Structure and Function in Agroecosystem Design and Management - Chapter 12 ppt

261 A Simulated Rotational Grazing Experiment Using the Alpine Meadow Grazing Ecosystem Model.. From thispoint of view, we are seeking, in the study, a rotational grazing scheme and opti

CHAPTER 12

Impact of Grazing on

the Ecosystems Daming Huang

CONTENTS

Introduction 253

The Observational Site of an Alpine Meadow Grazing Ecosystem for a Modeling Approach and Its Natural Conditions 254

Modeling of an Alpine Meadow Grazing Ecosystem 255

Computer Program 261

Test of the Model 261

Sensitivity Analysis of Rotational Grazing Scheme 261

A Simulated Rotational Grazing Experiment Using the Alpine Meadow Grazing Ecosystem Model 263

Maximum Potential Productivity of the Summer-Autumn Pasture under Grazing 267

Maximum Potential Productivity of the SAP under Grazing Pressure 267

Under Constant Grazing Pressure 269

Under Variable Grazing Pressure 269

Discussion 271

Acknowledgments 273

References 273

INTRODUCTION

The alpine meadow grazing ecosystem is a subsystem of the alpine meadow ecosystem in QingZang Plateau, China Grazing ecosystem research

253

0-8493-0904-2/01/$0.00+$.50

has been conducted using an alpine meadow ecosystem matter cyclingenergy flow biological complex modeling system approach since Shiyomi et

al (1983) The meadow or pasture forms an ecosystem in which matter cyclesand energy flows through the constitutive components such as atmosphere,plants, and animals, day by day The amount of energy and materials passingthrough or accumulating within these components is affected by factors incomplicated relations with each other A grazing system embraces an entirebiological complex of weather, soil, plants, and animals, together with themanagement imposed upon it by the grazier in order to attain desired objec-tives, and it should be subject to evaluation by Shiyomi’s system approach(1983, 1986) Modeling offers a way of bridging the gap between grazingexperiments and real grazing ecosystems, provided the model includes thedecision-making processes as well as the biological interactions between theanimals and the meadow Efficient utilization of alpine meadow is one factor

of importance The potential for highly efficient meadow husbandry mizing herd management can be evaluated by using modeling From thispoint of view, we are seeking, in the study, a rotational grazing scheme and

opti-an optimal grazing pressure for the alpine meadow husbopti-andry by modeling

an alpine meadow grazing ecosystem

THE OBSERVATIONAL SITE OF AN ALPINE MEADOW GRAZING ECOSYSTEM FOR A MODELING APPROACH AND

ITS NATURAL CONDITIONS

Alpine meadows cover vast areas of the QingZang (Tibet) Plateau, cially in the east and on high mountainous ranges Amounting to 16 million

espe-ha, alpine meadows cover 40% of the grassland in Qinghai Province Thealpine meadow ecosystem research station, AFS, is located at Menyuan StudRanch of Menyuan Hui Autonomous County, Haibei Tibetan Autonomous

station lies at the foothill on the south slope of Lenglongling Mountains in theeastern part of the Qilian Mountains, in the northwest valley of the DatongRiver The lowest lands on the south side range between 3200 m and 3400 m

in altitude, forming a natural pasture where the station is situated The est peak of the Lenglongling Mountain range has an altitude of 5076 meters

high-It is covered with snow all year, and the snow line is at about 4200 meters TheDatong River valley does not vary much in topography and has an altitude

of 2800–3000 meters In some places, the land has been farmed with rape

(Brassica campestris) as the main crop Field surveys were carried out on the

experimental pastures of the AFS There are 11 vegetation communities at the

AFS, of which the most important is a Kobresia humilis meadow It is the most

common in the area of the AFS as well as on the Qinghai-Xizang Plateau and

is regarded as the best natural pasture It is found on river banks, slopes, and

hills The dominant species is Kobresia humilis, and subdominant species are

Elymus nutans, Festuca ovina, Stipa aliena, etc., varying with the grazing

pres-sure As to domestic animals, there are horses, yaks, and sheep The AFS area

is grazed mainly by yaks and Tibetan sheep The site parameters and pastureconditions are summarized in Table 12.1

MODELING OF AN ALPINE MEADOW GRAZING

ECOSYSTEM

In the alpine meadow pasture ecosystem, a portion of the solar energy isfixed by pasture plants; some parts of these plants are grazed by grazing ani-mals, and a fraction of the plants is fixed in animal bodies as energy Energyescaping from this fixation is accumulated as soil organic matter via feces andurine, or diffused into the atmosphere from the animals as heat Residualplant matter changes into standing dead plant material and then into soil sur-face litter, and finally accumulates in the soil The system of energy flow inthe alpine meadow grazing ecosystem from sun to animals or soil is shown

in Fig 12.1 In this figure, sources and sinks of energy are denoted by flags;compartments in which energy accumulates temporarily are shown by rec-tangles; directions of energy flow are indicated by arrow-heated full lines,and influences, including environmental and artificial effects on the energyflows which impinge upon the points shown by arrow-heated broken lines,are denoted by ellipses Bows indicated by arrow-headed broken lines denotevalves for regulating the energy flow For example, the leaf area index or totalleaf area per given land area affects the amount of energy flowing from the

Table 12.1 Site Parameters and Experimental Pasture Conditions for

Modeling Approach

July), annual average 0°C

114.7mm (July), annual total 531.6mm

21767.2 kJ m2 day1, annual average

20930 kJ m2 day1

Festuca ovina, Carex spp., Poa spp., Elymus nutans, Saussurea superba, Gentiana straminea

sun to plants That is, if this valve opens and the leaf area index becomeslarger, the amount of energy fixed in plants increases.

The amounts of energy accumulated in eight different compartments on

Digestibility

Grazing pressure: S

Solar light intensity: A

Amount of above-ground

Leaf area index: L

Amount of feces +urine+methane:

liveweight, V7, (8) feces on the soil surface, V8 All these variables are

meas-ured in their calorific value and change with time t.

Changes in these variables can be formulated by a set of differentialequations as follow:

In Equations 12.1–12.8, the unit for these variables’ biomass (dry matter

change with the environmental temperature The other parameters, G, S, etc.,

in the equations are explained in the following paragraphs The main drivingvariables are functions of time and expressed by following equations

1991; Daming and Songling, 1992)

where t denotes the number of days counted from 21 April.

2 Global solar radiation on alpine meadow is expressed by a sine

func-tion as

plant material (aboveground live plant portion), and it is expressed as

above-ground plant portion, underabove-ground portion, etc., by respiration of plantsexpressed as linear functions of air temperature (dimensionless).

surface litter or feces, to the soil, and they are functions of air temperature(dimensionless) They and the other coefficients and parameters about pri-mary production are listed in Table 12.2

grazed by Tibetan sheep (Daming, 1993) The highest sheep food required is

F (kJ sheep1 day1)

0.75

follow-ing equations (Damfollow-ing, 1993):

HI

The amount of aboveground litter II, V5, grazed by sheep is

G56

grazed by sheep (Nanlin, 1982)

Table 12.2 Parameters for Energy Flow Equations in the Primary Productivity

Compartment of the Model Refs 5, 3

ME f67 V6The relationship between the rate of heat production as a multiple of basicmetabolism and the environmental temperature (Kleiber, 1961) is expressed as

Then

0.75

grams of digestible organic matter per day

account for greater energy spent in grazing such that (Huang, 1994):

where

10 Converse digestible organic matter intake to liveweight change The

Computer Program

The above process was written in BASIC as a program, Manager ofAlpine Meadow Grazing Ecosystems (MAMGE) The initial values of the

eight compartment values from which the program directly interpolates tocalculate and derive the value of the following function through integration

Test of the Model

The predictions of the model were compared with experimental dataobtained from a cutting trial carried out at the AMERS, as shown in Figure12.2(a) The modeling predicted the energy dynamics of the alpine meadowgrazing ecosystem as shown in Figure 12.2(b) for one year and in Figure12.2(c) for four years The calculated results fit the experimental data well.The model was tested against experimental data from another rotationgrazing trial carried out at AMERS Although the trial was not specificallydesigned for this purpose, the conditions under which it was undertakenseemed to be appropriate for comparison with the model output The graz-ing plan is described in Figure 12.3 Predicted and observed results of thealpine meadow and sheep liveweight are shown in Table 12.4 The energydynamics of aboveground biomass in paddocks of the rotation grazingexperiment are shown in Figures 12.4a–e The liveweight dynamics of sheep

in rotation grazing experiment are shown in Figures 12.4f and g

Sensitivity Analysis of Rotational Grazing Scheme

Sensitivity analysis was applied to the model The effects at 100 and 182

shown in Table 12.5 The effects of a 20% increase or decrease temperature

Table 12.3 Initial Values of the Variables on T  42 (21 April)

A

E B

C D

(b)

2 ) 7500

6500

5500 3000

Figure 12.2 The simulation results of MAMGE (a) The aboveground biomass and

underground biomass of Kobresia humilis meadow Solid line

repre-sents simulated values; Dotted line reprerepre-sents measured values (b) For one year (c) For 4 years A, live roots; B, dead roots; C, amount of above-

ground live portion (G1 ); D, litter I; E, litter II; F, amount of total

than the system on 30 October (t  182 day), and that it is not disturbed

eas-ily by the environmental temperature and global solar energy

A SIMULATED ROTATIONAL GRAZING EXPERIMENT USING THE ALPINE MEADOW GRAZING ECOSYSTEM MODEL

A simulation experiment using MAMGE analyzed different rotationalgrazing schemes for the common alpine meadow pastures at Qing-ZangPlateau, China The model is useful as a planning tool to enable subsequentfield research to focus on significant problems

The simulated rotational grazing experiment included managementvariables that reflect three options that can be chosen by a manager of rota-tional grazing One variable is the number of separate paddocks for rota-tional grazing Two to ten paddocks were included in this simulatedexperiment The second variable is the rotation period, which is the number

Figure 12.3 In a second rotational grazing trial, the meadow was divided into (a) a

SE1were grazed for 7 consecutive days, followed by SA2, SE2for 7 days, etc.,

paddock has ten sheep The initial values of all variables are shown in Table 12.3.

T

A J

1

1

2 3 4

1 2 3 4

c b

1 2 3 4

a

1 2 3 4

of consecutive days of grazing on each paddock For example, if there are twopaddocks and the rotational period is three days, paddock 1 will be grazedthree consecutive days, followed by paddock 2 for three days, followed by

Table 12.5 Sensitivity Analysis of Alpine Meadow Energy Dynamic System

paddock 1 for three days, etc Thirty different rotation periods (from 1 to 30days) were included in this simulation experiment The third variable is thesimulated grazing pressure Simulated grazing pressure refers to the amount

of dry biomass which is available for grazing This variable is difficult tostudy in actual grazing experiments because of variability in the grazingintake among animals However, the model can simulate different specifiedgrazing pressure by simulating different daily dry biomass grazed in kilo-

Two hundred and seventy different simulated grazing schemes (number

(Figure 12.5) The critical grazing pressure of the alpine meadow is defined inthis paper as the event when simulated herbage growth does not provide

Figure 12.5 Thirty-five rotational grazing shemes produced significantly

f(145)6 25.56 kJ m2 day1) than the other 235 schemes The three most ductive specified rotation grazing schemes, three paddocks with a rotationalperiod of seven days, three paddocks with a rotation period of 29 days, andfour paddocks with a rotational period of 14 days produced high accumulated

rotational period of 7 days, had the highest accumulated dry biomass grazed

(J(145) 4250.44 kJ/m2with f(145)6 30.14 kJ m2 day1) The results show thatthe optimal paddock number of rotational grazing is three or four in an alpinemeadow grazing ecosystem This is in accordance with Morley’s (1968) rec-ommendation that the optimal paddock number should be below ten

MAXIMUM POTENTIAL PRODUCTIVITY OF THE

SUMMER-AUTUMN PASTURE UNDER GRAZING

The potential productivity of the summer-autumn pasture (SAP) undergrazing is defined as the total herbage dry matter grazed by sheep over the

opti-mal control theory applied to compartment modeling of energy dynamics inalpine meadow grazing ecosystem (Equations 12.1–12.5), with the produc-tivity being regarded as an objective function to be maximized through opti-mization under the following grazing pressures over the time

Maximum Potential Productivity of the SAP under Grazing Pressure

Finding the maximum productivity of the SAP under constant grazingpressure mathematically as

Jmax t

tf(F16 F46 F56)dt

and the control constraint

Figure 12.5 The accumulated intake for 270 rotational grazing schemes under

critical grazing pressures.

271.382 kJ/m2 The results, given in Figure 12.6, were determined by theRunge-Kutta method (Rao, 1984).

Under Constant Grazing Pressure

J(1) 42

182f16dt

J(1) max 3268.1777 kJ/m2(184.2248 g/m2)

compartments are shown in Figures 12.6(a) and (c)

every compartment are shown in Figures 12.5b–f

Under Variable Grazing Pressure

where is Lagrangian multiplier According to the Pontryagin maximumprinciple,

grazing pressure, the dynamics of optimal grazing pressure are shown inFigures 12.7a–d and Equations 12.9–12.11, while the highest accumulated

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questions seem to be solved by creative research (Noy-Meir, 1976) using asimple mathematical model which represents only the minimum essentialfeatures of the major processes involved, actual questions from concrete pas-tures should be solved by more explicit models, ecosystem modeling, orexpert systems.

The productivity of the alpine meadow grazing ecosystem is alsostrongly affected by climate and soil conditions which are almost uncontrol-lable (Coupland, 1979) Our research purpose for the alpine meadow grazingecosystem is to raise primary and secondary production under conditions ofsustainable development It has been shown in this paper that if we managepasture more effectively, higher plant and animal production can be obtain-able Considering the dearth of information based on which the model isbuilt, it is concluded that the model gives encouragingly accurate predictions

of grass growth and liveweight changes in the alpine meadow grazingmeadow Given a broader data base on initial values in different situations,the model could be used by advisers to help farmers in similar environmentsand to decide the strategies for using their alpine meadows Output of the

800

0 8000

Figure 12.7 The potential productivity of the summer-autumn pasture (SAP) under

variable grazing pressure (a) The optimum variable grazing pressure (b) The maximum accumulated graze (c) The energy dynamics of aboveground biomass portion (d ) The energy dynamics of under-

ground biomass portion.

grazing pressure, the dynamics of optimal grazing pressure are shown inFigures 12. 7a–d and Equations 12. 9? ?12. 11, while the highest... the alpine meadow grazing ecosystem is alsostrongly affected by climate and soil conditions which are almost uncontrol-lable (Coupland, 1979) Our research purpose for the alpine meadow grazingecosystem... changes in the alpine meadow grazingmeadow Given a broader data base on initial values in different situations,the model could be used by advisers to help farmers in similar environmentsand to