AARI Direct Funding Project 960689

FEEDING SYSTEMS FOR FARMED DEER

Project Completion Report

 

 

Robert J Hudson and Jay Gedir
Renewable Resources
University of Alberta
Edmonton T6G 2P5
tel 403-492-2908
fax 403-492-0097

 

 

 

 

 

6 July 98

 

Contents

AARI Direct Funding Project 960689 *

FEEDING SYSTEMS FOR FARMED DEER *

Contents *

List of Figures *

List of Tables *

Updates and Maintenance *

EXECUTIVE SUMMARY *

INTRODUCTION *

OBJECTIVES AND APPROACH *

MODELING PERFORMANCE AND FEED REQUIREMENTS *

Goal and Scope *

Approach and Methods *

Structure and Implementation *

Interaction and Interface *

Seasonal Environment *

Resource Use and Activity Budgets *

Seasonal Requirements *

Ecological Maintenance *

Gestation *

Lactation *

Growth *

Protein requirements *

Nutrient Supply from Range and Pasture *

Dry matter intake *

Digestion *

Making up the Difference *

EVALUATION AND APPLICATION *

Liveweight and other production parameters *

Dry matter intakes *

VALIDATION THROUGH FIELD STUDIES *

Methods *

Study Area *

Grazing Trials *

Dry Matter Intake using N-Alkanes *

Dry Matter Intake by the Bite-Count Method *

Statistical Analysis *

Intakes and Gains *

Activity Budgets *

Foraging and Pasture Parameters *

CONCLUSIONS *

Electronic Feeding Standards *

Limitations *

Model Development *

Energy Balance of Grazing Animals *

World Feeding Standards for Farmed Deer *

REFERENCES *

List of Figures

Figure 1. Scope and structure of BION, a 'proof-of-concept' digital feeding standard for farmed wapiti. *

Figure 2. Control panel showing computational blocks, inputs and graphic outputs. *

Figure 3. Energy expenditures in relation to ambient temperature for wapiti calves that were bedded, standing or active (adapted from Gates and Hudson 1979). *

Figure 4. Daily deposition of energy and protein in the conceptus expressed per kg calf birth weight and proportion of gestation (days pregnant/gestation length). Curves fit to data from Adam et al. (1988a,b). *

Figure 5. Milk yield of wapiti on aspen parkland ranges in central Alberta (Hudson and Adamzcewski 1990). Y=0.022 (t+25)1.55 e -0.0195 (t+25) *

Figure 6. Compensatory gain of wapiti on summer pastures (Hudson et al 1985). *

Figure 7. Net protein value is the product of apparent digestibility and biological value Apparent digestibility of protein and its biological value is related to dietary crude protein concentrations (FP, frac). The following equations from Mould and Robbins (1981) were combined to obtain this relationship: *

Figure 8. Feeding rate of wapiti on Poa/Brome pastures (Hudson and Watkins 1986). Cured pasture (top), Y=22X/(533+X). Green pasture (bottom), Y=11X/(385+X). *

Figure 9. Weights, conceptus weight and milk yield of wapiti hinds from 16 months to maturity when shortfalls of pasture are fully met with supplemental feeds. *

Figure 10. Liveweight, conceptus weight and milk production of a lightly supplemented wapiti hind from 16 months to maturity. *

Figure 11. Weights of reproductive and non reproductive hinds on lightly supplemented pasture illustrating the demands of gestation and lactation. *

Figure 12. Seasonal constraints on dry matter intake. Actual intake is defined as the minim of metabolic, digestive and logistic constraints. *

Figure 13. Seasonal digestible dry matter intake (kg DM/day) of wapiti on Grazed and Ungrazed pasture based on two estimation methods. *

Figure 14. Average daily gain during seasonal trials. *

Figure 15. Seasonal activity budgets of wapiti hinds (n=10) at Ministik Research Station, AB. "Other" refers to any behaviours exhibited when not foraging or bedded (eg. standing, social interaction, nursing, movement, etc.). *

 

List of Tables

Table 1. Mean weights of wapiti hinds and their calves at trial commencement at Ministik Research Station, AB. Calf gender represents proportion of females (F) to males (M). *

Table 2. Seasonal dry matter intakes (kg/d). *

Table 3. Seasonal foraging parameters and forage availability for wapiti hinds (n=5) on heavily grazed and lightly grazed pasture (1997 only) at Ministik Research Station. *

 

Updates and Maintenance

Latest versions and documentation are available on the internet at:

<http://www.deer.rr.ualberta.ca>

The model is programmed in STELLA 5.0 and requires a free player from High Performance Systems:

<http://www.hps_inc.com>

 

 

EXECUTIVE SUMMARY

This report describes a model of bioenergetics and behaviour of wapiti (Cervus elaphus). It simulates weight changes, body composition, fetal development, milk production, energy and nitrogen balances, habitat and diet selection and activities of wapiti hinds (females) on pasture. It facilitates analysis of costs and consequences of supplementing shortfalls of pasture and serves as a preliminary dynamic electronic feeding standard.

The model was developed using functional relationships derived from several decades of research at the Ministik Research Station and elsewhere. Its ability to predict weight change and other production and behavioural parameters was informally tested against seasonal weight dynamics of wapiti hinds at the same research station.

Because weight changes are not a very critical test, the study also included an evaluation of alkane markers to determine energy balance of animals on pasture and hence evaluate predictions of the model. Trials with the double n-alkane ratio technique for estimating dry matter intake were encouraging although more work clearly is necessary. Calibration using feed/weight stations were excellent (y=1.09 X - 0.20 r2=0.84). Levels of C29 are very high in some plant tissues such as poplar leaves so other chain lengths are preferred. Seasonal consistency of C31 and C33 recoveries make them dependable compounds to pair with dosed C32 alkanes.

Hinds were unable to meet their nutritional requirements in late pregnancy. Since spring herbage quality is at its seasonal peak, improved pasture would not obviate this problem. Although energy requirements peak during early lactation, hinds were able to ingest enough high quality forage to achieve compensatory growth. Continued elevated intakes through late summer ensured hinds regained adequate condition in time for the oncoming breeding season.

Maternal care disrupts normal patterns of foraging and bedding. This occurs, most notably, through reductions in length of foraging bouts. To achieve satisfactory nutrient intake, hinds attempt to compensate by increasing frequency of grazing sessions. In summer, wapiti spent more time foraging and grazed longer on short than on tall swards, while intake and weight gain remained the same.

A major international project to develop dynamic feeding standards for the main species of farmed deer is needed. This project demonstrates the concept and provides a framework.

INTRODUCTION

There is a need for feeding standards for farmed deer and other diversified ruminant livestock along the lines of the National Research Council Nutrient Requirements. However, wapiti (and other farmed game) are raised predominantly in pasture-based systems and, compared with other livestock, the approach must be more ecological than physiological and dynamic rather than static. Also, because intake particularly on pasture is notoriously hard to predict, feeding standards are generally used to predict requirements to meet predetermined levels of production rather than to anticipate performance in defined nutritional environments. Whereas the former may be of value for finishing animals in feedlots, the latter is obviously more important for wildlife production and management.

This fundamental difference emphasizes a need for new methods for determining digestible dry matter intake and energy balance on pasture. This is necessary not only to corroborate feeding system models but also to give insight into the adaptive responses of wild ruminants to seasonal environments.

OBJECTIVES AND APPROACH

This project was conducted to provide a starting point for such a dynamic feeding system for farmed deer and a method for validating it under field conditions. The main objectives were to:

develop a modeling framework for predicting seasonal performance and nutrient requirements of farmed deer (specifically wapiti) on pasture,
assess the use of n-alkanes for measuring seasonal energy balance of wapiti on pasture in an attempt to validate predictions of this model.

The research proposal outlined 4 phases:

assemble international literature and data on nutrient requirements of farmed deer,
translate, update and extend the bioenergetics model using this information,
calibrate the alkane method for wapiti,
validate seasonal predictions of energy balance on pasture using the alkane method.

In this report, these are grouped into two sections; namely, model development (phases 1-2) and performance on pasture (phases 3-4).

MODELING PERFORMANCE AND FEED REQUIREMENTS

Goal and Scope

For pasture-based production systems, the goal is to calculate an animal's nutrient requirements for maintenance, growth, reproduction and lactation considering its age, sex, physiological status and environment and then to determine the daily allowances of alternative feedstuffs that would cover the shortfall of seasonal pastures. Unraveling the complicated interactions between animals (intake levels, productive processes, seasonal metabolism) and feeds (physicochemical characteristics) requires numerous balance trials with animals of various production levels offered a spectrum of common feedstuffs. Models reduce the numbers of combinations and permutations by allowing optimally interpolation among the empirical trials.

There are, of course, many gaps in our understanding of nutrient requirements of wapiti and other farmed game. Much less research has been done and the needs are somewhat more complex. The particular challenge for this project was to link bioenergetics and behaviour in order to capture the considerable ability of wild ruminants to capitalize on opportunities and offset stresses of seasonal environments. Necessarily, this model provides only a framework to condense the growing body of knowledge.

 

Approach and Methods

A model of seasonal energetics and growth of wapiti (BION, Hudson and White 1985) has been available for some time. However, it has become dated in research content and computer implementation (originally programmed in FORTH to achieve sufficient speed on 80s vintage microcomputers). BION was extended in some ways and simplified in others to improve performance and make best use of what is known about nutrient requirements of wapiti.

STELLA was selected as the modeling language for its simplicity, strict adherence to systems dynamics conventions, and availability of a free player for both MS-Windows and Mac OS. STELLA derives from DYNAMO, the language used for the MIT/Club of Rome study on limits to world growth. A new version (STELLA 5.0) which allows subscripted variables simplified programming and offered new scope for dealing with distributed systems.

A users' manual is available in electronic form. Latest versions and documentation are available on the internet at:
<http://www.deer.rr.ualberta.ca>

A player for the model is available from High Performance Systems:
 <http://www.hps_inc.com>

This model is part of the collaborative Digital Deer project which serves as a clearinghouse for information on the nutrition, bioenergetics and behaviour of deer. It features background papers and eventually regional reviews of feeding practices. At the present time, two models are under development: BION simulates daily energy exchanges and provides a means to evaluate performance of deer on pastures. ACTIVE in an 'animat' which simulates minute by minute decisions and energetic transactions of deer in natural environments and is used to study the response to disturbance.

 

Structure and Implementation

The model (BION) simulates bioenergetic transactions of individual female wapiti of any age from weaning to maturity that may or may not be pregnant and/or accompanied by a calf. Because of complications of antler growth and the rut, the current version does not provide a good representation of the bioenergetics of adult males. The model is designed to simulate changes over one year with a daily time step but can be cycled to reconstruct lifetime performance.

Energy is expressed in units of kJ (=4.184 kcal) and weights are in kilograms. The model builds on the Metabolizable Energy System. Although the US National Academy of Sciences reports the NE values of North American feeds for maintenance and production of conventional farm livestock, the ME system is most commonly used by deer nutritionists world-wide and we adopt it here. These systems are related in concept but differ in the protocol for determining feeding value (the NE system is based on comparative slaughter and is therefore of limited potential for studies on deer considering the high cost of experimental animals).

Biological processes are summarized in computational blocks which interface environment, behavior, and bioenergetics (Fig. 1). The following sections briefly describe the modeling approach and selection of preferred parameter values (background discussion is provided in shaded boxes).

Figure 1. Scope and structure of BION, a 'proof-of-concept' digital feeding standard for farmed wapiti.

 

 

Interaction and Interface

Interaction is via a control panel (Fig. 2). The model invites inputs in several ways. Graphical parameters such as seasonal patterns of temperature, precipitation and forage digestibility can be sketched to represent the year beginning 1 September. Numerical parameters describing the animal, pasture and management are entered in a tabular form with a page tab. There also is a switch to establish pregnancy.

Major tracking variables are summarized in graphic pads monitoring general parameters (weight, intake, conceptus weight, and milk production), activity budgets, feeding constraints, digestive kinetics, body composition and energy and nitrogen balance.

Figure 2. Control panel showing computational blocks, inputs and graphic outputs.

Seasonal Environment

The seasonal umwelt (operational environment) is defined by temperature, precipitation, snow pack and forage biomass and quality. Temperature influences both thermoregulation and pasture dynamics. Snow influences pasture availability and pools of green forage, dry forage and litter determine foraging rates and diet quality.

Animals are assumed to have access to two habitats or pasture types each with different parameters. Default settings assume that these are open and wooded habitats in the aspen parkland of western Canada.

A key feature of the pasture model is the explicit treatment of the impacts of grazing on regrowth of vegetation. Subject to temperature and soil moisture, the rate of pasture growth is defined in terms of the regenerative power of green plant tissue and feedback from accumulated green and dry biomass. By removing accumulated biomass, grazing can stimulate forage growth but heavy grazing ultimately reduces regenerative capacity.

Soil moisture within the rooting zone, a driving factor in plant growth, is modeled simplistically as the balance of precipitation, percolation, and evapotranspiration. Soil fertility and the influence of animals on it is not explicitly programmed. However, the general productivity of the site is established by parameters defining plant growth.

The dynamics of pastures grazed by wapiti is the subject of current work. However, some preliminary measurements to calibrate the following rudimentary model was available the Ministik Wildlife Research Station in the southern edge of the boreal aspen forest so default parameters describe a volunteer Bromus/Poa sward in open or aspen forest. Other forage resources of the aspen forest such as browse and leaf litter are not considered in this version despite their importance in the seasonal round of resource use (Gates and Hudson 1983).

In each of two habitats (open and closed), the flow of vegetation is traced through green, dry and litter pools. The regeneration of green vegetation is controlled by soil moisture, temperature and accumulated plant biomass. It matures and persists in the standing dry pool until it becomes litter which ultimately decays. Grazing wapiti remove material from the green and dry pools of each habitat according to the rules described in the next section. The two habitats differ in maximum forage biomass and rate of snow accumulation and melt.

Resource Use and Activity Budgets

Wapiti are able to select diets both by selecting feeding habitats and green/dry pools within each habitat. Selection of feeding stations within each habitat was not modeled mechanistically because it requires fine spatial resolution and unreasonably sophisticated pasture resource inventory (Jiang and Hudson 1993).

Spatial behavior of wapiti on seasonal pastures responds largely to foraging opportunities (Watkins et al. 1991; Wilmshurst et al. 1995). Time spent grazing in each of two habitats is considered linearly proportional to the relative green forage pools.

Grass swards offer modest opportunity for selection within a feeding patch because green and dry forage are intermixed. Selectivity is allowed by assigning a preference factor for green:dry pools and applies this to the size of the respective forage pools. From these rules regarding resource use, seasonal diets are composed and asymptotic digestibilities and protein concentrations are computed.

Like other wild ruminants, wapiti on pasture spend 90-95% of their day either grazing or resting/ruminating. They increase grazing time to narrow the difference between requirements and pasture supply and therefore increase grazing times when requirements increase or grazing efficiency declines. The limit to this adaptive behaviour is the time required for rumination which can be as high as 12 h/day. Rumination time is considered proportional to rumen dry matter which must be cleared to free rumen capacity for additional forage intake.

Seasonal Requirements

The daily nutritional requirement is the sum of costs associated with physiological maintenance, thermoregulation, activity, growth and, if a fecund female, gestation and lactation. Work on the nutrition of deer has been limited largely to energy requirements. This is justified because energy usually is the most important factor limiting animal productivity. However, protein is a close second and, because protein is required by rumen micro-organisms to unlock energy by the fermentation of cellulose, protein and energy nutrition are closely linked.

Daily requirements for energy and protein are determined by the factorial approach summing costs for maintenance, gestation, lactation and gain. Shortfalls in energy intake stimulate mobilization of body tissues and "negative gain".

Ecological Maintenance

Ecological maintenance represents the costs of free existence. Until recently, these costs had to be calculated, assuming various productive efficiencies, from fasting metabolic rate, and energy costs of activity and thermoregulation. Jiang and Hudson (1992, 1994) developed techniques for evaluating energy budgets of free ranging animals and provided the estimates for maintenance and gain used to parameterize this model.

Published estimates for minimum winter requirements of red deer and wapiti are in the order of 450-550 kJ/kg0.75/day (Fennessy et al. 1981, Suttie et al. 1987, Jiang and Hudson 1994, Cool and Hudson 1996). Summer and autumn values increased to 720 and 876 kJ/kg0.75/day (Jiang and Hudson 1994).

Based on this work, BION multiplies 550 kJ/kg0.75 as the winter nadir by the appetence cycle, a scalar ranging seasonally from 1 to 1.5. This cycle can be interpreted as a photoperiodic neuroendocrine response. The cycle is modulated by the nutritional environment but this is not known in a quantitative way. Relevant results will come from current studies supported by AARI (Christopherson and coworkers).

The incremental costs of free-existence increase this by about 200 kJ/kg0.75/day (Jiang and Hudson 1992, Wairimu et al. 1992) but the value varies with resting metabolism. Activity is better represented as a fixed scalar (1.15) rather than a fixed cost per unit activity. Although summer activities probably do not range widely, winter costs are expected to vary with snow cover and supplemental feeding. If supplement is available ad libitum, heavy snow forces animals to camp near the feeder and costs appear to decline. Under other conditions, they are eager to continue foraging despite supplementation and activity costs increase. The relationships are not known in a quantitative way.

In the original model, thermoregulatory costs were calculated as the difference between net thermal loss to the environment and the heat produced from tissue and food-related metabolism. Some of this information is provided by Parker and Robbins (1984). However, factors such as posture and activity have such a profound effect on tissue and external insulation that a more direct approach was adopted. Adult wapiti protected from wind are very resistant to temperatures as low as -25°C when standing quietly. Although calves have lower critical temperatures of -20°C when bedded, it rises to -5°C when they are standing or active (Fig. 3). Standing values were used in this version.

Figure 3. Energy expenditures in relation to ambient temperature for wapiti calves that were bedded, standing or active (adapted from Gates and Hudson 1979).

Gestation

Energy requirements for gestation are calculated from Adams et al.'s (1990) equation for red deer adjusting for the different birth weights and gestation lengths of wapiti (250 vs 233 days)(Fig. 4). From work on other ruminants, metabolizable energy was assumed to be used for gestation with an efficiency of only 13%.

Birth weights of healthy elk calves range from 15-22 kilograms (Hudson et al. 1991). Male calves are slightly heavier than female calves. Birth weights are directly related to maternal age and size (Blaxter and Hamilton 1980, Hudson et al. 1991). Good nutrition increases birth weights slightly (Hamilton and Blaxter 1980).

Birth weights of wapiti conform to interspecies allometric relationships and this may even hold for wapiti of different sizes (Robbins 1993):

BW = 0.2143 LVWT0.79

Conceptus weight (fetus plus associated uterine tissues) at any stage of gestation is estimated:

CW = 1.54 BW e(0.0195 DP -5.122)

Daily energy retention (PR) is:

PR = 4.184 BW e (0.0193 DP -1.7938)

Figure 4. Daily deposition of energy and protein in the conceptus expressed per kg calf birth weight and proportion of gestation (days pregnant/gestation length). Curves fit to data from Adam et al. (1988a,b).

Lactation

Several studies have been conducted on lactation in Cervus elaphus. Arman et al. (1974) studied the composition and yield of milk from red deer. Robbins (1981) and Hudson and Adamczewski (1990) provided comparable data for wapiti. Fitting the lactation curve to data for well-fed wapiti, potential milk yield (Milk, kg/d) is calculated from days lactating (DL)(Fig. 5):

Milk = 0.022*(DL+25)1.55*+exp(-.0195*(DL+25))

 

Figure 5. Milk yield of wapiti on aspen parkland ranges in central Alberta (Hudson and Adamzcewski 1990). Y=0.022 (t+25)1.55 e -0.0195 (t+25)

Although the effect of body size and condition is not known precisely, the following correction was made by multiplying the above equation by EBWsum/Mature_Wt.

The energy content of milk (EVl, kJ/kg) varies with the stage of lactation. Using data from Arman et al. (1974):

EVl = 4327 DL 0.096

Unsupplemented wapiti hinds on aspen ranges produce less but more concentrated milks so the energy supply to the calf is about the same (Hudson and Adamczewski 1990). This milk supports calf gains of 800-1000 g/d.

Growth

Liveweight is calculated from empty body weight by adding the weight of digesta pools and, for pregnant females, the developing conceptus. Empty body weight is determined by integration of daily gains. Daily gains can be determined either from direct estimations of the costs of gain or from information on the energy content and composition of gain and the expected efficiencies of utilisation of metabolizable energy. The current version uses new information on seasonal costs of gain in wapiti; namely, 27,000 kJ/kg during winter increasing by 1.5 at peak metabolic activity in early summer (Jiang and Hudson 1994). Where nitrogen is limiting, surplus energy is deposited solely as fat.

The efficiency of using ME for gain (kf) is similar in deer and sheep (Simpson et al. 1978a,b), about 0.55, slightly higher for concentrates and lower for forages. By calculation, ME requirements for growth are expected to be in the order of 40 MJ/kg liveweight gain. Research in New Zealand determined a value of 37 MJ/kg for 6-18 month-old stags (Fennessy et al. 1981) and 55 MJ/kg LWG for hinds (Suttie et al. 1987). Efficiencies of weaned red deer calves vary through the winter months (55 MJ/kg in November/December, 87 MJ/kg in January/February, and about 50 MJ/kg in March/April). Estimates of 38 MJ/kg are available for young hinds on spring pasture and 33 MJ/kg for yearling stags in Alberta (Jiang and Hudson 1992, Wairimu et al. 1992).

Lean tissues (wet weight) have energy contents of approximately 5,000 kJ/kg while fat has an energy content of 39,300 kJ/kg. As animals mature, priorities for tissue deposition change and most of the variation in the energy content of gain in immature animals is explained by liveweight After scaling for differences in mature weights of deer (80 kg) and wapiti (310 kg), the relationship between the energy content of gain (CG, kJ/kg) and liveweight (kg) can be estimated (Robbins et al. 1974).:

CG = 2000 LVWT 0.37

Which corresponds to a fat proportion (PFAT) of:

PFAT = 0.00885 LVWT 0.635

These relationships predict energy contents of gain of 11,000 kJ/kg (18% fat) at weaning and 16,500 kJ/kg (33% fat) at maturity.

Integrated over the growth trajectory, these rules give realistic body compositions at all stages of development. However, both environmental and physiological factors may cause short-term deviations. Animals on exceptionally high planes of nutrition tend to be fatter at similar liveweights because lean tissue growth is rate limited. Homeorhetic controls also may influence the seasonal partitioning of energy between lean and fat tissue growth. A further complication is the proportion of water associated with lean tissue growth which changes with maturity and with seasons.

The growth impetus of northern wild ruminants varies seasonally. These target gains have been established by regressing summer weight gains against spring weight and winter weight changes against peak autumn weights (Fig. 6, Hudson et al. 1985 and unpublished data). The interesting observation is that growth at all ages is dictated linearly to the deviation from asymptotic weight although different slopes apply in summer and winter. These relationships were manipulated to predict daily gains and to merge summer and winter relationships into a single expression modified by the seasonal appetence cycle.

Figure 6. Compensatory gain of wapiti on summer pastures (Hudson et al 1985).

Protein requirements

Maintenance requirements for protein (Nx6.25) must minimally cover endogenous urinary and fecal excretion, and (negligible) dermal losses. The constant endogenous component is assumed to arise from the degradation and replacement of protein and simple nitrogenous components of tissues.

Mould and Robbins (1981) estimated EUN to be 0.16 gN/W0.75 while metabolic fecal nitrogen was 5.58 gN/kg dry matter intake. In ruminants, these two quantities are not strictly independent and perhaps cannot simply be added to give total maintenance requirements. However, in the absence of relevant data for wapiti, the factoral approach is adopted (Robbins 1993).

Nitrogen required for development of the conceptus is:

NP = BW e (0.01969 DP-1.7274)

Nitrogen required for lactation is calculated using a value of 0.97% (6.2% protein) for the nitrogen content of wapiti milk. Protein requirements for growth are calculated assuming that lean tissue is 23% protein.

Feed protein to meet this net requirement is calculated by dividing by the digestibility of dietary protein and its biological value. Both are strongly influenced by dietary protein concentration and the two terms often are multiplied to obtain an overall efficiency called Net Protein Value (NPV). Over the range of typical diets, NPV varies little from 0.40-0.45 and is similar for most ruminants (Fig. 7).

There is some suggestion that digested protein, like energy, is not used equally efficiently for maintenance and various productive functions. Attempts at refinement define metabolizable protein as the proportion of digested protein absorbed as amino acids. This metabolizable protein is used with an efficiency of about 0.67 for maintenance, 0.50 for growth and gestation, and 0.65 for lactation.

Figure 7. Net protein value is the product of apparent digestibility and biological value Apparent digestibility of protein and its biological value is related to dietary crude protein concentrations (FP, frac). The following equations from Mould and Robbins (1981) were combined to obtain this relationship:

Apparent digestibility of protein = 0.98-0.035/FP
Biological value=.87- 1.85 FP (efficiency of use of digested protein).

This "black-box" approach does not distinguish the protein requirements of rumen microbes and host tissues and therefore does not address the issue of optimal ruminal degradation.

Nutrient Supply from Range and Pasture

The advantage offered by wild ruminants is that most of their seasonal nutrient requirements can be met by grazing. Of course, the adequacy of the nutrient supply from forage depends on both its quality and availability and how it is influenced by stocking rate.

Dry matter intake

Regulation of intake on pasture can be visualized as the minimum of 3 interacting constraints: metabolic demand (Illius and Jessup 1996), digestive capacity (Allen 1996) and logistics of foraging (Wickstrom et al. 1984, Forbes 1996).

Metabolic demand

Animals eat to meet nutrient requirements for maintenance, growth and reproduction. Intake is therefore limited ultimately by this demand. The target dry matter intake from pasture (metabolic constraint) is calculated as this metabolizable energy required to meet requirements for seasonal maintenance and production divided by the metabolizable energy concentration of the feed.

Digestive constraint

Within limits, ruminants can compensate for deteriorating diet quality simply by consuming more. But, low quality forages ferment and pass from the rumen slowly and intake becomes limited by gut fill. Although not quantified, rumen capacity seems to increase under these circumstances and also during lactation to accommodate higher intakes. Potential daily dry matter intake limited by the digestive constraint is determined as the difference between digesta mass and rumen capacity.

This parameter is sensitive to the integration interval. Animals can increase daily intakes through frequent short feeding bouts rather than a single large one. The simplest solution was to adjust rumen capacity to work with a daily time step.

Logistic constraint

Nutrient intakes on pasture are influenced by logistic as well as digestive factors. Pasture biomass/structure and snow cover are most important. The feeding rate on foliage and browse is not very sensitive to biomass because of the clumped distribution of these forages. However, intake on grass pastures is determined largely by standing crop although different maximum feeding rates occur on green and dry forage. The feeding rate of wapiti is reduced to 50% at about 500 kg/ha (Fig. 8). Wapiti compensate by grazing longer but reach an upper limit of about 12 h/day because of pre-emptive activities and the rumination requirement.

 

Figure 8. Feeding rate of wapiti on Poa/Brome pastures (Hudson and Watkins 1986). Cured pasture (top), Y=22X/(533+X). Green pasture (bottom), Y=11X/(385+X).

The model determines maximum forage intakes by multiplying feeding times (mins) by feeding rates (g/min). Maximum feeding rates are varied from 11 to 22 g/min in proportion to the relative proportion of dry and green pools.

 

Digestion

Ingested forage is subjected to the competing processes of digestion and passage. BION simulates this competition explicitly for soluble, potentially digestible and completely indigestible fractions. Estimating digestion and passage rates from Westra and Hudson (1981) and especially Jiang and Hudson's (1996) study of wapiti on seasonal pastures in Alberta, parameters were related to forage digestibility.

Physical properties of feed rather than specific morphophysiological adaptation explain most seasonal variation in digestive parameters. Among domestic ruminants, passage rates are influenced by intake level, forage type and forage quality. However, the relationship appears weak in deer (Milne et al. 1978, Renecker and Hudson 1990, Domingue et al. 1991 a,b 1992, Sibbald and Milne 1993). The simplest explanation is that digesta fill increases either by changing distension set-points or digestive tract dimensions. Evidence for the former comes from Sibbald and Milne (1993) who did not find differences in the weight of gut tissues but did find higher dry matter proportions and weights of digesta and water-filled capacity of the rumen when voluntary feed intake by red deer was high. Domingue et al. (1991a,b) also found that higher feed intake was accommodated by higher digesta loads.

 

Making up the Difference

Although wild wapiti and other deer are superbly adapted to smooth out the seasonality of nature, by stocking heavily and limiting their choices of habitats and foods, supplementary feeding becomes necessary. Shortfalls in pasture can be made up with a variety of conventional feedstuffs although attention to quality and palatability is more important than it is for beef cattle. Tables of ME values of feeds intended for sheep seem to work well with wapiti and red deer.

The amount of supplement to offer is determined by the shortfall of pasture intake. Although the requirements of animals for energy and protein are known rather precisely, the proportion obtained from pasture can only be very crudely estimated as discussed above. Also, heavy supplementation with palatable feeds reduces dependence on pasture forage and apparently reduces the efficiency of winter energy conservation (Kozak et al. 1994, 1995).

BION allows any proportion of the shortfall to be made up with supplemental feed and tracks the cumulative amount of supplemental feed used. Supplements can be offered at multiples of the shortfall and this will result in lower pasture use and properly adjust the rumen pools. However, unless the relative palatabilities of feeds and pastures are known, pasture intake at ad libitum supplementation cannot be accurately predicted.

 

EVALUATION AND APPLICATION

Models are never really validated since critical proof cannot be obtained. They are not right or wrong, simply more or less useful in ordering current information and guiding future work. One can do little more than gain confidence as models provide realistic predictions under a growing range of circumstances. This section displays predictions of the bioenergetics and productivity of wapiti under conditions for which we have at least some empirical data. We begin with a consideration of the growth trajectory throughout life and then take a closer look at bioenergetic transactions through the annual cycle.

Liveweight and other production parameters

Simulated lifetime growth, conceptus development and milk production of supplemented and lightly supplemented females on pasture are compared in Figs. 9, 10.

Heavily supplemented reproductive females are able to gain weight even in winter especially as long yearling and two year olds. At maturity, slight weight losses occur in mid winter before conceptus growth makes up for the loss of empty body weight. By their third year, hinds approach their asymptotic weight of over 300 kg. Conceptus weights and milk production increase markedly from first to second parities and slightly with age thereafter.

During winter, free-ranging animals lose weight in the face of declining quality and availability of native forage. The impact in both absolute and relative terms is greatest for larger individuals. Weight loss occurs mainly in late winter as snow deepens and forage quality declines to critical levels. Spring comes abruptly and weights, particularly of pregnant females, increase rapidly. Even at peak lactation, weight gains are positive and small females are able to narrow the contrast in weight with large females over the summer.

Wapiti hinds offered 30% of the pasture shortfall gain during their first winter but lose considerable weight in later years and attain mature weights about 20% below the genetic maximum. Under these harsher conditions, the weight gains of nonpregnant hinds greatly exceeds that of reproductive hinds (Fig. 11).

Figure 9. Weights, conceptus weight and milk yield of wapiti hinds from 16 months to maturity when shortfalls of pasture are fully met with supplemental feeds.

Dry matter intakes

Rumen distention, metabolic requirements, and the logistics of foraging interact in a complex way to give rather different voluntary forage intakes of small and large animals through the seasonal cycle (Fig. 12). In reproductive adult females, rumen-fill threatens to constrain intake only in autumn. Particularly in large individuals, weight loss appears to be due to the logistic constraint operating in late winter. With snowmelt, intake increases rapidly in compensation. However, as the spring flush of vegetation progresses, intake declines until lactation imposes additional demands after calving. The decline in requirements to support lactation is offset by declining forage quality so intake remains high for much of the summer.

A rather different pattern of constraints operates on weaned calves. Gut fill is predicted to be a major constraint on forage intake until the following spring and summer. Since logistic constraints appear less important, forage quality would be expected to be more important than availability. However, differences in foraging efficiency of large and small animals under harsh winter conditions have received only cursory attention.

 

Figure 10. Liveweight, conceptus weight and milk production of a lightly supplemented wapiti hind from 16 months to maturity.

Figure 11. Weights of reproductive and non reproductive hinds on lightly supplemented pasture illustrating the demands of gestation and lactation.

Figure 12. Seasonal constraints on dry matter intake. Actual intake is defined as the minim of metabolic, digestive and logistic constraints.

 

VALIDATION THROUGH FIELD STUDIES

Although models may generate outcomes that ‘look right’, there is a need for more formal corroboration. Weight change over a grazing season is one measure but it is not particularly sensitive. Therefore, we explored the use of internal/external alkane ratios to determine digestible dry matter intakes on pasture. We intended that weight gains and pasture intakes would be used to determine energy balance of wapiti hinds grazing pastures of contrasting quality or biomass. We attempted to use regression of ME intakes against relative gains to estimate seasonal energy requirements for maintenance (intercept) and gain (slope). These supplementary tracking variables should provide a much sounder evaluation of the models performance.

Methods

Study Area

Seasonal trials to determine digestible dry matter intake and energy balances of wapiti were conducted at Ministik Wildlife Research Station, located 48 km southeast of Edmonton, Alberta on the Cooking Lake glacial moraine. Vegetation is classified as boreal aspen forest (Rowe 1972). The experimental pastures were primarily composed of Kentucky bluegrass (Poa pratensis), smooth brome (Bromus inermis), white clover (Trifolium repens), dandelion (Taraxacum officinale), and Canada thistle (Cirsium arvense).

Grazing Trials

From June 1996 to April 1998, thirteen adult female wapiti were used (Table 1). Animals ranged from three to twelve years of age when study began (mean: 8± 2.6 years). Hinds were free-ranging but were supplemented with concentrate alfalfa-barley pellets (year-round) and hay (winter), except during pasture trials, when all supplemental feed was withdrawn. All hinds calved successfully in each year of the study and calves were present during all trials between parturition and weaning.

Table 1. Mean weights of wapiti hinds and their calves at trial commencement at Ministik Research Station, AB. Calf gender represents proportion of females (F) to males (M).

Seven grazing trials were conducted between June 1996 and November 1997. Four periods were selected based on importance in the annual reproductive cycle (early gestation (EG), late gestation (LG), peak lactation (PL), late lactation (LL)). Two enclosures were established as best available seasonal pasture (Lightly grazed) and previously grazed pasture (Heavily grazed). Except during late gestation, pasture biomass between enclosures differed by at least 20%. Stocking rate and trial length were chosen to minimize complications arising from pasture growth.

The first trial was in late June/early July 1996 (PL96). Heavily grazed pasture (G) (10.6 ha) was stocked with at least ten adults for two weeks prior to trial commencement to provide sufficient defoliation, while lightly grazed pasture (U) (9.0 ha) had been free of grazing for at least two months. Five lactating hinds (with calves) were held (without supplemental feed) in each enclosure for 16 days. An adjustment period was not considered necessary, as the animals grazed areas surrounding enclosures prior to trial. Second trial was conducted during late August of the same year (LL96). Between trials, G was always stocked (except during snow cover periods) to ensure continuous defoliation, while U remained empty.

Commencing November 1996 (EG96), smaller enclosures were used (G - 5.0 ha, U - 7.8 ha) to enable more rapid defoliation in G and provide more even representation of aspen forest and grassland between pastures. The early gestation trial in 1996 (EG96) was terminated after 11 days, as two heavy snowfalls greatly reduced forage availability and supplemental feeding became necessary. Five days (EG97 - 3 days) were added to the beginning of remaining trials, as marked differences in forage biomass required two to three days for hinds to adjust from the intermediate forage surrounding enclosures. Trials in 1997 were conducted in early May (LG97), late June/early July (peak lactation, PL97), late August (late lactation, LL97), and early November (EG97).

Dry Matter Intake using N-Alkanes

The double n-alkane ratio method was used to estimate forage digestibility and dry matter intake (DMI). At commencement of each trial (i.e. after the adjustment period for 1997 trials), a controlled release device was administered per os into the rumen of each hind. In 1996 trials, these capsules contained equal amounts of dotriacontane (C32) and hexatriacontane (C36) releasing 68 mg of each per day. To increase daily alkane dose, thereby improving accuracy of concentration estimations, capsules used in 1997 trials contained only C32, for a daily release rate of 102 mg.

Small samples of freshly voided faeces were collected from each hind on days 4 and 9 in 1996 trials. In 1997, collection was changed to days 5 and 10 to create a more accurate association with sampled vegetation. Faecals were also sampled on day -1 (1997) to utilize as a faecal alkane reference in non-dosed wapiti. In LL96, faecal samples from four calves were obtained (two from each pasture) to compare alkane concentrations with those found in non-dosed hinds. Samples were freeze-dried for 72 h at -60° C, ground through a 20-mesh screen in a Wiley mill, and alkanes extracted.

Dry matter intake was calculated using two pairings of adjacent alkanes (C31:C32, C33:C32):

Herbage intake (DMI)(kg DM/day)= (D32 x Fn/F32) /[(Hn - (Fn/F32) x H32]

where D32 is release rate (mg/day) of dosed alkane (C32), F32 and H32 are respective concentrations (mg/kg DM) of C32 in faeces and herbage, and Fn and Hn are natural dietary concentrations (mg/kg DM) of alkane (either C31 or C33) in faeces and herbage, respectively.

Faecal recovery of alkanes increases with increasing carbon-chain length (Dove and Mayes 1991). Therefore, C36 was used to determine herbage digestibility (%) following (Heydon et al. 1993):

Digestibility = [1 - (0.96 x D36)/ F36]/DMI

where D36 is release rate (mg/day) of dosed C36, F36 is faecal concentration (mg/kg DM) of C36, and 0.96 represents a correction factor to account for incomplete indigestibility of C36 (Heydon et al. 1993). DMI represents actual measured intake (kg).

To analyze N-alkanes, freeze-dried, ground duplicate faecal (0.30 g) and herbage (1.0 g) samples were weighed into 50 ml pyrex tubes fitted with teflon-lined screw caps. Added to each tube, was 200 m l tetratriacontane (C34) internal standard (100 mg C34/100 ml hexane), 10 ml methanol, 1 ml KOH (45%), and placed in water bath for 4.5 h at 90° C. Alkanes were extracted by adding 10 ml hexane (HPLC grade) and 5 ml distilled water, transferring separated hexane layer to a 20 ml scintillation vial, then repeating extraction with another 8 ml hexane. Pooled hexane layers were evaporated to approximately 500 m l and passed through a silica gel column (70-230 mesh) to separate lipids from alkanes. Scintillation vials were rinsed twice with 2 ml hexane which was also added to the silica gel column. Approximately 1 ml of remaining solution was transferred to a 1 ml glass gas chromatography (GC) vial.

Analysis was conducted on a Varian 3400 Capillary Gas Chromatographer equipped with a Varian 8100 Autosampler and EzChrom GC Data System (Version 3.1). Capillary column was an Rtx-1, 30 m x 0.25 mm ID x 0.25 m df (Restek Corporation) and the carrier gas was helium. Initial column temperature was set at 80° C, held for 0.04 min, then programmed to rise 20° C/min to a maximum of 280° C for a four minute holding time. Septum programmable injector (SPI) temperature commenced at 90° C and increased to 280° C at a rate of 150° C/min, at which it was held for 12 min. The flame ionization detector (FID) temperature was 280° C. Alkane-hexane solution (0.5 m l) was injected. Resulting chromatograms presented alkane concentrations for C29 to C36.

Dry Matter Intake by the Bite-Count Method

The bite count method was used both to estimate herbage intake (kg DM/day) (1997 trials only) and to explore the adaptive responses of wapiti to changing pasture biomass and structure. This technique is based on behavioural observation according to the following equation:

Herbage Intake (g DM/day)=BR x BS x FT

where BR is bite rate (bites/min), BS is bite size (g), and FT represents absolute feeding time (min) over 24 h. These behavioural parameters were related to sward characteristics as affected by season and grazing pressure. Estimates were only calculated for EG96 and subsequent trials, due to unavailability of 24 h activity budgets in prior trials.

Sward Measurement

On days 4 and 9 of each trial, 0.02-m2 plots paired with each grazing observation were hand-plucked to ground level to simulate maximum possible removal by grazing wapiti. This relatively small area of vegetation collected was in response to highly variable sward. Samples were freeze-dried for 72 h at -60° C and feeding patch biomass (FPB) calculated (g DM/m2). In addition, at the beginning, middle, and end of every trial in 1997, five 0.25 m x 0.25 m biomass plots were randomly sampled on grassland in each enclosure. These samples were oven-dried for 5 days at 60° C and pasture biomass estimated (kg DM/ha).

Foraging Behaviour

In each trial, foraging parameters were directly observed during normal feeding bouts on 2 to 7 days, in the morning (0800-1130) and afternoon (1400-1700). Cropping bite rates were determined in 4 to 15 minute sessions and corrected for non foraging activities exceeding thirty seconds. Observation began by selecting a group member and continued sequentially until all animals were observed. Attempts were made to acquire ten minutes per individual to correspond with the time interval selected for scan sampling. Bite rates observed during sessions less than 2 min duration were discarded. Cropping rates were not collected while animals were in aspen forest, as disproportionate time was spent in activities such as tree rubbing, chewing bark, eating twigs.

Following each session, mean bite size was estimated by hand-plucking 20 to 40 simulated "bites", to duplicate as closely as possible, amount and species composition of bites ingested by wapiti (Hudson and Nietfeld 1985). Variations in wapiti incisor bar width and observer bias were corrected with the following equation:

Corrected Bite Size =BS x I / O

where I is wapiti incisor bar width (mm) and O is width on observer hand that prehends vegetation (mm). Incisor bar width represents tooth surface available for forage prehension. O accounts for between-observer variation in hand-plucking techniques.

Activity Budgets

Activity budgets were determined using the predominant activity sampling method (Hutt and Hutt 1970). A behaviour is assigned if it occurs for more than half of the given interval (10-min), irrespective of its distribution within the interval. For each group, behaviours were recorded at 10-minute intervals over a 24-hour period, once per trial. Wapiti were fitted with patterned reflective neck collars, facilitating nocturnal observation and individual identification.

Activities were categorized as foraging, bedded, standing, and other (running, walking, grooming, rubbing (against fence post or tree), cow-calf interaction (nursing, grooming), and cow-cow interaction (agonistic, grooming). Time budgets and activity patterns (foraging bout distribution, frequency, and duration) for each individual were calculated.

Statistical Analysis

Digestibility estimates and marker recovery at different intake levels were compared by one-way analysis of variance (ANOVA). The preferred technique for assessing DDMI was determined by regressing estimated against actual intake, and ascertaining whether predicted slope differs from unity and intercept differs from zero.

Maintenance requirements of pen-fed wapiti was estimated by regression analysis of metabolizable energy intake (kJ/W0.75) against liveweight gain (g/W0.75/day).

Factorial ANOVA was used to compare DMI with main effects being season (May, June/July, August, November) and method (alkane (C31:32, C33:32), bite count). Seasonal differences in herbage alkane concentrations were tested using one-way ANOVA. Bonferroni’s pairwise multiple comparisons were applied when significant differences were detected.

For 1997 trials, linear regression tested relationship between predicted DMI and pasture biomass. Interrelationships among foraging parameters were tested by non-linear regression.

Treatment and seasonal differences in number and duration of feeding bouts, and foraging parameters were examined using factorial ANOVA. Scheffe’s pairwise multiple comparisons identified which means differed significantly. Variables were subjected to Bonferroni tests and if no significant difference occurred between respective seasons of 1996 and 1997, those data were pooled.

Intakes and Gains

DMI estimation techniques are compared in Table 2. For purposes of comparison, 1996 trials were excluded due to snow cover (EG96) or unavailability of 24 hour scan samples (PL96, LL96), precluding accurate intake estimates using the bite count method. Methods of estimating DMI, did not differ significantly (p>0.05). Estimates calculated using C33:C32 pairing will be used, as literature dictates that this pairing is preferable to C31:C32, due to greater similarity of faecal recoveries in adjacent alkanes of longer chain-length (Dove and Mayes 1991).

Table 2. Seasonal dry matter intakes (kg/d).

DMI

May

June/July

August

November

Alkane - C31:C32

3.46±0.18

5.43±0.25

5.16±0.65

4.29±0.41

Alkane - C33:C32

3.44±0.17

5.16±0.21

5.43±0.68

4.35±0.41

Bite Count

3.97±0.44

7.65±0.63

7.19±0.74

4.69±0.89

Alkane-based wapiti intakes increased significantly (p<0.001) in early summer, remained constant as weaning approached, then dropped off again in autumn (p>0.05). Bite count intakes followed similar seasonal trend as alkane determinations, however, there was a sharp decline in autumn (p<0.05). From the alkane method, differences between heavily grazed and lightly grazed pasture were not significant (p>0.05), with estimates from heavily grazed pasture being lower being lower in every season (Fig. 13). According to the bite count method, intake in heavily grazed pasture was similar to that in lightly grazed, except in late summer, when mean intake in lightly grazed pasture was significantly less (p<0.01) (Fig. 13).

Figure 13. Seasonal digestible dry matter intake (kg DM/day) of wapiti on Grazed and Ungrazed pasture based on two estimation methods.

Bite count method often overestimates DMI when compared with predictions using markers (e.g. Jiang and Hudson 1992). When measuring bite rate, Jamieson and Hodgson (1979) suggest that instantaneous (short-term) records may overestimate long-term means by at least 16%. In our study, bite count estimates consistently exceeded alkane predictions. Although, slight in May and November, overestimations were more pronounced in summer. This likely reflects the difficulty in accurately simulating bite size during periods of peak vegetation biomass.

Methods of estimating DMI, did not differ significantly (p>0.05), however, intercept (1.87± 1.15) was greater than zero, and slope (0.46± 0.12) was less than unity. A separate calibration trial using a feed/weigh station gave the following:

C31:C32 y=1.09X-0.20, r2=0.84

C33:C32 y=0.84X+1.71, r2=0.71

Seasonal mean daily liveweight gain (MDG) (g/kg0.75) of wapiti hinds are shown in Fig. 14. There was no significant difference between heavily grazed and lightly grazed pastures, therefore, the data were pooled. Gains peaked in early summer at 12.5± 1.4 g/kg0.75 (p<0.001), while differences among other seasons were not significant (p>0.05). Spring was the only season where hinds exhibited a negative MDG (-2.9± 0.8 g/kg0.75). These patterns for mature hinds are accurately predicted by BION.

Figure 14. Average daily gain during seasonal trials.

An attempt was made to predict seasonal maintenance requirements of reproductive wapiti hinds by regressing metabolizable energy intake (kJ/kg0.75/day) against hind mean daily gain (g/kg0.75). None of the relationships were significant (p>0.05) and in most cases, linear models fitted to the data had very low coefficients of determination (R2<0.5). The problem is expected to be variability of gut fill and hence weight rather than the estimation of intake.

Similar seasonal trends of intake have been reported for red deer (Clutton-Brock et al. 1982, Heydon et al. 1993). This pattern of marked increase in early summer and declining as lactation progresses, is likely due to either, higher energy requirements during peak lactation, decreasing towards weaning, or greater herbage mass, followed by a slight decrease when plants mature (or a combination of the two). The former is supported by Heydon et al. (1993) in their comparison of milk and yeld red deer hinds on hill pasture. Both exhibited same trend from July to October, with lactating hinds having significantly higher intakes, and difference decreasing as weaning approached. Results of Clutton-Brock et al. (1982) agree with the latter hypothesis, in that their lactating and non-lactating wild hinds adhered to the same intake pattern (i.e. based on gut content percentage of liveweight) from spring to late summer.

Disparity between intakes of Jiang’s (1993) barren hinds and gestating/lactating hinds in our study, was unexpected. His animals had nearly threefold greater daily intake (g DM/kg0.75) in spring (Jiang - 154; this study - 57± 3), when one might expect the opposite for an animal trying to meet the needs of a developing conceptus. However, gut capacity may be reduced through physical displacement by products of conception as occurs in other species.

Forage intakes during early summer were similar to those previously determined on lactating (Heydon et al. 1993, Niezen et al. 1993) and non-lactating (Heydon et al. 1992) red deer. Jiang (1993) did not present estimates in this season. Ruminant intake tends to be around two percent of bodyweight, approximately six kilograms in wapiti. This level may be very difficult to surpass, due to logistical (forage availability) and digestive (forage quality) constraints, and may act as an upper limit, regardless of animal’s energy requirements. While, this quantity may be suitable for maintenance in non-lactating females, penalty for lactating hinds would be loss of condition, which would have to be re-established prior to breeding season.

In late summer, Jiang’s hinds maintained higher intakes, although the difference was much less pronounced (Jiang - 103 g DM/kg0.75; this study - 86± 6 g DM/kg0.75). Other non-reproductive wapiti on pasture at the same research station, also had higher August intakes (9.5 kg DM/day (Hudson and Nietfeld 1985); this study - 6.17± 0.47 kg DM/day). As weaning approaches, nutrient requirements for lactating wapiti should decrease, as calves rely more heavily on grazing than nursing. Perhaps hinds are forced to augment intakes to regain loss of condition during peak lactation. They may also be capitalizing on persisting abundant forage to increase weight in preparation for the ensuing rut and winter. Rumen capacity may be another explanation, as Remond (1988) established in dairy cows, that rumen volume increases by 40% in the first two months of lactation. Other studies on C. elaphus reported similar late summer intakes (e.g. Hudson and Watkins (1986) (wapiti) - 6.1 kg/day; Niezen et al. (1993) (red deer) - 88 g DM/kg0.75/day).

Autumn decline in DMI may have been due to predominance of senescent vegetation, thereby increasing the rumination requirement. One would expect minimal difference between reproductive and non-reproductive wapiti, a consequence of calf weaning and negligible incremental energy requirements of early gestation. Intakes reported by Jiang (1993) (non-reproductive hinds) and Heydon et al. (1993) (both yeld and milk hinds) in autumn match the results of this study.

Bite count method often overestimates DMI when compared with predictions using markers (e.g. Jiang and Hudson 1992). When measuring bite rate, Jamieson and Hodgson (1979) suggest that instantaneous (short-term) records may overestimate long-term means by at least 16%. In our study, bite count estimates consistently exceeded alkane predictions. Although, slight in May and November, overestimations were more pronounced in summer. This likely reflects the difficulty in accurately simulating bite size during periods of peak vegetation biomass.

Maximum daily gains in early summer is interesting because peak lactation should be the hinds’ most energetically expensive season. However, these demands are coincident with peak pasture biomass and quality.

Activity Budgets

Wapiti spent a large portion of their active time foraging, however, seasonal variation was marked (p<0.01) (Table 3, Fig. 15). In both pastures, percentage of active time engaged in foraging activities was less in early summer, increasing in late summer, followed by a notable decline in autumn. Differences between heavily grazed and lightly grazed pastures were significant (p<0.05) in 1997, from early summer through November.

There was no significant difference in diel foraging and bedding (h) between pastures, therefore, data was pooled. Foraging time in early summer (10.85± 1.23 h/day) did not differ from spring (10.82± 0.90 h/day), however, there was a significant increase (p<0.01) to 12.77± 1.30 h/day in late summer, followed by a substantial decrease (p<0.001) to 8.23± 1.04 h/day in autumn. Time spent bedded was greater (p<0.05) in spring (11.60± 0.91 h/day), consistent through summer (June/July - 10.20± 0.80 h/day, August - 10.43± 0.99 h/day), and peaked at 12.64± 1.09 h/day in autumn.

Characteristics of foraging bouts showed marked seasonal variation. Differences between pastures were only significant during summer, when wapiti in lightly grazed pasture had more bouts of shorter duration. Overall, duration of foraging bouts (min) were longest (p<0.01) in August (99.5± 20.3), followed by a sharp decline in November (59.9± 11.1). Number of bouts in a day were highest (p<0.01) in spring (9.7± 1.2) and early summer (10.2± 2.2) and fewest in late summer (7.0± 0.8) and autumn (7.3± 0.6).

Table 3. Seasonal foraging parameters and forage availability for wapiti hinds (n=5) on heavily grazed and lightly grazed pasture (1997 only) at Ministik Research Station.

Figure 15. Seasonal activity budgets of wapiti hinds (n=10) at Ministik Research Station, AB. "Other" refers to any behaviours exhibited when not foraging or bedded (eg. standing, social interaction, nursing, movement, etc.).

Similarities between milk hinds in present study and Jiang’s (1993) yeld hinds, imply that greater nutrient requirements of gestating and lactating wapiti were not satisfied through increased grazing time, but possibly by augmenting other foraging parameters (e.g. bite rate, bite size). Gates and Hudson (1983) suggest that fatigue and demand of alternate activities (e.g. rumination, neonate care) place an upper limit on daily foraging time, and this is commonly cited to be around twelve hours. Presumption that these wapiti may have been constrained by this upper limit is supported by Clutton-Brock et al. (1982) and Heydon et al. (1993), whereby, increases in daily grazing time from yeld to milk hinds was 9.8 h to 11.8 h and 10.8h to 12.2 h, respectively.

Foraging and Pasture Parameters

Wapiti foraging rates followed the same seasonal trend as daily grazing time. There was no significant difference between moderately and lightly grazed pasture in any season, therefore data was pooled.

Bite rates (bites/min) were constant through spring (46.7± 1.3) and early summer (47.7± 1.0), increasing to 61.9± 1.6 in late summer, followed by a sharp decline to 37.2± 1.5 in autumn (p<0.001). Bite rate declined exponentially as a function of increasing bite size (y = 59.5e-0.0011x, p<0.01, R2=0.64) and inversely in relation to sward biomass (y = 25.1 + 5548/x, p<0.05, R2=0.36).

Attempts to maintain marked difference in forage biomass between heavily grazed and lightly grazed pastures was successful. Unfortunately, between-trial time constraints and concern of animal condition resulted in heavily grazed pasture biomass being well above that which would normally be regarded as limiting (i.e. 900 kg DM/ha (Gates and Hudson 1983)). This may explain the general lack of disparity in foraging behaviour between pastures. Heydon et al. (1993) found considerable difference in bite rate (high - 62 bites/min; low - 82 bites/min) among lactating red deer hinds on high and low biomass pastures. The ‘high’ pasture contained 1659 kg DM/ha, while forage availability would likely be considered a limiting factor in the ‘low’ pasture, with only 466 kg DM/ha.

On spring pasture of similar biomass (1880 kg DM/ha), Jiang’s (1993) yeld hinds had lower mean bite rate (34 bites/min) with nearly double the bite size (229 mg). In an attempt to maintain intake level, having already approached seasonal maximum of daily grazing time (Jiang - 10 h; present study - 10.8± 0.3 h), wapiti in this study may have been compensating for smaller bite size (127± 14 mg) by increasing foraging rate (46.7± 1.3 bites/min).

CONCLUSIONS

The emerging deer/wapiti industry needs ‘feeding standards’ similar to NRC Nutrient Requirements that have proved so useful for other farm livestock. Current information on nutrition is scattered and the relevance is difficult to evaluate. The proposal anticipated the following outcomes of this study:

an international database on energy and nutrient requirements of farmed deer.
a computer model of seasonal performance and requirements of free-grazing wapiti for the game and feed industry.
new approaches to modeling animals on pasture and range may emerge because of the relevance of nutritional ecology to wild ruminants.
slow-release alkane capsules will offer improved capability for studying energy balance of free-grazing animals.

Although much remains to be done to attain the sophistication of feeding standards for conventional farm livestock, these outcomes generally have been attained.

Electronic Feeding Standards

Several models of the bioenergetics of wild ruminants have been published (Hudson and White 1985, Hobbs et al. 1982, Moen et al. 1997). Generally these were intended to evaluate carrying capacity of ranges for wild populations. The current model extends this work in several ways:

Animals are linked interactively with pasture supply so stocking rate of like animals can be considered,
Constraints on foraging are explicitly modeled so sward structure, biomass and quality can be evaluated,
Lifelong production can be simulated with year-end condition setting state for subsequent years,
Supplementary feeding is accommodated in an interactive manner allowing evaluation of costs and consequences on productivity and allowable stocking rate.

 

Limitations

This version is limited to wapiti and red deer hinds. With appropriate scaling for body size, wapiti and red deer appear similar in nutrient requirements and performance (Haigh and Hudson 1993). After all, they are considered members of the same species. However, fallow, sika, white-tail and mule deer and aseasonal tropical deer such as sambar, rusa, and chital undoubtedly have very different requirements.

The peculiar requirements of stags for antler growth and the complex endocrine, behavioural and bioenergetic changes during the rut are not addressed in the current version.

Model Development

The immediate plan is to accommodate more habitats and complex pasture rotations. Explicit treatment of the substitution of concentrates, forage and pasture also is high on the priority list. Protein metabolism is crudely handled and poorly integrated with energy metabolism. Seasonal control of metabolism by photoperiod and its nutritional modulation demands more basic research.

Energy Balance of Grazing Animals

The double-alkane method for determining digestible DM intake of free-ranging animals offers promise for evaluating energy balance of wild ruminants in the field. If care is taken to select chain lengths that do not vary widely in forages, estimates of intakes appear reliable enough. Further calibration trials under controlled conditions have been conducted but results are not yet available. Precise estimates of metabolizable energy requirements for maintenance and gain must be based on animals varying widely in rates of gain. This means widely varying pasture qualities or younger animals that are growing rapidly. The precision of Jiang and Hudson's (1992, 1994) estimates from work on young non reproductive animals was not achieved in this study with reproductive adults.

Beyond the problem of sufficiently wide variation in intake and performance was the more fundamental problem of accounting for the flow of energy and nutrients to the conceptus and to the calf as milk. The conceptus is accounted in weight change although metablizable energy is used for conceptus growth much less efficiently than for liveweight gain. The transfer of milk to the calf is reflected in calf growth although the efficiency of its use for growth and the proportion of total nutrient intake from milk must be known. These complications are being studied.

World Feeding Standards for Farmed Deer

The main purpose of BION is to demonstrate a feasible approach that would allow deer researchers worldwide to collaborate on the development of species-individualized feeding standards.

 

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PRINCIPAL RESEARCHER - BIOGRAPHICAL DATA

HUDSON, ROBERT J.

Post-Secondary Education and Training Relevant to Proposal:

Institution

Field Specialization

Degree/Diploma

Year Completed

UBC

UBC

Range Management

Wildlife Management

BScAgr

PhD

1967

1971

Relevant Professional Experience (Begin with present position):

Dates

Position or Function

Employer

Location

1996-1

1985-present

1978-85

1974-78

1971-74

Assoc Dean (Acad)

Professor

Assoc. Prof

Assis. Prof

Assis Prof

Univ Alberta

"

"

"

UBC

Edmonton

"

"

"

Vancouver

Research Activities Related to Research Proposal (list up to 4 research project titles and dates):

Bioenergetics of wild ruminants. NSERC research grant 1990-96

Performance of bison on pasture : AARI direct grant 1993-95

Some Relevant Articles in Refereed Journals and Other Relevant Works Published in Last 3 Years:

Friedel, B.A. and R.J.Hudson. 1994. Productivity of farmed wapiti in Alberta (Cervus elaphus canadensis). Can. J. Anim. Sci. 74: 297-303.

Hudson, R.J. 1995 Wildlife ranching: Dancing with the Devil? In: Geist, V. and Cowan, I.McT. eds. Wildlife Conservation Policy Temeron Books, Calgary. in press.

Hudson, R.J. 1995. Paths to conservation. Pp. 318-322 In: J.A. Bissonette and P.R. Krausman, eds. Integrating People and Wildlife for a Sustainable Future. Proc. 1 Intl. Wildlife Management Congress. The Wildlife Society, Bethesda, MD

Hudson, R. J. 1995. Temporal and spatial dynamics of grazing systems. In: R.R. Hofmann and H.J. Schwartz, eds. Wild and Domestic Ruminants in Extensive Land Use Systems. Humboldt_Universitat zu Berlin. pp. 88-105. (Symposium proceedings).

Jiang, Z. and R.J. Hudson. 1994. Bite characteristics of wapiti (Cervus elaphus) in seasonal Bromus-Poa swards. J. Range Manage. 47:127-132.

Kozak, H.M., R. J. Hudson and L.A. Renecker. 1994. Effects of supplemental winter feeding on performance and foraging behaviour of wapiti. Rangelands 16:153-156.

Kozak, H.M., R.J. Hudson, N. French and L.A. Renecker. 1995. Winter feeding, lactation and calf growth of farmed wapiti. Rangelands 17: 116-120.

Wilmshurst, J.F., J.M. Fryxell and R.J. Hudson. 1995. Forage quality and patch choice by wapiti (Cervus elaphus). Behav. Ecol. 6: 209-217.