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PASTOR: A Technical Coefficient Generator for Pasture and Livestock Systems in the Humid Tropics; version 2.0

A User Guide

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vignet vignet Quantitative Approaches in Systems Analysis

The Quantitative Approaches in Systems Analysis series provides a platform for publication and documentation of simulation models, optimisation programs, Geographic Information Systems (GIS), expert systems, data bases, and utilities for the quantitative analysis of agricultural and environmental systems. The series enables staff members, students and visitors of AB-DLO and PE to publish, beyond the constraints of refereed journal articles, updates of models, extensive data sets used for validation and background material to journal articles. The QASA series thus primarily serves to support peer reviewed articles published elsewhere. The inclusion of listings of programs in an appendix is encouraged.

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Quantitative Approaches in Systems Analysis are issued by the DLO Research Institute for Agrobiology and Soil Fertility (AB-DLO) and The C.T. de Wit Graduate School for Production Ecology (PE). AB-DLO, with locations in Wageningen and Haren, carries out research into plant physiology, soil science and agro-ecology with the aim of improving the quality of soils and agricultural produce and of furthering sustainable production systems. The 'Production Ecology' Graduate School explores options for crop production systems associated with sustainable land use and natural resource management; its activities comprise research on crop production and protection, soil management, and cropping and farming systems.

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Addresses of editorial board (for submitting manuscripts): H.F.M. ten Berge M.K. van Ittersum AB-DLO TPE-WAU P.O. Box 14 Bornsesteeg 47 NL-6700 AA Wageningen NL-6708 PD Wageningen Phone: (+) 31 317.475951 Phone: (+) 31 317.482382 Fax: (+) 31 317.423110 Fax: (+) 31 317.484892 E-mail: [email protected] E-mail: [email protected] PASTOR: A Technical Coefficient Generator for Pasture and Livestock Systems in the Humid Tropics; version 2.0

A User Guide

B.A.M Bouman, A. Nieuwenhuyse & H. Hengsdijk

REPOSA: Research Program on Sustainability in Agriculture Apartado 224-7210, Guápiles, Costa Rica

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Quantitative Approaches in Systems Analysis No. xxx February 1998 CIP-DATA KONINKLIJKE BIBLIOTHEEK, DEN HAAG

B.A.M Bouman, A. Nieuwenhuyse & H. Hengsdijk

PASTOR: A technical coefficient generator for pasture and livestock systems in the humid tropics/ B.A.M Bouman, A. Nieuwenhuyse & H. Hengsdijk. - Wageningen : DLO Research Institute for Agrobiology and Soil Fertility ; Wageningen : The C.T. de Wit Graduate School for Production Ecology. - (Quantitative approaches in systems analysis ; no. xx) ISBN 90-73384-34-6 NUGI 835 Subject headings: technical coefficient / beef cattle ; pasture / humid tropics / Costa Rica

Keywords

Technical Coefficient Generator, Expert System, beef cattle, pasture, sustainability, Costa Rica

Guidelines 'Quantitative Approaches in Systems Analysis'

Manuscripts or suggestions should be submitted to the editorial board (H.F.M. ten Berge, AB-DLO, or M.K. van Ittersum, TPE-WAU). The final version of the manuscripts should be delivered to the editors camera-ready for reproduction. The submission letter should indicate the scope and aim of the manuscript (e.g. to support scientific publications in journals, program manual, educational purposes). The costs of printing and mailing are borne by the authors.

The English language is preferred. Authors are responsible for correct language and lay-out. Overall guidelines for the format of the texts, figures and graphs can be obtained from the publication editor at AB-DLO, or from the PE office:

H. Terburg Th.H. Jetten AB-DLO Secretariat C.T. de Wit Graduate School for Production Ecology P.O. Box 14 Lawickse Allee 13 NL-6700 AA Wageningen NL-6701 AN Wageningen Phone: (+) 31 317.475723 Phone: (+) 31 317.485116 Fax: (+) 31 317.423110 Fax: (+) 31 317.484855 E-mail: [email protected] E-mail: [email protected] Preface

This document is a users guide to the system PASTOR (PASture and livestock technical coefficient generatOR), version 2.0. PASTOR generates technical coefficients for pastures, herds and feed supplementing in cattle systems in the humid tropics. The system was developed in the project REPOSA (Research Programme on Sustainability in Agriculture) in Guápiles, Costa Rica. REPOSA is a cooperation between Wageningen Agricultural University (WAU), the Centre for Research and Education in Tropical Agriculture (CATIE), and the Ministry of Agriculture and Livestock, Costa Rica (MAG). PASTOR is complementary to LUCTOR (Land Use Crop technical coefficient generaTOR; Hengsdijk & Nieuwenhuyse, 1998), a system developed by REPOSA to generate technical coefficients for cropping systems in the North Atlantic Zone of Costa Rica.

The primary goal of PASTOR is to generate technical coefficients for linear programming models to explore sustainable land use options. The system has also been found to be useful as a stand- alone tool for simple cost-benefit analyses of proposed cattle livestock systems. PASTOR was especially developed for cattle livestock systems in the humid tropics using the Northern Atlantic Zone (NAZ) in Costa Rica as case-study. However, the system was set up in a generic manner so that, by adapting input files, users can make PASTOR suitable to other environments as well.

A complete listing of all PASTOR data files as used by REPOSA in the NAZ of Costa Rica is included as appendices to serve as documentation of current and possible alternative beef production systems in the NAZ.

PASTOR 2.0 can be obtained from:

B.A.M Bouman

Until October 1998: REPOSA: Research Program on Sustainability in Agriculture Apartado 224-7210, Guápiles, Costa Rica; Tel (+506) 710 6595; Fax (+506) 710 2327; Email: [email protected]

After October 1998: AB-DLO, P.O. Box 14, NL-6700 AA Wageningen, The Netherlands. Phone: (+) 31 317.475723; Fax: (+) 31 317.423110 ; E-mail [email protected] Table of Contents

Preface

Table of Contents

Summary 1

1 The PASTOR system 3

1.1 Animal Production Systems at a defined Technology 5 1.2 PAsture production Systems at a defined Technology 6 1.2.1 Fertilised pasture 6 1.2.2 Unfertilised pastures 9 1.2.3 Technical coefficients 11 1.3 Feed Acquisition Systems at a defined Technology 12

2 PASTOR structure and operation 13

2.1 File lay-out and model running 13 2.2 Input files 13 2.3 Output files 16 2.4 PASTOR language 18

3 Generating Animal Production Systems (APSTs) 19

3.1 CRIA model 19 3.1.1 Herd characteristics file 20 3.1.2 Herd management file 23 3.1.3 Site file 27 3.2 GORDO model 27 3.2.1 Herd characteristics file 28 3.2.2 Herd management and site file 30 3.3 Special case: reruns 30

4 Generating Pasture Production Systems (PASTs) 31

4.1 PASTOF model 31 4.1.1 Pasture data file 32 4.1.2 Soil data file 40 4.1.3 CAT_CHAR data file 42 4.1.4 Site file 43 4.2 PASTOU model 44 4.2.1 Pasture data file 44 4.2.2 Soil, CAT_CHAR and site data file 50 4.3 Special case: reruns 50

5 Generating Feed Acquisition Systems (FASTs) 52 6 Attribute files 54

7 Error and warning messages 55

References 57

Appendix I: PASTOR input files I-1

I.1 APST input files I-1 I.1.1 CRIAHRD.DAT I-1 I.1.2 CRIAMAN.DAT I-2 I.1.3 GORDHRD.DAT I-4 I.1.4 GORDMAN.DAT I-5 I.2 PAST input files I-7 I.2.1 ESTREL.DAT I-7 I.2.2 BBRIZAN.DAT I-10 I.2.3 TANNER.DAT I-13 I.2.4 NATURAL.DAT I-16 I.2.5 BPINTOI.DAT I-18 I.3 Other input files I-20 I.3.1 SOIL.DAT I-20 I.3.2 SITE.DAT I-21 I.3.3 FEEDS.DAT I-22

Appendix II: PASTOR attribute files I-24

II.1 Materials I-24 II.2 Equipment I-24 II.3 Traction I-25 II.4 Fertiliser I-25 II.5 Pesticide I-25 II.6 Cattle I-26 II.7 Feed I-27 1

Summary

This document is a users guide to the expert system PASTOR (PASture and livestock technical coefficient generatOR), version 2.0. PASTOR generates technical coefficients (TCs) for cattle systems in the humid tropics, using the target-oriented approach. Three components of a cattle system are defined, for which TCs are generated separately by individual models: Animal Production Systems at a defined Technology (APSTs), PASture systems at a defined Technology (PASTs) and Feed Acquisition Systems at a defined Technology (FASTs; feed supplements). For APSTs, separate models exist for cattle breeding and cattle fattening systems. For PASTs separate models exists for fertilised pastures with a user-defined soil nutrient balance and for unfertilised pastures with an ‘open’ soil nutrient balance. Technical coefficients are inputs and outputs of production systems, such as production (pasture yield, meat, milk), costs, labour use, soil nutrient balances, nutrient losses to the environment and pesticide use. PASTOR was especially developed for cattle livestock systems in the humid tropics using the Northern Atlantic Zone (NAZ) in Costa Rica as case-study. However, the system was set up in a generic manner so that, by adapting input files, users can make PASTOR suitable to other environments. Listings of all PASTOR data files are included in the appendices to document current and possible alternative beef production systems in the NAZ of Costa Rica as described and developed by REPOSA. 2

1 The PASTOR system

PASTOR generates technical coefficients for beef cattle livestock systems in the humid tropics. Technical coefficients are inputs and outputs of production systems (Van Ittersum & Rabbinge, 1997; Hengsdijk et al., 1996), and are used in Linear Programming models to explore or optimise land use systems (e.g. Griffith & Zepeda, 1994; Jones, 1989; Nicholson et al., 1994; Hazel & Norton, 1986). Examples of the use of PASTOR-generated technical coefficients in linear programming models are given in Bouman & Nieuwenhuyse (1998) and Bouman et al. (1998). PASTOR can also be used as a stand-alone tool for simple cost-benefit analyses of proposed alternative livestock systems.

A beef cattle system consists of three main components: 1. The herd, generating the marketable products meat and milk, and characterised by certain feed requirements. A herd system entails the management and maintenance of a collection of animals. Since management is explicitly addressed in the form of technology used, the term APST1 is used: Animal Production System at a defined Technology. 2. Pastures supplying feed. Pasture production system entails the growing and management of pasture (i.e. grass, or grass-legume mixtures). Here, the term PAST is used: PASture production system at a defined Technology. 3. Feed supplements providing an additional source of feed. Feed supplementing simply entails a specification of feed supplement options, and is abbreviated here as FAST: Feed Acquisition System at a defined Technology.

For each of these three sub-systems, PASTOR contains separate models that can be run individually (Figure 1.1). Within PASTOR, there is no formal relationship between APSTs, PASTs and FASTs. Generated technical coefficients can be analysed for each sub-system separately, or be integrally analysed in linear programming models (e.g. by equating feed requirements of APSTs to feed supplied by PASTs and FASTs; Bouman & Nieuwenhuyse, 1998).

Technical coefficients are generated using the so-called ‘target oriented’ approach (Van Ittersum & Rabbinge, 1997). This approach entails that target production levels are predefined and that subsequently the amount of required inputs is calculated by PASTOR. The calculation of inputs is based – as far as possible - on knowledge of physical, chemical, physiological and ecological processes involved. When process knowledge is incomplete/absent, calculations are based on expert knowledge, literature data and field observations. In this sense, PASTOR might be called an ‘expert system’. Target production levels may vary from potential production levels to very low levels. In the first case, high external input levels (e.g. in the case of pastures fertilisers, crop protection) will be required, and in the second case, low external input levels are needed. Next to desired production levels, the manner (technology) of production can be specified. For instance, certain operations may be performed with machines or may alternatively be done manually (or using a combination of both). By specifying a number of target production levels and a number of different technologies, PASTOR can generate technical coefficients of a large number of alternative production systems. ‘Classical’ input technical coefficients are the use of resources such as fertilisers, pesticides, machines, labour, and - of course - the total costs of production (using all the required resources). ‘Classical’ output technical coefficients are yields and the economic value of

1 APST, PAST and FAST names were suggested by D.M. Jansen, in analogy to the terminology developed earlier in REPOSA (Jansen & Schipper, 1995; Stoorvogel et al., 1995). 3 the yield. Next to these classical technical coefficients, PASTOR also calculates a number of other technical coefficients called ‘sustainability indicators’ (Bouman et al., 1998). Examples are the soil nutrient balance, losses of nutrients to the environment, and pesticide use.

PASTOR Breeding CRIA APST (herd) Fattening GORDO

Unfertilized PASTOU

PAST (Pastures) Fertilized PASTOF

FAST (Feed SUPP supplement)

Figure 1.1. Schematic presentation of the main components of PASTOR (APST, PAST, FAST) and its models (CRIA and GORDO for APSTs, PASTOU and PASTOF for PASTs, and SUPP for FASTs).

In the following paragraphs, a summary of the scientific background of PASTOR is given for each of the APSTs, PASTs and FASTs components separately. Chapter 2 gives the technical structure and lay-out of PASTOR, explains how to run the models and introduces all input and output files. Chapters 3-5 give detailed explanation on how to steer the generation of the technical coefficients of APSTs (Chapter 3), PASTs (Chapter 4) and FASTs (Chapter 5) by model input parameter values, and gives further explanation on how technical coefficients are calculated. Chapter 6 explains a special set of data files, called attribute files, that contain attribute characteristics of inputs used in the production systems. Chapter 7 mentions some possible error messages that might be obtained by incorrect running of PASTOR and gives some hints on how to remedy these. Finally, the appendices list all input files (model data files and attribute files) that accompany PASTOR 2.0, which serve as documentation of beef cattle production systems as described and developed for the North Atlantic Zone of Costa Rica by REPOSA. 4

1.1 Animal Production Systems at a defined Technology

PASTOR contains two separate models for the calculation of technical coefficients of APSTs (herds), one for cattle breeding, called CRIA (Spanish for ‘breeding’), and one for beef fattening, called GORDO (Spanish for ‘fattening’). The calculated technical coefficients are:

 Production, in terms of meat and milk  Feed requirements, in terms of metabolizable energy, crude protein and phosphorus  Costs of production  Labour required

The exact definitions and units of the technical coefficients are given in Table 2.3.1 (Paragraph 2.3). A breeding system is defined here as a system where calves are bred and subsequently sold at a certain age or live weight. No animals are bought externally. A fattening system is defined here as a system where young animals are bought, fattened for a period of time, and then sold. No animals are bred internally. For both types, the modelled herds are ‘stationary’, which means that there are no dynamics in herd size and composition over the year(s), (Upton, 1989; 1993). Based on a specification of herd structure characteristics, target growth of the animals and target buying/selling strategy, total composition, production and feed requirements of the herd are computed. The (stationary) composition of the herd, i.e. the number and type of animals per age class, is calculated using the method presented by Hengsdijk et al. (1996). The production of the herd is simply obtained by summing the user-specified target live weight gains and milk production over all animals in the herd, using the user-defined buying/selling strategy. Because of market price differentiation, four classes of live weight products are differentiated: i) male and female calves of a breeding system, ii) old cows of breeding and double purpose systems, iii) male animals of fattening system, and iv) male and female animals of double purpose system2. Next to live weight of the herd as ‘output’, the required ‘input’ of live weight is calculated as the weight of bought animals to maintain the herd composition (relevant in fattening systems).

Computations of feed requirements are based on equations for beef cattle as presented by the National Research Council (NRC, 1996), and on NRC (1989) for dairy cattle. Calculations were performed for each animal in the herd according to sex and age group, and for females according to stage of pregnancy and lactation, and then summed to get total herd requirements. The amount of milk produced and consumed internally in the herd is subtracted from these amounts to obtain ‘external’ feed requirements (i.e. that should be met by pasture or feed supplement intake; Hengsdijk et al., 1996). It is noted that in this approach, the source of feed (e.g. pasture, feed supplement) is not taken into account; i.e. the total amounts of metabolizable energy, crude protein and phosphorus are calculated that are needed to sustain the desired target growth without taking efficiency effects of feed composition into account (NRC, 1989). In the current form of CRIA and GORDO, there are no seasonal effects on animal growth and herd composition (stationary approach). The target live weight gains specified by the user are average values for a whole year. Therefore, the calculated feed requirements are uniformly distributed over the year, i.e. monthly feed requirements are calculated that are the same each month of the year. Yearly feed requirements are twelve times the monthly calculated values3.

2 The double purpose system, although not yet implemented as a separate model (such as CRIA and GORDO), already features as separate live weight class in anticipation of future developments in PASTOR. 3 If users want to apply CRIA or GORDO in an environment with seasonality, the models should be run with input data characteristic for each season, and the generated monthly feed requirements should be interpreted as being characteristic for that season. The generated production, cost and labour use technical coefficients should be summed with a weighing 5

The costs and labour requirements of the simulated APSTs are calculated from maintenance and operation specifications provided by the user (e.g. the use of corrals and troughs and the application of inoculations). Costs are expressed as an annuity factor to take account of investment costs in materials with a life span larger than one year. Annuity costs were calculated using the capital recovery factor (Price Gittinger, 1973) with a discount rate as specified by the user. Labour use is expressed in two units: physical labour, and ‘annuity’ labour. Physical labour is just the sum of all labour activities, where labour used in investment activities, such as building a corral, is divided by the life span of the investment activity. Annuity labour is based on the same calculation procedure as for costs: labour used in investment activities is ‘discounted’ into an annuity using the same capital recovery factor as used in the annuity cost calculation. This way, the price of labour can be kept a constant in LP modelling when computing total costs of alternative land use activities (Schipper, 1996).

1.2 PAsture production Systems at a defined Technology

PASTOR contains two separate models for the calculation of technical coefficients of PASTs (pastures), one for fertilised pastures with a ‘user-defined soil nutrient balance, called PASTOF, and one for unfertilised pastures, called PASTOU. The calculated technical coefficients are:

 Production, in terms of dry matter, metabolizable energy, crude protein and phosphorus  Costs of production  Labour required  Sustainability indicators: soil nutrient balances, N losses to the environment, pesticide use  Some fertiliser use specifications

The exact definitions and units of the technical coefficients are given in Table 2.3.2 (Paragraph 2.3).

1.2.1 Fertilised pasture

For fertilised grasses, PASTOF calculates technical coefficients for production techniques with a pre-defined soil nutrient balance, i.e. no more nitrogen (N), potassium (K) and phosphorus (P) are allowed to be removed from the soil than a pre-defined quantity by the user. For true sustainable and stable pasture systems, the soil nutrient balance should be zero (Hengsdijk et al., 1996). Variables that define alternative pasture production systems are grass species, soil type, stocking rate and fertiliser level. Stocking rate is explicitly taken into account because of its effect on pasture production (Ibrahim, 1994; Hernandez et al, 1995) and on the soil nutrient balance. The procedure for calculating the technical coefficients is quite complex but involves, schematically, the following steps (Figure 1.2). First, for each grass species, upper and lower production boundaries should be estimated for the soil types under study in terms of biomass and content of metabolizable energy, crude protein and phosphorus (user defined input). The upper boundary is the maximum attainable production with no nutrient constraints (Bouman et al., 1996), and the lower boundary is the minimum production level supposedly attained on exhausted soils where the grass just manages to

factor per season to get year totals. 6

Management: Grass charact. Soil charact. Climate stocking rate

Attainable Soil-limited Attainable biomass Nutrient production production on offer requirements on best soil Management: Manure allowed mining Deposition Labour use Fixation

Costs XXXXX : input data Actual biomass Fertilizer and nutrients : generated TC Nutrient loss requirements provided : intermediae Biocide use variables Soil charact. : model (nutrient Management: Management: loss fractions) : flow of information weed control fert. application fert. application

Figure 1.2. Schematic representation of calculation procedure of technical coefficients by PASTOF for fertilised pastures.

survive. On the basis of the maximum attainable production, PASTOF calculates attainable feed on offer as function of a range of (user-defined) stocking rates. With increasing stocking rate, less of the pasture biomass is available for uptake because of trampling and deposition of faeces and urine (Deenen, 1994; Van der Ven, 1992). For each feed level thus obtained (as function of grass species, soil type and stocking rate), the attainable amount of biomass and nutrients that may be removed by the grazing stock is calculated. The supposedly grazing stock associated with each stocking rate has a certain feed requirement and manure and urine production (which may be calculated by the CRIA or GORDO models, but not necessarily!), based on the assumption of a fixed target growth rate. A soil nutrient balance is calculated using an adapted version of the model presented by Stoorvogel (1993). This model determines the soil nutrient balance, where the user can specify the amount of nutrient mining (depletion of soil nutrient stock) that is allowed. The calculation of the soil nutrient balance is based on estimates/calculations for all inputs, namely atmospheric deposition, fixation by micro-organisms, weathering, manure and urine (from the grazing stock), and all outputs, namely the attainable amount that may be removed by grazing and losses by erosion, leaching, volatalization, denitrification/nitrification, and fixation (for P). A negative balance below the allowed mining level indicates the amount of fertiliser that is needed to sustain the attainable amount of biomass that may be removed (Hengsdijk et al., 1996). Next, a user- defined range of fertiliser application levels is specified, ranging from 0-100% of the amount needed to sustain attainable production. Gross fertiliser input is calculated from the required net amount, by taking account of loss fractions specified by the user per nutrient type (Hengsdijk et al., 1996). Next, nutrient concentrations in the biomass of the pasture are calculated for each fertiliser level by linear interpolation between the minimum and maximum production points given earlier (Figure 1.3), using the total amount of nutrients available for growth. With these concentrations, the soil nutrient balance is again invoked for each fertiliser level, and new amounts of feed on offer are calculated by matching all inputs with all outputs. 7

C P % 1 3 . 0 0

1 2 . 0 0

1 1 . 0 0

1 0 . 0 0

9 . 0 0

8 . 0 0

7 . 0 0

6 . 0 0

5 . 0 0 0 5 0 0 1 0 0 0 1 5 0 0 2 0 0 0

N A p p l i c a t i o n ( k g / h a )

Figure 1.3. Crude protein content (CP%) as function of N applied (in form of fertiliser, manure and urinary N). Drawn line is simulation by PASTOF for fertilised Cynodon nlemfuensis (Estrella) on fertile well drained soil, points are observed data in humid tropical environments: circles are mean values of Pangola grass and dots are observed mean values over a large number of species (source of observed data: Vicente-Chandler, 1974, as reported by Crowder & Chenda, 1982.

ME (Mcal/ha) 60000

30000 II

20000 I

0 0 2 4 6 8 10 Stocking rate (AU/ha)

Figure 1.4. Attainable feed on offer (black diamonds) and feed requirements (white diamonds) in terms of metabolizable energy (ME) versus stocking rate, for fertilised Cynodon nlemfuensis (Estrella) on fertile well drained soil. In section I, attainable feed on offer exceeds the intake requirements of the stock. In grazing only systems, the actual feed intake is limited by the ‘white diamond line’ ; in grazing plus mowing systems, the difference between the black and the white diamonds is supposed to be removed by mowing. In section II, the feed requirements of the stock are higher than what the pasture can offer, and supplements are supposed to be used to feed the stock. 8

E.g. in case of 0% fertiliser application, the amount of feed removed by grazing can not be higher than the amount that is produced with external inputs from atmospheric deposition, fixation by micro-organisms, weathering and faeces and urine only (minimum level). In case of 100% fertiliser gift, the amount that can be removed by grazing equals the attainable production.

There are two options of pasture grazing implemented that are governed by the user, i) pure grazing systems where pasture is only removed by the grazing stock, and ii) mixed grazing-mowing systems, where pastures are also occasionally mown. In the grazing only system, no more biomass can be removed than is eaten by the cattle, i.e. the actual amount of feed removed by the cattle is the minimum of the amount of feed on offer and the cattle intake requirements of the grazing stock. (Figure 1.4). In mixed grazing-mowing systems, there may exist a surplus of biomass on offer compared to cattle intake requirements, which is supposed to be removed from the pasture by mowing. In both systems, when cattle intake requirements exceed the amount on offer, the shortage is supposed to be balanced by feed supplements, thus constituting an alternative source of external nutrients to the pasture.

Costs and labour use involve material inputs such as fences, tools and herbicides, and operations such as establishment, weeding, fertiliser application (if any) and maintenance.

Input data and simulated output of PASTOF were checked against well-established agronomic knowledge (e.g. Figure 1.6) and field data from experiments in tropical humid climates reported in literature (e.g. Figure 1.3 and 1.5), and were carefully reviewed by a number of outside experts (e.g. CATIE and MAG experts).

1.2.2 Unfertilised pastures

For unfertilised pastures, the calculation procedures of PASTOU are relatively simple. Since no fertiliser is applied by definition, actual feed on offer is simply specified by the user as function of a range of feasible stocking rates. In the case of grass-legume mixtures, the soil nutrient balance model takes account of the additional input of N by the legume. The soil nutrient balance is merely the result of book-keeping of all nutrient inputs and outputs (Hengsdijk et al., 1996), and may be zero or negative. Negative soil nutrient balances indicate that the modelled production is not sustainable, i.e. the user-supplied yield levels can not be maintained on the long run. Many actual production systems in humid tropical environments are unsustainable in this sense (Bouman & Nieuwenhuyse, 1998). The calculation procedure for costs and labour requirements is the same as for the fertilised pastures. 9

2 0 D r y m a tte r ( t/ h a ) 1 8 m m m a tte r m a tte r

1 4 2 1 2 1 1 0

0 0 1 0 0 2 0 0 3 0 0 4 0 0 5 0 0 6 0 0 N f e r tiliz e r a p p lic a tio n ( k g / h a )

Figure 1.5. PASTOF simulated (drawn lines) and observed (markers with dotted lines) yield of fertilised Cynodon nlemfuensis (Estrella) on a fertile well-drained soil versus fertiliser-N application. Drawn line 1 was simulated with 40% N uptake efficiency; line 2 with 50% (estimated range in actual values). Experimental data were for a 14-day (diamonds), 21-day (squares) and 28-day (pyramids) grazing rotation. Experimental data from Salazar, 1977.

D r y m a t t e r y ie l d ( * 1 0 k g / h a ) 2 0 0 0

1 5 0 0

1 0 0 0

5 0 0 N a p p li c a t io n ( k g / h a ) N y i e l d ( k g / h a ) 0 - 1 0 0 0 - 8 0 0 - 6 0 0 - 4 0 0 - 2 0 0 0 2 0 0 4 0 0 6 0 0

- 5 0 0

- 1 0 0 0 N a p p l i c a t io n ( k g / h a ) - 1 5 0 0

Figure 1.6. Three quadrant diagram of PASTOF-simulated yield, fertiliser-N application and N yield for fertilised Cynodon nlemfuensis (Estrella) on a fertile well-drained soil. The solid line was simulated with a stocking rate of 0.25 AU ha-1, the broken line with 1 AU ha-1, and the large dotted line with 3 AU ha-1 . 10

1.2.3 Technical coefficients

Production The calculated production technical coefficients are ‘removed’ amounts (yield) of dry matter, metabolisable energy, crude protein and phosphorus, both on monthly and on yearly basis. The ’removed’ amount is either the amount eaten by the grazing stock, when pastures are grazed only, or the combination of the amount eaten plus the amount removed by cutting. This choice is governed by input control by the user (see Chapter 4). The pasture may not deliver sufficient removable feed to feed the grazing stock (in which case it is assumed that feed supplements are given to maintain the grazing stock at its fixed growth rate). Therefore, two coefficients express the difference between ‘removable’ feed and feed demand by the stock in terms of metabolisable energy (DMEHRD, Table 2.3.2) and crude protein (DCPHRD, Table 2.3.2), (these two being the most limiting parameters in terms of animal feed requirement). In the case of grazed pastures only, these parameters can be negative or zero only. In the case of the combination of grazing with cutting, these parameters may take negative as well as positive values.

Sustainability. Soil nutrient balances are given for nitrogen (N), phosphorus (P) and potassium (K). N losses to the environment are expressed in terms of leaching losses, volatilisation losses and denitrification losses. Volatilisation of N via ammoniac results in acid rain; leached N is a potential soil water pollutant; and denitrification/nitrification losses of N via N2O and NO add to the greenhouse gas effect (Keller et al., 1993). Two indicators are related to pesticide use: an ordinal so-called Pesticide Environmental Impact Index (PEII; Jansen et al., 19954), and the total amount of active ingredients used (PAI). Even though the latter is relatively easy to monitor and much used, it is not a particularly appropriate indicator as active ingredients differ considerably with regard to their environmental impact (Van der Werf, 1996). The PEII takes into account not only active ingredients used but also their degree of toxicity and their persistence in the environment. Both PEII and PAI are summed over all pesticide inputs applied.

Fertiliser use Some technical coefficients are generated that illustrate the use and some losses of N, P and K fertiliser applied. These concern gross N, P and K input, the yearly application frequency, the gift size per application, the fertiliser application time, and N, P and K leaching losses (see Table 2.3.2).

Labour use and costs Labour use and costs of production are calculated the same way as explained for APSTs (Paragraph 1.1).

4 Jansen et al., 1995, used the term Biocide Index (BILU). 11

1.3 Feed Acquisition Systems at a defined Technology

The model SUPP of PASTOR calculates technical coefficients for FASTs:

 Feed provided, in terms of metabolizable energy, crude protein and phosphorus  Costs of application  Labour required

The exact definitions and units of the technical coefficients are given in Table 2.3.3 (Paragraph 2.3). The SUPP model is very simple and merely ‘converts’ data supplied by the user in input files into the same format as that used for the technical coefficients of the other systems (i.e. APSTs and PASTs). Labour use and costs of application are calculated the same way as explained for APSTs (Paragraph 1.1). 12

2 PASTOR structure and operation

2.1 File lay-out and model running

PASTOR 2.0 consists of models (executable Fortran files) with corresponding input files, organised in a certain directory structure (Figure 2.1). There are five independent models to generate technical coefficients for alternative APSTs, PASTs and FASTs separately:

APST:  CRIA for cattle breeding systems  GORDO for cattle fattening systems

PAST:  PASTOF for fertilised pastures with a user-defined soil nutrient balance  PASTOU for unfertilised pastures with an ‘open’ soil nutrient balance

FAST:  SUPP for feed supplements

Each model is run by giving the command ‘MODEL.EXE’ (where MODEL stands for the name of the model to be run, i.e. CRIA, GORDO,…, SUPP) in the appropiate sub-directory where the model is located (Figure 2.1). Each model needs a set of input files as specified in the CONTROL.DAT file – and optionally in the RERUNS.DAT file, see Paragraph 2.2 - that accompanies each model. The PASTOR models create output files that contain the generated technical coefficients, and which are stored in a separate sub-directory (PASTOR\FILE_OUT; Figure 2.1). The names of the output files are specified in the CONTROL.DAT file accompanying each model. How to exactly run and control each model of PASTOR is explained in detail in Chapters 3-5.

2.2 Input files

The input files given in Figure 2.1 accompany PASTOR 2.0. They characterise systems applicable to the North Atlantic Zone of Costa Rica as collected in the REPOSA project (Bouman et al., 1998). There are two types of input files: model data files (*.DAT files) and so-called attribute files (*.ATF files), Table 2.1. In model data files, the user specifies characteristics and management of the system to be modelled (APST, PAST or FAST). For instance, for the PAST models PASTOF and PASTOU, the pasture input file contains data that characterise the type of pasture to be modelled (e.g. attainable production level, content of nutrients and metabolizable energy) and the way the pasture is managed (e.g. amount of fertiliser, manner of weeding). In model data files, reference is made to inputs that are used in the management, such as materials, pesticides, equipments or fertilisers. These inputs are listed with their characteristics (attributes) in the so-called attribute files. Attributes are e.g. cost price (or rent price), unit of measure and toxicity (in the case of pesticides). In principle, all model data and attribute files are self-explanatory, i.e. all parameters that need to be 13

PASTOR MOD_CRIA CRIA.EXE CONTROL.DAT (RERUNS.DAT)

MOD_GORD GORDO.EXE CONTROL.DAT (RERUNS.DAT)

MOD_PASF PASTOF.EXE CONTROL.DAT (RERUNS.DAT)

MOD_PASU PASTOU.EXE CONTROL.DAT (RERUNS.DAT)

MOD_SUPP SUPP.EXE CONTROL.DAT

FILE_IN HERD CRIAHRD.DAT GORDHRD.DAT CRIAMAN.DAT GORDMAN.DAT

PASTO ESTREL.DAT BBRIZAN.DAT TANNER.DAT NATURAL.DAT BPINTOI.DAT

FEED FEEDS.DAT SOIL.DAT SITE.DAT CAT_CHAR.DAT

FILE_ATR MATER.ATF EQUIP.ATF TRACTION.ATF FERT.ATF BIOCID.ATF CATTLE.ATF FEEDS.ATF

FILE_OUT *.PRN

Figure 2.1. Directory structure and files of PASTOR. Names in boxes are sub-directories, others are executable programs (*.EXE), run control files (CONTROL.DAT, RERUNS.DAT), input files (*.DAT), attribute files (*ATF) and output files (*.PRN) 14

Table 2.1. Model data and attribute files used by PASTOR 2.0

Directory File name Explanation FILE_IN\HERD CRIAHRD.DAT Herd characteristics for breeding herd GORDHRD.DAT Herd characteristics for fattening herd CRIAMAN.DAT Management characteristics for breeding herd GORDMAN.DAT Management characteristics for fattening herd FILE_IN\PASTO ESTREL.DAT Characteristics and management of Estrella grass BBRIZAN.DAT Characteristics and management of Brachiaria brizanta grass TANNER.DAT Characteristics and management of Tanner grass NATURAL.DAT Characteristics and management of ‘Natural’ grass BPINTOI.DAT Characteristics and management of Brachiaria brizanta with Arachis pintoi legume FILE_IN\FEED FEEDS.DAT Selection of feed supplements

FILE_IN SOIL.DAT Soil characteristics SITE.DAT Site characteristics CAT_CHAR.DAT Properties of grazing stock on pasture (optionally produced by APST model CRIA)

FILE_ATR BIOCID.ATF Properties of pesticides CATTLE.ATF Properties of specific inputs for cattle maintenance EQUIP.ATF Properties of equipments FEEDS.ATF Properties of feed supplements FERT.ATF Properties of fertilisers MATER.ATF Properties of materials TRACTION.ATF Properties of types of traction

supplied (quantified) are explained and their units given in the files themselves. All input files are in ASCII and can be changed or updated by the user. The standard input files of PASTOR 2.0 are listed in Table 2.1.

Other input files are the CONTROL.DAT and the optional RERUNS.DAT files that accompany each of the PASTOR models. Thus, the sub-directories MOD_CRIA, MOD_GORD, MOD_PASF, MOD_PASU and MOD_SUPP all contain an executable program (*.EXE) and their accompanying CONTROL.DAT and (optional) RERUNS.DAT file. CONTROL.DAT is used to specify the various model data and attribute files for the model. The names of these files in CONTROL.DAT may be changed by the user. For instance, the user that runs the model PASTOF for fertilised grasslands specifies the name of the grass file (e.g. ESTREL.DAT, TANNER.DAT or BBRIZAN.DAT) in the CONTROL.DAT file in the same directory. Of course, a user can also make a completely new input file, and specify this file name in CONTROL.DAT. All models can make so-called reruns. In a rerun, the program is repeatedly executed with different input files (or different parameter values). The name of the input file needs to be given in the RERUNS.DAT file. For instance, the PASTOF model can be run for all three available grass types by specifying ESTREL.DAT in the CONTROL.DAT file, and by specifying TANNER.DAT and BBRIZAN.DAT in the RERUNS.DAT file. When the RERUNS.DAT file is not present, the model is only executed one time (with the file specifications as in CONTROL.DAT). See Van Kraalingen (1995) for more details on using the rerun facility, plus the relevant paragraphs in Chapters 3-5. 15

2.3 Output files

The PASTOR models produce a number of output files that contain the generated technical coefficients. Table 2.3.1 lists and explains the files produced by the APST models CRIA and GORDO, Table 2.3.2 those produced by the PAST models PASTOF and PASTOU, and Table 2.3.3 those by the FAST model SUPP.

Table 2.3.1 Output files produced by CRIA (CRIA*) and GORDO (GORD*) herd models with an explanation of the technical coefficients (TCs) they contain. All TCs are on yearly basis unless otherwise specified.

File name TC Explanation Unit CRIAP, GORDP LWCY Live weight of sold male and female calves in breeding system kg/herd/y LWCO Live weight of sold old cows in breeding and double-purpose kg/herd/y system LWEY Live weight of sold male calves in fattening system kg/herd/y LWDY Live weight of sold male and female calves in double-purpose kg/herd/y system MLK Milk produced kg/herd/y

CRIALC, GORDLC HLABP Total physical labour needed for herd, per year d/herd/y HLABA Total ‘annuity’ labour needed for herd, per year d/herd/y HCOSTS Total annuity costs for herd colon/herd/y

CRIALM, GORDLM HLABP Total physical labour needed for herd, per month d/herd/mnth HLABA Total ‘annuity’ labour needed for herd, per month d/herd/mnth

CRIAR, GORDR HME Monthly required metabolizable energy Mcal/herd/mnth HCP Monthly required crude protein kg/herd/mnth HP Monthly required phosphorus kg/herd/mnth HSIZE Herd size in animals no HSAU Herd size in animal units (1 AU = 400 kg) no

CRIAIN, GORDIN LWCINP Inputted (bought) weight of animals (calves) kg/herd/y

CAT_CHAR* - No TCs generated, but general information (CRIA model only) -

*: the file CAT_CHAR does not contain technical coefficients, but general information on the characteristics of the simulated herd of a breeding system (thus produced by CRIA only). This file may optionally be used as input data file for the pasture models PASTOF and PASTOU (see Chapter 4). 16

Table 2.3.2 Output files produced by PASTOF (PFER*) and PASTOU (PUNF*) pasture models with an explanation of the technical coefficients (TCs) they contain. All TCs are on yearly basis unless otherwise specified.

File TC Explanation Unit PFERPM, PUNFPM SDMN Monthly supplied dry matter kg/ha/mnth HME Monthly supplied metabolizable Energy (ME) Mcal/ha/mnth HCP Monthly supplied crude Protein kg/ha/mnth HP Monthly supplied phosphorus kg/ha/mnth SR Stocking rate AU/ha DMEHRD Supplied ME by pasture - eaten ME by herd Mcal/ha/mnth DCPHRD Supplied CP by pasture - eaten CP by herd kg/ha/mnth

PFERPY, PUNFPY SDMN Yearly supplied dry matter kg/ha/y HME Yearly supplied metabolizable Energy (ME) Mcal/ha/y HCP Yearly supplied crude Protein kg/ha/y HP Yearly supplied phosphorus kg/ha/y SR Stocking rate AU/ha DMEHRD Yearly supplied ME by pasture - eaten ME by herd Mcal/ha/y DCPHRD Yearly supplied CP by pasture - eaten CP by herd kg/ha/mnth

PFERLM, PUNFLM GLABP Total monthly physical labour required by pasture d/mnth GLABA Total monthly ‘annuity’ labour required by pasture d/mnth

PFERLC, PUNFLC GLABP Total yearly physical labour required by pasture d/y GLABA Total yearly ‘annuity’ labour required by pasture d/y COST Total annuity costs for pasture production colon/ha/y COSTEST Annuity costs for pasture establishment colon/ha/y COSTBIO Annuity costs for herbicides, pesticides etc. colon/ha/y COSTFET Annuity costs for fertiliser colon/ha/y COSTOP Annuity costs for various materials used in operations colon/ha/y

PFERS, PUNFS NBAL Soil N balance kg/ha/y PBAL Soil P balance kg/ha/y KBAL Soil K balance kg/ha/y NLEA N leached kg/ha/y NVOL N volatilised kg/ha/y NDEN N denitrified kg/ha/y PEII Pesticide Environmental Impact Index - PAI Amount of active ingredients of pesticides applied kg/ha/y

PFERX, PUNFX FIN Gross fertiliser N input kg/ha/y FIP Gross fertiliser P input kg/ha/y FIK Gross fertiliser K input kg/ha/y FFREQ Fertiliser gift frequency no/ha/y FSGIFT Fertiliser gift size kg/ha/y FAPDRS Fertiliser application duration h/ha NLEA N leached kg/ha/y PLEA P leached kg/ha/y KLEA K leached kg/ha/y

PFERCOM, PUNFCOM - A list of generated alternative PASTs - 17

Table 2.3.3 Output files produced by SUPP feed supplement model with an explanation of the technical coefficients (TCs) they contain. All TCs are per kilogram applied feed supplement.

File TC Explanation Unit FEEDP HME Supplied metabolizable Energy in feed supplement Mcal/kg HCP Supplied crude Protein in feed supplement kg/kg HP Supplied phosphorus in feed supplement kg/kg

FEEDLC FLABP Total physical labour needed for application of feed supplement d/kg FLABA Labour ‘annuity’ labour needed for application of feed supplement d/kg FCOST Annuity costs for application of feed supplement colon/kg

The format of all output files (except CAT_CAR.DAT; see Chapter 3) is designed for easy reading by linear programming models programmed in GAMS (Brooke et al., 1992)5. The files are standard ASCII, and data columns are space-separated. Each output file contains a header explaining the technical coefficients in the columns. The lines of the headers begin with an asterix so that they are skipped while reading by GAMS (and other Fortran) programs.

2.4 PASTOR language

PASTOR is programmed in the language FORTRAN77. Use was made of a special modelling structure as developed for crop simulation, called FSE (Fortran simulation Environment; van Kraalingen, 1995), and of a set of Fortran utilities called TTUTIL (Rappoldt & Van Kraalingen, 1990). During development, guidelines for software quality control as under development by AB- DLO (Van Kraalingen, pers. comm.) have been applied as much as possible. This document describes the use of the Fortran executable files; the source code of PASTOR is available on request by the authors. PASTOR was compiled and linked on a 486 DOS Personal Computer, and should run on any 486 PC - or higher - operating under DOS.

5 The PASTOF and PASTOU models may also produce output files suitable for reading by the Century and the DNDC simulation models. This option, governed by the user in the CONTROL.DAT files, falls outside the scope of this manual. 18

3 Generating Animal Production Systems (APSTs)

The models to generate animal production systems (APSTs) are run by giving the *.EXE command in the appropriate subdirectory, i.e. CRAI.EXE for breeding herds in the PASTOR\CRIA_MOD sub- directory, or GORDO.EXE in the PASTOR\GORD_MOD sub-directory. In the following paragraphs, the control over executing the CRIA and GORDO models is explained in detail.

3.1 CRIA model

In CONTROL.DAT (in the sub-directory MOD_CRIA), the required model input and attribute files of the CRIA model for breeding herds are specified:

*************************** CONTROL.DAT *********************** * Control file for CRIA model * * PASTOR 2.0 * *************************************************************** * Detailed output control parameter: * 'Y' means that detailed data are written to file RES.DAT * 'N' means that no RES.DAT file is produced (for large reruns!) OUTPUT = 'N'

* FILEI0 Input file with financial data * FILEI1 Input file with herd data * FILEI2 Input file with ..... data * FILEI3 Input file with ..... data * FILEI4-8 Attribute input files

FILEI0 = 'C:\PASTOR\FILE_IN\SITE.DAT' FILEI1 = 'C:\PASTOR\FILE_IN\HERD\CRIAHRD.DAT' FILEI2 = 'C:\PASTOR\FILE_IN\HERD\CRIAMAN.DAT' FILEI3 = 'C:\PASTOR\FILE_ATR\MATER.ATF' FILEI4 = 'C:\PASTOR\FILE_ATR\CATTLE.ATF' FILEI5 = 'C:\PASTOR\FILE_ATR\FEEDS.ATF'

* Output files * FILEO1 Monthly feed requirements * FILEO2 Herd products ('yields') * FILEO3 Yearly labour req. plus costs for herd * FILEO4 Monthly labour req. for herd * FILEO6 Various data * FILEO8 Herd animal weight input

FILEO1 = 'C:\PASTOR\FILE_OUT\CRIAR.PRN' FILEO2 = 'C:\PASTOR\FILE_OUT\CRIAP.PRN' FILEO3 = 'C:\PASTOR\FILE_OUT\CRIALC.PRN' FILEO4 = 'C:\PASTOR\FILE_OUT\CRIALM.PRN' 19

FILEO6 = 'C:\PASTOR\FILE_IN\CAT_CHAR.DAT' FILEO8 = 'C:\PASTOR\FILE_OUT\CRIAIN.PRN'

The model input and attribute files needed are specified at the variables FILEI0-5. Note that, beside the file name, the complete path of the sub-directory where the files are stored is given. Users may change the names of the input files when they have created their own input files: FILEI0 contains site-characteristics; FILEI1 specifies the name of a file that contains characteristics of the herd to be modelled; FILEI2 contains the management of the herd. The site file contains so-called ‘site’ data, in PASTOR 2.0 only rate of interest and work hours in a day, and is also used by the other models of PASTOR. The herd characteristics, herd management and site file are explained in detail in the following paragraphs

Attribute files (FILEI3-5) are explained in Chapter 6.The names of the attribute files should not be changed by the user.

The names of the output files are given under the variables FILEO1-8. These names are the same as given in Table 2.3.1, but may be changed by the user. Next to these ‘standard’ output files indicated at the FILEO variables, CRIA provides an option to produce detailed output that specifies the herd structure, e.g. animal numbers and weights per age class. This file is called RES.DAT, and will be produced when the OUTPUT variable is put to ‘Y’. Be default, this variable is put to ‘N’ because RES.DAT can become quite large when making reruns. The output file specified under FILEO6, CAT_CHAR.DAT, contains summary characteristics of the simulated herd (herd size, feed requirements, outputs, manure production). This file may be used as input file for the pasture models PASTOF and PASTOU, see Chapter 4.

3.1.1 Herd characteristics file

Input parameters that characterise the structure, target selling strategy and target growth of the breeding herd to be modelled are specified in the so-called herd characteristics file. The parameters of this file are explained here, using the file CRIAHRD.DAT for a breeding herd in the North Atlantic Zone (NAZ) of Costa Rica as example. A complete listing of CRIAHRD.DAT is given in Appendix 1.1.1

The parameter MAINK specifies the manner in which the herd is supposedly fed, and entails a correction factor for maintenance energy required to support grazing6 (real). The following options may be selected: *MAINK = 1.0: for stable-fed *MAINK = 1.1: for good pasture *MAINK = 1.2: for sparse pasture MAINK = 1.2

A one-letter code is given that serves to ‘recognise’ the herd type that was modelled in the output files (character). E.g.: HCODE = 'B'

6 In truth, MAINK is a management characteristic 20

The size of the herd is given in total number of animals (i.e. calves, steers and cows all count as one animal), (integer): HSIZE = 50

The herd size is combined in CRIA with the one-letter code HCODE to produce a unique identification number for the herd under consideration. For this identification number, the actual herd number is increased with 100 for ‘programming’ reasons. Thus, in this example, the herd identification number will be B150 (HCODE followed by 100+HSIZE). The herd identification number is written as first column in all output files.

The ‘breed’ - or type - of animals is specified by a size/weight indication for females and males separately. This identification is used in the some of the calculation of feed requirements (NRC, 1989; p 74). The following options may be selected: *ITYPEF = 1: female, large breed; max weight is 800 kg *ITYPEF = 2: female, small breed; max weight is 600 kg *ITYPEM = 3: male, large breed; max weight is 1000 kg *ITYPEM = 4: male, small breed; max weight is 800 kg ITYPEF = 1 ITYPEM = 3

For the calculation of maintenance energy requirements, three parameters relating to breed and weight specifications should be given (NRC, 1996; p115-116): A breed effect on maintenance energy requirements (NRC, 1996; p 115). E.g. BE = 0.90; for Brahman and Nellore

Shrunk Relative Weight (NRC, 1996; p 116), e.g.: *SRW = 435. ; kg for animals finishing at trace marbling (25.2% body fat) *SRW = 462. ; kg for animals finishing at slight marbling (26.8% body fat) *SRW = 478. ; kg for animals finishing at small marbling (28% body fat) and replacement heifers SRW = 435. Final shrunk body weight at maturity (typically 0.96 times full final weight): FSBW = 550.

The maximum age of the reproductive female animals is given in years: (year) (integer; bounded by 0 and 20): IAMAX = 11

The live weight of animals at birth is given in kg (real): LWB = 32.

The age of selling of calves (called ‘surplus’) is specified in months for male and female calves separately (month) (real). The value of this parameter must lie between 0 (no negative ages!) and 12 times the maximum age IAMAX as specified above (calves can not be sold after their maximum age). For male calves: ASMS = 8.

For female calves: ASFS = 8. 21

The target growth rates of the animals are specified per age class. These targets are set by the user, and CRIA subsequently calculates the feed requirements necessary to accomplish these targets. Of course, there is a relationship with the management of the herd. For instance, high target growth rates should be accompanied by ‘good’ management as specified in the herd management file (e.g. good care-taking, sufficient inoculations etc.), Paragraph 3.1.2. The target growth rates for males are specified for age 0-1 years (LWGM0), age 1-2 years (LWGM1), age 2-4 years (LWGM2), and after 4 years of age (LWGM3). (kg/day) (real): LWGM0 = 0.65 LWGM1 = 0.45 LWGM2 = 0.25 LWGM3 = 0.

The target growth rates for females are specified for age 0-1 years (LWGF0), age 1-2 years (LWGF1), age 2-4 years (LWGF2), and after 4 years of age (LWGF3). (kg/day) (real): LWGF0 = 0.52 LWGF1 = 0.36 LWGF2 = 0.135 LWGF3 = 0.

The mortality rate is specified as fraction for both males and females together, for age class 0-1 years (MRATE0), age class 1-2 years (MRATE1), and after age of 2 years (MRATE). (-) (real, bounded by -0 and 0.99) MRATE0 = 0.1 MRATE1 = 0.02 MRATE = 0.01

The abortion rate is specified for both males and female together (real, bounded by -0 and 0.99): AR = 0.0

The first age at which reproductive female animals start calving, in months (month) (real; higher than 12. and lower than 60. months): AFC = 31.

The calving interval (from birth to birth) of reproductive females, in months (month) (real; higher than 0): CI = 14.

The duration of lactation is the period during and after pregnancy that the reproductive female gives milk (month) (real; for reasons of calculation procedures given by NRC (1989), DLAC should be smaller than the calving interval CI minus two months): DLAC = 8.

The duration of the pregnancy in months (month) (real; should be smaller than the calving interval CI): DPREG = 9.

The daily amount of milk produced during lactation (kg/d) (real; bounded by 0. and 100.): MILK = 3.5 22

A fraction of the daily milk production may be used for human consumption (selling, own consumption), as for example in double purpose systems. For pure breeding systems, this value should be set to 0. (-) (real; bounded by 0. and 1.): FMLKH = 0.

Some characteristics of the milk: Percentage milk fat (%) (real; bounded by 0. and 10.): FAT = 4.5 Specific weight of milk (kg/l) (real; bounded by 1. and 1.1): SWMILK = 1.03

Finally, a factor should be given that ‘scales’ the energy concentration of the diet fed according to NRC (1989) assumptions, with a suggested range from 0.95 - 1.05. (real; bounded by 0.9-1.1). It is suggested to leave this value at 1., unless strong evidence exists to change this value. FEDNRC = 1.

3.1.2 Herd management file

Input parameters that characterise the management strategy of the herd are specified in a so-called herd management file, and are used by CRIA to calculate costs and labour requirements. The parameters of this file are explained here using the file CRIAMAN.DAT DAT for a breeding herd in the North Atlantic Zone of Costa Rica as example. A complete listing of CRIAMAN.DAT is given in Appendix 1.1.2. In the herd management file, reference is made to ‘items’ that are specified in so- called attribute files. Attribute files are explained in Chapter 6. A complete listing of all attribute files is given in Appendix II.

HERD SIZE DEFINITION

For management and maintenance of a herd, necessary inputs are generally herd-size dependent. Therefore, a generic method was developed in which management is specified for various herd size classes (HRDCLAS) in the herd management file. The actual desired herd size (HSIZE) is inputted by the user in the herd characteristics file (see above, Paragraph 3.1.1). The CRIA model reads this actually desired herd size from the herd characteristics file, and retrieves the management and maintenance data for the appropriate herd size class. The definition of the herd size classes in the herd management file is as follows: *HRDCLAS Herd size class (number) (integer) *HRDMIN Minimum number of animals in the class (number) (INTEGER) *HRDMAX Maximum number of animals in the class (number) (INTEGER) HRDCLAS HRDMIN HRDMAX 1 1 10 2 11 30 3 31 60 4 61 100 The CRIA model checks that the ranges of the herd size classes are ‘unique’ and do not overlap. The user can change the values of HRDMIN and HRDMAX, and increase or decrease the number of rows (minimum of one row, maximum of 10). However, whenever reference is made to herd classes in the rest of the input file, these class references should be the same as given here (i.e. 23 the values of the parameters HRDCLAS, CRCLASS, MTCLASS, T1CLASS, T2CLASS, T3CLASS, CHCLASS, CMCLASS and I2CLASS should all be the same).

MATERIALS USED

Next, for each defined herd size class, input materials should be given. There is a fixed input section for a corral and for troughs, and one general section in which up to three types of inputs can be defined. Each input item should be selected from the attribute file in which materials are specified, i.e. the MATER.ATF file. When a user wants to input a material that is not (yet) present in the MATER.ATF file, he/she can update this attribute file by supplying the required information (see Chapter 6). If a name for a material is given that is not present in the MATER.ATF file, an error message is obtained during execution of CRIA. In general, for each inputted material item, the following information should be provided: the amount of labour used in its construction (if appropriate), the amount of the materials used, and its depreciation time. For corrals, the following inputs are required: * CRDCLAS Herd size class (number) (integer) * CROLAB Farm labour for corral construction (hour/corral) real) * CRMAT Name of corral material (name) (character), * Select from MATER.ATF attribute file. * CRQUAN Quantity of corrals (number) (real) * CRDEP Depreciation time of the corral (year) (real) CRCLAS CROLAB CRMAT CRQUAN CRDEP 1 0. 'corral1' 1. 30. 2 0. 'corral2r' 1. 30. 3 0. 'corral3r' 1. 30. 4 0. 'corral4r' 1. 30. Note that when no corral is to be used, the user can give ‘none’ in the column CRMAT. In this example, CROLAB = 0 because in the costs of the corrals (in MATER.ATF), the labour for construction is included. For troughs, the following inputs are required: * MTDCLAS Herd size class (number) (integer) * MTMAT Name of trough (name) (character) * Select from MATER.ATF attribute file. * MTQUAN Quantity of troughs (number) (real) * MTDEP Depreciation time of trough (year) (real) MTCLAS MTMAT MTQUAN MTDEP 1 'trough' 1. 5. 2 'trough' 4. 5. 3 'trough' 5. 5. 4 'trough' 6. 5. Note that when no troughs are to be used, the user can give ‘none’ in the column MTMAT. For any other materials, up to three inputs can be supplied: * T_CLAS Herd size class (number) (integer) * T_MAT Name of used materials (name) (character) * Select from MATER.ATF attribute file. * T_QUAN Materials quantity, in same unit as in materials file! (name) (real) * T_DEP Depreciation time of used materials (years) (real). * Note: when T_DEP is 0, the tools are yearly acquired. * Tool2 per herd size class 24

T1CLAS T1MAT T1QUAN T1DEP 1 'stools' 10. 5. 2 'stools' 10. 5. 3 'stools' 10. 5. 4 'stools' 10. 5. * Tool2 per herd size class T2CLAS T2MAT T2QUAN T2DEP 1 'ltools' 3. 3. 2 'ltools' 4. 3. 3 'ltools' 5. 3. 4 'ltools' 8. 3. * Tool3 per herd size class T3CLAS T3MAT T3QUAN T3DEP 1 'none' 0. 0. 2 'none' 0. 0. 3 'none' 0. 0. 4 'none' 0. 0. In this example, only ‘small tools’ and ‘large tools’ are used, and the option for input item number 3 is left unused by specifying ‘none’ under T3MAT.

OPERATIONS AND HEALTH CARE

Herd management entails the performance of various operations. There are ‘miscellaneous’ operations such as general inspection, and operations that are related to specific activities such as assistance at calving, salt application or the inoculation of animals. These operations require time and input materials that need to be specified by the user. Miscellaneous operations are such things as general inspection, snakes chasing, general health care etc. The amount of time spent on these miscellaneous operations should be provided. One input item can be given, to be selected from the attribute file CATTLE.DAT (if necessary, this file may be updated to include the desired item). Note: all inputs are on a yearly basis! * CHCLAS Herd size class (number) (integer) * CHLAB Own (farm) labour use (hours/year) (real) * CHMAT Health materials used (character). * Select from CATTLE.ATF attribute file. * CHQUAN Quantity of health materials used (unit) CHCLAS CHLAB CHMAT CHQUAN 1 180. 'emicina' 50. 2 240. 'emicina' 100. 3 300. 'emicina' 250. 4 360. 'emicina' 400.

Assistance at calving is independent of herd size and is expressed in labour hours per born animal: * BRTLAB Own (farm) labour use for assistance at calving (hour/born * calve) (real) BRTLAB = 3.

The application of (mineral) salt is specified by the type of salt applied, the amount applied per animal unit per day and the amount of (yearly) labour hours needed to fill the troughs with salt. One Animal unit is defined as an animal of 400 kg. The type of salt should be selected from the 25

FEED.ATF attribute file (if necessary, this file may be updated to include the desired type of salt). The unit of the quantity of (mineral) salt should be the same as that in the FEED.ATF attribute file. * MSNAME Name of salt (name) (character). Select from FEED.ATF attribute file * MSQUAN Quantity of salt application (kg/day/AU) (real) MSNAME MSQUAN 'salt' 0.05 Note that in the example given here, only one type of salt given. The user may increase the number of salts (lines) up to a maximum of five. When no salt is to be supplied, ‘none’ can be entered. Labour use for salt application is entered as follows: * CMCLAS Herd size class (number) (integer) * MSLAB Labour use to supply all mineral salt (hour/year) (real) CMCLAS MSLAB 1 26. 2 30. 3 40. 4 50.

Born animals may be given one-time-only health care treatments such as specific inoculations. For these treatments, the name and quantity of the supplied materials (inoculations) have to be selected from the attribute file CATTLE.ATF. The unit of the quantity of inoculation (I1QUAN) should be the same as that of the selected item in the CATTLE.ATF file. The amount of labour for these treatments/inoculations should include possible round-up of the animal tot a corral or the time needed to administer the treatment. All data are specified per animal: * I1NAME Name of (inoculation) material (name) (character) * Select from CATTLE.ATF attribute file. * I1QUAN Quantity (of inoculation) per application (unit) (real) * I1LAB Labour use per inoculation, including round-up to corral (hour/animal) I1NAME I1QUAN I1LAB 'brucel' 1. 0.15 'dectomax' 6. 0.30 'bacterine' 5. 0.10 The example given here is three rows long; the user may increase/decrease the number of rows (minimum of one, maximum of five). One row should always be present, but the user may give ‘none’ for the material used.

Beside one-time-only treatments/inoculations of animals, other treatments/inoculations may be administered with a certain yearly frequency. For these treatments, the name and quantity of the supplied materials (inoculations) have to be supplied (again selected from the attribute file CATTLE.ATF), the amount of labour required for the administration of these treatments/inoculations, and – separately! - the amount of yearly labour for round-up of the animals tot a corral. The unit of the quantity of inoculation (I2QUAN) should be the same as that of the selected item in the CATTLE.ATF file. The data on type and amount of treatment, and the labour hours for administration are specified per animal or per animal unit: * I2NAME Name of inoculation material (name) (character) * Select from CATTLE.ATF attribute file. * I2UNIT Herd unit for application, either 'animal' (per animal) or * 'aunit' (per animal unit) * I2FREQ Frequency of application (times per year per I2UNIT) (real) * I2QUAN Quantity of inoculation per application (unit) (real) * I2LAB Labour use for inoculation, without round-up time to corral 26

* (hour/I2UNIT) (real) I2NAME I2UNIT I2FREQ I2QUAN I2LAB 'ripercol' 'aunit' 2. 20. 0.1 'bacterine' 'animal' 2. 5. 0.1 'anthrax' 'animal' 2. 5. 0.1 'neguvon' 'aunit' 5. 0.005 0.07 The example given here is four rows long; the user may increase/decrease the number of rows (minimum of one, maximum of 10). One row should always be present, but the user may give ‘none’ for the material used. The amount of labour required for round-up to the corral (for treatment/inoculations) is specified for the whole herd: number of yearly round-ups and labour hours per round-up: * I2CLAS Herd size class (number) (integer) * I2RNO Number of round-ups per year for inoculation (number) (real) * I2RLAB Round-up time to corral for inoculation (hour/round up) * (real) I2CLAS I2RNO I2RLAB 1 6. 0.15 2 6. 0.30 3 6. 0.67 4 6. 1.00

3.1.3 Site file

The site file contains two parameters that are used by all PASTOR models: interest rate and the number of work hours in a day. The interest rate is used in the calculations of annuity costs of items/inputs that have a lifetime (renewal period) of more than one year. * Interest rate for cost calculations (%/year) (real) RINT = 7.

All labour specifications in the input files are given in hours. However, all PASTOR models compute total labour requirements on a daily basis, Therefore, the number of hours in a work-day is specified under DAYHR. * Hours of labour in one day (real) (h/d) DAYHR = 8.

3.2 GORDO model

Input and output file names for the GORDO model are specified in the file CONTROL.DAT the same way as for the CRIA model, Paragraph 3.1. The only differences are the names of the herd characteristics and the herd management data files:

FILEI1 = 'C:\PASTOR\FILE_IN\HERD\GORDHRD.DAT' FILEI2 = 'C:\PASTOR\FILE_IN\HERD\GORDMAN.DAT' 27

3.2.1 Herd characteristics file

Input parameters that characterise the structure, target selling strategy and target growth of the breeding herd to be modelled are specified in the so-called herd characteristics file. The parameters of this file are explained here, using the file GORDHRD.DAT DAT for a fattening herd in the North Atlantic Zone of Costa Rica as example. A complete listing of GORDHRD.DAT is given in Appendix 1.1.3.

The parameter MAINK specifies the manner in which the herd is supposedly fed, and entails a correction factor for maintenance energy required to support grazing7 (real). The following options may be selected: *MAINK = 1.0: for stable-fed *MAINK = 1.1: for good pasture *MAINK = 1.2: for sparse pasture MAINK = 1.2

A one-letter code is given that serves to ‘recognise’ the herd type that was modelled in the output files (character). E.g.: HCODE = 'F'

The size of the herd is given in total number of animals (i.e. calves, steers and cows all count as one animal), (integer): HSIZE = 50

The herd size is combined in GORDO with the one-letter code HCODE to produce a unique identification number for the herd under consideration. For this identification number, the actual herd number is increased with 100 for ‘programming’ reasons. Thus, in this example, the herd identification number will be F150 (HCODE followed by 100+HSIZE). The herd identification number is written as first column in all output files.

The ‘breed’ - or type - of animals is specified by a size/weight indication for females and males separately. This identification is used in the some of the calculation of feed requirements (NRC, 1989; p 74). The following options may be selected: *ITYPEF = 1: female, large breed; max weight is 800 kg *ITYPEF = 2: female, small breed; max weight is 600 kg *ITYPEM = 3: male, large breed; max weight is 1000 kg *ITYPEM = 4: male, small breed; max weight is 800 kg ITYPEF = 1 ITYPEM = 3

For the calculation of maintenance energy requirements, three parameters relating to breed and weight specifications should be given (NRC, 1996; p115-116): A breed effect on maintenance energy requirements (NRC, 1996; p 115). E.g. BE = 0.90; for Brahman and Nellore Shrunk Relative Weight (NRC, 1996; p 116), e.g.: *SRW = 435. ; kg for animals finishing at trace marbling (25.2% body fat) *SRW = 462. ; kg for animals finishing at slight marbling (26.8% body fat)

7 In truth, MAINK is a management characteristic 28

*SRW = 478. ; kg for animals finishing at small marbling (28% body fat) and replacement heifers SRW = 435. Final shrunk body weight at maturity (typically 0.96 times full final weight): FSBW = 550.

The ratio of male to female animals in the herd should be supplied: * Herd male/female animal ration: RATIOMF = 1.5

The live weight of young animals that are bought is specified separately for males (WBUYM) and females (WBUYF), (kg) (real). * Live weight of animal at buying (kg) (real); for male calves * (WBUYM) and female calves (WBUYF) WBUYM = 190. WBUYF = 160.

The live weight of the animals at selling is specified separately for males (WSELLM) and females (WSELLF), (kg) (real). GORDO assumes that animals are kept at least one complete month in the herd for fattening. Therefore, it computes the duration time of animals in the herd by dividing the ‘selling weight’ minus the ‘buying weight’ by the daily live weight gain (LWG, specified below). When this value is larger than 31 days, the user gets an error message from the program. * Live weight of animal at selling (kg) (real); for males (WSELLM) * and for females (WSELLF) WSELLM = 450. WSELLF = 400.

The target growth rates of the animals are specified for males (LWGM) and females (LWGF) separately (kg/day) (real). These target growths are set by the user, and GORDO subsequently calculates the feed requirements necessary to accomplish these targets. Of course, there is a relationship with the management of the herd. For instance, high target growth rates should be accompanied by ‘good’ management as specified in the herd management file (e.g. good care- taking, sufficient inoculations etc.), Paragraph 3.2.2. * Live weight gain of animals (kg/day) (real); for males (LWGM) * and for females (LWGF) LWGM = 0.5 LWGF = 0.4

The mortality rate is specified as fraction for both males and females together, (-) (real). Bounded by -0 and 0.99: * Mortality rate (real). Bounded by -0 and 0.99. MRATE = 0.01

Finally, a factor should be given that ‘scales’ the energy concentration of the diet fed according to NRC (1989) assumptions, with a suggested range from 0.95 - 1.05. (real; bounded by 0.9-1.1). It is suggested to put this value at 1., unless strong evidence exists to change this value. FEDNRC = 1. 29

3.2.2 Herd management and site file

The management data file for GORDO is very similar to that for CRIA in terms of structure and data input; see Paragraph 3.1.2. A complete listing of the data file GORDMAN.DAT is given in Appendix 1.1.4. There are only two differences with the management file for CRIA herds: 1. There is no specification of the labour use for assistance at calving (BRTLAB), since no calves are born in a fattening herd. 2. The inoculations given once to born animals in the CRIA model (I1NAME, I1QUAN, I1LAB) are inoculations given once for bought animals in the GORDO model. The inoculations that are regularly given (I2NAME, I2UNIT, I2FREQ, I2QUAN, I2LAB) are supplied with an indication of frequency per year (I2FREQ). GORDO automatically computes the correct number of inoculations applied when the duration time of animals in the herd is shorter than one year.

The information needed for the GORDO model in the site file is exactly the same as that for the CRIA model; see Paragraph 3.1.3.

3.3 Special case: reruns

The models CRIA and GORDO generate technical coefficients for alternative herds, i.e. Animal Production Systems (APSTs), as specified by the herd characteristics and herd management input files given in the CONTROL.DAT files. However, it could be interesting to generate various breeding and/or fattening APSTs. The rerun option of PASTOR allows that CRIA and GORDO are automatically executed several times by reading and using subsequent input data files. The following example explains the procedure for CRIA; the same applies to GORDO. A RERUNS.DAT file should be created and put in the CRIA or GORDO sub-directory. This RERUNS.DAT file should contain the names of alternative herd characteristics and/or herd management input files that should be used. This is done by repeating the name and path of the FILEI1 parameter in the CONTROL.DAT file, but using different data file names. For example, the following RERUNS.DAT file causes CRIA first to generate technical coefficients for an APST as specified by input files as in CONTROL.DAT, and than subsequently for an APST as specified by the herd characteristics file CALTHRD.DAT:

FILEI1 = 'C:\PASTOR\FILE_IN\HERD\CALTHRD.DAT'

The file CALTHRD could, for instance, be a herd with a different selling strategy, or a herd with a different target growth rate from the herd as specified in CRIAHRD.DAT.

Note: remember that each herd characteristics file should have a unique one-letter code to recognise the herd type (HCODE) in the generated output files.

When no reruns are wished, the RERUNS.DAT file should be removed from the sub-directory, or an asterix may be put in front of each line in the file. 30

4 Generating Pasture Production Systems (PASTs)

The models to generate pasture production systems (PASTs) are run by giving the *.EXE command in the appropriate subdirectory, i.e. PASTOF.EXE for fertilised pastures in the PASTOR\PASF_MOD sub-directory, or PASTOU.EXE for unfertilised pastures in the PASTOR\PASU_MOD sub-directory. In the following paragraphs, the control over executing the PASTOF and PASTOU models is explained in detail.

4.1 PASTOF model

In CONTROL.DAT (in the sub-directory MOD_PASF), the required model input, attribute and output files of PASTOF are specified:

*************************** CONTROL.DAT *********************** * Control file for PASTOF model * * PASTOR 2.0 * *************************************************************** * RUNMOD Select mode of model running: PASTOR or CENTURY RUNMOD = 'PASTOR'

* PASMAN select type of pasture use: SILAGE for silage (pasture * may produce more biomass than animals can eat, surplus is removed), * or GRAZING for truly grazed pastures. PASMAN = 'GRAZING'

*************************************************************** * INPUT FILES *************************************************************** * FILEI0 Input file with site data * FILEI1 Input file with grass data * FILEI2 Input file with soil data * FILEI3 Input file with herd data * FILEI4-8 Attribute input files

FILEI0 = 'C:\PASTOR\FILE_IN\SITE.DAT' FILEI1 = 'C:\PASTOR\FILE_IN\PASTO\ESTREL.DAT' FILEI2 = 'C:\PASTOR\FILE_IN\SOIL.DAT' FILEI3 = 'C:\PASTOR\FILE_IN\CAT_CHAR.DAT' FILEI4 = 'C:\PASTOR\FILE_ATR\MATER.ATF' FILEI5 = 'C:\PASTOR\FILE_ATR\BIOCID.ATF' FILEI6 = 'C:\PASTOR\FILE_ATR\EQUIP.ATF' FILEI7 = 'C:\PASTOR\FILE_ATR\FERT.ATF' FILEI8 = 'C:\PASTOR\FILE_ATR\TRACTION.ATF'

*************************************************************** 31

* PASTOR Output files *************************************************************** * FILEO1 Monthly yield data * FILEO2 Yearly yield data * FILEO3 'Extra' data (not directly for LP model) * FILEO4 Yearly sustainability indicators * FILEO5 Yearly labour use plus costs data * FILEO6 Monthly labour use data * FILEO8 Combination definition

FILEO1 = 'C:\PASTOR\FILE_OUT\PFERPM.PRN' FILEO2 = 'C:\PASTOR\FILE_OUT\PFERPY.PRN' FILEO3 = 'C:\PASTOR\FILE_OUT\PFERX.PRN' FILEO4 = 'C:\PASTOR\FILE_OUT\PFERS.PRN' FILEO5 = 'C:\PASTOR\FILE_OUT\PFERLC.PRN' FILEO6 = 'C:\PASTOR\FILE_OUT\PFERLM.PRN' FILEO8 = 'C:\PASTOR\FILE_OUT\PFERCOM.PRN'

First, it should be specified that PASTOF should produce technical coefficient outputs, always set: RUNMOD= ‘PASTOR’8

Next, it should be specified whether computations should be performed for a grazing system only (PASMAN=’GRAZING’), or for a system where the pasture is grazed and mown (PASMAN=’SILAGE’). See Paragraph 1.2.1 for further explanation.

The model data files needed are specified at the variables FILEI0-3. Note that, beside the file name, the complete path of the sub-directory where the files are stored is given. Users may change the names of the input files when they have created their own input files. FILEI0 contains site- characteristics; FILEI1 specifies the name of the file that contains characteristics and management of the pasture to be modelled; FILEI2 contains soil characteristics; and FILEI3 contains data on (a.o.) manure produced and feed requirements of the stocked herd on the pasture. The site file contains so-called ‘site’ data, of which some are also used by the other models of PASTOR. In the following paragraphs, the model data files are explained in detail.

Attribute files (FILEI4-8) are explained in Chapter 6. The names of the attribute files should not be changed by the user.

The names of the output files are given under the variables FILEO1-8. These names are the same as given in Table 2.3.1, but may be changed by the user.

4.1.1 Pasture data file

Input parameters that characterise species, production levels and management of the pasture to be modelled are specified in the pasture file. The parameters of this file are explained here, using the

8 If RUNMOD=’CENTURY’, PASTOF produces output for Century and DNDC simulation model. Not further explained. Also, some more FILEO files should then be specified, which is not shown here. 32 file ESTREL.DAT for fertilised Estrella (Cynodon nlemfuensis) in the North Atlantic Zone (NAZ) of Costa Rica as example. A complete listing of ESTREL.DAT is given in Appendix 1.2.1

PRODUCTION CHARACTERISTICS

First, the name and a one-letter code for the pasture type is given. The one-letter code will appear in the output files in the complete code that characterises the pasture being modelled (see below). Note: each pasture file should have a unique one-letter code (e.g. ‘E’ for Estrella).

* GNAME : Grass name (character) * GCODE : Grass code (one letter only!) (character) * ------GNAME = 'Estrella' GCODE = 'E'

Next, two pasture production levels need to be supplied: the ‘highest possible’, called ‘attainable’, and the ‘worst possible’, called ‘minimum’. These two levels are the maximum and minimum production levels between which target production of the pasture can be realised. Attainable production is defined here as the highest (total above-ground) production with the best quality in terms of energy, crude protein and phosphorus content, that can be obtained on the best soil type in the area under the prevailing climatic conditions, with optimum supply of nutrients and with optimum pest, disease and weed control (Bouman et al., 1996). The only growth-limiting factors are climatic, i.e. radiation, temperature and rainfall, and the physical soil properties of the best soil available. Attainable production values can be derived from well-calibrated crop growth simulation models, well-controlled field experiments, expert knowledge or literature (Van Ittersum & Rabbinge, 1997; Bouman et al., 1996). Differences among months can result from seasonal variation in weather (e.g. cold spells, droughts) and/or physiological development of the pasture (e.g. flowering period). The minimum pasture production is assumed to take place on poor soils (completely exhausted; hardly any nutrient stock available) with only natural input of nutrients, such as N deposition in rain and N fixation by micro-organisms, and P and K from weathering. The minimum production is also the production level, with corresponding N, P and K content, below which the pasture can no longer survive. The attainable production characteristics of the pasture under consideration have to be supplied per month. To characterise the minimum production, only the nutrient and energy content have to supplied as yearly value; PASTOF calculates the corresponding biomass level. * Pasture data at level of attainable production (PER MONTH): * MONTH: Name of month (character) * DMP: (above-ground total) Dry matter attainable production * on best soils (kg/month) (real) * CP: Crude Protein content (%) (real) * ME: Metabolizable energy content (Mcal/kg) (real) * P: Phosphorus content (%) (real) * K: Potassium content (%) (real) * ------MONTH DMP CP ME P K 'JAN' 1928. 11.0 2.3 0.35 3.7 ! Literature, expert knowledge 'FEB' 1928. 11.0 2.3 0.35 3.7 ! Total PP: 28 t/ha 'MAR' 1928. 11.0 2.3 0.35 3.7 'APR' 2468. 12.0 2.5 0.30 3.5 33

'MAY' 2468. 12.0 2.5 0.30 3.5 'JUN' 2468. 12.0 2.5 0.30 3.5 'JUL' 2468. 12.0 2.5 0.30 3.5 'AUG' 2468. 12.0 2.5 0.30 3.5 'SEP' 2468. 12.0 2.5 0.30 3.5 'OCT' 2468. 12.0 2.5 0.30 3.5 'NOV' 2468. 12.0 2.5 0.30 3.5 'DEC' 2468. 12.0 2.5 0.30 3.5

There is no distinction among months for the minimum production characteristics: * Minimum nutrient and energy concentrations when no external (manure, * fertiliser) nutrients are supplied. (minimum production level). * CPMIN: Minimum Crude Protein content (%) (real) * MEMIN: Minimum Metabolizable energy content (Mcal/kg) (real) * PMIN: Minimum Phosphorus content (%) (real) * KMIN: Minimum Potassium content (%) (real) *------* From variety of literature and expert knowledge CPMIN = 6. MEMIN = 1.5 PMIN = 0.12 KMIN = 1.4

EFFECT OF SOIL TYPE AND STOCKING RATE

The attainable production level applies to the best possible soil. In an area under study, there may exist a variety of soils characterised by physical and chemical properties. The influence of soil type on the attainable production level is expressed by two reduction factors, RDMP and RDMUSE. RDMP quantifies the reduction in attainable pasture production due to soil limitations such as acidity, poor drainage or low water holding capacity. Note that, on this level, it is still assumed that nutrients are in ample supply! RDMP values need to be supplied for each soil type in the area under study for which PASTs have to be generated. Soil types are indicated by a three letter code, in our example SFW (Soil Fertile Well drained), SIW (Soil Infertile Well drained) and SFP (Soil Fertile Poorly drained), Bouman et al. (1998). The soil name supplied here should correspond to the list of soil names given in the soil data file (SOIL.DAT; see Paragraph 4.1.2), and to the list of soil names given in the site data file (SITE.DAT; see Paragraph 4.1.4), because PASTOF calculates soil nutrient balances based on the soil properties supplied in these files. In the example below, it is specified that there is no reduction in attainable yield on SFW soils, since these soils are the best in the NAZ with no limitations to pasture growth. SIW are acid soils, and attainable yields are 80% of those on the best soils. SFP have excess water problems, and attainable yields are only 40% of those on the best soils. RDMUSE quantifies the effect of soil type on the potential use fraction of the total above-ground biomass as function of stocking rate. Not all above-ground production can be eaten by grazing animals because i) parts such as stubble are ‘unreachable’ and should be left for regrowth, ii) parts are trampled under the hooves of the animals, and iii) parts are (temporarily) unavailable because they are covered by manure or urine patches (Deenen, 1994; Van der Ven, 1992). The potential fraction of total above-ground biomass ‘on offer’ for consumption is called DMUSE, and depends on the amount of animals per surface unit (stocking rate). The factor DMUSE is - as standard - specified for the best soil type available in the area. The reduction factor RDMUSE adapts DMUSE to the conditions of the actual soil types to be studied. In our example, there is no 34 extra reduction in dry matter use on the soils SFW and SIW. The soil type SFP is poorly drained, however, and trampling on this soil causes an 80% reduction in potential dry matter use as compared to the potential dry matter use on the best soil. * Yield reduction factors * SOILP: Soil name (character) * RDMP: Reduction fraction of attainable production (DMP as above) * due to soil limitations (-) (real) * RDMUSE: Reduction fraction of potential dry matter use (DMUSE as below) due to * soil limitations. (-) (real) * ------SOILP RDMP RDMUSE 'SFW' 1.0 1.0 'SIW' 0.7 1.0 'SFP' 0.4 0.8 Note: in this example, three soil types are supplied. This list can be shortened (with a minimum of one soil type) or extended (up to a maximum of 10). The soil names will appear in the complete code that characterises the pasture(s) being modelled (see below).

The factor DMUSE specifies the fraction of the total-above ground matter potentially on offer for consumption as function of stocking rate, on the best soil type available in the area. Information on this relationship can be derived from experiments, expert knowledge or literature. The user is completely free to fill-in this table: the value of the stocking rates provided and the number of stocking rates can be adapted according to local conditions and wishes of the user (a minimum of one relationship should be provided; the maximum is 50). In our example, stocking rate varies from one to three. ***********************************************************************

* SRATE: Stocking rate (animal units per ha) (real) * DMUSE: Potential fraction dry matter on offer (fraction of total above- * ground biomass), as function of stocking rate (-) (real) * ------SRATE DMUSE ! Expert knowledge 1. 0.55 1.5 0.525 2. 0.50 2.5 0.475 3. 0.45

The stocking rates will appear (preceded by the letter ‘R’) in the complete code that characterises the pasture(s) being modelled (see below).

TECHNOLOGY: FERTILIZER AND WEEDING

At this moment, PASTOF has all the necessary information to calculate maximum attainable production levels (quantity and quality) for all combinations of given soil types and stocking rates. Based on the soil properties provided in the soil data file (SOIL.DAT; see Paragraph 4.1.2), PASTOF calculates the soil nutrient balance for all combinations of soil types and stocking rates. The amount of nutrients in manure and urine that is inputted into the system by the herd at each stocking rate is also taken into account. Characteristics of the manure are read from a file as 35 specified in CONTROL.DAT, in our example the file CAT_CHAR.DAT (see Paragraph 4.1.3). PASTOF next calculates the amount of extra (fertiliser) N, P and K nutrients that are required to obtain the attainable production levels for all combinations of soil types and stocking rates, under a user-specified soil nutrient balance. The maximum allowable soil nutrient mining (negative soil nutrient balance) is read from the site file, in our example SITE.DAT (Paragraph 4.1.4). Now, the user can specify options for management of the pasture related to i) actual amounts of fertiliser application, and ii) manner of weeding. The target amount of fertiliser applied, FGIFT, is expressed as fraction of the amount needed to realise the maximum attainable production for the specified soil-stocking rate combinations. Thus, the highest possible FGIFT is 1.0 (leading to maximum attainable production), and the lowest is 0.0 (leading to the lowest production level). The manner in which fertiliser is applied is specified under FERTAP. PASTOR is highly generic in the sense that the user can ‘build’ his own options for the manner in which fertiliser is applied at the end of the file. From these own-build options, a selection can be made and used as input under FERTAP. The same applies to the manner of weeding. At the end of the file, a number of alternatives can be ‘build’ from which a selection can be inputted under WEED. All three management input parameters (FGIFT, FERTAP and WEED) are preceded by a column that encodes the technology level as a two-digit number. This two-digit number will appear (preceded by the one-letter code that indicates the type of pasture, see above) in the complete code that characterises the pasture(s) being modelled (see below). * PLEVEL: Code for technology level (2 numbers only!) (integer) * FGIFT: Fraction of fertiliser N gift to realise maximum * attainable production (-) (real) * FERTAP: Manner of fertiliser application (name) (real) * Select from options given below under 4. OPERATIONS) * WEED: Manner of weeding (name) (character) * Select from options given below under 4. OPERATIONS) * ------PLEVEL FGIFT FERTAP WEED ! User defined 11 0.00 'manual' 'mixed' 20 0.20 'manual' 'mixed' 40 0.40 'manual' 'mixed' 60 0.60 'manual' 'mixed' 80 0.80 'manual' 'mixed' 99 1.00 'manual' 'mixed' In our example, there are six technology levels that will be modelled by PASTOF. However, this list can be shortened or expanded to include as many combinations of FGIFT, FERTAP and WEED desired (up to a maximum of 50). PASTOF will calculate technical coefficients for all combinations of soil types, stocking rates and technology levels so far specified (in our example three soil types, five stocking rates and six technology levels, leading to 90 PASTs).

ESTABLISHMENT AND MAINTENANCE OPERATIONS

The pasture specified so far has to be established by sowing or planting, and maintained and managed by operations. First, pasture establishment operations are specified by listing labour and material inputs required for two specific actions: i) application of herbicides to kill existing crops or natural vegetation, and ii) the application of a basic fertiliser gift. For herbicide application, the names of the herbicides, the amount of herbicides, the amount of labour used, the equipment and the type of traction used need to be specified. The herbicides used have to be selected from the attribute file BIOCID.ATF, the equipments from the attribute file EQUIP.ATF file, and the tractions 36 from the attribute file EQUIP.ATF. The units of the quantities of the herbicides, equipments and tractions have to be the same as those in these *.ATF files. When a desired herbicide/equipment/traction is not present in these files, they can be added by the user and then selected here. Several herbicides can be applied by listing these products in different rows. For the application of each herbicide, the amount of labour used is specified under EWLAB. Alternatively, a separate line can be used to enter all labour used for the application of all herbicides, and then a ‘0’ can be entered for each herbicide separately. For instance, in the example below, the first line is used to enter all labour, equipment and traction used for all herbicides together, and the herbicides are listed separately on the following lines. The number of entries (lines) is flexible and can be shortened or expanded by the user (minimum is one; maximum is five). Separate lines are used to enter the fertilisers applied at establishment. This follows the same scheme as for the herbicides, with the difference that the fertilisers are selected from the FERT.DAT attribute file. Since all these data are used by PASTOF to calculate costs and total labour use for the pasture, the duration of the pasture has to be supplied at EDEP (needed to calculate annuities of costs). * EDEP Depreciation time of pasture (year) (real). * EWLAB/EFLAB Farm labour use for weeding/fertilising (hours) (real) * EWNAME/EFNAME Herbicide/fertiliser name (name) (character); * to select from BIOCID.ATF and FERT attribute files. * EWQUAN/EFQUAN Herbicide/fertiliser quantity (unit) (real) * EWEQ/EFEQ Herbicide/fertiliser equipment name (name) (character); * to select from EQUIP.ATF attribute file. * EWQUSE/EFQUSE Herbicide/fertiliser equipment use (hours) (real) * EWTRAC/EFTRAC Herbicide/fertiliser traction for equipment (name) (character) * to select from TRACTION.ATF attribute file. * Input data: Andre Nieuwenhuyse, based on farmer inquiries in the AZ (96-97) EDEP = 10.

EWLAB EWNAME EWQUAN EWEQ EWQUSE EWTRAC 24.0 'None' 0. 'ksspray' 24. 'none' 0.0 'Tordon-101' 1. 'ksspray' 0. 'none' 0.0 '24D' 3. 'ksspray' 0. 'none' 0.0 'Round-up' 4. 'ksspray' 0. 'none'

EFLAB EFNAME EFQUAN EFEQ EFQUSE EFTRAC 4.0 'P' 4. 'none' 0. 'none'

Next, the input of labour and other materials for the establishment and maintenance of the pasture have to be supplied. Under OPER, a brief description of the operation can be supplied. The list then follows the same principle as above: materials have to be selected from the MATER.ATF attribute file, equipments from the EQUIP.ATF file, and tractions from the EQUIP.ATF file. The units of the quantities of the materials, equipments and tractions have to be the same as those in the *.ATF files. When a desired material/equipment/traction is not present in these files, they can be added by the user and then selected here. The duration/lifetime can vary per material and therefore the depreciation time DEPRET has to be specified per material input. When materials are inputted each year, DEPRET should be set to ‘0’. In the example file below, there are lines that specify the input of the Estrella grass stolons (line 1), lines for the establishment of fences (lines 2-5), lines for the maintenance of the fences (line 6) and for the use of five small tools in general (e.g. a saw, a machete, a hammer, a bucket, a knife) (line 7). The grass stolons are inputted every 10 years, which is the duration of the pasture; the fences (and the used fence materials) have a lifetime of six 37 years and need to be replaced; the fences are maintained every year (DEPRET = 0), and the small tools have a lifetime of five years. The user can decrease or increase the list according to own specifications (minimum is one; maximum is 25). * OPER Name of operation (name) (character) * OWNLAB Own (farm) labour use (hours) (real) * MATER Name of used materials (name) (character) * to select from MATER.ATF attribute file. * MQUANT Materials quantity, in same unit as in materials file! (name)(real) * DEPRET Depreciation time of used materials (years) (real). * Note: when DEPRET is 0, the operation/inputs are yearly recurrent. * EQUIP Name of equipment used (name) (character), * to select from EQUIP.ATF attribute file. * EQUSE Equipment use time (real) (hour) * TRAC Traction used to 'pull' equipment (name) (character) * to select from TRACTION.ATF attribute file. * Input data: Andre Nieuwenhuyse, based on farmer inquiries in the AZ (96-97) OPER OWNLAB MATER MQUANT DEPRET EQUIP EQUSE TRAC 'Grass sowing' 30. 'gstolE' 1.5 10. 'none' 0. 'none' 'Labour fence estab.' 12. 'none' 0. 6. 'none' 0. 'none' 'Fences barbed wire' 0. 'bwire-Cai' 350. 6. 'none' 0. 'none' 'Fences dead' 0. 'dposts-sl' 33. 6. 'none' 0. 'none' 'Fences nails' 0. 'cramp-l' 0.5 6. 'none' 0. 'none' 'Fence maintenance' 2. 'none' 0. 0. 'none' 0. 'none' 'Various small tools' 0. 'stools' 5. 5. 'none' 0. 'none'

WEEDING AND FERTILISING MANNER SPECIFICATION

The last section of the data file is meant to ‘build’ own specifications of i) recurrent weeding and ii) manner of fertiliser application. The amount of time and materials (herbicides) required for weeding depends on the cover - and thus production level - of the pasture. A high production with a good soil cover suppresses weeds, and therefore the amount of time and inputs spent on weeding can be relative low. On the contrary, a low producing pasture with a poor soil cover encourages weed infestation and more time and inputs need to be spent in controlling weeds. Since the actual production level varies for the various combinations of soil type, stocking rate and technology level as specified earlier, a whole range of weeding inputs would need to be specified. This problem is solved in PASTOF by specifying two input levels of weeding inputs: one for the maximum attainable production level and one for the minimum (extensive) production level. PASTOF calculates for each realised actual production level the amount of labour and herbicides needed by interpolation between the maximum and minimum amounts. The labour and herbicide inputs for the attainable level are recognised by the suffix ‘PP’, and those for the extensive level by the suffix ‘EX’. For each manner of weeding that the user wants to ‘build’, the following inputs need to be specified for both levels: labour use, type and amount of herbicides applied, and equipment and traction used in the application of the herbicides. All inputs are yearly totals (per hectare). Because more than one type of herbicide may be applied, there is provision to enter data for up to three herbicide types. The labour use, and the use of equipment and traction on each line are the totals of all labour, equipment and traction used in the whole year (summed over all manual weeding and the application of all the herbicides). On each line, manual weeding - in the form of labour hours invested - and chemical weeding may be combined by summing all labour used under OL. The user is free to ‘build’ any number of alternative weed control manners, as long as the manners are 38 quantified at both the PP and the EX technology level (a minimum of one, up to a maximum of five). The name of the manner should be entered under WEEDPP/WEEDEX. This name can then be used earlier in the file to select the manner of weeding that is to be modelled (under WEED; see above). In the example below, three weeding manners have been build; a strict manual weeding, a strict chemical weeding, and a mixed manner with both manual and chemical weeding. Quantitative data on labour hours and chemical inputs have to be obtained from field enquiries and from expert knowledge. * Input data: Andre Nieuwenhuyse, based on farmer inquiries in the AZ (96-97) * Note that all inputs are totals over the year. * All inputs/activities are specified for the level of potential production * (extension PP) and for the level of zero external inputs (extension EX) * WEED Name of weeding manner (name) (character) * OL (total) Own (farm) labour use (hour/year) (real) * C1N Name of first herbicide input (name) (character) * to select from BIOCIDE.ATF attribute file. * C1Q Quantity of first herbicide input (amount/year) (real) * Units of quantity should match those in biocide file! * C2N Name of second herbicide input (name) (character) * to select from BIOCIDE.ATF attribute file. * C2Q Quantity of second herbicide input (amount/year) (real) * Units of quantity should match those in biocide file! * C3N Name of third herbicide input (name) (character) * to select from BIOCIDE.ATF attribute file. * C3Q Quantity of third herbicide input (amount/year) (real) * Units of quantity should match those in biocide file! * WEQ Equipment used for weeding (name) (character) * to select from EQUIPMENT.ATF attribute file. * WEQU Use time of equipment (hours/year) (real) * WTRA Traction used to 'pull' equipment (name) (character) * to select from TRACTION.ATF attribute file. WEEDPP OLPP C1NPP C1QPP C2NPP C2QPP C3NPP C3QPP WEQPP WEQUPP WTRAPP 'manual' 7.0 'None' 0. 'None' 0. 'None' 0. 'none' 0. 'none' 'chemic' 3.5 '24D' 1.5 'Tordon-101' 0.5 'Combo' 0.035 'ksspray' 3.5 'none' 'mixed' 5.0 '24D' 1.5 'Tordon-101' 0.5 'None' 0. 'ksspray' 2.0 'none'

WEEDEX OLEX C1NEX C1QEX C2NEX C2QEX C3NEX C3QEX WEQEX WEQUEX WTRAEX 'manual' 20. 'None' 0. 'None' 0. 'None' 0. 'none' 0. 'none' 'chemic' 11.5 '24D' 4.5 'Tordon-101' 1.5 'Combo' 0.105 'ksspray' 10.5 'none' 'mixed' 14. '24D' 3.0 'Tordon-101' 1.0 'Combo' 0.035 'ksspray' 6. 'none'

In the same way as ‘building’ weeding manners, manners of fertiliser application can be ‘build’. A notable difference, however, is that here the labour required for fertiliser application is calculated by PASTOF and is not explicitized by the user. This is because the amount of fertiliser to be applied is calculated by PASTOF on the basis of the nutrient balance and the relative fraction inputted by the user under FGIFT (see above). For this calculation, two parameters need to be supplied: FSSIZE that quantifies the gross amount of fertiliser that can be applied on one hectare pasture in application time FSADUR. For instance in our example, 150 kg of fertiliser can be manually applied on one hectare in three hours. The parameter FOLAB can be used to specify whether own labour is used in the fertiliser application, or not (e.g. in the case of contract labour using tractors). No type of 39 fertiliser has to be indicated since PASTOF automatically takes average properties for N, P and K fertiliser from the FERT.ATF attribute file. The name of the fertiliser application manner should be entered under FERTIL. This name can then be used earlier in the file to select the manner of fertiliser application that is to be modelled (under FERTAP; see above). * FERTIL Manner of fertiliser application (name) (character) * FOLAB Fertiliser own (farm) labour (whether own labour is used in * application) * options: 'yes' or 'no' (e.g. when contract labour is used) * FEQUIP Fertiliser equipment (name) (character) * to select from EQUIP.ATF attribute file. * FSSIZE Fertiliser amount that can be applied in FSADUR time (kg) * (real) * FSADUR Fertiliser application duration for FSSIZE (hour) (real) * FTRAC Traction used to 'pull' equipment (name) (character) * to select from TRACTION.ATF attribute file. FERTIL FOLAB FEQUIP FSSIZE FSADUR FTRAC 'manual' 'yes' 'none' 150. 3. 'none'

In this example, only one fertiliser application manner is specified. However, the list can be extended to include more manners (a minimum of one, up to a maximum of five).

CODING OF GENERATED PASTS

PASTOF produces output files that contain technical coefficients of all modelled alternative pasture production systems (PAST). Many PASTs may be generated in one run of PASTOF for a single pasture type because the model is repeatedly executed with different combinations of soil type, stocking rate and technology level as specified in the pasture data file. Each PAST is recognised by a code, written in the first column of each output file. The explanation of this code is given for an example generated by PASTOF for one of the alternatives specified in the example pasture data file ESTREL.DAT

SFW.E20.R1.JAN where:  SFW is the soil type (SOILP)  E20 is a combination of the one-letter code for the pasture name (GCODE) with the technology level (PLEVEL)  R1 indicates the stocking rate (SRATE)  JAN indicates the month for which the particular technical coefficient in the file is valid (MONTH; not used in all files)

4.1.2 Soil data file

The soil file contains characteristics of various soil types which are used by PASTOF in the calculation of the soil nutrient balances. Soil types used in the pasture data file should also be present in the soil data file. The example file presented here, SOIL.DAT, contains characteristics for three soil types in the Atlantic Zone of Costa Rica (Bouman et al., 1998; Nieuwenhuyse, 1996): 40

SFW (Soil Fertile Well drained), SIW (Soil Infertile Well drained) and SFP (Soil Fertile Poorly drained).

First, some non-soil specific amounts of natural input of nutrients to all soil types are given: * Atmospheric nitrogen deposition (kg/ha/y) (real) AND = 1.7

* Atmospheric phosphorus deposition (kg/ha/y) (real) APD = 0.2

* Atmospheric potassium deposition (kg/ha/y) (real) AKD = 5.4

* Annual input of phosphorus by weathering (kg/ha/y) (real) WP = 0.

* Annual input of potassium by weathering (kg/ha/y) (real) WK = 0.

Next, soil properties are given that characterise loss fractions of fertiliser and manure (urine and faeces separately) nutrients. These loss fractions are specified for each type of loss (such as leaching or volatilisation) and for each nutrient N, P and K separately. For urine, a distinction is made for leaching losses through macropores and through the soil matrix (‘normal’ type of leaching loss). For phosphorus, a fixation fraction is to be supplied as well. When inputting the loss fractions, it should be checked that the sum of some loss fractions cannot be greater than 1: ULLMP + ULL + UVL + UDL <= 1 FLL + FVL + FDL <= 1 FELLN + FEVLN + FEDLN <= 1 Of course, single loss fractions are physically bounded by 0. and 1.

The first column of the table gives the three-letter code for the soils. Users can shorten, extend or edit the list of soil names and properties presented here (with a minimum of one, and a maximum of 10). * SOILS = soil type (name) (character) * NFIX = Nitrogen fixation by micro-organisms (kg/ha/y) (real) * ULLMP = Urinary leaching loss fraction through macropores (-) (real) * ULL = Urinary leaching loss fraction (-) (real) * UVL = Urinary volatalization loss fraction (-) (real) * UDL = Urinary (de)nitrification loss fraction (-) (real) * i.e.: NO, N2O and N2 loss * FLL = Faecal leaching loss fraction (-) (real) * FVL = Faecal volatalization loss fraction (-) (real) * FDL = Faecal denitrification loss fraction (-) (real) * FELLN = Fertiliser leaching loss fraction nitrogen (-) (real) * FELLK = Fertiliser leaching loss fraction potassium (-) (real) * FEVLN = Fertiliser volatalization loss fraction nitrogen (-) (real) * FEDLN = Fertiliser denitrification loss fraction nitrogen (-) (real) * FPXL = Phosphorus fixation fraction, for faeces, urine and * fertiliser (-) (real) 41

SOILS NFIX ULLMP ULL UVL UDL FLL FVL FDL 'SFW' 6.0 0.30 0.20 0.15 0.05 0.60 0.05 0.05 'SIW' 3.0 0.30 0.20 0.15 0.05 0.60 0.05 0.05 'SFP' 1.0 0.30 0.15 0.25 0.15 0.40 0.15 0.15

FELLN FEVLN FEDLN FELLK FPXL 0.40 0.13 0.02 0.40 0.0 0.45 0.13 0.02 0.45 0.0 0.40 0.15 0.10 0.40 0.0

PASTOF calculates the soil nutrient balance with fixed loss fractions of fertiliser, manure and urine (Stoorvogel, 1993; Hengsdijk et al., 1996). However, loss fractions are in reality not constant: with increasing fertiliser application, the ‘holding capacity’ of the soil steadily becomes saturated and increasing portions of additional fertiliser are lost by leaching, denitrification etc. Therefore, an extra ‘fertiliser loss factor’ can be specified, that is a multiplication factor on the calculated amount of needed gross fertiliser (with losses as specified above) as function of applied net (without losses) fertiliser. This fraction is an empirical parameter that can be derived from field experiments. The data values below are derived from Vicente-Chandler et al. (1974), who found that fertiliser use efficiency (losses) in tropical humid environments are constant up to a gross application rate of about 800-1000 kg ha-1, which coincides in our example with some 400 kg ha-1 net application rate. * 'Extra loss of fertiliser nitrogen (to be divided over leaching and * denitrification), as multiplication factor on calculated gross * N fertiliser gift (from loss fractions as above). * Give list as function of net fertiliser gifts (kg/ha)-fraction EXLOST = 0.0 1.0 250. 1.0 275. 1.0 300. 1.0 400. 1.0 425. 1.1 450. 1.2 475. 1.3 1000. 1.5

The extra losses are distributed over leaching and denitrification: * Fraction of 'extra' loss distribution over leaching and denitrification * LLEX = fraction to extra leaching loss (1-LLEX goes to denitr. loss) LLEX = 0.5

4.1.3 CAT_CHAR data file

The herd ‘manure’ file contains some characteristics of the stock that is supposed to graze the pasture. This file can be made by the user according to own insights, or be made by the CRIA model (see Chapter 3.1). The data in this file are used by PASTOF to calculate daily amounts of consumed nutrients and energy per animal unit, and in the calculation of the soil nutrient balance via inputs of nutrients by manure and urine per animal unit. 42

************************************************** * This file was created by CRIA.FOR * in its first run (no reruns used) * Contains characteristics of simulated herd. ************************************************** * Herd size (number) HSIZE = 50

* Herd size (animal unit) HSAU = 41.33

* Live weight of sold male calve (kg) SLWMS = 190.60

* Number of sold male calves (no) NSMS_HRD = 12.50

* Live weight of sold female calve (kg) SLWFS = 158.88

* Number of sold female calves (no) NSFS_HRD = 8.38

* Live weight of sold female cow (kg) SLWF = 452.90

* Metabolizable energy req. (Mcal/mth/herd MEHRD = 20419.71

* Crude protein required (kg/mth/herd) CPHRD = 943.64

* Phosphorus required (kg/mth/herd) PHRD = 20.97

* Crude protein in manure (kg/mth/herd) FCPHRD = 587.14

* Crude protein in urine (kg/mth/herd) UCPHRD = 275.96

4.1.4 Site file

The site file contains two parameters that are used by all PASTOR models: interest rate and the number of work hours in a day. The interest rate is used in the calculations of annuity costs of items/inputs that have a lifetime (renewal period) of more than one year. * Interest rate for cost calculations (%/year) (real) 43

RINT = 7.

All labour specifications in the input files are given in hours. However, all PASTOR models compute total labour requirements on a daily basis, Therefore, the number of hours in a work-day is specified under DAYHR. * Hours of labour in one day (real) (h/d) DAYHR = 8.

Next, the maximum allowable level of soil mining has to be supplied, per nutrient type and per soil type. For truly sustainable and stable production systems, the allowable mining is zero (Van Ittersum & Rabbinge, 1997). * ANMINE allowable nitrogen mining (kg/ha) (real) ( 0) * AKMINE allowable potassium mining (kg/ha) (real) ( 0) * APMINE: allowable phosphorus mining (kg/ha) (real) ( 0) SOIL ANMINE AKMINE APMINE 'SFW' 0. 0. 0. 'SIW' 0. 0. 0. 'SFP' 0. 0. 0.

4.2 PASTOU model

Input and output files are specified in CONTROL.DAT the same way is for the PASTOF model (Paragraph 4.1).

4.2.1 Pasture data file

As for PASTOF, input parameters that characterise pasture species, production levels and management of the pasture to be modelled are specified in the pasture file. The standard example files are NATURAL.DAT for non-fertilised natural pastures and BPINTOI for a grass-legume mixture (Brachiaria brizantha + Arachis pintoi), see Appendices 1.2.4 and 1.2.5. The parameters of the pasture file are explained here using NATURAL.DAT DAT for natural pasture in the North Atlantic Zone (NAZ) of Costa Rica as example.

PRODUCTION CHARACTERISTICS

First, the name and a one-letter code for the pasture type is given. The one-letter code will appear in the output files in the complete code that characterises the pasture being modelled (see below). Note: each pasture file should have a unique one-letter code (e.g. ‘N’ for Natural, ‘P’ for B. Brizantha + A. pintoi mixture etc.). * GNAME : Grass name (character) * GCODE : Grass code (one letter only!) (character) * ------GNAME = 'Natural' GCODE = 'N' 44

Next, the (target) production level needs to be specified in terms of above-ground dry biomass and contents of metabolisable energy, crude protein and phosphorus, on the best soil available in the area under study. This is different from the input for the PASTOF model; there is no quantification of ‘maximum attainable’ and ‘minimum’ production levels, but the desired target production is directly inputted. * Grass data at level of attainable production (PER MONTH): * MONTH: Name of month (character) * DMP: (above-ground total) Dry matter attainable production * (kg/month) (real) * CP: Crude Protein content (%) (real) * ME: Metabolizable energy content (Mcal/kg) (real) * P: Phosphorus content (%) (real) * K: Potassium content (%) (real) * ------* Data for attainable production estimated as two times that of current MONTH DMP CP ME P K ! data from various sources 'JAN' 1087. 10.0 2.1 0.15 1.5 ! literature, expert-knowledge 'FEB' 1087. 10.0 2.1 0.15 1.5 ! Total attain. prod: 15 t/ha/y! 'MAR' 1087. 10.0 2.1 0.15 1.5 ! Villareal pers. com. 'APR' 1304. 10.0 2.1 0.15 1.5 'MAY' 1304. 10.0 2.1 0.15 1.5 'JUN' 1304. 10.0 2.1 0.15 1.5 'JUL' 1304. 10.0 2.1 0.15 1.5 'AUG' 1304. 10.0 2.1 0.15 1.5 'SEP' 1304. 10.0 2.1 0.15 1.5 'OCT' 1304. 10.0 2.1 0.15 1.5 'NOV' 1304. 10.0 2.1 0.15 1.5 'DEC' 1304. 10.0 2.1 0.15 1.5

EFFECT OF SOIL TYPE AND STOCKING RATE

Next, effects of soil type on pasture production and nitrogen supply are given. The production specified above, DMP, applies to the best soil type in the area. For other soil types, two reduction factors linearly reduce these productions according to soil limitations: RDMP and RDMUSE. A third factor is needed per soil type to calculate the soil nitrogen balance: NSUPL (explained below). These tree parameters need to be supplied for all soil types under study. Soil types are indicated by a three letter code, in our example SFW (Soil Fertile Well drained), SIW (Soil Infertile Well drained) and SFP (Soil Fertile Poorly drained). The soil names given here should correspond to the list of soil names available in the soil data file (SOIL.DAT; see Paragraph 4.1.2). RDMP quantifies the reduction in pasture production due to soil limitations such as acidity, poor drainage, nutrient shortage or low water holding capacity. In the example below, it is specified that there is no reduction in production on SFW soils since these soils are the best soils in the NAZ. SIW are acid soils, and target production levels are 80% of those on the best soils. SFP has drainage problems, but the natural grasses assumed to grow here are supposed to be species adapted to water excesses. Therefore, the yields on SFP soils are the same as on SFW soils, and the reduction factor is 1. RDMUSE quantifies the effect of soil type on the potential use fraction of the total above-ground biomass as function of stocking rate. Not all above-ground production can be eaten by grazing animals because i) parts such as stubble are ‘unreachable’ and should be left for regrowth, ii) parts 45 are trampled under the hooves of the animals, and iii) parts are (temporarily) unavailable because they are covered by manure or urine patches (Deenen, 1994; Van der Ven, 1992). The potential fraction of total above-ground biomass ‘on offer’ for consumption is called DMUSE, and depends on the amount of animals per surface unit (stocking rate). The factor DMUSE is - as standard - specified for the best soil type available in the area. The reduction factor RDMUSE adapts DMUSE to the conditions of the actual soil types to be studied. In our example, there is no extra reduction in fraction dry matter on offer on the soils SFW and SIW. The soil type SFP is poorly drained, however, and trampling on this soil causes an extra 80% reduction in fraction dry matter on offer. NSUPL quantifies the amount of nitrogen supplied by the pasture to ‘itself’. NSUPL is meant for grass-legume mixtures where the legume supplies nitrogen to the grass. In our example of natural pasture, there are no leguminous species and NSUPL is 0 on all soils. For the example of the B.brizantha + A. pintoi mixture in the file BPINTOI.DAT (Appendix 1.2.5), NSUPL is 150 kg/ha. Note: NSUPL is not to be confused with the parameter NFIX in the soil file that quantifies the amount of nitrogen fixed in the soil by free-living micro-organisms (Paragraph 4.1.2). * Yield reduction factors * SOILP: Soil name (character) * RDMP: Reduction fraction of attainable production (DMP as above) * due to soil limitations (-) (real)

* RDMUSE: Reduction fraction of potential dry matter on offer (DMUSE * see below), due to soil limitations. (-) (real) * NSUPL: Supply of nitrogen from legumes that may be present * e.g. as in grass-legume mixtures. (kg/ha) (real) * ------SOILP RDMP RDMUSE NSUPL ! Estimates from expert knowledge 'SFW' 1.0 1.0 0. 'SIW' 0.8 1.0 0. 'SFP' 1.0 0.8 0. Note: in this example, three soil types are supplied. This list can be shortened or extended (with a minimum of one soil type, and a maximum of 10). The soil names will appear in the complete code that characterises the pasture being modelled (see below).

The factor DMUSE specifies the fraction of the total-above ground matter potentially on offer for consumption as function of stocking rate, on the best soil type available in the area. Information on this relationship can be derived from experiments, expert knowledge or literature. The user is completely free to fill-in this table: the value of the stocking rates provided and the number of stocking rates can be adapted according to local conditions and wishes of the user (a minimum of one relationship should be provided; the maximum is 50). In our example, stocking rate varies from one to three. * SRATE: Stocking rate (animal units per ha) (real) * DMUSE: Potential fraction above-ground dry matter on offer * on best soils, as function of stocking rate (-) (real) * ------SRATE DMUSE ! estimated from expert knowledge 1. 0.55 1.5 0.525 2. 0.50 2.5 0.475 3. 0.45 46

The stocking rates will appear (preceded by the letter ‘R’) in the complete code that characterises the pasture being modelled (see below).

TECHNOLOGY: WEEDING

At his moment, PASTOU calculates the amount of (target) above-ground production that is available for consumption by the herd, for each soil and for each stocking rate. Unlike as in PASTOF, no production levels are set by manipulating fertiliser application. Different technologies are only defined by specification of the manner of weeding. The system is generic in the sense that the user can ‘build’ his own options for the manner in which weeds are controlled at the end of the file. From these own-build options, a selection can be made and used as input under WEED. This management input parameter (WEED) is preceded by a column that encodes the ‘technology’ level as a two-digit number. This two-digit number will appear (preceded by the one-letter code that indicates the type of pasture, see above) in the complete code that characterises the pasture(s) being modelled (see below). * PLEVEL: Code for technology level (2 numbers only!) (integer) * WEED: Manner of weeding (name) (character) * Select from options given below under 4.OPERATIONS) * ------PLEVEL WEED 20 'mixed' In our example, there is only one technology level that will be modelled by PASTOU. However, this list can be shortened or expanded to include various manners of weed control desired (a minimum of one, and a maximum of 50). PASTOU will calculate technical coefficients for all combinations of soil type, stocking rate and technology level so far specified (in our example three soil types, five stocking rates and one technology level, leading to 15 PASTs).

ESTABLISHMENT AND MAINTENANCE OPERATIONS

The pasture specified so far has to be established by sowing or planting (the only exception being ‘natural’ grass), and maintained and managed by operations. First, pasture establishment operations are specified by listing labour and material inputs required for two specific actions: i) application of herbicides to kill existing crops or natural vegetation, and ii) the application of a basic fertiliser gift. For the application of herbicides, the names of the herbicides, the amount of herbicides, the amount of labour used, and the equipment type of traction used need to be specified. The herbicides used have to be selected from the attribute file BIOCID.ATF, the equipments from the attribute file EQUIP.ATF file, and the tractions from the attribute file EQUIP.ATF. The units of the quantities of the herbicides, equipments and tractions have to be the same as those in these *.ATF files. When a desired herbicide/equipment/traction is not present in these files, they can be added by the user and then selected here. Several herbicides can be applied by listing these products in different rows. For the application of each herbicide, the amount of labour used is specified under EWLAB. Alternatively, a separate line can be used to enter all labour used for the application of all herbicides, and then a ‘0’ can be entered for each herbicide separately. For instance, in the example below, the first line is used to enter all labour, equipment and traction used for all herbicides together, and the herbicides are listed separately on the following lines. The number of entries (lines) is flexible and can be shortened or expanded by the user (minimum is one; maximum is five). 47

Separate lines are used to enter the fertilisers applied at establishment. This follows the same scheme as for the herbicides, with the difference that the fertilisers are selected from the FERT.DAT attribute file. Since all these data are used by PASTOF to calculate costs and total labour use for the pasture, the duration of the pasture has to be supplied at EDEP (needed to calculate annuities of costs). * EDEP Depreciation time of pasture (year) (real). * EWLAB/EFLAB Farm labour use for weeding/fertilising (hours) (real) * EWNAME/EFNAME Herbicide/fertiliser name (name) (character); * to select from BIOCID.ATF and FERT attribute files. * EWQUAN/EFQUAN Herbicide/fertiliser quantity (unit) (real) * EWEQ/EFEQ Herbicide/fertiliser equipment name (name) (character); * to select from EQUIP.ATF attribute file. * EWQUSE/EFQUSE Herbicide/fertiliser equipment use (hours) (real) * EWTRAC/EFTRAC Herbicide/fertiliser traction for equipment (name) * (character) to select from TRACTION.ATF attribute file. EDEP = 100.

EWLAB EWNAME EWQUAN EWEQ EWQUSE EWTRAC 0.0 'None' 0. 'none' 0. 'none'

EFLAB EFNAME EFQUAN EFEQ EFQUSE EFTRAC 0.0 'none' 0. 'none' 0. 'none' Natural grasses are a special case because the pasture is not truly ‘established’ since, by definition, a natural pasture already exists. In our example above, therefore, entries ‘0’ and ‘none’ are given to indicate that no labour nor any inputs are used in the ‘establishment’ of natural pasture. The depreciation period is set to an arbitrary high value of 100 years. An example for the establishment of a grass-clover mixture is found in Appendix 1.2.5.

Next, the input of labour and other materials for the establishment and maintenance of the pasture have to be supplied. Under OPER, a brief description of the operation can be supplied. The list then follows the same principle as above: materials have to be selected from the MATER.ATF attribute file, equipments from the EQUIP.ATF file and tractions from the EQUIP.ATF file. The units of the quantities of the materials, equipments and tractions have to be the same as those in the *.ATF files. When a desired material/equipment/traction is not present in these files, they can be added by the user and then selected here. The duration/lifetime can vary per material and therefore the depreciation time DEPRET has to be specified per material input. When materials are inputted each year, DEPRET should be set to ‘0’. In the example for natural pastures below, there are lines that specify the establishment of fences (lines 1-4), lines for the maintenance of the fences (line 5) and for the use of 5 small tools in general (e.g. a saw, a machete, a hammer, a bucket, a knife) (line 6). Sine natural grass is existent, there is no input of seeds or stolons (see Appendix 1.2.5. for an example of inputs for a grass-legume mixture). The fences (and the used fence materials) have a lifetime of six years and need to be replaced; the fences are maintained every year (DEPRET = 0), and the small tools have a lifetime of five years. The user can decrease or increase the list according to own specifications (with a minimum of one, a maximum of five). * OPER Name of operation (name) (character) * OWNLAB Own (farm) labour use (hours) (real) * MATER Name of used materials (name) (character) * to select from MATER.ATF attribute file. * MQUANT Materials quantity, in same unit as in materials file! (name) * (real) 48

* DEPRET Depreciation time of used materials (years) (real). * Note: when DEPRET is 0, the operation/inputs are yearly recurrent. * EQUIP Name of equipment used (name) (character), * to select from EQUIP.ATF attribute file. * EUSE Equipment use time (real) (hour) * TRAC Traction used to 'pull' equipment (name) (character) * to select from TRACTION.ATF attribute file. * Input data: Andre Nieuwenhuyse, based on farmer inquiries in the AZ (96-97) OPER OWNLAB MATER MQUANT DEPRET EQUIP EQUSE TRAC 'Labour fence estab.' 12. 'none' 0. 6. 'none' 0. 'none' 'Fences barbed wire' 0. 'bwire-Cai' 350. 6. 'none' 0. 'none' 'Fences dead' 0. 'dposts-sl' 33. 6. 'none' 0. 'none' 'Fences nails' 0. 'cramp-l' 0.5 6. 'none' 0. 'none' 'Fence maintenance' 2. 'none' 0. 0. 'none' 0. 'none' 'Various small tools' 0. 'stools' 5. 5. 'none' 0. 'none'

WEEDING APPLICATION MANNER

The last section of the data file is meant to ‘build’ own specifications of recurrent weeding practices. Unlike as for PASTOF, the amount of labour and amount of herbicides can be entered directly, since the above-ground biomass (and hence the soil cover) are not calculated by the model but are entered directly by the user. The input for weeding operations follows the same structure as for PASTOF (Paragraph 4.1.1). For each manner of weeding that the user wants to ‘build’, the following inputs need to be specified: labour use, type and amount of herbicides applied, and equipment and traction used in the application of the herbicides. All inputs are yearly totals (per hectare). Because more than one type of herbicide may be applied, there is provision to enter data for up to three herbicides. The labour use, and the use of equipment and traction on each line are the totals of all labour, equipment and traction used in the whole year (summed over all manual weeding and the application of all the herbicides). On each line, manual weeding - in the from of labour hours invested - and chemical weeding may be combined by summing all labour used under OL. The name of the manner should be entered under WEEDN. This name can then be used earlier in the file to select the manner of weeding that is to be modelled (under WEED; see above). In the example below, three weeding manners have been build; a strict manual weeding, a strict chemical weeding, and a mixed manner with both manual and chemical weeding. The user is free to ‘build’ any number of alternative weed control manners (with a minimum of one, a maximum of five). Quantitative data on labour hours and chemical inputs have to be obtained from field enquiries and from expert knowledge. * WEEDN Name of weeding manner (name) (character) * OL (total) Own (farm) labour use (hour/year) (real) * C1N Name of first herbicide input (name) (character) * to select from BIOCIDE.ATF attribute file. * C1Q Quantity of first herbicide input (amount/year) (real) * Units of quantity should match those in biocide file! * C2N Name of second herbicide input (name) (character) * to select from BIOCIDE.ATF attribute file. * C2Q Quantity of second herbicide input (amount/year) (real) * Units of quantity should match those in biocide file! * C3N Name of third herbicide input (name) (character) * to select from BIOCIDE.ATF attribute file. 49

* C3Q Quantity of third herbicide input (amount/year) (real) * Units of quantity should match those in biocide file! * WEQ Equipment used for weeding (name) (character) * to select from EQUIPMENT.ATF attribute file. * WEQU Use time of equipment (hours/year) (real) * WTRA Traction used to 'pull' equipment (name) (character) * to select from TRACTION.ATF attribute file. * Input data: Andre Nieuwenhuyse, based on farmer inquiries in the AZ (96-97) WEEDN OLWEED C1N C1Q C2N C2Q C3N C3Q WEQ WEQU WTRA 'manual' 10. 'None' 0. 'None' 0. 'None' 0. 'none' 0. 'none' 'chemic' 6.0 '24D' 3.0 'Tordon-101' 1.0 'Combo' 0.035 'ksspray' 6.0 'none' 'mixed' 7.0 '24D' 1.5 'Tordon-101' 0.5 'Combo' 0.035 'ksspray' 3.5 'none'

CODING OF GENERATED PASTS

PASTOU produces output files that contain technical coefficients of all modelled alternative pasture production systems (PAST). Many PASTs may be generated in one run of PASTOF for a single pasture type because the model is repeatedly executed with different combinations of soil type, stocking rate and technology level as specified in the pasture data file. Each PAST is recognised by a code, written in the first column of each output file. The explanation of this code is given for an example generated by PASTOU for one of the alternatives specified in the example pasture data file NATURAL.DAT.

SFW.N20.R1.JAN where:  SFW is the soil type (SOILP)  N20 is a combination of the one-letter code for the pasture name (GCODE) with the technology level (PLEVEL)  R1 indicates the stocking rate (SRATE)  JAN indicates the month for which the particular TC in the file is valid (MONTH; not used in all files)

4.2.2 Soil, CAT_CHAR and site data file

The soil, CAT_CHAR and site data files used by PASTOU are exactly the same as those used by PASTOF (Paragraphs 4.1.2-4.1.4).

4.3 Special case: reruns

PASTOF and PASTOU calculate technical coefficients for all alternative pasture production systems (PASTs) as specified in the pasture data files. One pasture data file may lead to different PASTs for one pasture type (botanical composition, e.g. Estrella grass). However, it could be interesting to generate PASTs for a number of different pasture types. The rerun option of PASTOR allows that 50

PASTOF and PASTOU are automatically executed several times by reading and using subsequent pasture data files. A RERUNS.DAT file should be created and put in the PASTOF or PASTOU sub- directory. This RERUNS.DAT file should contain the names of alternative pasture input files that should be used. This is done by repeating the name and path of the FILEI1 parameter in the CONTROL.DAT file, but using different data file names. For example, the following RERUNS.DAT file causes PASTOF first to generate PASTs for the pasture Estrella (as ESTREL.DAT was specified in CONTROL.DAT; see Paragraph 4.1.1), and then subsequently PASTs for the pastures Brachiaria brizantha (as specified in BBRIZAN.DAT) and Tanner (as specified in TANNER.DAT)

FILEI1 = 'C:\PASTOR\FILE_IN\PASTO\BBRIZAN.DAT' FILEI1 = 'C:\PASTOR\FILE_IN\PASTO\TANNER.DAT'

Note: remember that each pasture file should have a unique one-letter code to indicate the pasture type (e.g. ‘E’ for Estrella, ‘T’ for Tanner etc.).

When no reruns are wished, the RERUNS.DAT file should be removed from the sub-directory, or an asterix may be put in front of each line in the file. 51

5 Generating Feed Acquisition Systems (FASTs)

The model to generate feed acquisition systems (FASTs) is run by giving the SUPP.EXE command in the PASTOR\PASF_SUPP sub-directory. In this chapter, the control over SUPP is explained. SUPP is a very simple model that merely selects a number of supplementary feed options and ‘transforms’ the data format of the file that contains the feed attributes to the standard output format.

In CONTROL.DAT (in the sub-directory MOD_SUPP), the required model input, attribute and output files of SUPP are specified:

*************************** CONTROL.DAT *********************** * Control file for SUPP model * * PASTOR 2.0 * *************************************************************** * FILEI1 Attribute file with supplementary feed attribute data * FILEI2 Input file with supplementary feed input data * FILEI3 Input file with site data * FILEO2 Output file with labour and costs data * FILEO3 Output file with nutrition value data

FILEI1 = 'C:\PASTOR\FILE_ATR\FEEDS.ATF' FILEI2 = 'C:\PASTOR\FILE_IN\FEED\FEEDS.DAT' FILEI3 = 'C:\PASTOR\FILE_IN\SITE.DAT' FILEO2 = 'C:\PASTOR\FILE_OUT\FEEDLC.PRN' FILEO3 = 'C:\PASTOR\FILE_OUT\FEEDP.PRN'

The input and attribute files needed are specified at the variables FILEI1-3. Note that, beside the file name, the complete path is given. Users may change the names of the data files when they have created their own input files: FILEI1 contains the attribute file of all feed supplements available; FILEI2 contains the names of the supplementary feeds selected, and FILEI3 lists the site file that contains so-called ‘site’ data, such as rate of interest and work-hours in a day, that are also used by the other models of PASTOR. The input file FEEDS.DAT is explained in detail below.

Attribute files (FILEI1) are explained in Chapter 6. The name of the attribute file should not be changed by the user.

The names of the output files are given under the variables FILEO2-3. These names are the same as given in Table 2.3.1, but may be changed by the user.

In the file FEEDS.DAT, a number of supplementary feed types should be supplied under SFNAME. Feed types are to be selected from the FEEDS.ATF file. If required, the FEEDS.ATF file can be updated to include the supplementary feed types of interest. Each selected supplementary feed type in FEEDS.DAT should be accompanied by a number of parameters that specify the labour and equipments involved in distributing the feed supplement to the cattle. The labour use (LABUSE; in hour per kg of product) typically involves carrying the feed supplement to a trough or to a common eating-place of the cattle. Equipments to carry the feed on the farm (EQUIP) can be selected from the EQUIP.ATF attribute file (e.g. wheel-barrow). Some equipments need ‘traction’ for pulling (e.g. a tractor to pull a chart), (TRAC), which may be selected from the TRACTION.ATF attribute file. All 52 entries for LABUSE, EQUIP, EQUSE and TRAC refer to activities in carrying and distributing the feed supplement on-farm to the animals. In the example below, four feed supplements have been selected from the FEEDS.ATF attribute file. It takes 0.01 hour to carry and distribute 1 kg of molasse to the animals; 0.003 hours for 1 kg of bananas; 0.007 hours for 1 kg of concentrate type number 2; and 0 hours for phosphorus concentrate p20 (because this product is mixed with salt, and the distribution time for salt to the animals is already included under MSLAB in the herd management data file; Paragraph 3.1.2!). All feed supplements are distributed by hand and by generally available tools on the farm (e.g. a spade as included under T3MAT in the herd management data file; Paragraph 3.1.2). * SFNAME Supplementary feed name (name) (character) * LABUSE Labour use to deliver supplementary feed on farm (hr/kg) (real) * EQUIP Equipment used to deliver suppl. feed on farm (name) (character) * EQUSE Time use of equipment (hr/kg) * TRAC Traction used to 'pull' equipment (name) (character)

SFNAME LABUSE EQUIP EQUSE TRAC 'molasse' 0.01 'none' 'none' 'none' 'banana' 0.003 'none' 'none' 'none' 'conc2' 0.007 'none' 'none' 'none' 'p20' 0.0 'none' 'none' 'none'

The list presented here contains four feed supplements. This list can be shortened (with a minimum of one) or extended (up to a maximum of 25). A complete FEEDS.DAT data file is given in Appendix 1.3.3. 53

6 Attribute files

There are seven so-called attribute files (Figure 2.1) that list attributes (characteristics) of items that can be referred to in input files of PASTOR. For example, in the pasture data and herd management input files, reference can be made to materials that are listed in the MATER.ATF attribute file. Wherever attribute files are used in the input data files, the name of these attribute files are explicitly mentioned in the input files. Having attributes of inputs of production systems stored in separate files facilitates the use of these attributes in various model input data files (Stoorvogel, 1995; Jansen & Schipper, 1995).

Common attributes of items in the attribute files are:

CODE a numerical code (obsolete) NAME name of the item DESCR brief description of the item UNIT unit of measure of item PRICE price of the item PY year that price information was collected PM month that price information was collected

The above names are generally preceded by a letter that indicates the type of the item, such as ‘M’ for ‘materials’, ‘E’ for ‘equipments’, ‘T’ for ‘traction types’, etc. Furthermore, different attribute files may hold additional attributes, such as nutrition data in the FEEDS.ATF file and pesticide data in the BIOC.ATF file. These data are all explained in the headers of the files. Attribute information is used by PASTOR in the computation of cost prices, labour requirement and some environmental indicators (namely the PEII, Paragraph1.2.3). Appendix II lists all attribute files currently present in PASTOR 2.0. Users may update these files according to own wishes and insights by editing the existing attributes (such as price updates) and/or by adding new lines with new items. The only restriction for adding new lines is that all columns must be filled-in. The CODE column is currently obsolete and any ‘dummy’ number can be filled-in.

In PASTOR, there is a fixed maximum number of the rows for each attribute file. When users make the number of rows too large, the file can not be read by the PASTOR programs and a Fortran error message occurs. This problem can be solved by removing some lines with items that are not used in the data input files. 54

7 Error and warning messages

Care has been taken to ‘safeguard’ the user from making errors - or getting model run time errors - when executing PASTOR. However, errors may still occur when running PASTOR models, and here are some solutions to possibly occurring problems. Some error and warning messages have been programmed by the authors of PASTOR (and by the subroutines that it uses), while other errors may come from Fortran itself in the form of run-time errors.

Input data error  All data in the input data files and in the attribute files are checked during model execution on impossible and/or unlikely values. For example, negative prices or negative growth rates of animals are not allowed, and the user gets an error message when PASTOR reads these data. In general, this error message is accompanied with a brief text explaining the nature of the problem. Refer to the corresponding section of this manual when the explanation for the particular error insufficiently clear to solve the problem.  The models of PASTOR are written in the Fortran language. This means that all input parameters must have a certain ‘format’. The format of each parameter is indicated in the example files: Integer: whole number (numeric) without a ‘dot’; e.g. 1, 50 or 100; Real: any number (numeric) with a ‘dot’; e.g. 0.23, 1. or 100.; Character: characters (words or abbreviations) put between ‘ ‘; e.g. ‘H’. When parameters are specified in the wrong format, the models give error messages when trying to read these data.  Some data in input and attribute files are supplied in columns (e.g. all attribute file data, the attainable production data in the pasture input files). In PASTOR, a maximum array-size is defined for each of these ‘column-variables’. When the column size (i.e. number of rows) has been made larger (by entering too many lines) than this pre-defined array-size, Fortran run-time errors are returned during execution of PASTOR. This problem can be solved by removing (condensing) some lines in the input files.  When required input data have been omitted in a data input file, an error message is returned when PASTOR tries to read this data from file. Generally, a good indication is given about which data element is lacking in which file.

File name/location error When files are not present under the name and in the directory as specified in the CONTROL.DAT files, PASTOR returns an error message on the file name that it is unable to find. Remedy: check thoroughly names and paths of the input/output files in CONTROL.DAT files.

Runtime error  Despite careful checking on impossible/unlikely input data, runtime errors during execution of PASTOR might still happen. Such errors are generally caused by execution of ‘impossible’ equations, such as division by zero. Another error might be the writing of output data to files with ‘insufficient’ space allocated (e.g. trying to write a seven digit number to a space for a six digit number only). Such errors are inherent in scientific programs and can not be avoided for 100%. The only solution is to double-check all data entries and look for unlikely combinations of input data.  A number of runtime checks have been build-in by the developers of PASTOR, and concern mass and nutrient balance checking. These checks are to safeguard against erroneous model results. 55 56

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Appendix I: PASTOR input files

I.1 APST input files

I.1.1 CRIAHRD.DAT

************************** CRIAHRD.DAT**************************** * Data file for CRIA.FOR, as in PASTOR version 2.0 * ****************************************************************** * Correction factor for maintenace energy required to support grazing * (NRC, 1989; page 7): * MAINK = 1.0: for stable-fed * MAINK = 1.1: for good pasture * MAINK = 1.2; for sparse pasture and long walking distance * Bounded by 1.0 - 1.2 MAINK = 1.2

* One-letter code for herd (B from breeding) HCODE = 'B'

* Herd size (no) (INTEGER); bounded by 1 and 900 HSIZE = 50

* ITYPEF/M: Type of DAIRY cattle (-) (integer) * ITYPEF = 1: female, large breed (max weight is 800 kg) * ITYPEF = 2: female, small breed (max weight is 600 kg) * ITYPEM = 3: male, large breed (max weight is 1000 kg) * ITYPEM = 4: male, small breed (max weight is 800 kg) ITYPEF = 1 ITYPEM = 3

* Breed effect on maintenace requirements (NRC, 1996, p 115) BE = 0.90

* SRW: see page 116 (NRC, 1996); * FSBW = actual final shrunk body weight at maturity SRW = 435. FSBW = 550.

* Maximum age of reproductive female animal (year) (integer) * bounded by 0 and 20. IAMAX = 11

* Live weight of animal at birth (kg) (real) LWB = 32.

* Age of selling of male surplus (month) (real), bounded by 0 * and 12 * IAMAX ASMS = 8.

* Age of selling of female surplus (month) (real), bounded by 0 * and 12 * IAMAX ASFS = 8.

* Live weight gain of males in year 0-1 (LWGM0), year 1-2 (LWGM1), * year 2-4 (LWGM2), and after year 4 (LWGM3). (kg/day) (real) LWGM0 = 0.65 LWGM1 = 0.45 LWGM2 = 0.25 LWGM3 = 0.

* Live weight gain of females in year 0-1 (LWGF0), year 1-2 (LWGF1), * year 2-4 (LWGF2), and after year 4 (LWGF3). (kg/day) (real) LWGF0 = 0.52 LWGF1 = 0.36 LWGF2 = 0.135 LWGF3 = 0. I-2

* Mortality rate in age class 0 (0-1 years), age class 1 (1-2 years), * and after age class 1 (-) (real). Bounded by -0 and 0.99. MRATE0 = 0.1 MRATE1 = 0.02 MRATE = 0.01

* Abortion rate (-) (real), bounded by -0 and 0.99 AR = 0.0

* Age at first calving of reproductive female (month) (real) * Should be higher than 12 and lower than 60 months AFC = 31.

* Calving interval (month) (real), bounded by -0. CI = 14.

* Duration of lactation (month) (real). Should be <= CI - 2. DLAC = 8.

* Duration of pregnancy (month) (real). Should be <= CI DPREG = 9.

* MILKKG: Milk production during lactation, bounded by 0 and * 100 (kg/d) (real) MILK = 3.5

* Fraction of milk produced by herd that is used for human consumption * bounded by 0. and 1. (-) (real) FMLKH = 0.

* Percentage milk fat, bounded by 0 and 10 (%) (real) FAT = 4.5

* Specific weight of milk (kg/l) SWMILK = 1.03

* Energy concentration of diet fed/NRC (1988) assumption (FEDNRC) with * suggested range from 0.95 - 1.05. (bounded by 0.9-1.1) (-) (real)

FEDNRC = 1.

I.1.2 CRIAMAN.DAT

************************** CRIAMAN.DAT**************************** * Data file for CRIA.FOR; as in PASTOR 2.0 * * Management data of cria herd * * THESE DATA FOR CRIA HERDS IN AZ; A. NIEUWENHUYSE, APRIL 97 * ******************************************************************

****************************************************************** * 1. Definition of herd sizes that have scale-specific requirements ****************************************************************** * HRDCLAS Herd size class (number) (integer) * HRDMIN Minimum number of animals in herd (number) (INTEGER) * HRDMAX Maximum number of animals in herd (number) (INTEGER)

HRDCLAS HRDMIN HRDMAX 1 1 10 2 11 30 3 31 60 4 61 100

****************************************************************** * 2. Materials and tools * 2.1 Corral construction per herd size class ****************************************************************** * CRDCLAS Herd size class (number) (integer) * CROLAB Own (farm) labour for corral construction (hour/corral) (real) * CRMAT Name of corral material (name) (character) * Select from MATER.ATF attribute file. I-3

* CRQUAN Quantity of corrals (number) (real) * CRDEP Depreciation time of the corral (year) (real)

CRCLAS CROLAB CRMAT CRQUAN CRDEP 1 0. 'corral1' 1. 30. 2 0. 'corral2r' 1. 30. 3 0. 'corral3r' 1. 30. 4 0. 'corral4r' 1. 30.

****************************************************************** * 2. Materials and tools * 2.2 Mineral salt troughs per herd size class ****************************************************************** * MTDCLAS Herd size class (number) (integer) * MTMAT Name of trough (name) (character) * Select from MATER.ATF attribute file. * MTQUAN Quantity of troughs (number) (real) * MTDEP Depreciation time of trough (year) (real)

MTCLAS MTMAT MTQUAN MTDEP 1 'trough' 1. 5. 2 'trough' 4. 5. 3 'trough' 5. 5. 4 'trough' 6. 5.

****************************************************************** * 2. Materials and tools * 2.3 Tools 1 to 3 used. ****************************************************************** * T_CLAS Herd size class (number) (integer) * T_MAT Name of used materials (name) (character) * Select from MATER.ATF attribute file. * T_QUAN Materials quantity, in same unit as in materials file! (name) (real) * T_DEP Depreciation time of used materials (years) (real). * Note: when T_DEP is 0, the tools are yearly acquired.

* Tool1 per herd size class T1CLAS T1MAT T1QUAN T1DEP 1 'stools' 10. 5. 2 'stools' 10. 5. 3 'stools' 10. 5. 4 'stools' 10. 5.

* Tool2 per herd size class T2CLAS T2MAT T2QUAN T2DEP 1 'ltools' 3. 3. 2 'ltools' 4. 3. 3 'ltools' 5. 3. 4 'ltools' 8. 3.

* Tool3 per herd size class T3CLAS T3MAT T3QUAN T3DEP 1 'none' 0. 0. 2 'none' 0. 0. 3 'none' 0. 0. 4 'none' 0. 0.

****************************************************************** * 3. Operations * 3.1 Miscellaneous operations on the herd (general health care, * presence, snakes chasing,..) per herd size class ****************************************************************** * CHCLAS Herd size class (number) (integer) * CHLAB Own (farm) labour use (hours/year) (real) * CHMAT Health materials used (character) * Select from CATTLE.ATF attribute file. * CHQUAN Quantity of healht materials used (unit) CHCLAS CHLAB CHMAT CHQUAN 1 180. 'emicina' 50. 2 240. 'emicina' 100. 3 300. 'emicina' 250. 4 360. 'emicina' 400.

****************************************************************** * 3. Operations * 3.2. Assistance at birth I-4

****************************************************************** * BRTLAB Own (farm) labour use for assistence at calving (hour/born calve) (real) BRTLAB = 3.

****************************************************************** * 3. Operations * 3.3. Salt application ****************************************************************** * MSNAME Name of salt (name) (character) * Select from FEED.ATF attribute file. * MSQUAN Quantity of salt application (kg/day/AU) (real)

MSNAME MSQUAN 'salt' 0.05

* Labour Labour needed for application of minerals and salts * CMCLAS Herd size class (number) (integer) * MSLAB Labour use to supply all mineral salt (hour/year) (real) CMCLAS MSLAB 1 26. 2 30. 3 40. 4 50.

****************************************************************** * 3. Operations * 3.4. One-time inocculation/protection of born animals ****************************************************************** * I1NAME Name of (inocculation) material (name) (character) * Select from CATTLE.ATF attribute file. * I1QUAN Quantity (of inocculation) per application (unit) (real) * I1LAB Labour use per inocculation, including round-up to corral (hour/animal) (real) I1NAME I1QUAN I1LAB 'brucel' 1. 0.15 'dectomax' 6. 0.30 'bacterine' 5. 0.10

****************************************************************** * 3. Operations * 3.5. Recurrent inocculation (I2) of all animals ****************************************************************** * I2NAME Name of inocculation material (name) (character) * Select from CATTLE.ATF attribute file. * I2UNIT Herd unit for application, either 'animal' (per animal) or 'aunit' (per an. unit) * I2FREQ Frequency of application (times per year per I2UNIT) (real) * I2QUAN Quantity of inocculation per application (unit) (real) * I2LAB Labour use for inocculation, without round-up time to corral (hour/I2UNIT) (real) I2NAME I2UNIT I2FREQ I2QUAN I2LAB 'ripercol' 'aunit' 2. 20. 0.1 'bacterine' 'animal' 2. 5. 0.1 'anthrax' 'animal' 2. 5. 0.1 'neguvon' 'aunit' 5. 0.005 0.07

* I2CLAS Herd size class (number) (integer) * I2RNO Number of round-ups per year for inocculation (number) (real) * I2RLAB Round-up time to corral for inocculation (hour/round up) (real) I2CLAS I2RNO I2RLAB 1 6. 0.15 2 6. 0.30 3 6. 0.67 4 6. 1.00

I.1.3 GORDHRD.DAT

************************** GORDHRD.DAT**************************** * Data file for GORDO.FOR, as in PASTOR version 2.0. * ****************************************************************** * Correction factor for maintenace energy required to support grazing * (NRC, 1989; page 7): * MAINK = 1.0: for stable-fed * MAINK = 1.1: for good pasture * MAINK = 1.2; for sparse pasture I-5

* Bounded by 1.0 - 1.2 MAINK = 1.2

* One-letter code for herd (F from fattening) HCODE = 'F'

* Herd size (no) (INTEGER); bounded by 1 and 900 HSIZE = 50

* ITYPEF/M: Type of cattle (-) (integer) * ITYPEF = 1: female, large breed (max weight is 800 kg) * ITYPEF = 2: female, small breed (max weight is 600 kg) * ITYPEM = 3: male, large breed (max weight is 1000 kg) * ITYPEM = 4: male, small breed (max weight is 800 kg) ITYPEF = 1 ITYPEM = 3

* Breed effect on maintenace requirements (NRC, 1996, p 115) BE = 0.90

* Herd male/female animal ration: RATIOMF = 1.5

* SRW: see page 116 (NRC, 1996); * FSBW = actual final shrunk body weight at maturity SRW = 435. FSBW = 550.

******************************************************************* * WBUY, WSELL and LWG: make sure that animals are at least 1 month * on the farm, i.e.: (WSELL-WBUY)/LWG should be larger than 31 days. ******************************************************************* * Live weight of animal at buying (kg) (real); for male calves * (WBUYM) and female calves (WBUYF) WBUYM = 190. WBUYF = 160.

* Live weight of animal at selling (kg) (real); for males (WSELLM) * and for females (WSELLF) WSELLM = 450. WSELLF = 400.

* Live weight gain of animals (kg/day) (real); for males (LWGM) * and for females (LWGF) LWGM = 0.5 LWGF = 0.4

* Mortality rate (real). Bounded by -0 and 0.99. MRATE = 0.01

* Energy concentration of diet fed/NRC (1988) assumption (FEDNRC) with * suggested range from 0.95 - 1.05. (bounded by 0.9-1.1) (-) (real)

FEDNRC = 1.

I.1.4 GORDMAN.DAT

************************** GORDMAN.DAT**************************** * Data file for GORDO.FOR, as in PASTOR version 2.0. * * Management data of engorde herd * * THESE DATA FOR ENGORDE HERDS IN AZ; A. NIEUWENHUYSE, APRIL 97 * ******************************************************************

****************************************************************** * 1. Definition of herd sizes that have scale-specific requirements ****************************************************************** * HRDCLAS Herd size class (number) (integer) * HRDMIN Minimum number of animals in herd (number) (INTEGER) * HRDMAX Maximum number of animals in herd (number) (INTEGER)

HRDCLAS HRDMIN HRDMAX 1 11 30 2 31 60 I-6

3 61 100

****************************************************************** * 2. Materials and tools * 2.1 Corral construction per herd size class ****************************************************************** * CRDCLAS Herd size class (number) (integer) * CROLAB Own (farm) labour for corral construction (hour/corral) (real) * CRMAT Name of corral material (name) (character) * Select from MATER.ATF attribute file. * CRQUAN Quantity of corrals (number) (real) * CRDEP Depreciation time of the corral (year) (real)

CRCLAS CROLAB CRMAT CRQUAN CRDEP 1 0. 'corral2' 1. 25. 2 0. 'corral3' 1. 25. 3 0. 'corral4' 1. 25.

****************************************************************** * 2. Materials and tools * 2.2 Mineral salt troughs per herd size class ****************************************************************** * MTDCLAS Herd size class (number) (integer) * MTMAT Name of trough (name) (character) * Select from MATER.ATF attribute file. * MTQUAN Quantity of troughs (number) (real) * MTDEP Depreciation time of trough (year) (real)

MTCLAS MTMAT MTQUAN MTDEP 1 'trough' 4. 5. 2 'trough' 5. 5. 3 'trough' 6. 5.

****************************************************************** * 2. Materials and tools * 2.3 Tools 1 to 3 used. ****************************************************************** * T_CLAS Herd size class (number) (integer) * T_MAT Name of used materials (name) (character) * Select from MATER.ATF attribute file. * T_QUAN Materials quantity, in same unit as in materials file! (name) (real) * T_DEP Depreciation time of used materials (years) (real). * Note: when T_DEP is 0, the tools are yearly acquired.

* Tool1 per herd size class T1CLAS T1MAT T1QUAN T1DEP 1 'stools' 10. 5. 2 'stools' 10. 5. 3 'stools' 10. 5.

* Tool2 per herd size class T2CLAS T2MAT T2QUAN T2DEP 1 'ltools' 4. 3. 2 'ltools' 5. 3. 3 'ltools' 8. 3.

* Tool3 per herd size class T3CLAS T3MAT T3QUAN T3DEP 1 'none' 0. 0. 2 'none' 0. 0. 3 'none' 0. 0.

****************************************************************** * 3. Operations * 3.1 Miscellaneous operations on the herd (general health care, * presence, snakes chasing,..) per herd size class ****************************************************************** * CHCLAS Herd size class (number) (integer) * CHLAB Own (farm) labour use (hours/year) (real) (Put to * 70% of cria herd) * CHMAT Materials used in health care (character) * Select from CATTLE.ATF attribute file. * CHQUAN Quantity of materials used in health care (in same unit as in * CATTLE.ATF file) CHCLAS CHLAB CHMAT CHQUAN 1 168. 'emicina' 100. I-7

2 210. 'emicina' 250. 3 252. 'emicina' 400.

****************************************************************** * 3. Operations * 3.3. Salt application ****************************************************************** * MSNAME Name of salt (name) (character) * Select from FEED.ATF attribute file. * MSQUAN Quantity of salt application (kg/day/AU) (real)

MSNAME MSQUAN 'salt' 0.05

* Labour Labour needed for application of minerals and salts * CMCLAS Herd size class (number) (integer) * MSLAB Labour use to supply all mineral salt (hour/year) (real) CMCLAS MSLAB 1 30. 2 40. 3 50.

****************************************************************** * 3. Operations * 3.4. One-time inocculation/protection of bought animals ****************************************************************** * I1NAME Name of (inocculation) material (name) (character) * Select from CATTLE.ATF attribute file. * I1QUAN Quantity (of inocculation) per application (unit) (real) * I1LAB Labour use per inocculation, including round-up to corral (hour/animal) (real) I1NAME I1QUAN I1LAB 'none' 0. 0.

****************************************************************** * 3. Operations * 3.5. Recurrent inocculation (I2) of all animals ****************************************************************** * I2NAME Name of inocculation material (name) (character) * Select from CATTLE.ATF attribute file. * I2UNIT Herd unit for application, either 'animal' (per animal) or 'aunit' (animal unit) * I2FREQ Frequency of application (times per year per I2UNIT) (real) * I2QUAN Quantity of inocculation per application (unit per I2UNIT) (real) * I2LAB Labour use for inocculation, without round-up time to corral (hour/I2UNIT) (real) I2NAME I2UNIT I2FREQ I2QUAN I2LAB 'dectomax' 'aunit' 3. 8. 0.1 'bacterine' 'animal' 2. 5. 0.1 'anthrax' 'animal' 2. 5. 0.1 'neguvon' 'aunit' 5. 0.005 0.07

* I2CLAS Herd size class (number) (integer) * I2RNO Number of round-ups per year for inocculation (number) (real) * I2RLAB Round-up time to corral for inocculation (hour/round up) (real) I2CLAS I2RNO I2RLAB 1 6. 0.30 2 6. 0.67 3 6. 1.00

I.2 PAST input files

I.2.1 ESTREL.DAT

******************************* ESTREL.DAT *************************** * Pasto input data file for program PASTOF, as in PASTOR version 2.0 * * All data are per hectare * * Date: 09-09-1997; Author: B.A.M. Bouman, REPOSA. * * Data for grass: Estrella (Cynodon nlemfuensis) * * Most data are based on expert knowledge, an interpretation of * * various literature sources, and data collected by REPOSA. * * Experts: A. Nieuwenhuyse, M. Ibrahim, M. Villareal Castro. * * Literature: separate list available. * *********************************************************************** I-8

* GNAME : Pasture name (character) * GCODE : Pasture code (one letter only!) (character) * ------GNAME = 'Estrella' GCODE = 'E'

***************************************************************** * 1. PASTURE CHARACTERISTICS * ***************************************************************** * Pasture data at level of attainable production (PER MONTH): * MONTH: Name of month (character) * DMP: (above-ground total) Dry matter attainable production * on best soils (kg/month) (real) * CP: Crude Protein content (%) (real) * ME: Metabolizable energy content (Mcal/kg) (real) * P: Phosphorus content (%) (real) * K: Potassium content (%) (real) * ------MONTH DMP CP ME P K 'JAN' 1928. 11.0 2.3 0.35 3.7 ! Literature, expert knowledge 'FEB' 1928. 11.0 2.3 0.35 3.7 ! Total PP: 28 t/ha 'MAR' 1928. 11.0 2.3 0.35 3.7 'APR' 2468. 12.0 2.5 0.30 3.5 'MAY' 2468. 12.0 2.5 0.30 3.5 'JUN' 2468. 12.0 2.5 0.30 3.5 'JUL' 2468. 12.0 2.5 0.30 3.5 'AUG' 2468. 12.0 2.5 0.30 3.5 'SEP' 2468. 12.0 2.5 0.30 3.5 'OCT' 2468. 12.0 2.5 0.30 3.5 'NOV' 2468. 12.0 2.5 0.30 3.5 'DEC' 2468. 12.0 2.5 0.30 3.5

* Minimum nutrient and energy concentrations when no external (manure, * fertilizer) nutrients are supplied. (minimum production level). * CPMIN: Minimum Crude Protein content (%) (real) * MEMIN: Minimum Metabolizable energy content (Mcal/kg) (real) * PMIN: Minimum Phosphorus content (%) (real) * KMIN: Minimum Potassium content (%) (real) *------* From variety of literature and expert knowledge CPMIN = 6. MEMIN = 1.5 PMIN = 0.12 KMIN = 1.4

******************************************************************* * 2. PASTURE RESPONSES TO SOIL TYPES: ATTAINABLE PRODUCTION * ******************************************************************** * Yield reduction factors * SOILP: Soil name (character) * RDMP: Reduction fraction of attainable production (DMP as above) * due to soil limitations (-) (real) * RDMUSE: Reduction fraction of potential dry matter on offer (DMUSE * see below), due to soil limitations. (-) (real) * ------SOILP RDMP RDMUSE ! literature, expert knowledge 'SFW' 1.0 1.0 'SIW' 0.7 1.0 'SFP' 0.4 0.8

********************************************************************** * 3. MANAGEMENT CHARACTERISTICS * *********************************************************************** * SRATE: Stocking rate (animal units per ha) (real) * DMUSE: Potential fraction above-ground dry matter on offer * on best soils, as function of stocking rate (-) (real) * ------* Note: keep 'definition' the same in all files: SRATE DMUSE ! Expert knowledge 1. 0.55 1.5 0.525 2. 0.50 2.5 0.475 3. 0.45

* Data for target Production level I-9

* PLEVEL: Code for technology level (2 numbers only!) (integer) * FGIFT: Fraction of fertilizer N gift to realize maximum * attainable production (-) (real) * FERTAP: Manner of fertilizer application (name) (real) * Select from options given below under 4.OPERATIONS) * WEED: Manner of weeding (name) (character) * Select from options given below under 4.OPERATIONS) * ------PLEVEL FGIFT FERTAP WEED ! User defined 11 0.00 'manual' 'mixed' 20 0.20 'manual' 'mixed' 40 0.40 'manual' 'mixed' 60 0.60 'manual' 'mixed' 80 0.80 'manual' 'mixed' 99 1.00 'manual' 'mixed'

*********************************************************************** * 4.OPERATIONS * *********************************************************************** * 4.0 establishment of pasto: herbicides and fertilizer application * Note: land preparation and sowing/planting are specified in * section 4.1 below * EDEP Depreciation time of pasto (year) (real). Note: see also 4.1 below * EWLAB/EFLAB Farm labour use for weeding/fertilizing (hours) (real) * EWNAME/EFNAME Herbicide/fertilizer name (name) (character); * to select from BIOCID.ATF and FERT attribute files. * EWQUAN/EFQUAN Herbicide/fertilizer quantity (unit) (real) * EWEQ/EFEQ Herbicide/fertilizer equipment name (name) (character); * to select from EQUIP.ATF attribute file. * EWQUSE/EFQUSE Herbicide/fertilizer equipment use (hours) (real) * EWTRAC/EFTRAC Herbicide/fertilizer traction for equipment (name) (character) * to select from TRACTION.ATF attribute file. * Input data: Andre Nieuwenhuyse, based on farmer inquiries in the AZ (96-97)

EDEP = 10.

* 4.1 Operations that are investments and recurrent variables independent * of production level (all entries per ha) * OPER Name of operation (name) (character) * OWNLAB Own (farm) labour use (hours) (real) * MATER Name of used materials (name) (character) * to select from MATER.ATF attribute file. * MQUANT Materials quantity, in same unit as in materials file! (name) (real) * DEPRET Depreciation time of used materials (years) (real). * Note: when DEPRET is 0, the operation/inputs are yearly recurrent. * EQUIP Name of equipment used (name) (character) * to select from EQUIP.ATF attribute file. * EUSE Equipment use time (real) (hour) * TRAC Traction used to 'pull' equipment (name) (character) * to select from TRACTION.ATF attribute file. * Input data: Andre Nieuwenhuyse, based on farmer inquiries in the AZ (96-97) * Fences: 2. Short lasting fences; dead posts

OPER OWNLAB MATER MQUANT DEPRET EQUIP EQUSE TRAC 'Grass sowing' 30. 'gstolE' 1.5 10. 'none' 0. 'none' 'Labour fence estab.' 12. 'none' 0. 6. 'none' 0. 'none' 'Fences barbed wire' 0. 'bwire-Cai' 350. 6. 'none' 0. 'none' 'Fences dead' 0. 'dposts-sl' 33. 6. 'none' 0. 'none' 'Fences nails' 0. 'cramp-l' 0.5 6. 'none' 0. 'none' 'Fence maintenance' 2. 'none' 0. 0. 'none' 0. 'none' 'Various small tools' 0. 'stools' 5. 5. 'none' 0. 'none'

* 4.2 Description of options for special activities: recurrent weeding. * Note that all inputs are totals over the year. * 4.2.1 Weeding at attainable production level of pasture * All inputs/activities are specified for the level ofattainable production * (extension PP) and for the level of zero external inputs (extension EX) I-10

* WEED Name of weeding manner (name) (character) * OL (total) Own (farm) labour use (hour/year) (real) * C1N Name of first herbicide input (name) (character) * to select from BIOCIDE.ATF attribute file. * C1Q Quantity of first herbicide input (amount/year) (real) * Units of quantity should match those in biocide file! * C2N Name of second herbicide input (name) (character) * to select from BIOCIDE.ATF attribute file. * C2Q Quantity of second herbicide input (amount/year) (real) * Units of quantity should match those in biocide file! * C3N Name of third herbicide input (name) (character) * to select from BIOCIDE.ATF attribute file. * C3Q Quantity of third herbicide input (amount/year) (real) * Units of quantity should match those in biocide file! * WEQ Equipment used for weeding (name) (character) * to select from EQUIPMENT.ATF attribute file. * WEQU Use time of equipment (hours/year) (real) * WTRA Traction used to 'pull' equipment (name) (character) * to select from TRACTION.ATF attribute file.

* Input data: Andre Nieuwenhuyse, based on farmer inquiries in the AZ (96-97) WEEDPP OLPP C1NPP C1QPP C2NPP C2QPP C3NPP C3QPP WEQPP WEQUPP WTRAPP 'manual' 7.0 'None' 0. 'None' 0. 'None' 0. 'none' 0. 'none' 'chemic' 3.5 '24D' 1.5 'Tordon-101' 0.5 'Combo' 0.035 'ksspray' 3.5 'none' 'mixed' 5.0 '24D' 1.5 'Tordon-101' 0.5 'None' 0. 'ksspray' 2.0 'none'

* 4.3 Description of options for special activities: fertilizer application. * FERTIL Manner of fertilizer application (name) (character) * FOLAB Fertilizer own (farm) labor (whether own labor is used in application) * options: 'yes' or 'no' (eg when contract labor is used) * FEQUIP Fertilizer equipment (name) (character) * to select from EQUIP.ATF attribute file. * FSSIZE Fertilizer amount that can be applied in FSADUR time (kg) (real) * FSADUR Fertilizer application duration for FSSIZE (hour) (real) * FTRAC Traction used to 'pull' equipment (name) (character) * to select from TRACTION.ATF attribute file.

* Input data: Andre Nieuwenhuyse, based on farmer inquiries in the AZ (96-97) FERTIL FOLAB FEQUIP FSSIZE FSADUR FTRAC 'manual' 'yes' 'none' 150. 3. 'none'

I.2.2 BBRIZAN.DAT

******************************* BBRIZAN.DAT *************************** * Pasto input data file for program PASTOF, as in PASTOR version 2.0. * * All data are per hectare * * Date: 09-09-1997; Author: B.A.M. Bouman, REPOSA. * * Data for grass: Brachiaria brizantha * * Most data are based on expert knowledge, an interpretation of * * various literature sources, and data collected by REPOSA. * * Experts: A. Nieuwenhuyse, M. Ibrahim, M. Villareal Castro. * * Literature: separate list available. * ***********************************************************************

* GNAME : Pasture name (character) * GCODE : Pasture code (one letter only!) (character) * ------GNAME = 'Bbrizantha' GCODE = 'B'

***************************************************************** * 1. PASTURE CHARACTERISTICS * ****************************************************************** * Pasture data at level of attainable production (PER MONTH): * MONTH: Name of month (character) * DMP: (above-ground total) Dry matter attainable production * on the best soil (kg/month) (real) I-11

* CP: Crude Protein content (%) (real) * ME: Metabolizable energy content (Mcal/kg) (real) * P: Phosphorus content (%) (real) * K: Potassium content (%) (real) * ------MONTH DMP CP ME P K ! data from thesis Ibrahim (1994) 'JAN' 1806. 11.0 2.3 0.35 3.7 ! Total PP: 35 t/ha 'FEB' 1806. 11.0 2.3 0.35 3.7 'MAR' 1806. 11.0 2.3 0.35 3.7 'APR' 3287. 12.0 2.5 0.3 3.5 'MAY' 3287. 12.0 2.5 0.3 3.5 'JUN' 3287. 12.0 2.5 0.3 3.5 'JUL' 3287. 12.0 2.5 0.3 3.5 'AUG' 3287. 12.0 2.5 0.3 3.5 'SEP' 3287. 12.0 2.5 0.3 3.5 'OCT' 3287. 12.0 2.5 0.3 3.5 'NOV' 3287. 12.0 2.5 0.3 3.5 'DEC' 3287. 12.0 2.5 0.3 3.5

* Minimum nutrient and energy concentrations when no external (manure, * fertilizer) nutrients are applied (minimum production level) * CPMIN: Minimum Crude Protein content (%) (real) * MEMIN: Minimum Metabolizable energy content (Mcal/kg) (real) * PMIN: Minimum Phosphorus content (%) (real) * KMIN: Minimum Potassium content (%) (real) *------CPMIN = 6. MEMIN = 1.5 PMIN = 0.12 KMIN = 1.4

*********************************************************************** * 2. PASTURE RESPONSES TO SOIL TYPES: ATTAINABLE PRODUCTION * *********************************************************************** * Yield reduction factors * SOILP: Soil name (character) * RDMP: Reduction fraction of attainable production (DMP as above) * due to soil limitations (-) (real) * RDMUSE: Reduction fraction of potential dry matter on offer (DMUSE * see below), due to soil limitations. (-) (real) * ------SOILP RDMP RDMUSE ! Expert knowledge, various literature 'SFW' 1.0 1.0 'SIW' 0.7 1.0

********************************************************************** * 3. MANAGEMENT CHARACTERISTICS * *********************************************************************** * SRATE: Stocking rate (animal units per ha) (real) * DMUSE: Potential fraction above-ground dry matter on offer * on best soils, as function of stocking rate (-) (real) * ------SRATE DMUSE ! Expert knowledge 1. 0.55 1.5 0.525 2. 0.50 2.5 0.475 3. 0.45

* Data for target Production level * PLEVEL: Code for technology level (2 numbers only!) (I) * FGIFT: Fraction of fertilizer N gift to realize maximum * attainable production (-) (real) * FERTAP: Manner of fertilizer application (name) (real) * Select from options given below under 4.OPERATIONS) * WEED: Manner of weeding (name) (character) * Select from options given below under 4.OPERATIONS) * ------PLEVEL FGIFT FERTAP WEED ! User defined 11 0.00 'manual' 'mixed' 20 0.20 'manual' 'mixed' 40 0.40 'manual' 'mixed' 60 0.60 'manual' 'mixed' 80 0.80 'manual' 'mixed' 99 1.00 'manual' 'mixed' I-12

*********************************************************************** * 4.OPERATIONS * *********************************************************************** * 4.0 establishment of pasto: herbicides and fertilizer application * Note: land preparation and sowing/planting are specified in * section 4.1 below * EDEP Depreciation time of pasto (year) (real). Note: see also 4.1 below * EWLAB/EFLAB Farm labour use for weeding/fertilizing (hours) (real) * EWNAME/EFNAME Herbicide/fertilizer name (name) (character); * to select from BIOCID.ATF and FERT attribute files. * EWQUAN/EFQUAN Herbicide/fertilizer quantity (unit) (real) * EWEQ/EFEQ Herbicide/fertilizer equipment name (name) (character); * to select from EQUIP.ATF attribute file. * EWQUSE/EFQUSE Herbicide/fertilizer equipment use (hours) (real) * EWTRAC/EFTRAC Herbicide/fertilizer traction for equipment (name) (character) * to select from TRACTION.ATF attribute file. * Input data: Andre Nieuwenhuyse, based on farmer inquiries in the AZ (96-97)

EDEP = 10.

* 4.1 Operations that are investments and recurrent variables independent * of production level (all entries per ha) * OPER Name of operation (name) (character) * OWNLAB Own (farm) labour use (hours) (real) * MATER Name of used materials (name) (character) * to select from MATER.ATF attribute file. * MQUANT Materials quantity, in same unit as in materials file! (name) (real) * DEPRET Depreciation time of used materials (years) (real). * Note: when DEPRET is 0, the operation/inputs are yearly recurrent. * EQUIP Name of equipment used (name) (character) * to select from EQUIP.ATF attribute file. * EUSE Equipment use time (real) (hour) * TRAC Traction used to 'pull' equipment (name) (character) * to select from TRACTION.ATF attribute file. * Fences: 2. Short lasting fences; dead posts * land preparation by contract removed; compensated by 1.5 times seed use

* Input data: Andre Nieuwenhuyse, based on farmer inquiries in the AZ (96-97) OPER OWNLAB MATER MQUANT DEPRET EQUIP EQUSE TRAC 'Grass sowing' 27. 'seedBB' 7.5 10. 'none' 0. 'none' 'Labour fence estab.' 12. 'none' 0. 6. 'none' 0. 'none' 'Fences barbed wire' 0. 'bwire-Cai' 350. 6. 'none' 0. 'none' 'Fences dead' 0. 'dposts-sl' 33. 6. 'none' 0. 'none' 'Fences nails' 0. 'cramp-l' 0.5 6. 'none' 0. 'none' 'Fence maintenance' 2. 'none' 0. 0. 'none' 0. 'none' 'Various small tools' 0. 'stools' 5. 5. 'none' 0. 'none'

* 4.2 Description of options for special activities: recurrent weeding. * Note that all inputs are totals over the year. * 4.2.1 Weeding at attainable production level of pasture * All inputs/activities are specified for the level ofattainable production * (extension PP) and for the level of zero external inputs (extension EX) * WEED Name of weeding manner (name) (character) * OL (total) Own (farm) labour use (hour/year) (real) * C1N Name of first herbicide input (name) (character) * to select from BIOCIDE.ATF attribute file. * C1Q Quantity of first herbicide input (amount/year) (real) * Units of quantity should match those in biocide file! * C2N Name of second herbicide input (name) (character) * to select from BIOCIDE.ATF attribute file. * C2Q Quantity of second herbicide input (amount/year) (real) * Units of quantity should match those in biocide file! * C3N Name of third herbicide input (name) (character) * to select from BIOCIDE.ATF attribute file. * C3Q Quantity of third herbicide input (amount/year) (real) * Units of quantity should match those in biocide file! I-13

* WEQ Equipment used for weeding (name) (character) * to select from EQUIPMENT.ATF attribute file. * WEQU Use time of equipment (hours/year) (real) * WTRA Traction used to 'pull' equipment (name) (character) * to select from TRACTION.ATF attribute file.

* Input data: Andre Nieuwenhuyse, based on farmer inquiries in the AZ (96-97) WEEDPP OLPP C1NPP C1QPP C2NPP C2QPP C3NPP C3QPP WEQPP WEQUPP WTRAPP 'manual' 3.5 'None' 0. 'None' 0. 'None' 0. 'none' 0. 'none' 'chemic' 1.75 '24D' 0.75 'Tordon-101' 0.25 'Combo' 0.018 'ksspray' 1.75 'none' 'mixed' 2.5 '24D' 0.75 'Tordon-101' 0.25 'None' 0. 'ksspray' 1.0 'none'

FERTIL FOLAB FEQUIP FSSIZE FSADUR FTRAC 'manual' 'yes' 'none' 150. 3. 'none'

I.2.3 TANNER.DAT

******************************* TANNER.DAT **************************** * Pasto input data file for program PASTOF, as in PASTOR version 2.0 * * All data are per hectare * * Date: 09-09-1997; Author: B.A.M. Bouman, REPOSA. * * Data for grass: Tanner (Brachiaria radicans) * * These grass data only for poorly drained soils! * * Most data are based on expert knowledge, an interpretation of * * various literature sources, and data collected by REPOSA. * * Experts: A. Nieuwenhuyse, M. Ibrahim, M. Villareal Castro. * * Literature: separate list available. * *********************************************************************** * GNAME : Pasture name (character) * GCODE : Pasture code (one letter only!) (character) * ------GNAME = 'Tanner' GCODE = 'T'

******************************************************************* * 1. PASTURE CHARACTERISTICS * ******************************************************************* * Grass data at level of attainable production (PER MONTH): * MONTH: Name of month (character) * DMP: (above-ground total) Dry matter attainable production * on best soils (kg/month) (real) * CP: Crude Protein content (%) (real) * ME: Metabolizable energy content (Mcal/kg) (real) * P: Phosphorus content (%) (real) * K: Potassium content (%) (real) * ------MONTH DMP CP ME P K ! Estimated expert knowledge 'JAN' 1583. 11.0 2.3 0.35 3.7 ! various literature 'FEB' 1583. 11.0 2.3 0.35 3.7 ! Total dry matter is 19 t/ha 'MAR' 1583. 11.0 2.3 0.35 3.7 'APR' 1583. 11.0 2.3 0.35 3.7 'MAY' 1583. 11.0 2.3 0.35 3.7 'JUN' 1583. 11.0 2.3 0.35 3.7 'JUL' 1583. 11.0 2.3 0.35 3.7 'AUG' 1583. 11.0 2.3 0.35 3.7 'SEP' 1583. 11.0 2.3 0.35 3.7 I-14

'OCT' 1583. 11.0 2.3 0.35 3.7 'NOV' 1583. 11.0 2.3 0.35 3.7 'DEC' 1583. 11.0 2.3 0.35 3.7

* Minimum nutrient and energy concentrations when no external (manure, * fertilizer) nutrients are applied (minimum production level). * CPMIN: Minimum Crude Protein content (%) (real) * MEMIN: Minimum Metabolizable energy content (Mcal/kg) (real) * PMIN: Minimum Phosphorus content (%) (real) * KMIN: Minimum Potassium content (%) (real) *------* Expert knowledge, various literature CPMIN = 6. MEMIN = 1.5 PMIN = 0.12 KMIN = 1.4

*********************************************************************** * 2. PASTURE RESPONSES TO SOIL TYPES: ATTAINABLE PRODUCTION * *********************************************************************** * Yield reduction factors * SOILP: Soil name (character) * RDMP: Reduction fraction of attainable production (DMP as above) * due to soil limitations (-) (real) * RDMUSE: Reduction fraction of potential dry matter on offer (DMUSE * see below), due to soil limitations. (-) (real) * ------SOILP RDMP RDMUSE ! Tanner does only apply to SFP soils! 'SFP' 1.0 1.0

********************************************************************** * 3. MANAGEMENT CHARACTERISTICS * *********************************************************************** * SRATE: Stocking rate (animal units per ha) (real) * DMUSE: Potential fraction above-ground dry matter on offer * on best soils, as function of stocking rate (-) (real) * ------SRATE DMUSE ! Estimated expert knowledge 1. 0.55 1.5 0.525 2. 0.50 2.5 0.475 3. 0.45

* Data for target Production level * PLEVEL: Code for technology level (2 numbers only!) (I) * FGIFT: Fraction of fertilizer N gift to realize maximum * attainable production (-) (real) * FERTAP: Manner of fertilizer application (name) (real) * Select from options given below under 4.OPERATIONS) * WEED: Manner of weeding (name) (character) * Select from options given below under 4.OPERATIONS) * ------PLEVEL FGIFT FERTAP WEED ! User defined 11 0.00 'manual' 'mixed' 20 0.20 'manual' 'mixed' 40 0.40 'manual' 'mixed' 60 0.60 'manual' 'mixed' 80 0.80 'manual' 'mixed' 99 1.00 'manual' 'mixed'

*********************************************************************** * 4.OPERATIONS * *********************************************************************** * 4.0 establishment of pasto: herbicides and fertilizer application * Note: land preparation and sowing/planting are specified in * section 4.1 below * EDEP Depreciation time of pasto (year) (real). Note: see also 4.1 below * EWLAB/EFLAB Farm labour use for weeding/fertilizing (hours) (real) * EWNAME/EFNAME Herbicide/fertilizer name (name) (character); * to select from BIOCID.ATF and FERT attribute file. * EWQUAN/EFQUAN Herbicide/fertilizer quantity (unit) (real) * EWEQ/EFEQ Herbicide/fertilizer equipment name (name) (character); * to select from EQUIP.ATF attribute file. * EWQUSE/EFQUSE Herbicide/fertilizer equipment use (hours) (real) * EWTRAC/EFTRAC Herbicide/fertilizer traction for equipment (name) (character) I-15

* to select from TRACTION.ATF attribute file.

EDEP = 10.

* Input data: Andre Nieuwenhuyse, based on farmer inquiries in the AZ (96-97) EWLAB EWNAME EWQUAN EWEQ EWQUSE EWTRAC 24.0 'None' 0. 'ksspray' 24. 'none' 0.0 'Tordon-101' 1. 'ksspray' 0. 'none' 0.0 '24D' 3. 'ksspray' 0. 'none' 0.0 'Round-up' 4. 'ksspray' 0. 'none'

EFLAB EFNAME EFQUAN EFEQ EFQUSE EFTRAC 0.0 'none' 0. 'none' 0. 'none'

* 4.1 Operations that are investments and recurrent variables independent * of production level (all entries per ha) * OPER Name of operation (name) (character) * OWNLAB Own (farm) labour use (hours) (real) * MATER Name of used materials (name) (character) * to select from MATER.ATF attribute file. * MQUANT Materials quantity, in same unit as in materials file! (name) (real) * DEPRET Depreciation time of used materials (years) (real). * Note: when DEPRET is 0, the operation/inputs are yearly recurrent. * EQUIP Name of equipment used (name) (character) * to select from EQUIP.ATF attribute file. * EUSE Equipment use time (real) (hour) * TRAC Traction used to 'pull' equipment (name) (character) * to select from TRACTION.ATF attribute file. * Fences: 2. Short lasting fences; dead posts * land preparation by contract removed; compensated with 1.5 times stolon use

* Input data: Andre Nieuwenhuyse, based on farmer inquiries in the AZ (96-97) * Fences: 2. Short lasting fences; dead posts OPER OWNLAB MATER MQUANT DEPRET EQUIP EQUSE TRAC 'Grass sowing' 30. 'gstolT' 1.5 10. 'none' 0. 'none' 'Labour fence estab.' 12. 'none' 0. 6. 'none' 0. 'none' 'Fences barbed wire' 0. 'bwire-Cai' 350. 6. 'none' 0. 'none' 'Fences dead' 0. 'dposts-sl' 33. 6. 'none' 0. 'none' 'Fences nails' 0. 'cramp-l' 0.5 6. 'none' 0. 'none' 'Fence maintenance' 2. 'none' 0. 0. 'none' 0. 'none' 'Various small tools' 0. 'stools' 5. 5. 'none' 0. 'none'

* 4.2 Description of options for special activities: recurrent weeding. * Note that all inputs are totals over the year. * 4.2.1 Weeding at attainable production level of pasture * All inputs/activities are specified for the level ofattainable production * (extension PP) and for the level of zero external inputs (extension EX) * WEED Name of weeding manner (name) (character) * OL (total) Own (farm) labour use (hour/year) (real) * C1N Name of first herbicide input (name) (character) * to select from BIOCIDE.ATF attribute file. * C1Q Quantity of first herbicide input (amount/year) (real) * Units of quantity should match those in biocide file! * C2N Name of second herbicide input (name) (character) * to select from BIOCIDE.ATF attribute file. * C2Q Quantity of second herbicide input (amount/year) (real) * Units of quantity should match those in biocide file! * C3N Name of third herbicide input (name) (character) * to select from BIOCIDE.ATF attribute file. * C3Q Quantity of third herbicide input (amount/year) (real) * Units of quantity should match those in biocide file! * WEQ Equipment used for weeding (name) (character) * to select from EQUIPMENT.ATF attribute file. * WEQU Use time of equipment (hours/year) (real) * WTRA Traction used to 'pull' equipment (name) (character) * to select from TRACTION.ATF attribute file.

* Input data: Andre Nieuwenhuyse, based on farmer inquiries in the AZ (96-97) WEEDPP OLPP C1NPP C1QPP C2NPP C2QPP C3NPP C3QPP WEQPP WEQUPP WTRAPP 'manual' 7.0 'None' 0. 'None' 0. 'None' 0. 'none' 0. 'none' 'chemic' 3.5 '24D' 1.5 'Tordon-101' 0.5 'Combo' 0.035 'ksspray' 3.5 'none' 'mixed' 5.0 '24D' 1.5 'Tordon-101' 0.5 'Combo' 0. 'ksspray' 2.0 'none'

WEEDEX OLEX C1NEX C1QEX C2NEX C2QEX C3NEX C3QEX WEQEX WEQUEX WTRAEX 'manual' 15. 'None' 0. 'None' 0. 'None' 0. 'none' 0. 'none' 'chemic' 7.0 '24D' 3.0 'Tordon-101' 1.0 'Combo' 0.070 'ksspray' 7.0 'none' 'mixed' 11.5 '24D' 1.5 'Tordon-101' 0.5 'Combo' 0.035 'ksspray' 3.5 'none' I-16

* Input data: Andre Nieuwenhuyse, based on farmer inquiries in the AZ (96-97) FERTIL FOLAB FEQUIP FSSIZE FSADUR FTRAC 'manual' 'yes' 'none' 150. 3. 'none'

I.2.4 NATURAL.DAT

******************************* NATURAL.DAT *************************** * Pasto input data file for program PASTOU, as in PASTOR version 2.0 * * All data are per hectare * * Date: 09-09-1997; Author: B.A.M. Bouman, REPOSA. * * Data for grass: Some kind of 'natural/improved grass' mixture that * * is representative for the various soil types. * * Most data are based on expert knowledge, an interpretation of * * various literature sources, and data collected by REPOSA. * * Experts: A. Nieuwenhuyse, M. Ibrahim, M. Villareal Castro. * * Literature: separate list available. * *********************************************************************** * GNAME : Pasture name (character) * GCODE : Pasture code (one letter only!) (character) * ------GNAME = 'Natural' GCODE = 'N'

*********************************************************************** * 1. PASTURE CHARACTERISTICS * *********************************************************************** * Grass data at level of attainable production (PER MONTH): * MONTH: Name of month (character) * DMP: (above-ground total) Dry matter attainable production * (kg/month) (real) * CP: Crude Protein content (%) (real) * ME: Metabolizable energy content (Mcal/kg) (real) * P: Phosphorus content (%) (real) * K: Potassium content (%) (real) * ------* Data for attainable production estimated as two times that of current MONTH DMP CP ME P K ! data from various sources 'JAN' 1087. 10.0 2.1 0.15 1.5 ! literature, expert-knowledge 'FEB' 1087. 10.0 2.1 0.15 1.5 ! Total attain. prod: 15 t/ha/y! 'MAR' 1087. 10.0 2.1 0.15 1.5 ! Villareal pers. com. 'APR' 1304. 10.0 2.1 0.15 1.5 'MAY' 1304. 10.0 2.1 0.15 1.5 'JUN' 1304. 10.0 2.1 0.15 1.5 'JUL' 1304. 10.0 2.1 0.15 1.5 'AUG' 1304. 10.0 2.1 0.15 1.5 'SEP' 1304. 10.0 2.1 0.15 1.5 'OCT' 1304. 10.0 2.1 0.15 1.5 'NOV' 1304. 10.0 2.1 0.15 1.5 'DEC' 1304. 10.0 2.1 0.15 1.5

*********************************************************************** * 2. PASTURE RESPONSES TO SOIL TYPES: ATTAINABLE PRODUCTION * *********************************************************************** * Yield reduction factors * SOILP: Soil name (character) * RDMP: Reduction fraction of attainable production (DMP as above) * due to soil limitations (-) (real) * RDMUSE: Reduction fraction of potential dry matter on offer (DMUSE * see below), due to soil limitations. (-) (real) * NSUPL: Supply of nitrogen from legumes that may be present I-17

* e.g. as in grass-legume mixtures. (kg/ha) (real) * ------SOILP RDMP RDMUSE NSUPL ! Estimates from expert knowledge 'SFW' 1.0 1.0 0. 'SIW' 0.8 1.0 0. 'SFP' 1.0 0.8 0.

********************************************************************** * 3. MANAGEMENT CHARACTERISTICS * *********************************************************************** * SRATE: Stocking rate (animal units per ha) (real) * DMUSE: Potential fraction above-ground dry matter on offer * on best soils, as function of stocking rate (-) (real) * ------SRATE DMUSE ! estimated from expert knowledge 1. 0.55 1.5 0.525 2. 0.50 2.5 0.475 3. 0.45

* Data for manner of herbicide control (parallel to production level) * PLEVEL: Code for technology level (2 numbers only!) (I) * WEED: Manner of weeding (name) (character) * Select from options given below under 4.OPERATIONS) * ------PLEVEL WEED ! User supplied 11 'mixed'

*********************************************************************** * 4.OPERATIONS * *********************************************************************** * 4.0 establishment of pasto: herbicides and fertilizer application * Note: land preparation and sowing/planting are specified in * section 4.1 below * EDEP Depreciation time of pasto (year) (real). Note: see also 4.1 below * EWLAB/EFLAB Farm labour use for weeding/fertilizing (hours) (real) * EWNAME/EFNAME Herbicide/fertilizer name (name) (character); * to select from BIOCID.ATF and FERT attribute files. * EWQUAN/EFQUAN Herbicide/fertilizer quantity (unit) (real) * EWEQ/EFEQ Herbicide/fertilizer equipment name (name) (character); * to select from EQUIP.ATF attribute file. * EWQUSE/EFQUSE Herbicide/fertilizer equipment use (hours) (real) * EWTRAC/EFTRAC Herbicide/fertilizer traction for equipment (name) (character) * to select from TRACTION.ATF attribute file.

EDEP = 100. ! natural grass is 'forever'

EWLAB EWNAME EWQUAN EWEQ EWQUSE EWTRAC 0.0 'None' 0. 'none' 0. 'none'

EFLAB EFNAME EFQUAN EFEQ EFQUSE EFTRAC 0.0 'none' 0. 'none' 0. 'none'

* 4.1 Operations that are investments and recurrent variables independent * of production level (all entries per ha) * OPER Name of operation (name) (character) * OWNLAB Own (farm) labour use (hours) (real) * MATER Name of used materials (name) (character) * to select from MATER.ATF attribute file. * MQUANT Materials quantity, in same unit as in materials file! (name) (real) * DEPRET Depreciation time of used materials (years) (real). * Note: when DEPRET is 0, the operation/inputs are yearly recurrent. * EQUIP Name of equipment used (name) (character) * to select from EQUIP.ATF attribute file. * EUSE Equipment use time (real) (hour) * TRAC Traction used to 'pull' equipment (name) (character) * to select from TRACTION.ATF attribute file.

* Input data: Andre Nieuwenhuyse, based on farmer inquiries in the AZ (96-97) * Fences: 2. Short lasting fences; dead posts OPER OWNLAB MATER MQUANT DEPRET EQUIP EQUSE TRAC 'Labour fence estab.' 12. 'none' 0. 6. 'none' 0. 'none' 'Fences barbed wire' 0. 'bwire-Cai' 350. 6. 'none' 0. 'none' 'Fences dead' 0. 'dposts-sl' 33. 6. 'none' 0. 'none' 'Fences nails' 0. 'cramp-l' 0.5 6. 'none' 0. 'none' I-18

'Fence maintenance' 2. 'none' 0. 0. 'none' 0. 'none' 'Various small tools' 0. 'stools' 5. 5. 'none' 0. 'none'

* 4.2 Description of options for special activities: recurrent weeding. * Note that all inputs are totals over the year. * 4.2.1 Weeding of pasture * WEED Name of weeding manner (name) (character) * OL (total) Own (farm) labour use (hour/year) (real) * C1N Name of first herbicide input (name) (character) * to select from BIOCIDE.ATF attribute file. * C1Q Quantity of first herbicide input (amount/year) (real) * Units of quantity should match those in biocide file! * C2N Name of second herbicide input (name) (character) * to select from BIOCIDE.ATF attribute file. * C2Q Quantity of second herbicide input (amount/year) (real) * Units of quantity should match those in biocide file! * C3N Name of third herbicide input (name) (character) * to select from BIOCIDE.ATF attribute file. * C3Q Quantity of third herbicide input (amount/year) (real) * Units of quantity should match those in biocide file! * WEQ Equipment used for weeding (name) (character) * to select from EQUIPMENT.ATF attribute file. * WEQU Use time of equipment (hours/year) (real) * WTRA Traction used to 'pull' equipment (name) (character) * to select from TRACTION.ATF attribute file.

* Input data: Andre Nieuwenhuyse, based on farmer inquiries in the AZ (96-97) WEEDN OLWEED C1N C1Q C2N C2Q C3N C3Q WEQ WEQU WTRA 'manual' 10. 'None' 0. 'None' 0. 'None' 0. 'none' 0. 'none' 'chemic' 6.0 '24D' 3.0 'Tordon-101' 1.0 'Combo' 0.035 'ksspray' 6.0 'none' 'mixed' 7.0 '24D' 1.5 'Tordon-101' 0.5 'Combo' 0.035 'ksspray' 3.5 'none'

I.2.5 BPINTOI.DAT

******************************* BPINTOI.DAT *************************** * Pasto input data file for program PASTO, as in PASTOR version 2.0 * * All data are per hectare * * Date: 09-09-1997; Author: B.A.M. Bouman, REPOSA. * * Data for grass: Mixture of Brachiaria brizantha with Arachis pintoi * * Data taken from Ibrahim, 1994. * * Most data are based on expert knowledge, an interpretation of * * various literature sources, and data collected by REPOSA. * * Experts: A. Nieuwenhuyse, M. Ibrahim, M. Villareal Castro. * * Literature: separate list available. * *********************************************************************** * GNAME : Pasture name (character) * GCODE : Pasture code (one letter only!) (character) * ------GNAME = 'Bpintoi' GCODE = 'I'

*********************************************************************** * 1. PASTURE CHARACTERISTICS * *********************************************************************** * Grass data at level of attainable production (PER MONTH): * MONTH: Name of month (character) * DMP: (above-ground total) Dry matter attainable production * on best soils (kg/month) (real) * CP: Crude Protein content (%) (real) * ME: Metabolizable energy content (Mcal/kg) (real) * P: Phosphorus content (%) (real) * K: Potassium content (%) (real) * ------MONTH DMP CP ME P K 'JAN' 1024. 9.0 2.0 0.20 2.5 ! Data M. Ibrahim thesis, 1994 'FEB' 1024. 9.0 2.0 0.20 2.5 ! Total production 20 t/ha 'MAR' 1024. 9.0 2.0 0.20 2.5 ! Data 'CIAT's contribution' 'APR' 1862. 11.0 2.1 0.20 2.5 'MAY' 1862. 11.0 2.1 0.20 2.5 'JUN' 1862. 11.0 2.1 0.20 2.5 'JUL' 1862. 11.0 2.1 0.20 2.5 'AUG' 1862. 11.0 2.1 0.20 2.5 I-19

'SEP' 1862. 11.0 2.1 0.20 2.5 'OCT' 1862. 11.0 2.1 0.20 2.5 'NOV' 1862. 11.0 2.1 0.20 2.5 'DEC' 1862. 11.0 2.1 0.20 2.5

*********************************************************************** * 2. PASTURE RESPONSES TO SOIL TYPES: ATTAINABLE PRODUCTION * *********************************************************************** * Yield reduction factors * SOILP: Soil name (character) * RDMP: Reduction fraction of attainable production (DMP as above) * due to soil limitations (-) (real) * RDMUSE: Reduction fraction of potential dry matter on offer (DMUSE * see below), due to soil limitations. (-) (real) * NSUPL: Supply of nitrogen from legumes that may be present * e.g. as in grass-legume mixtures. (kg/ha) (real) * ------SOILP RDMP RDMUSE NSUPL ! Expert knowledge, Ibrahim thesis 1994 'SFW' 1.0 1.0 150. ! 'CIAT's contribution' for NSUPL, p.124 'SIW' 0.66 1.0 100.

********************************************************************** * 3. MANAGEMENT CHARACTERISTICS * *********************************************************************** * SRATE: Stocking rate (animal units per ha) (real) * DMUSE: Potential fraction above-ground dry matter on offer * on best soils, as function of stocking rate (-) (real) * ------SRATE DMUSE ! Expert estimates 1. 0.55 1.5 0.525 2. 0.50 2.5 0.475 3. 0.45

* Data for manner of herbicide control (parallel to production level) * PLEVEL: Code for technology level (2 numbers only!) (I) * WEED: Manner of weeding (name) (character) * Select from options given below under 4.OPERATIONS) * ------PLEVEL WEED 11 'manual'

*********************************************************************** * 4.OPERATIONS * *********************************************************************** * 4.0 establishment of pasto: herbicides and fertilizer application * Note: land preparation and sowing/planting are specified in * section 4.1 below * EDEP Depreciation time of pasto (year) (real). Note: see also 4.1 below * EWLAB/EFLAB Farm labour use for weeding/fertilizing (hours) (real) * EWNAME/EFNAME Herbicide/fertilizer name (name) (character) * EWQUAN/EFQUAN Herbicide/fertilizer quantity (unit) (real) * EWEQ/EFEQ Herbicide/fertilizer equipment name (name) (character) * EWQUSE/EFQUSE Herbicide/fertilizer equipment use (hours) (real) * EWTRAC/EFTRAC Herbicide/fertilizer traction for equipment (name) (character)

EDEP = 10.

* Input data: Andre Nieuwenhuyse, based on farmer inquiries in the AZ (96-97) EWLAB EWNAME EWQUAN EWEQ EWQUSE EWTRAC 24.0 'None' 0. 'ksspray' 24. 'none' 0.0 'Tordon-101' 1. 'ksspray' 0. 'none' 0.0 '24D' 3. 'ksspray' 0. 'none' 0.0 'Round-up' 4. 'ksspray' 0. 'none'

* 4.1 Operations that are investments and recurrent variables independent * of production level (all entries per ha) * OPER Name of operation (name) (character) * OWNLAB Own (farm) labour use (hours) (real) * MATER Name of used materials (name) (character) * MQUANT Materials quantity, in same unit as in materials file! (name) (real) * DEPRET Depreciation time of used materials (years) (real). I-20

* Note: when DEPRET is 0, the operation/inputs are yearly recurrent. * EQUIP Name of equipment used (name) (character) * EUSE Equipment use time (real) (hour) * TRAC Traction used to 'pull' equipment (name) (character)

* Input data: Andre Nieuwenhuyse, based on farmer inquiries in the AZ (96-97) * Fences: 2. Short lasting fences; dead posts OPER OWNLAB MATER MQUANT DEPRET EQUIP EQUSE TRAC 'Grass sowing' 27. 'seedBB' 7.5 10. 'none' 0. 'none' 'Arachis planting' 18. 'stolAP' 1.5 10. 'none' 0. 'none' 'Labour fence estab.' 12. 'none' 0. 6. 'none' 0. 'none' 'Fences barbed wire' 0. 'bwire-Cai' 350. 6. 'none' 0. 'none' 'Fences dead' 0. 'dposts-sl' 33. 6. 'none' 0. 'none' 'Fences nails' 0. 'cramp-l' 0.5 6. 'none' 0. 'none' 'Fence maintenance' 2. 'none' 0. 0. 'none' 0. 'none' 'Various small tools' 0. 'stools' 5. 5. 'none' 0. 'none'

* Original: *'Land preparation' 0. 'contract1' 1. 10. 'none' 0. 'none' *'Grass sowing' 18. 'seedBB' 5. 10. 'none' 0. 'none'

* 4.2 Description of options for special activities: recurrent weeding. * Note that all inputs are totals over the year. * 4.2.1 Weeding of pasture * WEEDN Name of weeding manner (name) (character) * OL (total) Own (farm) labour use (hour/year) (real) * C1N Name of first herbicide input (name) (character) * C1Q Quantity of first herbicide input (amount/year) (real) * Units of quantity should match those in biocide file! * C2N Name of second herbicide input (name) (character) * C2Q Quantity of second herbicide input (amount/year) (real) * Units of quantity should match those in biocide file! * C3N Name of third herbicide input (name) (character) * C3Q Quantity of third herbicide input (amount/year) (real) * Units of quantity should match those in biocide file! * WEQ Equipment used for weeding (name) (character) * WEQU Use time of equipment (hours/year) (real) * WTRA Traction used to 'pull' equipment (name) (character)

* Input data: Andre Nieuwenhuyse, based on farmer inquiries in the AZ (96-97) * Three times a year, five hours chapia WEEDN OLWEED C1N C1Q C2N C2Q C3N C3Q WEQ WEQU WTRA 'manual' 15. 'None' 0. 'None' 0. 'None' 0. 'none' 0. 'none'

I.3 Other input files

I.3.1 SOIL.DAT

*************************** SOIL.DAT ***************************** * Soil input data file, for PASTOR version 2.0 * ******************************************************************

****************************************************************** * NON SOIL TYPE SPECIFIC * ****************************************************************** * Atmospheric nitrogen deposition (kg/ha/y) (real) AND = 1.7

* Atmospheric phosphorus deposition (kg/ha/y) (real) APD = 0.2

* Atmospheric potassium deposition (kg/ha/y) (real) AKD = 5.4

* Annual input of phosphorus by weathering (kg/ha/y) (real) WP = 0.

* Annual input of potassium by weathering (kg/ha/y) (real) WK = 0. I-21

****************************************************************** * SOIL TYPE SPECIFIC * ****************************************************************** * SOILS = soil type (name) (character) * NFIX = Nitrogen fixation by micro-organisms (kg/ha/y) (real) * ULLMP = Urinary leaching loss fraction through macropores (-) (real) * ULL = Urinary leaching loss fraction (-) (real) * UVL = Urinary volatalization loss fraction (-) (real) * UDL = Urinary (de)nitrification loss fraction (-) (real) * i.e.: NO, N2O and N2 loss * FLL = Fecal leaching loss fraction (-) (real) * FVL = Fecal volatalization loss fraction (-) (real) * FDL = Fecal denitrification loss fraction (-) (real) * FELLN = Fertilizer leaching loss fraction nitrogen (-) (real) * FELLK = Fertilizer leaching loss fraction potassium (-) (real) * FEVLN = Fertilizer volatalization loss fraction nitrogen (-) (real) * FEDLN = Fertilizer denitrification loss fraction nitrogen (-) (real) * FPXL = Phosphorus fixation fraction, for feces, urine and * fertilizer (-) (real)

SOILS NFIX ULLMP ULL UVL UDL FLL FVL FDL 'SFW' 6.0 0.30 0.20 0.15 0.05 0.60 0.05 0.05 'SIW' 3.0 0.30 0.20 0.15 0.05 0.60 0.05 0.05 'SFP' 1.0 0.30 0.15 0.25 0.15 0.40 0.15 0.15

FELLN FEVLN FEDLN FELLK FPXL 0.40 0.13 0.02 0.40 0.0 0.45 0.13 0.02 0.45 0.0 0.40 0.15 0.10 0.40 0.0

* 'Extra'loss of fertizer nitrogen (to be divided over leaching and * denitrification), as multiplication factor on calculated gross * N fertilizer gift (from loss fractions as above). * Give list as function of nett fertilizer gifts (kg/ha)-fraction EXLOST = 0.0 1.0 250. 1.0 275. 1.0 300. 1.0 400. 1.0 425. 1.1 450. 1.2 475. 1.3 1000. 1.5

* Fraction of 'extra' loss distribution over leaching and denitrification * LLEX = fraction to extra leaching loss (1-LLEX goes to denitr. loss) LLEX = 0.5

I.3.2 SITE.DAT

*************************** SITE.DAT **************************** * Site information; for PASTOR version 2.0 * ***************************************************************** * Interest rate for cost calculations (%/year) (real) * Real interest rate (mean bank interest rate corrected for inflation), * mean of 1991-1996. Note RINT should be ò 0. RINT = 7.

* Hours of labour in one day (real) (h/d) Should be: 0 < DAYHR < 24. DAYHR = 8.

****************************************************************** * Characteristics per soil type ****************************************************************** * ANMINE allowable nitrogen mining (kg/ha) (real) (ò 0) * AKMINE allowable potassium mining (kg/ha) (real) (ò 0) * APMINE: allowable phophorus mining (kg/ha) (real) (ò 0)

SOIL ANMINE AKMINE APMINE I-22

'SFW' 0. 0. 0. 'SIW' 0. 0. 0. 'SFP' 0. 0. 0.

I.3.3 FEEDS.DAT

**************************** FEEDS.DAT ******************************** * Feed supplement input file * Labour use calculated bu Nieuwenhuyse, april 1997. * For PASTOR version 2.0 *********************************************************************** * SFNAME Supplementary feed name (name) (character) * LABUSE Labor use to deliver supplementary feed on farm (hr/kg) (real) * EQUIP Equipment used to deliver suppl. feed on farm (name) (character) * EQUSE Time use of equipment (hr/kg) * TRAC Traction used to 'pull' equipment (name) (character)

SFNAME LABUSE EQUIP EQUSE TRAC 'molasse' 0.01 'none' 'none' 'none' 'banana' 0.003 'none' 'none' 'none' 'conc1' 0.007 'none' 'none' 'none' 'conc2' 0.007 'none' 'none' 'none' 'p20' 0.0 'none' 'none' 'none' I-23

Appendix II: PASTOR attribute files

II.1 Materials

**************************** MATER.ATF ***************************** * Material attribute file, for PASTOR version 2.0 * Updated by A.Nieuwenhuyse April 1997 ******************************************************************** * MCODE Material code (number) (real) * MDESCR Material description (name) (character) * MNAME Material name (name) (character) * MUNIT Materials unit for MPRICE (name) (character) * ('kg', 'li', 'no', 'm') * MPRICE Materials price, per unit as in MUNIT (colon) (real) * MPY Year of material price (number) (real) * MPM Month of material price (number) (real)

MCODE MDESCR MNAME MUNIT MPRICE MPY MPM 0000.00 'No material' 'none' 'no' 0. 1991. 06. 0000.00 'Contract land prep pasto' 'contract1' 'no' 20000. 1997. 04. 0000.00 'Grass stolons Estrella' 'gstolE' 'ha' 3000. 1997. 04. 0000.00 'Grass stolons Tanner' 'gstolT' 'ha' 3000. 1997. 04. 0000.00 'Stolons Arachis pintoi' 'stolAP' 'ha' 6000. 1997. 04. 0000.00 'Stumps Poro' 'stumP' 'no' 25. 1997. 04. 0000.00 'Grass seed Brachiaria br.' 'seedBB' 'kg' 3500. 1997. 04. 0000.00 'Grass seed Ratana' 'seedR' 'kg' 500. 1997. 04. 0000.00 'Living fence posts' 'lposts' 'no' 25. 1996. 06. 0000.00 'Short-living dead fence post' 'dposts-sl' 'no' 300. 1996. 06. 0000.00 'Long-living dead fence post' 'dposts-ll' 'no' 800. 1996. 06. 0000.00 'Barbed wire Caiman' 'bwire-Cai' 'm' 12.1 1997. 04. 0000.00 'Barbed wire Cabra' 'bwire-Cab' 'm' 21.7 1997. 04. 0000.00 'Barbed wire Moto' 'bwire-Mot' 'm' 14.1 1997. 04. 0000.00 'Cramps-small' 'cramp-s' 'kg' 425. 1997. 04. 0000.00 'Cramps-large' 'cramp-l' 'kg' 230. 1997. 04. 0000.00 'Small tools (saw,mach,..)' 'stools' 'no' 500. 1996. 06. 0000.00 'Medium tools' 'mtools' 'no' 750. 1996. 06. 0000.00 'Large tools (spade, ..)' 'ltools' 'no' 1500. 1996. 06. 0000.00 'Contr. corral 1-10 animals roof' 'corral1' 'no' 77000. 1997. 04. 0000.00 'Contr. corral 10-30 animals' 'corral2' 'no' 193900. 1997. 03. 0000.00 'Contr. corral 10-30 animals roof' 'corral2r' 'no' 353150. 1997. 03. 0000.00 'Contr. corral 30-60 animals' 'corral3' 'no' 338250. 1997. 03. 0000.00 'Contr. corral 30-60 animals roof' 'corral3r' 'no' 661880. 1997. 03. 0000.00 'Contr. corral 60-100 animals' 'corral4' 'no' 463500. 1997. 04. 0000.00 'Contr. corral 60-100 animals roof' 'corral4r' 'no' 907500. 1997. 04. 0000.00 'Salt trough' 'trough' 'no' 2300. 1996. 06. 0000.00 'Salt trough roof' 'troughr' 'no' 6000. 1997. 06.

II.2 Equipment

********************** EQUIP.ATF ******************************** * Equipment attribute file, for PASTOR version 2.0 ***************************************************************** * ECODE Equipment code (number) (real) * EDESCR Equipment description (name) (character) * ENAME Equipment name (name) (character) * EPRICE Equipments depreciation plus use, or rental price, per hour * (colon/hour) (real) * EPY Year of equipment price date (number) (real) * EPM Month of equipment price date (number) (real)

ECODE EDESCR ENAME EPRICE EPY EPM 0000.00 'No equipment' 'none' 0. 1997. 03. 0000.00 'Fertilizer spreader' 'spreader' 0. 1997. 03. 7020.00 'Moulboard plough' 'mplough' 1500. 1991. 06. 7030.00 'Disc plough, one way' 'dplough' 1500. 1991. 06. I-24

7040.00 'Disc harrow' 'dharrow' 1500. 1991. 06. 7210.00 'Row seeder' 'rseeder' 1500. 1991. 06. 7320.00 'Motor sprayer rental' 'mspray-r' 1200. 1997. 03. 0000.00 'Motor sprayer own' 'mspray-o' 800. 1997. 03. 7330.00 'Knapsack sprayer' 'ksspray' 30. 1997. 03. 8810.00 'Chainsaw rental' 'csaw-r' 1500. 1997. 03. 0000.00 'Chainsaw own' 'csaw-o' 900. 1997. 03.

II.3 Traction

************************* TRACTION.ATF *************************** * Traction attribute file, fpr PASTOR version 2.0 * ****************************************************************** * TCODE Traction code (number) (real) * TDESCR Traction description (name) (character) * TNAME Traction name (name) (character) * TPRICE Traction depreciation or rental price, per hour * (colon/hour) (real) * TPY Year of traction price (number) (real) * TPM Month of traction price (number) (real)

TCODE TDESCR TNAME TPRICE TPY TPM 0000.00 'No traction' 'none' 0. 1997. 03. 5011.00 'Draugh cattle span' 'draught1' 500. 1991. 06. 6100.00 'Field tractor 15-40 hp' 'tractor1' 1700. 1991. 06. 6200.00 'Field tractor 40-100 hp' 'tractor2' 2300. 1991. 06. 6300.00 'Field tractor > 100 hp' 'tractor3' 3000. 1991. 06. 6310.00 'Crawler tractor' 'tractor4' 4000. 1991. 06. 6910.00 'Airplane' 'plane' 5080. 1991. 06.

II.4 Fertiliser

**************************** FERT.ATF ***************************** * Fertilizer attribute file, for PASTOR version 2.0 * * Note: Nirtogen, Phosphorus and Potassium are obligated entries * * MNGIFT is obligated entry * ******************************************************************* * MNGIFT = Maximum nutrient gift in one application (kg) (real) * (note: nutrient, and not gross fertilizer product) MNGIFT = 50.

* FCODE Fertilizer code (number) (real) * FDESCR Fertilizer description (name) (character) * NNAME Nutrient name in fertilizer (name) (character) * NCNT (mean) Nutrient concentration in fertilizer (-) (real) * NPRICE (mean) Nutrient price (colon) (real) * NPY Year of nutrient price (number) (real) * NPM Month of nurteint price (number) (real)

FCODE FDESCR NNAME NCNT NPRICE NPY NPM 0000.00 'none' 'none' 1.00 000. 1997. 03. 0000.00 'N-mean' 'N' 0.33 180. 1997. 03. 0000.00 'P-mean' 'P' 0.33 390. 1997. 03. 0000.00 'K-mean' 'K' 0.33 128. 1997. 03.

II.5 Pesticide

******************************* BIOCID.ATF ********************************* * Biocide attribute file, for PASTOR version 2.0 * Date updated by A. Nieuwenhuyse March 1997 (toxic data for combo have to be checked) **************************************************************************** * BCODE Biocide code (number) (real) I-25

* BNAME Biocide name (name) (character) * BPRICE Biocide price per unit as in BUNIT (colon) (real) * BPY Year of biocide price (number) (real) * BPM Month of biocide price (number) (real) * BUNIT Biocide unit (name) (character] [kg' or 'li') * AI Active ingredient fraction of main biocide (-) (real) * WHO WHO code for severity of main biocide (name) (character) * DUR Duration of main biocide in days of residual action (d) (real) * SOL Solubility of main biocide (g/l) (real) * COMNAME Common name of biocide in product (name) (character)

BCODE BNAME BPRICE BPY BPM BUNIT AI WHO DUR SOL COMNAM 0000.000 'None' 0. 1997. 03. 'kg' 0. 'Ia' 0. 0. 'Zero input' 0000.000 'none' 0. 1997. 03. 'kg' 0. 'Ia' 0. 0. 'Zero input' 0000.000 'Combo' 10468.0 1997. 03. 'li' 0.24 'II' 8. 0.61 1600.000 'Basagram' 4635.0 1997. 03. 'li' 0.04 'III' 48. 0.5 'Bentazone' 1609.904 'Banvel-S' 2250.0 1997. 03. 'li' 0.48 'III' 48. 4.5 'Dicamba' 1600.202 'Diuron-kg' 1095.0 1991. 06. 'kg' 0.8 'III' 64. 0.042 'Diuron' 1600.202 'Diuron-li' 1600.0 1997. 03. 'li' 0.8 'III' 64. 0.042 'Diuron' 1600.204 'Karmex' 1183.0 1991. 06. 'li' 0.9 'III' 64. 0.042 'Diuron' 1600.204 'Karmex-kg' 2875.0 1997. 03. 'kg' 0.9 'III' 64. 0.042 'Diuron' 1601.001 'Gardoprim' 2000.0 1997. 03. 'li' 0.5 'III' 70. 0.0085 1601.201 'Gesaprim' 628.0 1991. 06. 'li' 0.5 'III' 50. 0.03 'Atrazine' 1601.201 'Gesaprim-kg' 2100.0 1997. 03. 'kg' 0.5 'III' 50. 0.03 'Atrazine' 1600.206 'Goal-2EC' 5950.0 1997. 03. 'li' 0.02 'III' 35. 0.0001 'Oxyfluorfen' 1600.208 'Gramoxone' 1127.0 1997. 03. 'li' 0.2 'II' 1000000. 700. 'Paraquat' 1600.209 'Gramuron' 1630.0 1997. 03. 'li' 0.2 'II' 1000000. 700. 'Paraquat 1601.002 'Hedonal' 1180.0 1997. 03. 'li' 0.48 'II' 8. 0.61 '2,4D' 1600.212 'Lazo-EC(=Lasso)' 1835.0 1997. 03. 'li' 0.04 'III' 84. 0.24 'Alachlor' 1600.215 'Prowl-500E' 3060.0 1997. 03. 'li' 0.5 'III' 171. 0.0003 1601.005 '24D' 744.0 1997. 03. 'li' 0.414 'II' 8. 0.61 '2,4D' 1600.217 'Round-up' 2040.0 1997. 03. 'li' 0.41 'III' 30. 12. 'Glyphosate' 1601.006 'Tordon-101' 2800.0 1997. 03. 'li' 0.24 'II' 8. 0.61 'Picloram + 1611.000 'Afungil-50PM' 4000.0 1997. 03. 'kg' 0.5 'III' 225. 0.003 'Benomyl' 1610.000 'Antracol' 1773.0 1997. 03. 'kg' 0.7 'III' 1000000. 0. 'Propineb' 1611.001 'Benlate' 8080.0 1997. 03. 'kg' 0.5 'III' 225. 0.003 'Benomyl' 1614.200 'Daconil-500' 2915.0 1997. 03. 'li' 0.75 'III' 24. 0.006 1614.201 'Daconil-2787W75' 3915.0 1997. 03. 'kg' 0.75 'III' 24. 0.006 1610.001 'Dithane-M-45' 1278.0 1997. 03. 'kg' 0.8 'III' 5. 0. 'Mancozeb' 1610.006 'Manzate-200' 1350.2 1997. 03. 'kg' 0.8 'III' 5. 0. 'Mancozeb' 1610.904 'Orthocide' 1040.0 1997. 03. 'kg' 0.5 'II' 3650. 0.003 'Captan' 1610.905 'Poliram-combi' 1439.0 1997. 03. 'kg' 0.8 'III' 0. 0.01 'Metiram' 1610.007 'Ridomil-MZ58' 5180.0 1997. 03. 'kg' 0.1 'III' 5. 0. 'Mancozeb 1621.000 'Counter' 575.0 1997. 03. 'kg' 0.1 'Ia' 15. 0.0125 'Terbufos' 1620.001 'Diazinon' 2150.0 1997. 03. 'li' 0.6 'II' 23. 0.04 'Diazinon' 1620.302 'Furadan' 1030.0 1997. 03. 'kg' 0.1 'Ib' 37. 0. 'Carbofuran' 1621.401 'Lannate' 11800.0 1997. 03. 'kg' 0.9 'Ib' 6. 58. 'Methomyl' 1620.004 'Lorsban' 2700.0 1997. 03. 'li' 0.04 'II' 89. 0.32 'Chlorpyrifos' 1620.005 'Malathion-li' 1435.0 1997. 03. 'li' 0.57 'III' 30. 0.145 'Malathion' 1620.006 'Malathion-kg' 390.0 1997. 03. 'kg' 0.05 'III' 30. 0.145 'Malathion' 1620.007 'Methil-parathion' 2600.0 1997. 03. 'li' 0.46 'Ia' 19. 0.0575 'Parathion- 1621.001 'Mocap' 1058.0 1997. 03. 'kg' 0.05 'Ia' 32. 0. 'Ethoprophos' 1623.003 'Orthene' 5033.0 1997. 03. 'kg' 0.95 'III' 2. 0.0005 'Acephate' 1621.003 'Perfektion' 2860.0 1997. 03. 'li' 0.5 'II' 14. 25. 'Dimetoate' 1623.004 'Tamaron' 2570.0 1997. 03. 'li' 0.6 'Ib' 3. 500. 1621.100 'Thiodan' 2800.0 1997. 03. 'li' 0.35 'II' 70. 0.00032 'Endosulfan' 1621.402 'Vydate-L' 4720.0 1997. 03. 'li' 0.24 'Ib' 18. 280. 'Oxamyl'

II.6 Cattle

********************** CATTLE.ATF ******************************* * Cattle data attribute file, for PASTOR version 2.0 ***************************************************************** * CCODE Cattle input code (number) (real) * CDESCR Cattle input description (name) (character) * CNAME Cattle input name (name) (character) * CUNIT cattle input unit (measure unity) (character) * CPRICE Cattle input depreciation or rental price, per unit * (colon/unit) (real) * CPY Year of cattle input price date (number) (real) * CPM Month of cattle input price date (number) (real)

CCODE CDESCR CNAME CUNIT CPRICE CPY CPM 0000.00 'No cattle input' 'none' 'no' 0. 1997. 03. 0000.00 'Dectomax antiparasite' 'dectomax' 'ml' 92. 1997. 02. 0000.00 'Panacur inocculation' 'panacur' 'ml' 9.9 1996. 06. I-26

0000.00 'Ripercol inocculation' 'ripercol' 'ml' 7.7 1996. 06. 0000.00 'Neguvon external par.' 'neguvon' 'kg' 4660. 1996. 06. 0000.00 'Nuvan external par.' 'nuvan' 'l' 9750. 1996. 06. 0000.00 'Butox external par.' 'butox' 'l' 21690. 1997. 04. 0000.00 'Bacterine Doble vaccine' 'bacterine' 'ml' 5.1 1996. 06. 0000.00 'Bacterine Triple vaccine' 'bacterine' 'ml' 5.3 1996. 06. 0000.00 'Anthrax vaccine' 'anthrax' 'ml' 4. 1996. 06. 0000.00 'Leptopsirosis vaccine' 'lepto' 'ml' 39. 1996. 08. 0000.00 'Brucellosis vaccine' 'brucel' 'ml' 250. 1996. 06. 0000.00 'Emicine antibiotics' 'emicina' 'ml' 15. 1996. 06.

II.7 Feed

********************** FEED.ATF ******************************* * Supplementary feed data attribute file, for PASTOR version 2.0 * Updated by A.Nieuwenhuyse April 1997 ***************************************************************** * FCODE Suppl. feed input code (number) (real) * FDESCR Suppl. feed input description (name) (character) * FNAME Suppl. feed input name (name) (character) * FUNIT Suppl. feed input unit (measure unity) (character) * FCOD Suppl. feed input three-letter code (name) (character) * FPRICE Suppl. feed input price, per unit (colon/unit) (real) * FPY Year of Suppl. feed input price date (number) (real) * FPM Month of Suppl. feed input price date (number) (real) * FDM dry matter content of fresh suppl. feed (%) (real) * FCP Crude protein content of fresh material (%) (real) * FME Metabolizable energy content of fresh material (Mcal/kg) (real) * FP Phosphorus content of fresh material (%) (real) * FK Potassium content of fresh material (%) (real)

FCODE FDESCR FNAME FUNIT FCOD FPRICE FPY FPM FDM FCP FME FP FK 0000.00 'No supl. feed' 'none' 'no' 'NON' 0. 1997. 04. 0. 0. 0. 0. 0. 0000.00 'Molasse of cana' 'molasse' 'kg' 'MOL' 21.7 1997. 04. 77. 7.44 2.7 0.054 1.94 0000.00 'Green banana' 'banana' 'kg' 'BAN' 2.9 1997. 04. 17. 0.74 0.41 0.017 0.48 0000.00 'Gallinaz.engorde' 'conc1' 'kg' 'CN1' 21.7 1997. 04. 87. 17.0 2.5 0.8 0. 0000.00 'Gallinaz.engorde' 'conc2' 'kg' 'CN2' 19.6 1997. 04. 87. 16.0 2.25 1.3 0. 0000.00 'Gallinaz.leche' 'conc3' 'kg' 'CN3' 26.1 1997. 04. 87. 17.0 2.55 0.9 0. 0000.00 'Gallinaz.leche' 'conc4' 'kg' 'CN4' 34.8 1997. 04. 87. 13.0 3.04 0.8 0. 0000.00 'Mineral salt' 'minsalt' 'kg' 'MNS' 69. 1996. 06. 100. 0. 0. 0. 0. 0000.00 'Pecutrin salt' 'pecutrin' 'kg' 'PEC' 222. 1996. 06. 100. 0. 0. 19. 0. 0000.00 'Common salt' 'salt' 'kg' 'SAL' 20. 1997. 04. 100. 0. 0. 0. 0. 0000.00 'P20 phosphorus' 'p20' 'kg' 'P20' 178. 1996. 06. 100. 0. 0. 19. 0. 0000.00 'MG micronutrients' 'MG' 'kg' 'MG0' 117. 1996. 06. 100. 0. 0. 0. 0. I-27

(Sectie 5) Appendix II: titel Deze sectie en de sectie hieronder zijn alleen nodig als men een programmalisting in twee kolommen geprint wil hebben. Hier worden twee secties voor gebruikt omdat er anders geen normale kop boven de listing geplaats kan worden. Vergeet niet om de stijl Listing 2 voor Sectie 6 gebruiken. Voor de paginanummering zie Sectie 4 hierboven.

(Sectie 6) deze sectie is bedoeld voor een programmalisting in twee kolommen.