反刍动物瘤胃甲烷产量预测模型

本文综述了反刍动物瘤胃甲烷(CH4)产生的基本过程、瘤胃CH4产量预测模型的类型及特点,分析了现有模型存在的问题,指出了研究瘤胃CH4产量预测模型的重要性.     

Comparison of Time Series Models for Predicting Campylobacteriosis Risk in New Zealand

Predicting campylobacteriosis cases is a matter of considerable concern in New Zealand, after the number of the notified cases was the highest among the developed countries in 2006. Thus, there is a need to develop a model or a tool to predict accurately the number of campylobacteriosis cases as the Microbial Risk Assessment Model used to predict the number of campylobacteriosis cases failed to predict accurately the number of actual cases. We explore the appropriateness of classical time series modelling approaches for predicting campylobacteriosis. Finding the most appropriate time series model for New Zealand data has additional practical considerations given a possible structural change, that is, a specific and sudden change in response to the implemented interventions. A univariate methodological approach was used to predict monthly disease cases using New Zealand surveillance data of campylobacteriosis incidence from 1998 to 2009. The data from the years 1998 to 2008 were used to model the time series with the year 2009 held out of the data set for model validation. The best two models were then fitted to the full 1998–2009 data and used to predict for each month of 2010. The Holt‐Winters (multiplicative) and ARIMA (additive) intervention models were considered the best models for predicting campylobacteriosis in New Zealand. It was noticed that the prediction by an additive ARIMA with intervention was slightly better than the prediction by a Holt‐Winter multiplicative method for the annual total in year 2010, the former predicting only 23 cases less than the actual reported cases. It is confirmed that classical time series techniques such as ARIMA with intervention and Holt‐Winters can provide a good prediction performance for campylobacteriosis risk in New Zealand. The results reported by this study are useful to the New Zealand Health and Safety Authority's efforts in addressing the problem of the campylobacteriosis epidemic.     

利用广义线性模型预测家畜离散性状育种值

将广义线性混合模型(GLMM)引入动物离散性状的遗传分析及个体的遗传评定,初步比较了GLMM方法与一般线性方法(LM)的估计效果。模拟研究的性状为单阈值二项分类性状,选用的连接函数为对数连接μi=eη/(1+eη),方差函数为V(μi)=μ(i1-μi)/n,试验设计为全同胞-半同胞混合家系,参数估计采用Fisher迹法。结果表明:GLMM方法能较准确地估计公畜的个体育种值,在个体的遗传评定效果方面要明显优于常规的线性方法,其预测的育种值排序结果与真实育种值的排序之间存在极显著的相关性(P<0.001)。     

Resilience and Resistance of Sagebrush Ecosystems: Implications for State and Transition Models and Management Treatments

In sagebrush ecosystems invasion of annual exotics and expansion of piñon (Pinus monophylla Torr. and Frem.) and juniper (Juniperus occidentalis Hook., J. osteosperma &lsqb;Torr.] Little) are altering fire regimes and resulting in large-scale ecosystem transformations. Management treatments aim to increase resilience to disturbance and enhance resistance to invasive species by reducing woody fuels and increasing native perennial herbaceous species. We used Sagebrush Steppe Treatment Evaluation Project data to test predictions on effects of fire vs. mechanical treatments on resilience and resistance for three site types exhibiting cheatgrass (Bromus tectorum L.) invasion and/or piñon and juniper expansion: 1) warm and dry Wyoming big sagebrush (WY shrub); 2) warm and moist Wyoming big sagebrush (WY PJ); and 3) cool and moist mountain big sagebrush (Mtn PJ). Warm and dry (mesic/aridic) WY shrub sites had lower resilience to fire (less shrub recruitment and native perennial herbaceous response) than cooler and moister (frigid/xeric) WY PJ and Mtn PJ sites. Warm (mesic) WY Shrub and WY PJ sites had lower resistance to annual exotics than cool (frigid to cool frigid) Mtn PJ sites. In WY shrub, fire and sagebrush mowing had similar effects on shrub cover and, thus, on perennial native herbaceous and exotic cover. In WY PJ and Mtn PJ, effects were greater for fire than cut-and-leave treatments and with high tree cover in general because most woody vegetation was removed increasing resources for other functional groups. In WY shrub, about 20% pretreatment perennial native herb cover was necessary to prevent increases in exotics after treatment. Cooler and moister WY PJ and especially Mtn PJ were more resistant to annual exotics, but perennial native herb cover was still required for site recovery. We use our results to develop state and transition models that illustrate how resilience and resistance influence vegetation dynamics and management options.     

Monitoring British Upland Ecosystems With the Use of Landscape Structure as an Indicator for State-and-Transition Models

Remote sensing and landscape ecology concepts can provide a useful framework for state-and-transition models (STM) in order to quantify thresholds at different scales, and provide useful information for scientists, land managers, and conservationists in relation to resilience management. The overall aim of this research was to develop a spatially explicit STM to quantify thresholds based on the scale of disturbance processes impacting a grazing system. Specific objectives were to develop a conceptual STM framework for upland grazing ecosystems, to quantify spatial dynamics of stable and degraded pastures, and to assess threshold occurrence. Color aerial photography from Armboth Fell in the English Lake District National Park (United Kingdom) was classified into bare rock, dwarf shrub heath (DSH), and grassland/degraded wet heath (GDWH) in four pastures with different degrees of grazing pressure. Vegetation communities from these pastures were combined with soils, climate, and landform data to create a conceptual STM framework. Each pasture was sampled with 2-ha plots to quantify DSH and GDWH spatial structure. The proposed STM consisted of two reference and three alternative states. Low–grazing-pressure areas showed significantly higher percentage of DSH cover with larger contiguous patches and lower patch density than high–grazing-pressure areas. Breakpoints, considered to be thresholds, in mean patch area were identified in our data when DSH percentage cover was < 63% and GDWH, > 77%. The present study has shown the value of a robust, reliable, and repeatable approach to identify landscape dynamics and integrate it with field data to inform a conceptual STM framework for upland grazing ecosystems. It also demonstrates the importance of selecting scales relevant to the predominant disturbance process to test for threshold occurrence, and how this approach can be integrated with current assessment methods for resilience management.     

建立各种饲料能量预测模型方法的比较研究

理论上饲料的能量应经动物消化试验洲定,但在实际生产中饲料能量一般是通过营养素的体内消化率,体外消化率及不同化学成分分析参数建立的预测模型经计算得到。近年来的趋势是将化学成分分析参数与体外有机物消化率参数结合起来,作为预测因子建立饲料能量预测模型。笔者就用各种方法建立的各种饲料能量预测模型的准确性与可行性进行了比较。     

动物疫情预测预报工作模式的初步探索

本文介绍了重庆市在动物疫情预测预报工作中的一些尝试,主要从组织机构、建立规范、疫情分析评估、取得成效及存在问题等方面进行了阐述。     

基于牦牛氨态氮和尿素氮分布特征构建粗蛋白质进食量估测模型

本试验旨在探讨饲粮氮水平对牦牛体内不同部位氨态氮和尿素氮浓度的影响,以期了解牦牛机体对氮胁迫的适应性响应,并构建粗蛋白质进食量估测模型。采用4×4拉丁方设计,选取4头体重[(192±12)kg]相近的3岁去势健康牦牛。分4个试验期,每期21 d;4头牦牛分成4组,每组1头,分别饲喂4个氮水平的饲粮[以粗蛋白质水平(干物质基础)计,分别为6.45%、12.18%、17.81%和23.49%]。结果表明,1)瘤胃液氨态氮(RNN)、血浆尿素氮(PUN)、唾液尿素氮浓度以及尿中尿素氮(UUN)、尿中氨态氮日排泄量均随着饲粮氮水平的升高而极显著增加(P<0.01);瘤胃液尿素氮(RUN)浓度有随着饲粮氮水平升高而增加的趋势(P<0.10)。2)RNN、RUN和PUN浓度(mg/d L)以及UUN日排泄量(g/d)与牦牛饲粮蛋白质摄入水平密切相关,可建立以下估测牦牛粗蛋白质进食量(CPI,g/d)和可消化粗蛋白质进食量(DCPI,g/d)的模型:CPI=174.102+840.096RNN-3.068RNN2,CPI=185.818+47.744RNN+22.258RUN;DCPI=36.037UUN0.712,DCPI=-0.789+8.375UUN+101.275PUN。综上,饲粮氮水平对牦牛体内氨态氮和尿素氮浓度具有广泛的影响,由此建立的估测模型可为牦牛的放牧和管理提供参考。     

Managing Complex Problems in Rangeland Ecosystems

Management of rangelands, and natural resources in general, has become increasingly complex. There is an atmosphere of increasing expectations for conservation efforts associated with a variety of issues from water quality to endangered species. We argue that many current issues are complex by their nature, which influences how we approach them. We define a complex problem as one that varies in time and space. In other words, one answer may not be correct for all sites or during all years. For simple problems a generalized answer may be sufficient, and even for complex problems, general rules provide a good starting point. However, we suggest that it is important to distinguish between simple and complex problems. Several key obstacles emerge when considering complex natural resource problems, namely, 1) no single entity can handle all aspects of the problem and 2) significant knowledge gaps exist and will continue to exist into the future. We suggest that overcoming these obstacles will benefit from 1) a framework for effective partnerships and 2) a mechanism for continuous learning. Managing complex problems will require some combination of the following: 1) a process-based understanding of the problem (i.e., what causes variation in time and space), 2) adaptive management, and 3) effective coordination of research and management. There are many examples of organizations applying portions of these approaches to complex problems; however, it seems that in many cases the process has simply evolved in that direction rather than being a planned strategy. We suggest that as a profession we need to have a discussion about the nature of the problems we are addressing and how researchers and managers can jointly address these problems.     

Comparison of Unmanned Aerial Vehicle Platforms for Assessing Vegetation Cover in Sagebrush Steppe Ecosystems

In this study, the use of unmanned aerial vehicles (UAVs) as a quick and safe method for monitoring biotic resources was evaluated. Vegetation cover and the amount of bare ground are important factors in understanding the sustainability of many ecosystems. Methods that improve speed and cost efficiency could greatly improve how biotic resources are monitored on western lands. Sagebrush steppe ecosystems provide important habitat for a variety of species including sage grouse and pygmy rabbit. Improved methods of monitoring these habitats are needed because not enough resource specialists or funds are available for comprehensive on-the-ground evaluations. In this project, two UAV platforms, fixed-wing and helicopter, were used to collect still-frame imagery to assess vegetation cover in sagebrush steppe ecosystems. This paper discusses the process for collecting and analyzing imagery from the UAVs to 1) estimate percentage of cover for six different vegetation types (shrub, dead shrub, grass, forb, litter, and bare ground) and 2) locate sage grouse using representative decoys. The field plots were located on the Idaho National Laboratory site west of Idaho Falls, Idaho, in areas with varying amounts and types of vegetation cover. A software program called SamplePoint was used along with visual inspection to evaluate percentage of cover for the six cover types. Results were compared against standard field measurements to assess accuracy. The comparison of fixed-wing and helicopter UAV technology against field estimates shows good agreement for the measurement of bare ground. This study shows that if a high degree of detail and data accuracy is desired, then a helicopter UAV may be a good platform to use. If the data collection objective is to assess broad-scale landscape level changes, then the collection of imagery with a fixed-wing system is probably more appropriate.     

草地生态系统土壤氮转化过程研究进展

针对草地生态系统土壤氮的转化过程中氮的矿化和固定、硝化和反硝化的研究进展进行综述,总结了不同草地利用方式、主要环境因素变化对氮转化过程的影响,并对草地生态系统土壤氮转化研究的前沿进行了展望。     

DGGE/TGGE技术在瘤胃微生物生态学研究中的应用

在分子生物学技术出现之前，人们对微生物的认识大多数是靠纯培养，或者靠直接形态观察来获得的。动物的胃肠道是一个复杂的生态环境，特别是反刍动物的瘤胃需要严格的厌氧环境，过去对瘤胃微生物的研究主要是一些经典的方法如享氏滚管法（Hungate．1969）和最大可能计数法（Dehority等，1989）。因为微生物形态简单，缺乏明显的外部特征，所以胃肠道中的大多数微生物由于难于模拟其生长繁殖的真实条件而很难培养。能培养的微生物只是天然微生物中的一小部分，     

Using Unmanned Helicopters to Assess Vegetation Cover in Sagebrush Steppe Ecosystems

Evaluating vegetation cover is an important factor in understanding the sustainability of many ecosystems. Remote sensing methods with sufficient accuracy could dramatically alter how biotic resources are monitored on both public and private lands. Idaho National Laboratory (INL), in conjunction with the University of Idaho, evaluated whether unmanned aerial vehicles (UAVs) are sufficiently accurate and more efficient than the point-frame field method for monitoring vegetative cover and bare ground in sagebrush steppe ecosystems. These values are of interest to land managers because typically there are limited natural resource scientists and funding for comprehensive ground evaluations. In this project, unmanned helicopters were used to collect still-frame imagery to determine vegetation cover during June and July 2005. The images were used to estimate percent cover for six vegetative cover classes (shrub, dead shrub, grass, forbs, litter, and bare ground). Field plots used to collect imagery and on-the-ground measurements were located on the INL site west of Idaho Falls, Idaho. Ocular assessments of digital imagery were performed using SamplePoint, and the results were compared with field measurements collected using a point-frame method. The helicopter imagery evaluation showed a high degree of agreement with field cover class values for grass, litter, and bare ground and reasonable agreement for dead shrubs. Shrub cover was often overestimated, and forbs were generally underestimated. The helicopter method took 45% less time than the field method. This study demonstrates that UAV technology provides a viable method for monitoring selective types of cover on rangelands and could save time and resources.     

Fuel homeostasis in the ruminant

Sufficient amounts of energy are stored in the animal body to support its needs during periods when dietary intake does not meet energy requirements. To be utilized, these energy reserves must be converted to compounds appropriate for oxidation at the cellular level. In addition, energy supplies must be transferred from storage sites to sites of utilization. The biochemical pathways of oxidation provide not only a means of deriving energy from carbon compounds, but also a means of transferring carbons from one type of energy source to another. The transfer of carbons between carbohydrates, lipids, ketone bodies, and proteins is regulated by endocrine and substrate effects. Regulation of this activity constitutes fuel homeostasis. Breakdowns in these homeostatic mechanisms result in metabolic disease.     

Predicting rates of inbreeding for livestock improvement schemes

This article presents a deterministic method to predict rates of inbreeding (deltaF) for typical livestock improvement schemes. The method is based on a recently developed general theory to predict rates of inbreeding, which uses the concept of long-term genetic contributions. A typical livestock breeding population was modeled, with overlapping generations, BLUP selection, and progeny testing of male selection candidates. Two types of selection were practiced: animals were either selected by truncation on estimated breeding values (EBV) across age classes, or the number of parents selected from each age class was set to a fixed value and truncation selection was practiced within age classes. Bulmer's equilibrium genetic parameters were obtained by iterating on a pseudo-BLUP selection index and deltaF was predicted for the equilibrium situation. Predictions were substantially more accurate than predictions from other available methods, which ignore the effect of selection on deltaF. Predictions were accurate for schemes with up to 20 sires. Predicted deltaF was somewhat too low for schemes with more than 20 sires, which was due to the use of simple linear models to predict genetic contributions. The present method provides a computationally feasible (i.e., deterministic) tool to consider both the rate of inbreeding and the rate of genetic gain when optimizing livestock improvement schemes.     

Markers for Predicting Overweight or Obesity of Broodmares

Obesity has become of great concern to all equine community from both veterinary and welfare points of view. For estimating obesity markers of brood mares, 17 mares with body conditions were subjected to blood sampling and ultrasound examination to measure rump fat for 6 consecutive weeks. Body length (L), girth (G), and height (H) were measured to estimate body weight (BW), body fat %, body fat mass (BFM) and body mass index (BMI). Mares were classified into three groups according to body condition score (BCS) and rump fat thickness (RF). Overweight mares (O) had BCS >7 and RF >7 mm, moderate (M) had BCS and RF >3 to ≤7, and emaciated (E) had BCS and RF ≤ 3 mm. Glucose, triglycerides, nitric oxide (NO), insulin, insulin-like growth factor-I (IGF-1), leptin, ovarian hormones, and thyroid hormones were measured. Results revealed that BCS, G, L, L × G × H, BW, RF, fat %, and BFM correlated significantly (P < .0001) with body condition. Tetraiodothyronine concentrations of E mares were significantly high (P = .04), but triiodothyronine concentrations tended (P = .07) to be low. Insulin (P = .06) and IGF-1 (P = .07) concentrations tended to be high in O mares. Moderate mares had the highest leptin concentrations (P = .007), but E mares had the lowest P4 concentrations (P = .01). Overweight mares had nonsignificantly high glucose, NO, and triglycerides. In conclusion, back fat and morphometric measurements are the easiest and simple assessment of overweight and obesity. Obese and overweight mares showed slight hyperinsulinemia, hypertriglyceridemia, and hyperglycemia. Hyperleptinemia alone is not indicative of obesity.