Spatiotemporal patterns of the forage-livestock balance in the Xilin Gol steppe,China:implications for sustainably utilizing grassland-ecosystem services

Understanding the spatiotemporal patterns of the forage-livestock balance is imperative for regionally arranging animal husbandry production while ensuring sustainable grassland-ecosystem service use.The Xilin Gol steppe is an important native grassland resource in Inner Mongolia Autonomous Region,China.This study aimed to elucidate the dynamics of the forage-livestock balance in the Xilin Gol steppe during the period 2000–2015.We evaluated the forage production and corresponding livestock carrying capacity(LCC)in the growing seasons of 2000–2015 using remote sensing data and field surveys.The spatiotemporal patterns of the forage-livestock balance were then assessed at regional,city(including city,county and banner),and village scales using statistical and household survey data.The results showed that both forage production and LCC decreased in the Xilin Gol steppe from east to west.During the period 2000–2015,the regional average forage production and corresponding LCC fluctuated without following a distinct trend,but were consistent with the variations in precipitation.The forage-livestock balance varied with time,space,and scale.At the regional scale,steppes were overgrazed in the early 2000s,but a forage-livestock balance or even grazing potential was achieved in other years.At the city scale,approximately half of the region exhibited a"forage-livestock balance"since 2000.However,about half of the region still experienced overgrazing,which mainly located in the southwest sandy zones.Such changes may have been affected by the variations in grassland quality,forage production,compensation payment,and so on.We suggest a location-specific management scheme for grazing constraints,ecological compensation payment,and industry development to aid in harmonizing animal husbandry and environmental restoration,while promoting sustainable development goals by 2030.

Rumen methane output and fermentation characteristics of gramineous forage and leguminous forage at differing harvest dates determined using an in vitro gas production technique

An in vitro rumen gas production technique was employed to determine the methane production and fermentation characteristics of Leymus chinensis and Medicago ruthenica at differing harvest dates（May 15,May 30,June 30,July 30,August 30 and September 30）,which are sequential phases within a single continuous growth of two 10-year-old pastures.To quantify the rate of degradation and compare in vitro rumen fermentation characteristic,a logistic-exponential model,where initial gas volume was zero（LE_0）,was used to fit gas production and methane output results.Dried,milled forage samples were incubated in vitro for 72 h at 39℃ and gas production was recorded intermittently throughout the incubation and gas samples were collected to measure methane production.Results showed that there were significant interactions between species and harvest for all chemical composition variables（P〈0.001） and condensed tannin content（P〈0.001）.L.chinensis produced more total gas and methane than M.ruthenica（P〈0.001）.Both total gas and methane production decreased lineally（P〈0.001） with advancing harvest date.The degradation rates of L.chinensis and M.ruthenica harvested on September 30 were lower than those on the other harvest dates（P〈0.01）.M.ruthenica fermented fluid had higher concentration of ammonia N（P〈0.05） and molar proportions of isobutyrate（P〈0.01）,valerate（P〈0.001） and isovalerate（P〈0.01） in total volatile fatty acids than L chinensis.Furthermore,concentration of isovalerate decreased cubically with advancing harvest date（P〈0.05）.In conclusion,M.ruthenica produced less methane than L.chinensis and the total gas and methane production decreased with advancing harvest date for both species,which may be due to the changes in contents of chemical compositions and condensed tannin in forages.

Improvement of Native Pasture Productivity through Introduction of Various Types of Palatable Species on Dry Lands in Timor

This research was aimed to evaluate the productivity of native pasture in Timor Island by introducing various palatable species.The study was carried out on native pasture in Tuatuka,Timor Island for seven months.The study was performed by using randomized block design(RBD)with eight treatments(S0:no introduction,S1:Cynodon dactilon,S2:Dicanthium aristatum,S3:C.plectotachyus,S4:Brachiaria decumbens,S5:Desmanthus virgatus,S6:Macroptilium atropurpureum,S7:Clitoria ternatea)with four replications.Procedures on this study include trial plots preparation,tillers preparation for each species,introduction of species in trial plots,maintenance and observation of the productivity.Variables observed were forage production(fresh and dry matter(DM)in ton/ha),nutrient content(%)and stock capacity(animal unit(AU)/ha).Data were analyzed for variance based on RBD and followed by Duncan’s test.Analysis of variance showed that introduction of species had a very significant effect(p<0.01)on all observed variables.The introduction of M.atropurpureum produced the highest fresh forage(2.1 t/ha)and DM production(0.69 t/ha).M.atropurpureum also had the highest DM content(43.61%),nitrogen free extract(52.52%)and stock capacity(1.06 AU/ha).The highest crude protein and crude fiber content were found in D.virgatus(4.31%and 36.62%).The highest extract ether was observed in D.aristatum(1.48%).No introduction had the lowest productivity,but demonstrated the highest ash content.The introduction of palatable species increased the productivity of native pasture in Timor and M.atropupureum was the best introduced species.

Modelling the impact of climate change on rangeland forage production using a generalized regression neural network:a case study in Isfahan Province,Central Iran

Monitoring of rangeland forage production at specified spatial and temporal scales is necessary for grazing management and also for implementation of rehabilitation projects in rangelands. This study focused on the capability of a generalized regression neural network（GRNN） model combined with GIS techniques to explore the impact of climate change on rangeland forage production. Specifically, a dataset of 115 monitored records of forage production were collected from 16 rangeland sites during the period 1998–2007 in Isfahan Province, Central Iran. Neural network models were designed using the monitored forage production values and available environmental data（including climate and topography data）, and the performance of each network model was assessed using the mean estimation error（MEE）, model efficiency factor（MEF）, and correlation coefficient（r）. The best neural network model was then selected and further applied to predict the forage production of rangelands in the future（in 2030 and 2080） under A1 B climate change scenario using Hadley Centre coupled model. The present and future forage production maps were also produced. Rangeland forage production exhibited strong correlations with environmental factors, such as slope, elevation, aspect and annual temperature. The present forage production in the study area varied from 25.6 to 574.1 kg/hm^2. Under climate change scenario, the annual temperature was predicted to increase and the annual precipitation was predicted to decrease. The prediction maps of forage production in the future indicated that the area with low level of forage production（0–100 kg/hm^2） will increase while the areas with moderate, moderately high and high levels of forage production（≥100 kg/hm^2） will decrease both in 2030 and in 2080, which may be attributable to the increasing annual temperature and decreasing annual precipitation. It was predicted that forage production of rangelands will decrease in the next couple of decades, especially in the western and southern parts of Isfahan Province. These changes are more pronounced in elevations between 2200 and 2900 m. Therefore, rangeland managers have to cope with these changes by holistic management approaches through mitigation and human adaptations.

Validation of a Technique for Estimating Alfalfa (Medicago sativa) Biomass from Canopy Volume

Determining biomass production of individual alfalfa (Medicago sativa L.) plants in space planted evaluation studies is generally not feasible. Clipping plants is time consuming, expensive, and often not possible if the plants are subjected to grazing. A regression function (B′ = 0.72558 + 0.11638 × V′) was developed from spaced plants growing on rangeland in northwestern South Dakota near Buffalo to nondestructively estimate individual plant biomass (B) from canopy volume (V). However, external validation is necessary to effectively apply the model to other environments. In the summer of 2015, new data to validate the model were collected from spaced plants near Brookings, South Dakota. Canopy volume and clipped plant biomass were obtained from ten alfalfa populations varying in genetic background, growth habit, and growth stage. Fitted models for the model-building and validation data sets had similar estimated regression coefficients and attributes. Mean squared prediction errors (MSPR) were similar to or smaller than error mean square (MSE) of the model-building regression model, indicating reasonable predictive ability. Validation results indicated that the model reliably estimated biomass of plants in another environment. However, the technique should not be utilized where individual plants are not easily distinguished, such as alfalfa monocultures. Estimating biomass from canopy volume values that are extrapolations (>2.077 × 106 cm3) of the model-building data set is not recommended.

Annual yields of multispecies grassland mesocosms outperformed monocultures across a drought gradient due to complementarity effects and rapid recovery

Background:More frequent and severe drought events due to climate change pose a major challenge for sustainable forage production in managed grasslands.This study investigated whether multispecies grassland communities can provide greater resistance to and/or recovery from drought compared to monoculture communities.Methods:Mesocosms of Lolium perenne L.,Cichorium intybus L.,Trifolium repens L.and Trifolium pratense L.were established as monocultures,and a four-species mixture.A drought gradient with five levels of water supply ranging from a mild to a severe treatment was applied for 10 weeks,in each of 2 years.Shoot biomass was harvested to assess drought resistance,drought recovery and annual yields.Root mass density and specific root length were measured in Year 2.Results:Across the drought gradient,four-species communities had significantly larger annual yields than each of the four monocultures,indicating transgressive overyielding.This was despite relatively low drought resistance for four-species communities compared with L.perenne and C.intybus monocultures.Recovery of yields following drought was high for all communities.Conclusions:Multispecies swards with complementary traits can provide a viable adaptation option across a wide range of drought severities.Application of a stress gradient methodology allowed a more detailed understanding of stress responses.