations in fresh-cut grass offered to non-pregnant non-lactating cows at maintenance energy level, which may be more suitable for grazing cattle. Data were collected from three digestibility trials performed over consecutive grazing seasons. In order to cover a range of commercial conditions and data availability in pasture-based systems, thirty-eight equations for the prediction of energy concentrations and ratios were developed. An internal validation was performed for all equations and also for existing predictions of grass ME. Prediction error for ME using nutrient digestibility was lowest when gross energy (GE) or organic matter digestibilities were used as sole predictors, while the addition of grass nutrient contents reduced the difference between predicted and actual values, and explained more variation. Addition of N, GE and diethyl ether extract (EE) contents improved accuracy when digestible organic matter in DM was the primary predictor. When digestible energy was the primary explanatory variable, prediction error was relatively low, but addition of water-soluble carbohydrates, EE and acid-detergent fibre contents of grass decreased prediction error. Equations developed in the current study showed lower prediction errors when compared with those of existing equations, and may thus allow for an improved prediction of ME in practice, which is critical for the sustainability of pasture-based systems.