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The effects of agricultural management on carbon and nitrogen dynamics in dairy farms (in B.C. and Austria) Persy, Eva 2000

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THE E F F E C T S OF AGRICULTURAL MANAGEMENT ON CARBON AND NITROGEN DYNAMICS IN DAIRY FARMS (IN B.C. AND AUSTRIA) By EVA PERSY Dipl. Ing., Universitaet fuer Bodenkultur Wien, 1998 A THESIS SUBMITTED IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF MASTER OF SCIENCE In THE FACULTY OF GRADUATE STUDIES Resource Management and Environmental Studies We accept this degree as conforming to the required standard THE UNIVERSITY OF BRITISH COLUMBIA August 2000 (£) Eva Persy, 2000 In presenting this thesis in partial fulfilment of the requirements for an advanced degree at the University of British Columbia, 1 agree that the Library shall make it freely available for reference and study. I further agree that permission for extensive copying of this thesis for scholarly purposes may be granted by the head of my department or by his or her representatives. It is understood that copying or publication of this thesis for financial gain shall not be allowed without my written permission. Department of ft&sourc? flQM&$Xvu±u\ &Uoi VlCOiA The University of British Columbia Vancouver, Canada DE-6 (2/88) ii Abstract Environmental impacts of conventional agricultural practices - especially the contribution to C 0 2 emissions and nitrate losses to water bodies - have intensified, and with it the need for studying carbon and nitrogen cycling in soils. In North America and Europe agricultural management practices of specialisation and intensification have resulted in soil degradation including loss of organic matter and consequent increase in C 0 2 emissions, and the leaching of nutrients, notably nitrate. Mass balance calculations for carbon and nitrogen in agroecosystems can provide informa-tion about their turnover in relation to crop demand and potential losses to the environment. Such calculations may be used to analyse the influence of different farm management practices on C and N dynamics of agricultural systems. The case study employed in this research were typical dairy farms in British Columbia (B.C.), Canada and Austria. The dairy farms - a conventionally managed farm in B.C., a conventionally managed farm in Austria, and an organically managed farm in Austria1 - were selected as these are comparable in terms of climatic conditions and soil materials. The field scale carbon balances are calculated as the difference between C additions to, and C removals from, the soil root zone. Input organic matter flows are root and plant residues as well as manure additions. Decomposition of new (root and plant residues, manure) and old organic matter as well as leaching of dissolved carbon are considered to be output flows. The field scale nitrogen balances are calculated in the same way: N additions are assumed to come from manure, inorganic fertiliser, biological N fixation and atmospheric sources. N removal is by crop harvest and denitrification. Results for the C balances of the Austrian farms show that organic management, compared to conventional management, has a positive balance (393 kg C/ha/yr) and thus contributes to soil storage of carbon. For the Austrian conventional fields the C output exceeds the C input. The resulting negative balance (-123 kg C/ha/yr) indicates net C 0 2 emissions. The C balances comparison of the conventional farms (B.C. vs. Austria) show, that farm management in B.C. causes more net C 0 2 emissions (-364 vs. -123 kg C/ha/yr, respectively) and this is attributed to more intensive management. Sensitivity analyses for the carbon balance model show that the deciding factors are associated with high uncertainties. Thus goals for future research are (i) to improve further the estimates of C 0 2 release due to organic matter decomposition, and (ii) to understand how climatic changes influence changes in soil organic matter. iii Results for the N balances of the Austrian farms show that organic management, compared to conventional management, has a negative N balance (- 43 vs. 1 kg N/ha/yr, respectively). The N balances comparison of the conventional study farms (B.C. vs. Austria) show that for the B.C. farm management the N input is significantly exceeding the N output. In contrast, in the Austrian fields, input and output flows are balanced. Thus it can be assumed that the Austrian farm management does not contribute significantly to nitrate pollution of surface and ground -waters. Sensitivity analyses for the N balance model show that the deciding factors (mineral fertiliser rate, plant N removal, and livestock density) are associated with small uncertainties. However, a major uncertainty is atmospheric deposition of ammonia. This requires future research. Nitrogen fertilisation must be more closely adjusted to crop requirements (Austrian conventional farm) and suited to the environmental conditions to prevent nitrogen losses. As organic dairy farming has a higher C- and N-efficiency than conventional dairy farming, the possibilities to reduce C- and N-loss by conversion to organic dairy production appear to be promising. A comparable organically managed farm in B.C. could not be found. Table of Contents ABSTRACT " TABLE OF CONTENTS i v LIST OF TABLES Vti LIST OF FIGURES , '. *x 1 INTRODUCTION 1 1.1 G E N E R A L I N T R O D U C T I O N l 1.2 N E G A T I V E C O N S E Q U E N C E S O F C O N V E N T I O N A L A G R I C U L T U R E 1 1.2.1 The environmental impact of agricultural practices 2 1.2.1.1 Air pollution 2 1.2.1.2 Water pollution 3 1.2.1.3 Loss of Biodiversity 3 1.2.1.4 Soil degradation 4 1.3 I M P O R T A N C E O F S O I L H E A L T H 4 1.3.1 Approach to assess impact of agricultural activities on soils: Development of effective agri-environmental indicators 5 1.4 S T U D Y O U T L I N E 7 2 CONTRIBUTION OF CONVENTIONAL AGRICULTURE TO GREENHOUSE GAS EMISSIONS AND AGROCHEMICAL WATER CONTAMINATION 8 2.1 C O N T R I B U T I O N T O G R E E N H O U S E G A S E M I S S I O N S : 8 2.1.2 Situation in Canada 10 2.1.2.1 Climate change in B.C 10 2.1.3 Situation in the EU. 11 2.1.3.1 Situation in Austria 12 2.2 C O N T R I B U T I O N T O A G R O C H E M I C A L W A T E R C O N T A M I N A T I O N 13 2.2.1 Situation in Canada ...13 2.2.1.1 Situation i n B .C 13 2.2.2 Situation in the EU. 14 2.2.2.1 Situation in Austria 14 3 C 0 2 EMISSIONS AND NITRATE LEACHING AS ENVIRONMENTAL INDICATORS THAT RELATE TO AGRICULTURAL SOIL MANAGEMENT 15 3.1 T H E O R E T I C A L B A C K G R O U N D R E G A R D I N G C 0 2 E M I S S I O N S 15 3.1.1 Concepts and Cycling of Soil Carbon 75 3.1.1.1 The G l o b a l C a r b o n C y c l e . . . 1 5 V 3.1.1.2 The Terrestrial Carbon Cycle 16 3.1.1.3 Soil Organic Matter (SOM) 18 3.1.1.4 Soil Carbon Models 22 3.1.1.5 Carbon Balances 23 3.1.2 Management Effects on Soil Carbon Dynamics 24 3.2 T H E O R E T I C A L B A C K G R O U N D R E G A R D I N G N I T R A T E L E A C H I N G 26 3.2.1 Concepts and Cycling of Soil Nitrogen 26 3.2.1.1 The Global Nitrogen Cycle 26 3.2.1.2 Soil Nitrogen 26 3.2.1.3 Nitrogen models 27 3.2.1.4 Nitrogen balances 28 3.2.1.5 Carbon and Nitrogen Interactions in Soils 29 3.2.2 Management Effects on Soil Nitrogen Dynamics .....30 3.3 N U T R I E N T B A L A N C I N G : , 32 The Importance of Nutrient Balancing for Sustainable Agricultural Management 32 4 D I F F E R E N C E S I N A G R I C U L T U R A L M A N A G E M E N T 34 4.1 I M P O R T A N T M A N A G E M E N T F A C T O R S 34 4.2 M A N A G E M E N T O F G R A S S L A N D S Y S T E M S 35 4.3 O R G A N I C F A R M I N G : D O I N G IT T H E S U S T A I N A B L E W A Y ....37 4.3.2 Organic Grassland Farming as a Carbon Sink 39 4.4 A G R I C U L T U R E I N B.C. A N D A U S T R I A 42 5 T H E C O M P A R A T I V E R E S E A R C H C A S E S T U D I E S 44 5.1 R E S E A R C H O B J E C T I V E S A N D H Y P O T H E S E S i 44 5.1.1 Hypotheses 46 Hypotheses for comparing budgets in conventional vs. organic farms in Austria 46 Hypotheses for comparing budgets in conventional farms in Canada and Austria 46 5.2 M A T E R I A L S A N D M E T H O D S ,....47 5.2.1 Description of the Study Regions 47 5.2.1.1 Study region in British Columbia, Canada: Fort Langley 47 5.2.1.2 Study region in Austria: Molln and Laussa-Losenstein 48 5.2.2 Selection of farms : 49 5.2.3 Data collection :'. 50 5.2.3.1 Collection of farm management data 50 5.2.3.2 Soil Sampling and Analysis 52 5.2.4 Carbon balances 52 5.2.4.1 Calculation of field scale carbon balances with a static input-output model 52 5.2.4.2 Calculation of steady state carbon inputs with a dynamic SOM model (ICBM) 55 5.2.5 Nitrogen Balances : 57 5.2.5.1 Calculation of field scale nitrogen balances with a static input-output model 58 5.2.5.2 Calculation of farm scale nitrogen balances with a static input-output model 60 5.2.6 Uncertainties, Limitations, Sensitivity Analysis 61 5.2.6.1 Accuracy of the budgets 61 5.2.6.2 Sensitivity Analyses 62 5.2.6.3 Limitations of black box models 62 V i 5.3 RESULTS - FORT L A N G L E Y CONVENTIONAL DAIRY F A R M 63 5.3.1 Collected data 63 5.3.2 Carbon Balance • 65 5.3.3 Nitrogen Balance 67 5 .4 RESULTS - AUSTRIAN CONVENTIONAL DAIRY FARM 69 5.4.1 Collected data .' : 69 5.4.2 Carbon Balance : 70 5.4.3 Nitrogen Balance 72 5.5 RESULTS - AUSTRIAN ORGANIC DAIRY FARM 73 5.5.1 Collected data -73 5.5.2 Carbon Balance 75 5.5.3 Nitrogen Balance 77 5.6 COMPARISON OF THE RESULTS 79 5.6.1 Field scale carbon balances ,-. 79 5.6.2 Steady state carbon inputs 81 5.6.3 Field scale nitrogen balances 81 5.6.4 Farm scale nitrogen balances '. 83 5.7 SENSITIVITY ANALYSES 85 5.8 DISCUSSION OF THE RESULTS FROM THE CASE STUDIES 88 5.5.7 General remarks 88 5.8.2 Comparison with related findings 88 5.9 DISCUSSION OF THE HYPOTHESES 92 5.9.7 Hypotheses for conventional vs. organic comparisons in Austria 92 5.9.2 Hypotheses for BC vs. A comparisons in conventional farms 93 6 S U M M A R Y , C O N C L U S I O N 9 5 6.3.1 Options and Recommendations 97 7 R E F E R E N C E S , 9 9 8 A P P E N D I X 1 0 4 8.3 A D CHAPTER 4 104 8.4. A D CHAPTER 5 , ; 105 8.4.1 Additional Farm Data: Fort Langley dairy farm , 705 8.4.2 Additional Farm Data: Austrian conventional dairy farm 108 8.4.3 Additional Farm Data: Austrian organic dairy farm '. 709 8.4.4 Sensitivity Analyses HO List of Tables Table 1.3-1: Potential cumulative effects of agricultural activities on soils 6 Table 1.3-2: Selected Indicators 7 Table 2.1-1: Energy use in crop and animal production (Jackson, 1993 in Rosenzweig and Hillel, 1998) 10 Table 2.1-2: Median value of the monthly change ih temperature and precipitation projected by three General Circulation Models, comparing a 1 x C02 to a 2 x C02 scenario (source: Zebarth etal., 1997) 11 Table 3.1-1: Major active reservoirs in the natural global carbon cycle and geological stores of recoverable fossil fuels (adapted from Post et al., 1990)... 15 Table 3.1-2: Fluxes of Carbon to and from the Atmosphere (adapted from Post et al., 1990) 16 Table 3.1-3: Examples of C sequestration rates with conversion of agricultural land in some temperate locations (Paustian et al., 1997) 18 Table 3.1-4: Mean C content of soils in major ecosystems in 1980 (Houghton, 1995) 19 Table 3.1-5: Partial composition [%] of mature plant tissue and SOM (source: Foth, 1984) 20 Table 3.1-6: Soil organic matter fractions and their turnover times 21 Table 3.1-7: Annual balance for a submontane non-cultivated Bohemian grassland (Tesarova, 1988) and a cultivated Swedish grassland ley (Paustian, 1990) 23 Table 3.2-1: Characteristics of the three types of nitrogen (source: Plaster, 1992). 26 Table 3.2-2: Nitrogen balances for different regions in B.C. [kg N/ha/yr] 28 Table 3.2-3: N farm balances on a conventional and organic farm in Sweden ( Cederberg and Mausson, 2000) 29 Table 3.2-4: Carbon concentrations after 30 years of different treatments (source: Paustian etal., 1992) 30 Table 3.2-5: Global conversion of fertilizer nitrogen to nitrous oxide in soils (Jackson in Rosenzweig and Hillel, 1998) 31 Table 3.3-1: Definitions of Sustainability 33 Table 4.1-1: Most important management factors that influence carbon and nitrogen flows in agroecosystems 34 Table 4.2-1: Grassland farming compared to arable farming 36 Table 4.3-1: Ecological and productional-economic differences between conventional and organic management of grassland systems (adapted from Kleber, 1997) 39 Table 4.4-1: Statistics on Agriculture in B.C. and Austria (BCMAFF 1990, 1996; BMLF, 1998; COABC, 1997) .,43 Table 5.2-1: Short description of the study sites 50 Table 5.2-2: Short description of site identification 50 Table 5.2-3: Dairy Farm Questionnaire 51 Table 5.2-4: Example for a management scheme 51 Table 5.2-5: Soil carbon balance 54 Table 5.2-6: Root-shoot data (kg C/ha) for forage grasses 55 Table 5.2-7: Conversion of cattle type to LU 55 Table 5.2-8: IBCM parameters (adapted from Katterer and Andren, 1997, 1999) 57 Table 5.2-9: Field scale nitrogen balance 59 Table 5.2-10: Conversion of cattle type to LU 59 Table 5.2-11: Nitrogen losses [%] from animal manure as affected by method of handling/storage and application 60 Table 5.2-12: Farm scale nitrogen balance (in kg N) 61 vm Table 5.3-1: Dairy Farm Questionnaire - Fort Langley dairy farm 63 Table 5.3-2 Carbon balance for all fields (40 ha) of the Fort Langley dairy farm 65 Table 5.3-3: LU - Fort Langley dairy farm 66 Table 5.3-4: ICBM data for Fort Langley farm 66 Table 5.3-5 Nitrogen balance for all fields (40 ha) of the Fort Langley dairy farm 67 Table 5.3-6; Farm scale nitrogen-balance for the Fort Langley farm (in kg N) 68 Table 5.4-1: Dairy Farm Questionnaire - Austrian conventional dairy farm 69 Table 5.4-2 Carbon balance for the Austrian conventional dairy farm 70 Table 5.4-3: LU - Austrian conv. dairy farm 71 Table 5.4-4: ICBM data for the Austrian conventional farm 71 Table 5.4-5 Nitrogen balance for the Austrian conventional dairy farm 72 Table 5.4-6; Farm scale nitrogen-balance for the Austrian conv. dairy farm (in kg N) 73 Table 5.5-1: Dairy Farm Questionnaire - Austrian dairy farm 73 Table 5.5-2 Carbon balance for the Austrian organic dairy farm 75 Table 5.5-3: LU - Austrian organic dairy farm 75 Table 5.5-4: ICBM data for the Austrian organic farm 76 Table 5.5-5 Nitrogen balance for the Austrian dairy farm 77 Table 5.5-6; Farm scale nitrogen-balance for the Austrian organic farm (in kg N) 78 Table 5.6-1: Comparison of the C-balances (summary) 79 Table 5.6-2: Comparison of the C input flows 81 Table 5.6-3: Comparison of the N-balances at field scale (summary) 82 Table 5.6-4; Comparison of the farm scale nitrogen-balances (summary) 83 Table 5.7-1: Carbon model - Sensitivity and uncertainty 86 Table 5.7-2: Nitrogen model - Sensitivity and uncertainty 87 Table 5.8-1: Carbon balances [kg C/ha/yr]: comparison with grassland systems from literature 89 Table 5.8-2: Field Scale Nitrogen balances [kg N/ha/yr]: comparison with grassland systems from literature 90 Table 5.8-3: Farm Scale Nitrogen Balances [kg N/ha/yr]: comparison with grassland systems from literature 91 Table 5.9-1: outcome for the C balances regarding conventional vs. organic comparisons in Austria [HYPOTHESES 1+2] 92 Table 5.9-2: outcome for the N soil balances regarding conventional vs. organic comparisons in Austria [HYPOTHESIS 3] 93 Table 5.9-3: outcome for the C balances regarding BC vs. A comparisons in conventional farms [HYPOTHESIS 4] 93 Table 5.9-4: outcome for the N farm balances regarding BC vs. A comparisons in conventional farms [HYPOTHESIS 5 + 6] 94 Table 5.9-1: Policy instruments and measures that influence C- and N- losses from agriculture (adapted from Storey and McKenzie-Hedger, 1997) 98 Table 8.3-1: Figures on organic farming in Europe and Canada (http://www.ifoam.de/statistics) 105 Table 8.4-1: Manure-N production rate 106 Table 8.4-2: Management scheme 1999 - Fort Langley dairy farm 106 Table 8.4-3: concentrations [ppm] of nitrate, ammonium, DOC, TOC - farm ditch water (neutral pH) 106 Table 8.4-4: Management scheme - Austrian conv. dairy farm 109 Table 8.4-5: Management scheme - Austrian organic dairy farm 110 List of Figures Figure 3.1-1: Terrestrial C-Cycle Figure 3.1-2: Theoretical changes in soil C as influenced by management (AGRI CAN, 1999) Figure 3.2-1: N flows in agricultural soils Figure 3.2-2: Carbon and Nitrogen Interactions in Soils Figure 5.1-1: influence of different management regimes on soil input-output flows Figure 5.2-1: Mean monthly temperature and precipitation for the study regions in B.C. and Austria 49 Figure 5.2-2: Flow chart of the carbon static model Figure 5.2-3: Field scale and farm scale for the nitrogen balances Figure 5.6-1: Comparison of the C-balances Figure 5.6-2: Comparison of the N-balances at field scale Figure 5.6-3: Comparison of the farm scale nitrogen-balances Figure 5.7-1: Sensitivity analyses for the carbon model Figure 5.7-2: Sensitivity analysis for the nitrogen model Figure 8.4-1: Location of the sampling sites - Fort Langley dairy farm 1 Figure 8.4-2: Results Soil Carbon (Fort Langley) 1 Figure 8.4-3: Results Soil Carbon (Austrian conventional farm) 1 Figure 8.4-4: Results Soil Carbon (Austrian organic farm) 1 1 1 INTRODUCTION 1.1 General Introduction For most of the twentieth century, industrialisation and economic growth have been the main aims of mankind in the world. Still for most people and their political leaders economic growth is by far more important than the ecological condition of the countries they live in. Nevertheless the public concern for environmental issues has risen rapidly during the last few decades, and voices coming from all corners of the society now draw attention to the severity of present ecological crises. Scholars too are calling for shifts in human behaviour. A worldwide collection of 1575 scientists, including 99 Nobel Price winners, noted that "human beings and the natural world are on a collision course. A great change in lifestyle and stewardship of the earth resources is needed if we hope to prevent widespread human misery, and irreversible mutilation of the global resources" (Karr, 1996). Numerous international research programs (for example, Man and Biosphere, IGBP) were initiated during the last few years and they clearly show the important role of ecology and ecological change in both theoretical and applied science. Special attention needs to be given to the ecological health of the agroecosystems1 particularly in terms of sustainable use. 1.2 Negative Consequences of Conventional Agriculture Over the past 50 years, agriculture within developed countries has become increasingly dependent upon external inputs of chemicals and mechanisation (Storey and McKenzie-Hedger, 1997). This specialisation and intensification of agricultural production (often including the de-coupling of livestock and arable farming) caused: • Environmental problems 1 Agroecosystems have perhaps the greatest impact on our lives of any ecosystem because they provide food and fibre and have large impacts upon the environment (Elliott and Cole, 1989). They cover about 11 % of the land surface of the earth, located on some of the most productive and richest soils. 2 Environmental problems caused by agriculture have become a major concern in most industrialised nations. In Canada soil degradation alone has been estimated to cost over $2 billion per year (Hill and MacRae, 1993). These concerns have been magnified by Canada's limited supply of high quality agricultural land. • Health concerns Consumer-surveys conducted in industrialised countries have confirmed high levels of concern regarding pesticides and other health-threatening contaminants in foods. In Canada more and more farmers are regarding pesticides as a threat to health (Hill and MacRae, 1993). • A suffering farm economy Conventional farmers are caught in a cost-price squeeze. In most industrialised nations massive government subsidies have been required to prevent numerous farm failures. In Saskatchewan alone ten thousand farms were facing foreclosure in 1990 (Hill and MacRae, 1993). With the progressive growth of the world population and the increase in prosperity in the developed countries the demand for food increased also progressively and thus the pollution of air, water and soil caused by agriculture. The following section focuses on describing the environmental degradation that results from agricultural activities. 1.2.1 The environmental impact of agricultural practices 1.2.1.1 Air pollution The emissions produced by an intensified agriculture are carbon mono- and dioxide, methane, nitrous oxide, ammonia and diverse hydrocarbons. Carbon dioxide, methane and nitrous oxide are greenhouse gases and their impact will be discussed further down (Chapter 2). Ammonia emissions are primarily from livestock farming and can cause acidification of soils and water as well as odour problems. Losses of ammonia occur during (1) slurry application, (2) storage, (3) grazing, (4) fertiliser application and from (5) crops. Animal waste is the major source in four of the six cases (Bussink and Oenema, 1998). This ranking varies 3 between farms and between countries, depending on environmental conditions and management practices. 1.2.1.2 Water pollution Impacts to water quality from agricultural practices depend upon a range of factors including the type of crop, intensity of activity, physical features of the landscape, soil type, precipitation patterns, and precautions undertaken by the producer. In general, agricultural water contamination originates from diffuse sources (e.g. fertilisation and manure application) rather than from point sources (e.g. inappropriate storage of manure). Resulting impacts to water quality from intensive agricultural practices are (a) loss or damage of riparian vegetation and (b) agricultural runoff. (a) Damage to or elimination of riparian habitat causes sedimentation of stream beds, high suspended sediment levels, and elevated water temperatures. • The clearing of streamside vegetation can result in increased summer water temperatures, which decreases the oxygen carrying capacity of water and increases the metabolic rate of aquatic organisms. An increased metabolic rate coupled with decreased oxygen concentrations in water can cause physical and physiological stress, possibly leading to death of aquatic organisms. • Loss of riparian vegetation also affects physical fish habitat, and eliminates an important source of fish food - insects which drop from overhanging vegetation, and leaf litter, an important food source for many insects which in turn are consumed by fish. • erosion and siltation due to removal of riparian vegetation (b) Problems associated with agricultural runoff are high concentrations of nutrients (leading to eutrophication and low dissolved oxygen concentrations), bacteria, salts and metals; and in some cases direct toxicity from substances such as ammonia and pesticides. 1.2.1.3 Loss of Biodiversity Agricultural activities such as tillage, drainage, and extensive usage of pesticides and fertilisers have significant impacts on wild species of flora and fauna. According to van Elsen 4 (2000) today's intensive agriculture is considered to be the main agent responsible for the decline of plant species. Biodiversity may be limited directly by the disturbance from mechanical operations associated with agricultural activity or by the use of pesticides (McLaughlin and Mineau, 1995). Some species of flora and fauna disappear because of the abundance of plant and insect foods available (indirect limitation). Certain management techniques, such as drainage, create such fundamental habitat changes that there are significant shifts in species composition. 1.2.1.4 Soil degradation Agricultural activities can cause several forms of soil degradation: erosion, compaction, desertification, and water-logging (physical stress); contamination by heavy metals, pesticides and nutrients (mostly N and P), acidification, and salinisation (chemical degradation). In general, the more an agricultural activity disturbs the land's natural ecology, the greater it affects soil quality. For example, row-cropping systems offer less protection against erosion than crops that provide continuous ground cover. Intensive tillage alters soil structure more than minimal tillage (Acton and Gregorich, 1995). Soil ecosystems are highly complex. Together with water and biota, they form a system of interrelationships changing over time and space. Erosion, for example, affects soil health in many ways: soil water storage capacity is reduced, nutrients are lost and soil structure is changed, as the finer soil particles are moved further away than the coarser ones (Skinner et al, 1997). In some areas the removed materials are transported to the water body and affect the water quality. 1.3 Importance of soil health Soil health is a key component of environmental health. Central to this thesis is the concept that "healthy agriculture" starts with the soil. Only a well-balanced and biologically-active soil will provide the crop with sufficient nutrients for optimum growth and yields, and with a minimum of pest and disease problems. As already discussed, the impacts on agricultural soils are characterised by multiple stress factors, such as application of agrochemicals and disturbance due to mechanical operations. 5 Their cumulative effects change the viability of the system. To assess this change agri-environmental indicators are used. An agri-environmental indicator is a measure of change either in the state of environmental resources used or affected by agriculture, or in farming activities that affect the state of these resources (Acton and Gregorich, 1995). 1.3.1 Approach to assess impact of agricultural activities on soils: Development of effective agri-environmental indicators The following section discusses the general concept of cumulative effects and how to assess them with the help of indicators. Multiple stress factors cause cumulative effects Cumulative effects are characterised by the temporal and spatial accumulation of change in an environmental system. They can arise from multiple human activities in a certain area or from multiple impacts on the environment from a single, repeated activity. Many diverse and distant factors are now recognised as causing cumulative effects. For example, certain economic sectors may be directed or controlled by governments or jurisdictional institutions in ways that cause long-term environmental degradation. The agricultural industries of the European Union provide a good example of this case. Pre-1992 Common Agricultural Policy supported enhanced production at virtually any environmental cost, resulting in an uncontrolled expansion of the agricultural base. Concentration, intensification and specialisation at farm level caused severe environmental problems such as increased nitrate concentration in ground water, the decline of endangered plant species (Hoell and von Meyer, 1996) and soil compaction leading to higher surface-runoff. A working definition of cumulative effects based on the CEARC/U.S. National Research Council's definition has been proposed by Lane (1998): 1. Cumulative effects happen over a period of time when the same type of perturbation occurs with high frequency such that the separate perturbations are not damped out by the ecosystem (time crowding). 2. Cumulative effects happen in space when the same perturbation occurs in locations so close together that effects overlap spatially (space crowding). 6 3. Cumulative effects occur from different types of perturbations (possibly from separate activities) that affect similar environmental components if the spatial-temporal scales of the perturbations overlap sufficiently. An application of this typology to agricultural activities is shown in Table 1.3-1. Table 1.3-1: Potential cumulative effects of agricultural activities on soils Cumulative Effect J Description time crowding multiple perturbations to the environment from a single, repeated activity: e.g. application of agrochemicals space crowding multiple human activities in a given region: soil compaction, drainage, irrigation, Health indicators for agricultural soils Soil health is a composite picture of the soil's various parts and functions. It can be compared to human health, which is also a composite picture of the body's condition. Just as there is no single indicator for human health, there are many possible measures for soil health.Traditionally, the following indicators are used to assess soil quality: Physical Plant-available water Soil structure Soil strength Maximum rooting depth Erosion Compaction Chemical PH Base saturation Salinity Intrinsic Resources Total nitrogen Total carbon Cation exchange capacity Biological Biodiversity of microorganisms These indicators provide a measure for the chemical, physical, biological, and intrinsic resource characteristics of a soil. However, they do not measure dynamic soil processes. Recently, soil scientists recognised the importance of studying the flow of nutrients through an ecosystem. Attention has shifted from nutrient stocks per se, to the balance between 7 inputs and outputs, and the agronomic and environmental consequences of disturbing these balances (Smaling and Oenema, 1997). Mass balance calculations for carbon and nitrogen in agroecosystems provide information about potential losses of these elements to the environment (van Faassen and Lebbink, 1994). It is the aim of this project to use such calculations to analyse the influence of different farm management practices on net C 0 2 emissions and nitrate leaching (Table 1.3-2) of typical dairy farms in B.C. and Austria. Table 1.3-2: Selected Indicators. Indicator Translation into concept of nutrient balanc ing Nitrate leaching Positive N balance (N surplus) Net C02 emissions Negative C balance (C source) Net CO? emissions and nitrate leaching have been selected as effective indicators to assess the impact of agricultural activites on soils for the following reasons: • link to an agri-environmental issue (climatic change and water quality, respectively. The contribution of conventional agriculture to greenhouse gas emissions and reduced water quality are discussed in Chapter 2). • ability to assess cumulative effects (ability to integrate effects over time and space) • sensitivity to the impacts being evaluated • response to changes over time • applicability 1.4 Study Outline Chapter 2 focuses on the contribution of conventional agriculture to greenhouse gas emissions and agrochemical water contamination. Chapter 3 offers a literature review on the theoretical background of this thesis. The concepts and cycling of soil organic matter, carbon and nitrogen will be explained. Also the importance of mass balance calculations for carbon and nitrogen in agroecosystems will be discussed. Chapter 4 is devoted to differences in agricultural mgt. Chapter 5 describes the case studies (3 typical dairy farms in B.C. and Austria) evaluated for this thesis. A relevance of the research and the conclusions are presented in Chapter 6. 8 2 Contribution of Conventional Agriculture to Greenhouse G a s Emissions and Agrochemical Water Contamination In the following sections the contribution of conventional agriculture to greenhouse gas emissions and agrochemical water contamination will be discussed - in general, for Canada (focussing on B.C.) and for the European Union (EU)2 (focussing on Austria). 2.1 Contribution to Greenhouse Gas Emissions In June 1992, 154 countries and the EU signed the United Nations Framework Convention on Climate Change at the United Nations Conference on Environment and Development (UNCED). The objective of this Convention was to achieve stabilisation of greenhouse gas concentrations in the atmosphere at a level that would prevent dangerous anthropogenic interference with the climate system. This Convention explicitly acknowledges the significance of agriculture. Agricultural activities are responsible for about 20% (Watson, 1996) of total anthropogenic emissions of greenhouse gases, particularly the emission of carbon dioxide, methane and nitrous oxide. Carbon dioxide, the most prominent greenhouse gas, is emitted because of initial cultivation of soils, management of existing fields, and the use of fossil fuels to produce fertilisers and drive farm machinery. Methane is the second most important greenhouse gas after C 0 2 . It is released through digestive processes (enteric fermentation) in domestic livestock and while manure is stored. Of all domestic animal types, beef and dairy cattle are by far the largest emitters of methane. Other C H 4 sources are fields of wetland rice, called rice paddies. Source of nitrous oxide emissions are manure management, fertiliser application and biomass burning. As this thesis focuses on agricultural activities associated with soils, the issues regarding emissions of methane and nitrous oxide will not be discussed. The European Union currently comprises of Austria, Belgium, Denmark, Finland, France, Germany, Great Britain, Greece, Holland, Ireland, Italy, Luxembourg, Portugal, Spain and Sweden. 9 Carbon dioxide emissions from agriculture Today, the conversion of natural ecosystems into agricultural land is the second largest source of C 0 2 emissions after fossil fuel combustion (Rosenzweig and Hillel, 1998). When natural ecosystems are turned into agricultural land, much of the vegetation originally present is removed. Usually, the material above ground is burned or decomposes rapidly. The organic material in the soil does decompose more slowly, but over time releases significant quantities of C 0 2 . Much land clearing occurs in the tropics, where population increase, desire for higher living standards, and other socio-political factors drive the demand for new cropland. Currently only half of the conversion of tropical forests to agriculture contributes to an increase in productive cultivated area; the rest is used to replace degraded agricultural land (Watson, 1996, chapter 23). In temperate regions the cultivated land base has remained approximately constant, and in regions with food surpluses, such as N-America and Western Europe it has even reduced (partly due to urban expansion). Not only the initial cultivation of soils, but also the ongoing management of existing fields contributes to greenhouse gas build-up. By choosing the crops, fertilizer treatments, and other management options, farmers can influence the amount of C 0 2 being released from the fields. Tillage, for example, accelerates the loss of soil carbon by increased oxidation, erosion and decreased physical protection through mechanical stress. Other practices that increase C 0 2 emission rates are biomass burning, cultivation of marginal lands, expansion of agricultural activities to ecologically-sentitive ecoregions, and systems that exacerbate soil degradative processes (Lai et al., 1995). The IPCC (Intergovernmental Panel on Climate Change) estimates the global historical (since initial cultivation) losses of soil carbon to be 55 Gt carbon (Watson, 1996, chapter 23). These global estimates of carbon loss from cultivated soils provide a reference level for the carbon sequestration that might be achieved though improved management. Assuming a recovery of one-half to two-thirds of historic carbon losses, the global potential for carbon sequestration over the next 50 - 100 years would be about 20 - 30 Gt carbon (Watson, 1996, chapter 23). Also the combustion of fossil fuels to provide energy - needed to drive farm machinery and to produce agricultural chemicals - contributes to C 0 2 emissions. For example, to produce synthetic fertiliser containing 1 kg of nitrogen about 1.2 kg of fossil carbon are needed (Rosenzweig and Hillel, 1998). 10 Energy is required for all agricultural operations, but the energy requirements of different systems vary (Table 2.1-1). In traditional farming, animal and human labor, as well as solar energy (photosynthesis) are the primary energy sources. Modern intensive agriculture requires much greater energy inputs, especially due to tillage and harvest operations. The largest consumer of fossil energy in modern agriculture is high-intensity animal production. Table 2.1-1: Energy use in crop and animal production (Jackson, 1993 in Rosenzweig and Hillel, 1998) Agricultural system energy demands (GJ/ha) traditional up to 5 transitional 6 - 1 4 intensive 15-40 2.1.2 Situation in Canada In Canada, agricultural activities are responsible for about 10 % of total national greenhouse gases emissions, particularly carbon dioxide, methane, and nitrous oxide (AAFC, 1998). The significance of agriculture as a source of greenhouse gas emissions is closely related to the intensity of agricultural production (use of fossil fuels, fertilisers). The following section is devoted to the impact of increased greenhouse gas levels on climate change. It focuses on the effects of climate change on agricultural production in B.C. 2.1.2.1 Climate change in B .C . Some climate models suggest a rise in average temperature over the next 100 years of 2 to 4 °C in southern Canada, and even higher in the North (BCMEPR and BCMELP, 1995). The general prediction for B.C. is, that winters will be warmer and wetter, and summers will be warmer and drier. The predicted changes in temperature and precipitation vary from region to region (Table 2.1-2: Predicted changes in temperature and precipitation for four regions in B.C.; Zebarth et al., 1997) because of the distinct nature of the climate within each region. 11 Table 2.1-2: Median value of the monthly change in temperature and precipitation projected by three General Circulation Models, comparing a 1 x C02 to a 2 x C02 scenario (source: Zebarth et al., 1997). Temperature changesi (°G)lr ^ Precipitation changes (%) South South North Peace South South North Peace Coast Interior Interior River Coast Interior Interior River Jan +3 +3 +3 +3 +10 +10 +10 +20 Feb +2 +2 +2 +2.5 +10 0 0 +5 Mar +1.5 +2 +2 +2 +5 +15 +5 0 Apr +2.5 +3 +3 +3 +5 +15 +5 +10 May +2.5 +3 +3 +3.5 +5 +10 +5 +10 Jun +2 +2.5 +2.5 +2.5 -20 0 -10 +5 Jul +2.5 +2.5 +2.5 +2.5 -10 0 -5 -5 Aug +2.5 +3 +3 +3 -10 0 +5 -5 Sep +3 +3 +3 +3 -20 -10 -20 0 Oct +1.5 +3 +2.5 +2.5 0 +15 +10 +10 Nov +3 +3 +3 +2 +10 +15 +10 +10 Dec +3 +3 +3 +3.5 +10 +15 +15 +15 Zebarth et al. (1997) examined the expected impact of climate change on agriculture in B.C. within 4 different zones. For one of these zones, south coastal B.C., the following effects may be expected: • increased horticultural production due to increased length of the growing season and reduced risk of winter injury. • increased forage crop production; new varieties may be introduced to take advantage of the longer and warmer growing season. • increased crop damage by pests due to an increased winter survival of insects, but on the other hand reduced fungal disease problems due to drier summers (but more during winter) 2.1.3 Situation in the EU Under the Kyoto Protocol, the European Union is committed to a reduction of C 0 2 emissions by 8 % compared to 1990 levels during the first commitment period (2008-2012). The Kyoto Protocol allows carbon emissions to be offset by demonstrable removal of carbon from the atmosphere. Thus, land-use/land-management change (including improved management of agricultural soils) and forestry activities (including afforestation, reforestation and deforestation) that are shown to reduce atmospheric CO2 levels can be included in the Kyoto targets. 12 Accoring to Smith et al. (2000) a reduction in C 0 2 emissions will be the key to meeting Europe's Kyoto targets, and forestry activities (afforestation, reforestation and deforestation) will play a major role. However, the authors demonstrate the considerable potential of changes in agricultural land-use and -management for carbon mitigation. As all sources3 of carbon mitigation will be important in meeting Europe's climate change commitments, agricultural carbon mitigation options should be taken very seriously. 2.1.3.1 Situation in Austria In Austria agriculture's share in national warming potential is about 10% (Dersch and Bohm, 1997). If only emissions in direct connection with agricultural land use (including fuel consumption, use of mineral and organic N-fertilisers and use of herbicides, but excluding emissions from livestock husbandry and from use of energy for heating) are included agriculture's share is about 5%. In the past specialisation in agricultural production resulting in unbalanced crop rotations and intensification of soil cultivation might have contributed to degradation of organic carbon on arable land. However, topsoils are still an important carbon reservoir, which must be preserved by competent and sustainable soil cultivation (Dersch and Bohm, 1997). Climate model projections for Europe suggest a general increase in temperature as well as a possible increase in winter and a possible decrease in summer precipitation (Watson et al., 1998). In Austria an increase of about 1° in average temperature has been measured over the last 100 years. Also exceptional warm years have been observed during the last 15 years (FMEYF, 1997). In Austria the following effects of climate change on agriculture may be expected (FMEYF, 1997): • lower yields due to increased temperatures, reduced vegetation density, diminished soil carbon input and increased danger of erosion • a marked yield decline in arid areas, where irrigation is limited, accompanied by the danger of wind erosion and decreased carbon input or increased carbon output. 3 In keeping with the definition used in the UN Framework Convention on Climate Change (Article 1), a source of a greenhouse gas is any process or activity which releases a greenhouse gas into the atmosphere. A sink is a process or activity, which removes a greenhouse gas from the atmosphere. Thus, an ecosystem represents a sink for C 0 2 if its assimilation of carbon exceeds its loss of carbon through respiration and harvest. 13 • the predicted increase in soil erosion will lower food production and jeopardize the ecosystem. 2.2 Contribution to Agrochemical Water Contamination Residues of pesticides, herbicides and insecticides in water bodies pose a threat to the environment as well as to human health. Excessive nitrate and phosphorus from mineral fertilisers and manure lead to eutrophication and low dissolved oxygen in water bodies and contamination of groundwater, which could affect the quality of drinking water. High levels of nitrate in drinking water can cause methaemoglobinaemia in babies resulting in a blue coloration of the skin (blue-baby syndrome). Recent research on animals has suggested a link between nitrosamines, which can be derived from nitrate during digestion, and gastric cancer. Although there is no proof that this causes cancer in humans, it is considered to be a risk factor (Skinner et al., 1997). 2.2.1 Situation in Canada Structural changes in the intensity, concentration, and specialisation of agricultural production have created nutrient surpluses in some of the humid and intensively farmed regions of Canada. Nitrates introduced by agricultural activities have been detected in groundwater underlying the principal, intensively farmed regions of Canada. In general, the nitrate levels are within regulatory standards (AAFC, 1998). However, there are areas in B.C. where nitrate levels are relatively high (see below). 2.2.1.1 Situation in B.C. Throughout the 20th century, the total area of farmland and cropland has increased steadily in many parts of British Columbia. At the same time, much prime agricultural land has been lost to urban expansion e.g. in the Lower Fraser Valley (LFV). Most farms in B.C. are intensively worked and have the potential to cause agrochemical contamination of surface water and groundwater (especially in areas such as the LFV where intensive cultivation involves much fertilization, heavy applications of manure from high-density livestock operations, and irrigation). For example, results from two studies on the Abbotsford Aquifer (Berka and Schreier, 1996; Zebarth et al., 1998) show, that intensive agricultural production is a primary contributor to elevated nitrate concentrations in the aquifer (nitrate concentrations measured from one well increased from less than 10 mg/l in 1970 to an average of 19.5 mg/l between 1990 and 1995; Zebarth et al., 1998). 14 An assessment of water quality for the Sumas River Watershed by Nener and Wernick (1997) shows, that fish kills can been attributed to pesticides and agricultural runoff in the system. Berka et al. (2000) have shown, that excessive surplus application of nitrate and phosphorus in the Sumas River Watershed can be linked to ammonia toxicity and dissolved oxygen problems in streamwater. 2.2.2 Situation in the EU In the EU post-war changes in farming systems and especially the decoupling of arable and livestock farming, together with the general intensification of agriculture have had negative effects on the water quality. Water pollution by nitrates has been worsened with increased use of chemical fertilisers and higher concentrations of animals in smaller areas. The 1980s saw a progressive worsening of the situation (nitrate concentrations in water rose by an average of 1 mg/l per year) owing to the growth of intensive livestock farming (chickens, pigs) in areas already saturated, and of intensive crop-growing involving herbicides and overfertilisation (EU-CD, 1991). Thus in 1991 the European Council adopted a Directive on nitrates (Council Directive 91/676/EEC of 12 December 1991 concerning the protection of waters against pollution caused by nitrates from agricultural sources). However, nitrate pollution is still causing problems in all EU member states. Especially for member countries, that are highly dependent on groundwater for their drinking water, high nitrate levels in water bodies is a major concern. For example, the Netherlands and Denmark are affected due to their high density of population and production (AAFC, 1998). 2.2.2.1 Situation in Austria For Austria the concerns discussed above are prevalent only in specific regions, i. e. the agriculturally intensively used plains and lowlands in Eastern and Southern Austria and along the Danube valley. Results from a comprehensive groundwater analysis for the whole of Austria (conducted between 1995 and 1997; UBA, 1998) showed that 69% of the samples contained less than 30 mg/l nitrate and can therefore be considered uncontaminated. However, 16% of the samples contained nitrate concentrations higher than 50 mg/l (threshold value for drinking water). Results also showed a clear difference between the alpine western and the non-alpine eastern provinces: In Vorarlberg and Tyrol for example the threshold value for drinking water was never exceeded, whereas 37% and 57 % of the samples in Burgenland and Vienna (respectively) showed levels of nitrate above the threshold value. 15 3 CO2 Emissions and Nitrate Leaching as environmental indicators that relate to agricultural soil management Agri-environmental indicators that relate to soil quality and management can help to assess the environmental effects of agriculture and to monitor the progress towards a more sustainable agriculture. For this thesis two indicators that relate to soil quality and management have been identified: net C 0 2 emissions and nitrate leaching. Both are part of a complex web of various C- and N-flows in soils. Thus chapter 3 offers a literature review on the concepts and cycling of soil organic carbon and nitrogen. 3.1 Theoretical background regarding C0 2 Emissions 3.1.1 Concepts and Cycling of Soil Carbon 3.1.1.1 The Global Carbon Cycle Carbon fluxes between the atmosphere, oceans, and terrestrial systems are in a dynamic equilibrium. One generally accepted estimate of the sizes of these fluxes and pools, is shown in Table 3.1-1 and Table 3.1-2, adapted from Post et al. (1990). The atmospheric pool (750 Gt C) is reliably measured and is increasing as a result of two primary human activities, land use change and fossil fuel combustion. Many recent studies have projected that this increase will cause world-wide climate change. Table 3.1-1: Major active reservoirs in the natural global carbon cycle and geological stores of recoverable fossil fuels (adapted from Post et al., 1990) Reservoir Oceans Terrestrial system Vegetation Soil Recoverable fossil fuels j 4,000 Atmosphere j 750 38,000 420 - 830 1 ,200-1 ,600 16 Table 3.1-2: Fluxes of Carbon to and from the Atmosphere (adapted from Post et al., 1990) From atmosphere to | I Vegetation (photosynthesis) ! 1 0 0 - 1 2 0 Ocean I 1 0 0 - 1 1 5 Land (silicate weathering) | 0.06 To atmosphere from ! j Ocean I 1 0 0 - 1 1 5 I Plant respiration I 40 - 60 | Decay of residues I 50 - 60 I Fossil fuel burning I 5.3 | Land use ! 0 . 6 - 2 . 6 Over 2000 Gt C are contained in the terrestrial pool, about one third in living vegetation and about two thirds in SOM (Soil Organic Matter). Because this pool is three times larger than the atmospheric pool, and because the annual flux between the two pools is large (Table 3.1-2), changes in terrestrial systems are important in affecting the sensitive atmospheric pool (Flach etal., 1997). 3.1.1.2 The Terrestrial Carbon Cycle The ultimative source of soil organic carbon is photosynthesis (Figure 3.1-1): carbon dioxide is absorbed from the atmosphere by plants, and transformed into carbon-containing compounds such as cellulose, hemicellulose, and lignin (Table 3.1-5). Some of this material is used by the plant, a portion is removed (if the land is harvested), and the rest is returned to the soil. These plant residues, including roots, become part of the soil organic matter. Microorganisms in the soil, in turn, decompose the soil organic matter, releasing carbon dioxide into the atmosphere and closing the loop (AGRI CAN, 1999). 17 Figure 3.1-1: Terrestrial C-Cycle Are terrestrial ecosystems releasing C to the atmosphere, or are they withdrawing C from the atmosphere and accumulating it in vegetation and soils? The question was first asked more than 20 years ago and the answer was and still is controversial4. Agroecosystems play a significant role in the storage and release of C within the terrestrial C cycle. They are highly impacted through human activities; as a result processes determining net C emissions to the atmosphere are to a large degree influenced by land management practices (Paustian, 1995). 4 According to Houghton (1995), the following "equation" applies: Fossil fuel emissions = Atmospheric increase + Oceanic uptake + Terrestrial uptake 6(+0.6)GtC 3(±0 .1)GtC 2 ( ± 0 . 5 ) G t C ??? If terrestrial uptake is calculated by difference, terrestrial ecosystems are accumulating about 1 Gt C/year, and the carbon budget is balanced. On the other hand, if the terrestrial term is determined on the basis of changes in forest area (Houghton, 1995), terrestrial ecosystems are releasing about 1.5 Gt C/year to the atmosphere, and the terms of the global C equation are not balanced. 18 Land use changes can contribute to C sequestration. The reversion of cultivated land to perennial grassland, wetland or forest leads to a recovery of soil C stocks depleted as a result of cultivation (Table 3.1-3). Table 3.1-3: Examples of C sequestration rates with conversion of agricultural land in some temperate locations (Paustian et al., 1997) Canada Abandoned to native shortgrass prairie 25 15 7-13 USA Abandoned to native shortgrass prairie 50 10 3 UK Abandoned to forest 81 23 25 UK Planted grassland 15 15 75 New Zealand Planted grassland 18 20 100 3.1.1.3 Soil Organic Matter (SOM) „I sometimes think that never grows so red The Rose as where some buried Caesar bled." [Perhaps the most poetic expression of the effects of organic materials on soil fertility. By Khayyam in: Foth, 1984] Soil organic matter is a general term that refers to all the organic components of the soil: living biomass, identifiable dead plant and animal tissues, as well as nonliving nontissue-substances (soil humus). The amount of organic matter in soils varies widely, from 1 to 10% (total dry weight) in most agricultural soils to more than 90% in wetlands where peat has accumulated (Gregorich, 1995). It is most commonly estimated by multiplying the soil organic carbon content by 1.724 (Foth, 1984). Estimates of the organic carbon in the top meter of soil have been summarised by Houghton (1995; Table 3.1-4). 19 Table 3.1-4: Mean C content of soils in major ecosystems in 1980 (Houghton, 1995) Mean C content of soil (Mg C/ha) Tropical evergreen forest 104 Tropical seasonal forest 86 Temperate evergreen forest 134 Temperate deciduous forest 134 Boreal forest 206 Tropical fallow (shifting cultivation) 83 Tropical open forest/woodland 64 Tropical grassland and pasture 48 Temperate woodland 69 Temperate grassland and pasture 189 Tundra and alpine meadow 204 Desert scrub 58 Rock, ice, and sand 2 Cultivated, temperate zone 128 Cultivated, tropical zone 53 Swamp and marsh 725 Soil organic matter is an important component of terrestrial ecosystems and has been strongly implicated as a source-sink in global carbon calculations that attempt to balance the gains and losses of soil carbon. Humus format ion In the formation of humus from plant residues, there is (i) a rapid reduction of the watersoluble constituents, of cellulose, and of hemicellulose; (ii) a relative increase in the percentage of lignin and lignin complexes, and (iii) an increase in the protein content (Table 3.1-5). The new protein is believed to be formed mostly through the synthesising activities of microorganisms (Foth, 1984). 20 Table 3.1-5: Partial composition [%] of mature plant tissue and SOM (source: Foth, 1984) Component Plant tissue Soil Organic Matter Cellulose 20 -50 2 - 10 Hemicellulose 10 -30 0- 2 Lignin 10 -30 "35 -50 Protein 1 -15 28 -35 Waxes, fats,.. 1- 8 1- 8 Climate and soil parent material are key factors for humus formation: Climatic conditions, especially temperature and rainfall, play probably the most significant role in determining the amounts of organic carbon found in soils. Climate controls the adaptation of plant and microbial species, quantity of vegetative material, and the rate of decomposition or accumulation (Johnson et al., 1994). The lowest natural levels of soil organic matter and the greatest difficulty in maintaining those levels are found where annual mean temperature is high and rainfall is low. Parent material has an effect on soil organic matter due to its effect on soil texture. Soils high in clay and silt are generally higher in organic matter than are sandy soils due to • their greater nutrient and water holding capacities, which promote greater plant production • the formation of clay-humus complexes: this formation plays a central role in stabilising organic matter in soil. The soil clay fraction includes a diversity of minerals with different surface areas and arrangements of individual clay particles. The formation of soil particle aggregates through polycation bridging, organism glues or organic-inorganic bonds, results in a structure that can entrap organic matter and protect it from organisms and their extracellular enzymes (Post, 1993). 1 Composition of SOM (Soil Organic Matter) Traditionally, SOM fractions have been described with the help of chemical or physical properties. Using the humic and fulvic acid classification, the bulk (60 - 80%) of SOM is composed of humic substances: these are ill-defined, complex, resistant, polymeric compounds. They are generally dark-colored with molecular weights varying from 2000 to 300000 g/mol. The less resistant, identifiable biomolecules produced by microbial action (such as amino and organic acids, waxes and fats) are grouped together as nonhumic or fulvic substances (Brady and Weil, 1996). The information obtained by such concepts, which are based on chemical or physical properties, does not yield much insight into the potential dynamics of the fractions. 21 Jenkinson and Rayners (1977; in Kleber, 1997) were among the first to introduce the concept of mean residence time5 as means to identify SOM fractions. They divided soil C into active, slow and passive pools that have different turnover times (1yr, 30 yrs, and 1500 yrs, respectively). The turnover time is the average time that a C atom resides in a given fraction and is equal to the amount of C in the fraction divided by the amount of C entering (or leaving) the fraction each year (Rowell, 1994). Katterer and Andren (1999) proposed that SOM can be divided into 2 components: old organic matter (relatively stable: 167 years turnover time) and young organic matter (active: 1.25 years turnover time). Jenkinson (1981) improved his concept and defined five SOM fractions (Table 3.1-6). In order of ease of decomposition they are readily decomposed plant material, resistant plant material, microbial biomass, physically protected organic matter and chemically stabilised organic matter. Table 3.1-6: Soil organic matter fractions and their turnover times Fraction turnover time (yr.) fraction T r time (yr.) F. action turnover time (yr.) Young organic matter 1.25 readily decomposed plant material resistant plant material 0.2 _ metabolic plant m. structural plant m. 0.5 3 microbial biomass 2.4 active soil 1.5-10 old organic matter 167 physically protected OM 71 slow soil 25 - 50 chemically stabilised OM 2900 passive soil 1000 1500 Models which assume that soil organic matter is the sum of several fractions have proven very useful to quantify changes in organic carbon storage. Studies on the dynamics of soil organic matter have demonstrated that the different fractions of soil organic matter play quite different roles in soil management and in the carbon cycle (Paustian et al, 1992; Post, 1993). 5 For any biogeochemical reservoir, the mean residence time (MRT) of the substance considered is defined as: MRT = Q/(dQ/dt) with Q = flux (input/loss from reservoir), t = time 22 3.1.1.4 Soil Carbon Models „Analogies decide nothing, that is true, but they can make one feel more at home" [Sigmund Freud, 1933] Static Soil Carbon Models The static model by Tesarova (1988) lists litter and root production, C-assimilation by soil micro-organisms, animal and microbial litter production as C- input pathways, and identifies respiration of aboveground litter, living roots and SOM as output variables. A less comprehensive approach to establish a C model was chosen by Coleman (1973; in Kleber, 1997), who compared total soil respiration with organic matter input on a successional grassland in South Carolina. Dynamic Soil Organic Matter Models Soil organic matter (SOM) models are good tools to understand soil carbon dynamics (Smith6 et al., 1997). In terms of estimating and verifying management induced changes in carbon stocks in agricultural soils, models: - can be used to compare the effectiveness of different proposed carbon sequestering practices; - allow comparisons of management-induced changes in carbon stocks under different climates and soil types The CENTURY model developed by Parton et al. (1987, 1988) simulates the long term dynamics of carbon and nitrogen (as well as of P and S) in cultivated and grassland soils. Recently a research group at Colorado State University (Metherell et al., 1993) has added algorithms and incorporated crop parameters which allow for the simulation of crop growth, crop rotations, and tillage practices. CENTURY is written in Fortran and cannot easily be used by non-experts. 6Smith et al. ( 1997) evaluated nine soil organic matter models using twelve data sets from seven long-term experiments. Datasets represented three different land-uses (grassland, arable cropping and woodland) and a range of climatic conditions within the temperate region. Different treatments at the same site allowed the effects of differing land management to be explored. Model simulations were evaluated against the measured data and the performance of the models was compared both qualitatively and quantitatively. 23 The INTRODUCTORY C BALANCE MODEL (ICBM; Katterer and Andren, 1999), used in this thesis, is an analytical model that allows predictions of carbon budgets using a computer spreadsheet. The model parameters can quite easily be estimated from generally available data, such as climate, soil type and crop. Thus, it is a model that can be used by non-experts to make reasonable estimates regarding SOM dynamics as affected by management and climate. 3.1.1.5 Carbon Balances Complete C balances for nation states There are few countries to date for which complete C balances have been drawn up, among them are Austria (Korner et al., 1993; Jonas, 1997) and Switzerland (Paulsen, 1995). C balances for different grassland systems Only one C budget for a cultivated grassland system - Sweden, grassland ley (Paustian, 1990) - could be found in literature. For a submontane non-cultivated Bohemian grassland Tesarova (1988) provides an annual balance of carbon (Table 3.1-7). Table 3.1-7: Annual balance for a submontane non-cultivated Bohemian grassland (Tesarova, 1988) and a cultivated Swedish grassland ley (Paustian, 1990) litter production ; 2370 root production 13410 C-assimilation ;150 animal litter i 80 640 3870 microbial litter ! 1260-2280 Z input [7270-8290 {4500 respiration of j 1800 aboyeground litter j I2400 respiration of SOM [4030 .!^?.pirati°n..°ll!y^ 11900 £ output 8000 j 4300 _sunplus/deficit j -730/+290 i 200 24 3.1.2 Management Effects on Soil Carbon Dynamics A change in the way land is managed can disrupt the C cycle and this changes the amount of C stored. Perhaps the most drastic example of this is the initial cultivation of soils for farming, which results in high losses of soil carbon. Mann (1986) reported that soils initially high in organic matter lost at least 20% during cultivation (over a time period of 20 years). There are several reasons for this loss. First, farming involves the harvest of C from the fields and the removal of this C means less input of new C (AGRI CAN, 1999). As well, cultivation and growing annual crops often speed up the conversion of soil C to CO2 by soil microbes as a result of aeration and fertilisation. After soils have been cultivated in the same way for a few decades losses of C usually slow down or cease entirely, and the level of soil C is again stable (Figure 3.1-2). However, a change in management, especially regarding inputs of organic matter to soil and/or soil organic matter decomposition rates, can result in losses or gains of C. Management practices to build up soil C must (i) increase the input of organic matter to soil and/or (ii) decrease soil organic matter decomposition rates (AGRI CAN, 1999). (i) Organic Matter Additions Soil C gains can be achieved by keeping actively growing plants on the land as often and as long as possible (e.g. planting perennial crops), by using cropping practices that keep all residues in the field, by using appropriate crop rotations, and by planting crops (like forage grasses) that store a lot of their C in roots. Often, animals help recycle the C back into soil. In many livestock-based systems, a large part of the plant yield is returned to the soil as manure, and only a small portion is actually exported from the land. (ii) Decay Rate Making conditions less favourable for soil microbes will slow the rate of organic matter decay in the soil. Thus, decay rate can be slowed by keeping soils cooler (cover crops) or by shielding the organic matter from soil microbes. Soils are usually granulated, with organic materials protected inside the aggregates. Breaking these aggregates open by intensive tillage exposes that organic matter to soil microbes. As a result, practices that use minimal disturbance of soils tend to preserve the soil C. 25 Figure 3.1-2: Theoretical changes in soil C as influenced by management (AGRI CAN, 1999). AC<0 AC=Q ikC>0 initial cultivation management change 26 3.2 Theoretical background regarding Nitrate Leaching 3.2.1 Concepts and Cycling of Soil Nitrogen 3.2.1.1 The Global Nitrogen Cycle Like carbon, nitrogen cycles between the living world and the soil, water, and atmosphere. Nitrogen is essential to living organisms and its availability plays a crucial role in the organisation and functioning of the world's ecosystems. In many ecosystems the supply of nitrogen is a key factor controlling the nature and diversity of plant and animal life, and vital ecological processes such as plant productivity and the cycling of carbon and soil minerals. Excessive nitrogen additions can pollute ecosystems and alter both their ecological functioning and the living communities they support (Vitousek etal, 1997). 3.2.1.2 Soil Nitrogen In most soils more than 95 % of the soil nitrogen is tied-up in organic matter. This organic nitrogen is made up of a vast range of compounds, derived from biological materials and from humification processes. However, only a relatively small amount of nitrogen is present in inorganic form as ammonium and nitrate. The 3 types of nitrogen behave very differently in the soil (Table 3.2-1). Table 3.2-1: Characteristics of the three types of nitrogen (source: Plaster, 1992). Storage in humus adsorbed ^ / w m w m w w w m _ y little storage Losses mineralisation, erosion volatilisation, erosion leaching, denitrification Plant Use not used can be used common form Changes mineralisation immobilisation, nitrification immobilisation, denitrification The transformations of nitrogen between the various forms form a complex web of processes and biochemical oxidation/reduction-reactions that make up the nitrogen cycle. Figure 3.2-1 shows the major processes in the nitrogen cycle. Soil N contents are generally in the range of 0.1 to 0.3 %. 27 Figure 3.2-1: N flows in agricultural soils Plant Leaching to ' hydrosphere 3.2.1.3 Nitrogen models Nitrogen models for specific soil processes N models have been developed to simulate specific soil processes such as ammonia N volatilisation (Parton etal, 1983) and leaching (Addiscott, 1981). Comprehensive nitrogen models Examples for comprehensive nitrogen models are the models by Frissel and Van Veen (1981) and by Hansen et al. (1990). The latter model is called DAISY and can be used for the simulation of nitrogen and soil water dynamics in the plant-soil system. The Fortran model allows for the simulation of different management strategies and crop rotations. 28 the simulation of nitrogen and soil water dynamics in the plant-soil system. The Fortran model allows for the simulation of different management strategies and crop rotations. Daisy is executed in two steps. In a first step, the models for soil water dynamics, soil heat and crop production (limited by radiation and soil water content only) are solved. In a second step, carbon turnover, microbial biomass-dynamics, solute-dynamics, and nitrogen limited crop production are calculated. 3.2.1 .4 Nitrogen balances For different regions in B.C. Brisbin (1995) provides annual balances of nitrogen (Table 3.2-2). Table 3.2-2: Nitrogen balances for different regions in B .C. [kg N/ha/yr] North Langley, large farms (Brisbin, 95) North Langley, small farms (Brisbin, 95) Fraser Valley, large farms (Brisbin, 95) Fraser Valley, small farms (Brisbin, 95) mineral fertilizer 129 103 140 100 adding from atmosphere 34 34 40 40 manure 119 60 138 53 Sum input flows 282 197 318 193 plant uptake 179 177 187 167 denitrification 12 6 16 5 Sum output flows 191 183 203 172 Surplus/deficit 91 15 115 21 leaching 30 6 45 13 Examples for N farm balances for different management practices are shown in Table 3.2-3. 29 Table 3.2-3: N farm balances on a conventional and organic farm in Sweden ( Cederberg and Mausson, 2000) kg N/ha/a conventional crrjamc i Input componen ts i M inera l fert i l izer 1 86 0 : Imported feed ! 134 29 I 1 A t m o s . Add i t ions i 10 10 ! B io l . N f ixation 1 1 5 46 | S u m Input: ! 245 85 j Output c o m p o n e n t s ! products I 47 20 \ ! surplus ! 198 65 1 S u m Output I 245 85 3.2.1.5 Carbon and Nitrogen Interactions in Soils The C and N cycles are closely linked, e.g. in the storage and accumulation of N in organic compounds. Thus the soil organic nitrogen content correlates with the soil organic carbon content (For example, the C/N ratio in grassland soils is in the order of 12:1 to 15:1. BCFA, 1993) and both change with soil type and climate as well as with agricultural management (Figure 3.2-2). Figure 3.2-2: Carbon and Nitrogen Interactions in Soils Decomposition is controlled to a large extend by litter quality, the important factor being the C/N ratio. In this respect the available nitrogen plays an important role in carbon dynamics. When plant residues with low C/N ratios are added to soils, maintenance or accumulation of organic matter is enhanced (Carter, 1996). Because of this linkage between soil nitrogen and organic matter, nitrogen inputs also can increase organic matter content. This could be 30 achieved through the inclusion of legumes in crop rotation for N fixation and/or the use of nitrogen fertiliser. A study7 (Paustian et al., 1992) on a 30 year old Swedish field experiment shows that fields receiving carbon and nitrogen additions (treatments 5 and 9 in Table 3.2-4) have soil organic matter levels greater than the comparable treatments without nitrogen fertilisation (treatments 4 and 8 in Table 3.2-4). Table 3.2-4: Carbon concentrations after 30 years of different treatments (source: Paustian et al., 1992) MEP 11S1 j Bare fallow ; 2.7 i No additions ! 2.9 1 i N fertilizer added | 3.4 I i Straw added 13850 70 I 3.7 ~ | Straw plus N fertilizer 13850 70 ! 4.4 | Green manure 13760 16.8 U t | Farmyard manure {3950 21.5 | 4.8 t | Sawdust added 13970 450 I 4.2 t | Sawdust plus N fertilizer 13970 450 ! 4.8 t 3.2.2 Management Effects on Soil Nitrogen Dynamics Agricultural activities have not only increased the nitrogen supply but enhanced the global movement of various forms of nitrogen through air and water. Because of this increased mobility, excess nitrogen from agricultural activities has serious and long-term environmental consequences for large regions of the Earth (Vitousek et al., 1997): • leaching of nitrates to groundwater or in runoff to surface waters (Greatly increased transport of nitrogen by rivers into estuaries and coastal waters where it is a major pollutant) 7 Field treatments on a sandy clay loam included biannual addition (up to 4000 kg C/ha) of straw, sawdust, and no organic additions, with and without nitrogen fertiliser (80 kg nitrogen /ha), and green manure, farmyard manure, and bare fallow. Results showed that after 30 years total carbon concentration ranged from a low of approx. 2,7 kg/m 2 in the bare fallow to approx. 4,8 kg/m 2 in the farmyard and sawdust plus nitrogen fertiliser treatment. Thus changes in organic-matter content ranged from a 30 % decrease to a 30 % increase from that present at the start of the experiment (3,7 kg/m2). 31 • increased global concentrations of nitrous oxide (N20), a potent greenhouse gas, in the atmosphere • losses of soil nutrients such as calcium and potassium that are essential for long-term soil fertility • volatilisation of ammonia • Excess nitrogen can result in a loss of biodiversity both on land and in the aquatic system I n c r e a s e d nitrogen supply due to agricultural act iv i t ies The use of synthetic fertilisers for agricultural crops has grown widely since their advent in the late 1800s. Since the mid-1980s, more than 70 million metric tons of nitrogen have been applied to crops each year (Table 3.2-5). Table 3.2-5: Global conversion of fertilizer nitrogen to nitrous oxide in soils (Jackson in Rosenzweig and Hillel, 1998) 1985 - 1986 69.803 0.007- 1.43 1986 - 1987 ! 71.555 0.007- 1.47 1987 - 1988 j 75.511 0.008- 1.55 1988 - 1989 | 79.580 0.008 - 1.63 The industrial fixation of nitrogen gas for fertiliser is now almost equal to the natural bacterial fixation (Rosenzweig and Hillel, 1998). This represents a large change in a natural cycle. High rates of nitrogen fertiliser often exceed plant uptake and result in leaching of nitrates to groundwater or in runoff to surface waters. High nitrate levels in soils and water bodies provide a substrate for denitrification, the major process that releases N 2 0 to the atmosphere. However, organic manures also contribute to greenhouse gas emissions. Significant amounts of nitrous oxide are emitted from poorly aerated soils fertilised with organic manures. 32 3.3 Nutrient Balancing There is a shift in soil science research. Where scientists had previously focused on nutrient stocks they are now studying the flow of nutrients through an ecosystem. Similarly, attention has shifted from soil fertility per se, to the balance between inputs and outputs, and the agronomic and environmental consequences of disturbing these balances (Smaling and Oenema, 1997). Nutrient balances are powerful instruments in determining present and future productivity of agricultural land, as well as undesirable environmental effects such nutrient losses (van Faassen and Lebbink, 1994). It is the aim of this project to use such instruments to analyse the influence of different farm management practices on net C 0 2 emissions and nitrate leaching (Table 1.3-2) of typical dairy farms in B.C. and Austria. The choice of a method to calculate nutrient balances strongly depends on the purpose of the research. Compartment models are used at plot and farm levels and these have the potential to help farmers and policy makers in evaluating the environmental impact of agricultural management. Black-box models are mostly used at higher spatial scales (Smaling and Oenema, 1997). The Importance of Nutrient Balancing for Sustainable Agricultural Management An important aim of sustainable development is the redirection from linear to circular material-fluxes in order to use natural resources without disturbing the ecological equilibrium nor the social and economic conditions of future generations (Table 3.3-1). To evaluate environmental programs and to create concepts for a sustainable management in agriculture long-term ecological, economic and socio-economic consequences have to be documented and taken into consideration. To do this, suitable instruments and methods are needed - the balancing of material-fluxes is widely seen as practical indicator for the agricultural and environmental sector. 33 Table 3.3-1: Definitions of Sustainability Sustainability • use of natural resources without disturbing the ecological equilibrium • process, that neither limits the environment nor the social and economic conditions of future generations (BRUNDTLAND-Report, 1987) Sustainable agriculture (also encompasses organic farming systems) • farming systems that are environmentally sound, profitable, productive, and maintain the social fabric of the rural community (Hatfield and Karlen,1994) • production of food and fiber without degrading natural resources and preservation of the economic health and the social values of the agricultural community 34 4 Differences in Agricultural Management 4.1 Important Management Factors Cultivation and fertilisation of soils, and the removal of crops identify humans as an outstanding biological soil-forming factor (Jenny, 1941). The most important management factors that influence carbon and nitrogen flows in agroecosystems are planted crops, fertilisation and soil usage (e.g. tillage, irrigation) (Table 4.1-1). Table 4.1-1: Most important management factors that influence carbon and nitrogen flows in agroecosystems planted crops • determination of residue quality and quantity (mixed vs. monoculture crops; perennial vs. annual crops) as well as use of certain cultivation techniques. With grassland vegetation for example, a relatively high proportion of the plant residues consists of root matter, which decomposes more slowly and contributes more effectively to soil humus than does forest leaf litter. • determination of nitrogen removal and ability to f ix atmospheric nitrogen (e.g. clover) fertilisation • increases plant biomass production, but also SOM decomposition • site-adapted organic fertilisation helps to control C- and N - dynamics • mineral N-fertilisation increases N input to soils soil usage different effects ( o r t ) on SOM content: t irrigation and fertilisation to increase plant biomass production T restoration of grasslands removing plant products t applying manure or other C rich wastes •I increasing decomposition by drainage, tillage f decreasing decomposition by keeping soil saturated and no till 35 4.2 Management of Grassland Systems Over 40% of the land surface of the temperate world is devoted to grassland, much of it a product of human activities. Therefore, grasslands could be a significant factor in cycles of atmospheric CO2. Grassland systems comprise three main components: the soil, the vegetation, and the livestock; each of them interacting closely with the others. The aim of the farmer is to control all three components, thereby regulating the inputs to and the outputs from the system, as well as its internal structure (Briggs and Courtney, 1985). Feeding crops to livestock results in effective recycling of C and N if the manure is managed well. Thus, while production of forages and silage crop may result in large amounts of C and N removal from the field, much of it can eventually be returned as manure. This manure not only recycles C and N, but also promotes crop growth and photosynthesis, favouring new soil C inputs (AGRI CAN, 1999). The classic experiments at Rothamsted (Johnston, 1986) demonstrate a three-fold increase in soil C storage through application of farm-yard manure at a rate nearly twice the rate commonly used in conventional farming. It is probably not possible to achieve these results on a large scale, but the data do demonstrate the potential of carbon accumulation in soils. An interesting note concerning these data is that soil C still has an upward trend even after 140 yr of active management. Over the same 140 years, the non-manured plots lost some SOC and plots fertilised with NPK gained some SOC until about 1920 and then equilibrated about 10 Mg/ha higher than the unfertilised plots. Characteristics of grasslands Grasslands are different from arable farming systems (Table4.2-1), especially regarding soil organic matter transformations. For example, grasses transport much of the organic matter they synthesise into their roots and hence into the soil. 3 6 Table 4.2-1: Grassland farming compared to arable farming farming arable farming (cereal; 1 Planted crop type | perennial crop, aboveground vegetation cut or grazed annual plants, grown for seed dense mat of roots -> grasses direct much more C and N into SOM cereal plants die before harvest and do not grow as much root material | Fertilisation (Addiscott | etal., 1991) I ["Contribution to build-J up of SOM grass absorbs N whenever mineralisation is occuring (all year round, particularly in spring and autumn) less nitrate leaching winter cereals remove most N from soil in spring and early summer up to 400 kg N/ha may be applied to mown grass before substantial N leakage occurs build up SOM reserves only up to 200 kg N/ha may be applied before substantial N leakage occurs do contribute to lesser extent { Biological soil activity good low j Exposure to erosion low ...high : i Resistance to pests good minimal 37 4.3 Organic Farming: doing it the sustainable way Being a modern catchword, most people, who use the term sustainability, associate different meanings with it. To some, the concept of sustainable agriculture means a complete switchover to all organic inputs, crop rotations, and low inputs, while to others, sustainability evokes ideas of changing practices which improve efficiency in the use of all resources and increases the profitability of the farming enterprise (Hatfield and Karlen, 1994). Sustainable agriculture encompasses, but is not limited to, organic farming systems, which rely increasingly on soil nutrient cycling systems and are characterised by the absence of synthetic fertilisers and pesticides. "Land should be thought of as a bank. If we think that the land is an unlimited resource that we can continuously withdraw' from, our account will eventually be used up. If instead we are wise stewards and invest back into the land, our account will balance and will continue to give us a good return in the future.", [J. Dumanski, A A F C , Ottawa, Ont] Organic farming - an alternative approach The goal of organic agriculture is to create a sustainable agriculture system. Organic farming emphasises management practices that work with natural processes and cycles to conserve all resources (including beneficial soil organisms and natural pest controls), and minimise waste and environmental damage, prevent problems, and promote agroecosystem resilience, self-regulation, and sustained production (Hill and MacRae, 1993). Organic farmers avoid the use of synthetic fertilizers, pesticides, growth regulators, and livestock feed additives. Instead, they rely upon crop residues, animal manures, legumes, green manures, crop rotations, mechanical cultivation, and mineral-bearing rocks to maintain soil fertility and productivity. Insects, weeds and other pests are managed by means of natural, cultural and biological controls. 38 The COG (Canadian Organic Growers) Organic Field Crop Handbook (COG, 1992) describes three principles to illustrate how an organic farm functions within an ecological framework. 1. The principle of interdependency The organic farmer regards the farm unit as an ecosystem arid recognizes that a change to one part of the system may upset the many complex interrelationships that exist within the unit. For example, high nitrogen levels in the soil can contaminate the groundwater with nitrates. The organic farmer addresses the problem by planting a crop that will utilize the nitrogen, preventing it from leaching into the groundwater and creating a more normal balance of soil nutrients. 2. The principle of diversity Organic farmers maintain natural habitats on the farm, and limit livestock numbers so that the balance between crops and livestock is maintained. The diversity of crops and livestock creates an ecosystem that has biological checks and balances that help prevent any one species of insect, weed or disease from becoming a problem. 3. The principle of recycling The organic farmer works towards self-sufficiency on the farm by recycling the nutrients on the farm. Plant and animal residues are returned to the soil to help build biological fertility, thereby minimising the quantity of soil amendments that must be purchased. The ecological and productional-economic differences between conventional and organic management of grassland systems can be seen in Table 4.3-1. 39 Table 4.3-1: Ecological and productional-economic differences between conventional and organic management of grassland systems (adapted from Kleber, 1997) Ecological: Diversity of species high low Refuge of endangered yes partly species Adaptation to variation of high partial climate Stability of natural high temporary production Productional-economic: Dietetic diversity good low Need of pesticides nil Low Condition of cattle excellent good Utilisation of solar energy high good Figures on organic farming in Europe and Canada are shown in the Appendix. The following section discusses how organic farming can help to reduce C 0 2 emissions. 4.3.2 Organic Grassland Farming as a Carbon Sink As already pointed out, the soil-biota system can change from a source to a sink of C 0 2 when conditions change so that the rate of formation of soil organic matter exceeds the rate of its decomposition. This can be achieved through the following practices: Better Management of Existing Agricultural Soils Management practices to build up soil carbon must increase the input of organic matter (and thus carbon) to soil and/or reduce the rate of organic matter decay in the soil. In general, (a) reduced tillage, (b) perennial forage crops, and (c) higher yielding crops will promote carbon sequestration (Watson, 1996, chapter 23). (a) Reduced tillage practices (compared to conventional tillage practices8, which accelerate the loss of soil carbon by increased oxidation and erosion) have the potential to increase soil carbon because less organic matter is lost to oxidation from mixing of the soil. Kern and Johnson (1993) examined changes in soil carbon content in response to conversion of conventional tillage to reduced tillage in the contiguous U S A for field crop production by the year 2020. They compared 3 40 (b) Perennial forage crops often remain active for more months of the year than annual crops, trapping more atmospheric C 0 2 . Because there is no tillage, decay rates may also be slower. In North America and Europe, conversion of marginal arable land to permanent perennial vegetation, to protect fragile soils and landscapes and/or reduce agricultural surpluses, provides additional opportunities for carbon sequestration (Paustian et al., 1997). (c) Higher yielding crops or varieties have more efficient photosynthesis and will often produce more residues and hence favour soil carbon increases. Restoration of Degraded Lands & Set-aside Programs From a global perspective, restoration of degraded lands offers a tremendous potential to sequester atmospheric carbon. Restoration of biological productivity of these lands would enhance their soil organic carbon content and qualify them as effective terrestrial carbon sinks (Lai et al., 1995). Examples for restorative practices are erosion control, construction of runoff management, application of soil amendments, ban against deforestation and biomass burning, incentives for the adoption of conservation tillage and use of cover crops, and large-scale afforestation. In the EU and N-America about 25 million hectares have been taken out of production in government set-aside programs (Watson, 1996, chapter 23). If soils are left uncultivated and allowed to return to native vegetation, carbon contents in upper horizons could eventually reach levels comparable to their precultivation condition. However, this will take a long time. Indirect Carbon Sequestration: Reduced Fossil Fuel Use & Energy Crops for Fossil Fuel Substitution Energy is required for all agricultural operations, but the energy requirements of different systems vary. Modern intensive agriculture requires much greater energy inputs than organic agriculture, especially due to till and harvest operations. A different way by which agriculture could indirectly sequester carbon is to produce biomass that is used as a substitute for fossil fuels. The production of grasses or of rapidly growing trees in plantations as energy crops could deliver major savings of fossil fuels (WBGU, 1998). Thereby the level of C 0 2 savings depends upon the net energy yield of bioenergy showed that maintaining the use of conventional tillage (73%) until 2020 would result in loss of 31 to 52 Tg production (energy input during growth, harvesting and processing) and is determined by the global warming potential of emissions occurring during growth. All three recommended practices to increase soil carbon can be realised with the help of organic grassland farming: Recommended practices to increase soil C Realisation through organic grassland farming ' Better Management of Existing Agricultural Soils Reduced tillage practices Perennial forage crops Higher yielding crops or varieties Fields are usually not tilled at all. V The aim is to maintain high biodiversity, not to specialise on high yielding varieties (conventional mgt). However, the grasses trap more C02 compared to conventional mgt because of increased root production. Restoration of Degraded Lands & Set-aside Programs Organic farming practices (Controlled grazing at low stocking rates, the use of diverse pasture species and organic soil amendments) are important considerations in restoration of degraded pastures. Indirect Carbon Sequestration Reduced Fossil Fuel Use Energy Crops for Fossil Fuel Substitution V (no mineral fertilisation, ...) production of grasses as energy crops Problem 1: Uncertainty surrounding "sink potentials" Terrestrial carbon fluxes are climate-dependent and vary widely in space and time (even from day to day). Estimates exist that the carbon balance of the terrestrial biosphere during the past 60 years has oscillated by more than 1 Gt C between net carbon assimilation and dissimilation solely as a result of climate variability (WBGU, 1998). Sinks can even turn into sources because of seasonal changes. Uncertainties remain also on the spatial variability of carbon sinks. Problem 2: Finite capacity Soils have only a finite capacity to sequester soil carbon. It is important to remember that we are dealing with dynamic processes which should not be considered as eternal sinks. C; scenarios 2 and 3 would result in loss of 18 to 30 and 9 to 16 Tg C, respectively. 42 4.4 Agriculture in B.C. and Austria In B.C. only 3 per cent of total provincial land is considered arable or potentially arable, although up to 30 per cent of the province has some agriculture potential (BCMAFF, 1996). However, the share of farmland of the total area is 2.7 % (2.5 million hectares; Table 4.4-1). Of this, 566,000 hectares are in crops and 1.4 million hectares are for pasture or grazing. All arable soils have been mapped and classified on the basis of quality, and the best classes have been placed within the Agricultural Land Reserve (ALR) to be maintained for agricultural and related purposes. Slightly over 4.7 million hectares of land are in the ALR (BCMAFF, 1996). Farm sizes (from thousands of hectares in grain production to less than five hectares in e.g. greenhouse businesses) and types of agricultural activities (dairy farming; cattle-ranching; poultry-raising; and growing of tree fruits, vegetables, berries, grapes, mushrooms, bulbs, ornamental flowers and shrubs) vary greatly. Agriculture is the province's third largest primary industry, behind forestry and mining (BCMAFF, 1996). Organic farming in B.C. is a young industry, producing mostly vegetables, berries, tree fruits & nuts; but also grain & oilseeds, and herbs & flowers. In Austria farm holdings (225,847 farms in 1999; Table 4.4-1) cover more than 3.4 million hectares (41 % of the total area). Of this, over 1.9 million hectares are considered grassland. The importance of agriculture in Austria is comparable to that in B.C.. However, in Austria the number of organic farms and their share of the total area is quite high. Approximately nine per cent of all farms in Austria are organic farms, covering a total area of 287,900 hectares, including alpine pastures. This means that almost nine per cent of Austria's farmland has been converted to organic farming (Table 4.4-1). Three main factors contributed to the rapid conversion of farms in the mid-1990s: • the federal subsidies that were introduced in 1991 • the agri-environmental program (EU), which was introduced in 1995 • and favourable conditions for the conversion of many grassland farms (Pohl, 2000). Table 4.4-1: Statistics on Agriculture in B.C. and Austria (BCMAFF 1990, 1996; BMLF, 1998; COABC, 1997) Tota l a rea in ha 89,307,184 8 ,386 ,995 Popu la t ion 3 ,200,000 8 ,071 ,900 (1997) Contr ibut ion to G D P C A N $ 2.2 billion (share of agricul ture, 1996) 2 .49 bil l ion Eu ro (share of farming, forestry and f ish ing, 1997) S h a r e of fa rmland of total a rea in % 2.8 (1996) 41 Tota l fa rmland in ha 2 ,529 ,060 (1996) 3 ,422 ,499 (1997) G r a s s l a n d in ha 1,412,827 (1996) 1,943,443 (1997) Dai ry c o w s 82 ,008 (1996) 890 ,900 (1997) Mi lk product ion in mil l ion 1 572 4 7 1 2 Tota l number of fa rms 21 ,835 (1996) 225 ,847 (1999) A v e r a g e s i ze of fa rms in ha > 100 15.4 N u m b e r of o rgan ic fa rms 240 cert i f ied, 49 transit ional 20 ,207 (1999) Propor t ion of o rgan ic fa rms about 1 .1% 8.9 % Organ ica l l y cult ivated a rea Propor t ion of organica l ly cul t ivated farmland 2 8 7 , 9 0 0 ha (1999) 8.4 % Organ ica l l y grown products S i z e of o rgan ic fa rms in ha Most ly vege tab les , berr ies, t ree fruits & nuts; a lso grain & o i l seeds , herbs & f lowers 42 % are < 2.1 ha 20 % are < 4 .2 ha 80 % g rass land , 19 % predominant ly a rab le , 1 % spec ia l c rops (fruit, herbs, etc.) and wine A v e r a g e 14 ha ; 50 % between 5 and 15 ha Dairy cows on organ ic fa rms N o organ ic dairy fa rms in 1997 97,751 Dairy cows per o rgan ic farm (average) N o o rgan ic dairy fa rms in 1997 1 1 - 1 8 44 5 The Comparative Research Case Studies As already pointed out, net C 0 2 emissions and nitrate leaching from soils are used in this thesis to indicate the environmental impact of farming systems. Three case studies - two conventionally managed dairy farms (B.C. and Austria) and one organically managed dairy farm (Austria) - were conducted to test hypotheses about the influence of different agricultural management practices on these indicators. Nutrient balancing was used as a tool to assess carbon balances at field scale and nitrogen balances at field and farm scale. 5.1 Research Objectives and Hypotheses Overall aim: determine the influence of management practices on carbon and nitrogen dynamics in grassland-agroecosystems at the field and farm scale. Specific objectives (1) identify all relevant carbon and nitrogen input-output flows for grassland soils and the possible influence of different management regimes on these flows (Figure 5.1-1) Figure 5.1-1: influence of different management regimes on soil input-output flows organic farming farming in B .C . conventional farming farming in Austria (2) calculate the nutrient balances and steady state carbon flows, namely of • field scale carbon balances with a static input-output model • steady state carbon inputs with a dynamic soil organic matter model • field scale nitrogen balances with a static input-output model 45 • farm scale nitrogen balances with a static input-output model for the different management regimes over one growing season: • a conventionally managed farm in B.C. (Fort Langley) • a conventionally managed farm in Austria (Laussa-Losenstein) • an organically managed farm in Austria (Molln)9 (3) compare results of: • conventional vs. organic comparisons • BC vs. A comparisons with the help of (a) balances: comparison C field scale balances input < output Negative C balance (C source) indicates net C 0 2 emiss ions N field scale balances input > output Posit ive N balance (N surplus) indicates Nitrate leaching N farm scale balances High, medium, low input of conventional sources of nitrogen (mineral fertiliser, imported feeds) imports < , = , > exports (b) calculation of the steady-state carbon input (with a dynamic soil organic matter model): comparison carbon input steady-state carbon input10 < , = , > actual carbon input A comparable organically managed farm in B.C. could not be found (For details see chapter Selection of farms). 3 For details see chapter Calculation of steady state carbon inputs with a dynamic S O M model (ICBM) 46 5.1.1 Hypotheses Hypotheses for comparing budgets in conventional vs. organic farms in Austria Organic farms only use organic amendments (such as manure and compost) that maintain balances without the addition of synthetic fertilisers and pesticides. It is hypothesised that organic farm management, compared to conventional farm management, • enhances soil organic matter (carbon) storage [HYPOTHESIS 1] • has a positive C balance = no net C 0 2 emissions [HYPOTHESIS 2] • has a negative N balance = no nitrate leaching [HYPOTHESIS 3] Hypotheses for comparing budgets in conventional farms in Canada and Austria The south coastal region of British Columbia provides a good climate for growing forage crops. Until recently the management strategy of the dairy industry has been to maximise the yield of forage nutrients and to maximise production without accounting for the impact on water and soil quality. Compared to Canada, Austria's dairy farming operations, which are located mostly in the pre-alpine and alpine region (difficult conditions), are relatively small. The average milking cow stock is 9 (!) animals (PRAEKO, 1998). It is hypothesised that conventional dairy farm management in B.C., compared to conventional dairy farm management in Austria, • causes more net C02 emissions [HYPOTHESIS 4] • uses higher inputs of conventional sources of nitrogen (such as mineral fertilizer, imported feeds) [HYPOTHESIS 5] • imports much more nitrogen than it exports [HYPOTHESIS 6] 47 5.2 Materials and Methods 5.2.1 Description of the Study Regions 5.2.1.1 Study region in British Columbia, Canada: Fort Langley Fort Langley lies within the Lower Fraser Valley (LFV), where the area of land in agricultural production is small, but animal and crop production is very intensive. For example, the LFV contains approximately 67% of the dairy cattle, 74% of the swine, and 79% of the poultry in British Columbia on less than 4% of the agricultural land (Statistics Canada, 1992). Crop production in this region is very diverse (Zebarth et al., 1997). Forage crops in support of the dairy industry are most common, including forage grasses (used for hay, silage or as pasture) and silage corn. Most forage crops are not irrigated in the Fraser Valley. Large areas are also in small fruit production and a range of field vegetable crops. According to Brisbin (1995) the average Fraser Valley dairy farm has about 79 dairy cows (milking and dry cows). 94 % of the 636 dairy operations are large farms (annual gross farm receipts > $40,000). The average large Langley11 dairy farm has about 56 cows and 45.5 ha of forage. Thus the relation of cows to hectares grassland is 1.23 to 1. Climate The LFV-region is characterised by wet, mild climatic conditions. The mean annual temperature is about 10° C. Mean annual precipitation varies substantially throughout the region ranging from about 800 to 1700 mm, generally increasing in an easterly direction. Most of the precipitation falls as rainfall, and about 70% occurs from October to March when crop growth is limited. The frost free period ranges from about 175 to 240 days. In general climatic conditions are very favourable for production of a wide range of crops. Thus virtually all land suitable for agriculture has already been brought into production (Zebarth et al., 1997). Fort Langley, located about 50 km east of Vancouver, is subject to a maritime climate with mild, rainy winters and relatively cool, dry summers. The average during the October to March period (approx. 70% of the total ppt) is 1052 mm (BCAFF, 1992). 48 Mean monthly temperature (in degrees C; Environment Canada) and precipitation (in cm) are shown in Figure 5.2-1 (further below). 5.2.1.2 Study region in Austria: Molln and Laussa-Losenstein The municipalities "Molln" and " Laussa-Losenstein" are situated in the "Eisenwurzen"-region, province Upper Austria, where grassland farming is most common. The semi-intensive to extensive grassland is cut 2 to 3 times (seldom 4 times) and receives up to 4 applications of manure. In general, Austria's dairy farming operations are relatively small. The average milking cow stock is 9 animals, and only 2.5 % of the dairy cows belong to dairy operations with more than 30 cows. (PRAEKO, 1998). Organic dairy farms are small and medium-scale (on average between eleven and eighteen dairy cows), and the average size is approximately fourteen hectares. Climate The region lies in a transition zone, where the relatively warm centre of Upper Austria changes into the wetter and colder subalpine part of the country. The mean annual temperature is about 8°C, the mean annual precipitation about 1230 mm, respectively. Mean monthly temperature (in degrees C; HDO, 1983) and precipitation (in cm; HDO, 1994) are shown in the following figure. In this context Langley is defined as the Langley waste management zone (Brisbin, 1994) 49 Figure 5.2-1: Mean monthly temperature and precipitation for the study regions in B.C. and Austria I cm ppt (B.C.) I cm ppt (A) • degree C (B.C.) • degree C (A) This figure also shows that the temperature range in the Austrian study region is comparable to that in the B.C. study region. However, the rainfall regimes for the two regions are different. In the Austrian region most rainfall occurs in the summer months, whereas in the B.C. region the time-period with the highest precipitation is from November to January. 5.2.2 Selection of farms The dairy farms - two conventionally managed farms (B.C. and Austria) and one organically managed farm (Austria) - were selected to be somewhat comparable between Austria and British Columbia in terms of climatic conditions, soil parent material, and size; Table 5.2-1) and farm management (Table 5.2-2). A comparable organically managed farm in B.C. could not be found: according to COABC (1997) no organic dairy farms existed in 1997 (see also Table 4.4-1). 50 Table 5.2-1: Short description of the study sites Fort Langley farm (soil data from Luttmerding, 1981) Austrian farms Conventional: \ Laussa-Losenstein .Organic: Molln -, soil "Fairfield" (gleyed eluviated melanic brunisol) "Hazelwood" (orthic humic gleysol) "Pseudogley" "Braunlehm" FAO equivalent Cambisol Gleysol Gleysol Cambisol soil texture Silt loam Heavy clay Loam Loam soil drainage imperfect poor maessig feucht (poor) maessig feucht (poor) bulk density 1 (average) 1.08 0.9 C content 6.56 % (average) 5.1 % 5.5 % farm size 42 ha 26 ha 16 ha dairy cows 51 13 9 ppt/a 1502 mm 1230 mm Table 5.2-2: Short description of site identification site identification description convent iona l fa rms success fu l l y us ing pract ices that are predominant in region o rgan ic a b s e n c e of synthet ic fert i l isers and pes t i c ides , use of o rgan ic a m e n d m e n t s 5.2.3 Data collection 5.2.3.1 Collection of farm management data A questionnaire and example management scheme (Table 5.2-3, Table 5.2-4) were developed, which help to thoroughly characterise the individual farming operations. 51 Table 5.2-3: Dairy Farm Questionnaire Dairy Farm Questionnaire Fields 1 2 3 size (ha) crop type (fescue, orchard grass, clover,....) years under same crop type Cattle and calves number o f animals milking cows dry cows heifers, 6 months & older calves, under 6 months number of animals - history at start of operation (19..) planned housing free stall - tie stall waste handling scraper - flushing - dropping (slotted floor) - other Manure data manure production per year (any units) manure import/export per year (any units) manure storage facility type earth/ concrete - uncovered /covered storage capacity (months or other units) physical dimensions (any units) Manure application spreading practice splash plate - mechanical - irrigation disposal season, amount, area see management scheme Mineral fertiliser application type, frequency, amount, area see management scheme Import/Export of feed Irrigation Pesticides Table 5.2-4: Example for a management scheme Date Field 1 Field 2 Field x (Day/month/year) adding fertiliser: type & amount (mass/area) (Day/month/year) adding manure: amount (mass/area) (Day/month/year) cutting: yield (mass/area) 52 5.2.3.2 Soil Sampling and Analysis Soil carbon content Soil samples were collected after the end of the growing season as most recent amendments would have the least effect on biasing the organic C determination. Sampling Strategy • Sample depths: 0 -10 and 10 - 20 cm • Bulk sampling for each field: 3 bulk samples per field for 2 depths • Stratified bulk sampling for whole site: Subareas are delineated, according to unique characteristics that can be readily identified. Then bulk samples are collected within each subarea, e.g. "wet", "sandy" 3 bulk samples (formed from 10 field samples) per subarea for 2 depths The advantage of this approach is that it allows the investigator to characterise each subarea and improve the precision of estimating the entire sampling area (SSSA, 1996). 5.2.4 Carbon balances 5.2.4.1 Calculation of field scale carbon balances with a static input-output model The static model contains all important carbon pools and flows in a soil agroecosystem (Figure 5.2-2). 53 Figure 5.2-2: Flow chart of the carbon static model. C A T T L E G R A S S producing decomposing of roots and roots and grass grass litter litter M A N L I K E decomposing of manure decomposing of old SOM Soil su rface SOIL Leachingto hydrosphere Field scale balance Root and plant residues as well as manure additions are considered to be of major importance as input parameters. Carbon efflux from soils happens through decomposition of new (root and plant residues, manure) and old organic matter as well as through leaching of dissolved carbon. These essential input and output parameters are included in the balance sheet for the soil carbon balance (Table 5.2-5) and calculated as follows: Equa t ions of input pa ramete rs (for units s e e Tab le 5.2-5): • p roduc ing roots = G r a s s l a n d a rea * Y ie ld * C a r b o n content * Rat io of shoo ts to roots • p roduc ing g rass litter = G r a s s l a n d a rea * Y ie ld * C a r b o n content * P r o d u c i n g litter fract ion • sp read ing manure = L ives tock units * M a n u r e - C product ion rate Equa t ions of output parameters (for units s e e Tab le 5.2-5): • d e c o m p o s i n g of old soi l o rgan ic matter to C 0 2 = G r a s s l a n d a rea * S O C * Decompos i t i on rate of S O C • d e c o m p o s i n g of manure to C 0 2 = S P R E A D M A N U R E * Decompos i t i on rate of manure • d e c o m p o s i n g of roots and g rass litter to C 0 2 = R O O T S and L I T T E R * Decompos i t i on rate of plant res idues • leach ing of S O C = G r a s s l a n d a rea * L e a c h i n g 54 The sums of input and output flows are compared in two ways: as "surplus/deficit" and as "input/output ratio". A negative C balance (C deficit) indicates net C 0 2 emissions (see also Table 1.3-2). Table 5.2-5: Soil carbon balance Input flows [kg C/yr] producing roots GRASS [kg C/yr] Grassland area [ha] Farm data Yield [kg dry mass/ha/yr] Farm data Carbon content [kg C/kg D M ] 1 2 0.45 (general accepted value, see e.g. Jenkinson, 1981) Ratio of shoots to roots [Index] Table 5.2-6 (see below) producing grass litter GRASS [kg C/yr] < same same Producing litter fraction [Index] 10 % (adapted from LBL, 1993) spreading manure MANURE [kg C/yr] Livestock units [LU] Farm data + Table 5.2-8 (see below) Manure-C production rate [kg C/LU/yr] 626 (Leithold and Hulsbergen, 1998) Output flows [kg C/yr] decomposing of old soil organic matter to C 0 2 SOC [kg C] Grassland area [ha] Farm data SOC [kg C/ha] Sampling and analysis Decomposition rate of SOC [/yr] 0.01 (Buyanovsky, 95) Decomposing of manure to C 0 2 SPREAD MANURE [kg C] Farm data Decomposition rate of manure [/yr] 0.9 (Buyanovsky, 95) decomposing of roots and grass litter to C 0 2 ROOTS and LITTER [kg C] Farm data Decomposition rate of plant residues [/yr] 0.63 (Buyanovsky, 95) leaching of SOC Grassland area [ha] Farm data Leaching [kg C/ha/yr] 20 (Moore, 1997) A N N U A L S U R P L US/DEFICIT INPUT/OUTPUT RATIO Additional tables as mentioned in Table 5.2-5: DM.. . dry mass 55 Table 5.2-6: Root-shoot data (kg C/ha) for forage grasses Root-shoot ratio R/S aboveground (shoot) belowground (root) reference 0.84 3380 - 3780 2640-2950 mean for conventional grass (Paustian, 3650 3320 1990; Korner) 1 only root/shoot ratio available mean for organic grass (BMUJF, 1997) Table 5.2-8: Conversion of cattle type to L U 'comment "'; dairy heifer dairy calf Assumed weight in kg 650 475 135 Livestock units 1 LU 0.73 LU 0.2 LU C balances are based on a thorough calculation (based on farm statistics and literature data), sampling/chemical analysis or expert judgement of all major flows. Minor losses: [not accounted for] Carbon loss as dissolved inorganic carbon According to Kleber (1997), only small amounts of C are lost from soils through HC0 3 " export with groundwater. Carbon loss through erosion Erosion is not accounted for in the balance, because it is generally thought that erosion in western Canada (www.agr.ca/policy/evironment/sustainability/performance/potf/chap09.pdf) as well as in Austria mainly redistributes soil in the agricultural landscape rather than removes it, and under pasture losses are small. 5.2.4.2 Calculation of steady state carbon inputs with a dynamic SOM model (ICBM) The introductory C Balance Model (ICBM; Katterer and Andren, 1997, 1999) consists of two state variables and four fluxes (governed by four rate-determining parameters), and one parameter, r e , combining most external factors affecting C mineralization (temperature, precipitation, drainage, etc.) (Table 5.2-9). 56 The ICBM model is based on the assumption of first-order kinetics, i.e., where the rate of C mineralisation is directly proportional to the amount of C in the SOM pool. It includes 2 first-order components: Cm = C i (1 - ei"kt) + Oi (1 - e2-kt) C i ... labile C pool C-2... resistant C pool Katterer and Andren (1997, 1999) used simple 'front-end models' to estimate values for h (humification coefficient) initially based on records from field trials, official agricultural statistics and other literature. They then optimized the r e parameter (parameter for external influences) for each class of treatments, using an algorithm for non-linear least squares. The model can be used • for medium-term (about 30 yrs) predictions of the effects of changed inputs, climate, initial pools, litter quality, etc., on soil carbon pools. • to calculate steady-state flows and pool sizes (suffix: s s) for agroecosystems, depending on manure and litter inputs, crop type, climate, etc. For this thesis the latter approach was chosen (as data from 30 years ago was not available!). The necessary carbon input to reach a steady state (balanced budget) - i s s - for the study management scheme was calculated and can be used for a comparison with the actual carbon input. If the actual carbon input is larger (smaller) than i s s , the examined study management system is in the process of accumulating (loosing) carbon. actual carbon input > Us -> soilecosystem is a C sink actual carbon input < i s s -> soilecosystem is a C source Remark: The actual carbon input is the sum of ROOTS and LITTER [kg/m2/yr] and SPREAD MANURE [kg/m2/yr] (Table 5.2-5). 57 Table 5.2-9: IBCM parameters (adapted from Katterer and Andren, 1997,1999) Input parameters parameter for pool of total soil C [kg/m2] Farm data parameter for external influences: To combining most external factors affecting C mineralization (temperature, precipitation, drainage, etc.). According to treatment class parameter for humification: h weighted according to proportions of C input via manure (hm = 0.31) and crop-derived C sources (he = 0.125) Calculated according to farm data decay constant young soil C: k y rate constant for decomposition 0.8 (Katterer and Andren, 1997,1999) decay constants old soil C: ko rate constant for decomposition 0.006(Katterer and Andren, 1997, 1999) Output parameter steady-state carbon input: i ss [kg/m2/yr] Output 5.2.5 Nitrogen Balances N i t r o g e n b a l a n c e s a r e c a l c u l a t e d at t w o s c a l e s : f i e ld s c a l e a n d f a r m s c a l e ( F i g u r e 5 .2 -3 ) . Figure 5.2-3: Field scale and farm scale for the nitrogen balances Imported feed Milk Cattle import Cattle export Leaching to hydrosphere Field scale balance Farm scale balance 58 5.2.5.1 Calculation of field scale nitrogen balances with a static input-output model The field scale nitrogen balance is calculated as the difference between N additions to (Input flows), and N removals from (Output flows), the soil root zone. N additions are assumed to come from manure, inorganic fertiliser, biological N fixation and atmospheric sources. N removal is by crop harvest and denitrification. These input and output parameters are included in the balance sheet and calculated as follows: Equa t ions of input parameters (for units s e e ba lance sheet ) : • sp read ing minera l ferti l iser = G r a s s l a n d a rea * Fert i l iser appl icat ion rate • add ing from a tmosphe re = G r a s s l a n d a rea * Addi t ion rate • sp read ing manure = L ives tock units * M a n u r e - N product ion rate * M a n u r e loss rate • N fixing = G r a s s l a n d a rea * N f ixation rate Equa t ions of output parameters (for units s e e ba lance sheet) : • remov ing g r a s s e s = G r a s s l a n d a rea * Y ie l d * N content • los ing through denitr i f ication = App l i ed N * Denitr i f ication rate The balance (Annual surplus/deficit) acts as a basis for estimating nitrate emissions to groundwater: a certain percentage of the annual surplus (positive N balance) is attributed to nitrate leaching (see also Table 1.3-2). • leaching = ANNUAL SURPLUS * Leaching rate 59 Table 5.2-9: Field scale nitrogen balance Input flows [kg N/yr] spreading mineral fertilizer Grassland area [ha] Farm data Fertilizer application rate [kg N/ha/yr] Farm data adding from atmosphere Grassland area [ha] Farm data Addition rate [kg N/ha/yr] 18 for Austrian study region (Wieser, 96) 40 for south coastal BC (Belzer 97 in Zebarth, 98) spreading manure MANURE [kg N/yr] Livestock units [LU] Farm data + Table 5.2-10 (see below) Manure-N production rate [kg N/LU/yr] 93 (Table in Appendix) Manure loss rate [Index] Table 5.2-11 (see below) N fixing (through micro-organisms) Grassland area [ha] Farm data N fixation rate [kg N/ha/yr] Asymbiotic: 10 (Nolte 89 in Wieser, 96) Symbiotic: according to N fixing species Output flows [kg N /yr] removing grasses Grassland area [ha] Farm data Yield [kg dry mass/ha/yr] Farm data N content [kg N/ kg dry mass] 0.02 Austrian organic grassland (Wieser, 96) 0.025 B.C. south coast (BCFA, 93) losing through denitrification Applied N [kg N/yr] SPREAD FERTIL. + SPREAD MANURE Denitrification rate [Index] (Isermann 90 in Wieser, 96) ANNUAL SURPLUS/DEFICIT [kg N/yr] calculating surplus/deficit Input flows - output flows [kg N/yr] leaching ANNUAL SURPLUS [kg N/yr] Leaching rate [Index] 0.3 (EC-DG VI, 1997; Brisbin 95) Additional tables (mentioned above): Table 5.2-10: Conversion of cattle type to L U comment (lain con d,iii\ hritiT Assumed weight in kg 650 475 135 Livestock units 1 LU 0.73 LU 0.2 LU 60 Table 5.2-11: Nitrogen losses (%] from animal manure as affected by method of handling/storage and application. 1 Brisbin, 1995 Manure handling and storage method Solid systems 32 Liquid systems slurry/tank 25 23 20 slurry/earth 30 23 20 Application method Liquid systems without incorporation 25 21 22 with incorporation 5 Example for combined losses from handling/storage and application slurry/tank storage & application without incorporation 43 39 38 Minor losses [not accounted for] As stated earlier erosion is not accounted for in the balance, because it is generally thought that erosion in western Canada and Austria mainly redistributes soil in the agricultural landscape rather than removes it, and under pasture losses are small. 5.2.5.2 Calculation of farm scale nitrogen balances with a static input-output model The farm scale nitrogen balance is calculated as the difference between N additions to, and N removals from the farm area. N additions are assumed to come from inorganic fertiliser as well as imported feed and cattle. N removal is by export of milk, cattle and plants. 61 Table 5.2-12: Farm scale nitrogen balance (in kg N) Input components Output components Mineral fertilizer Imported feed Cattle import Atmos. Additions Biol. N fixation Farm data Farm data Farm data Literature Literature Farm data Farm data Farm data Literature Literature Cattle export Milk Plant products Gaseous losses Leaching Sum Input: [kg N/yr] [kg N/yr] Sum Output balance = annual surplus/deficit (+- kg N/year) 5.2.6 Uncertainties, Limitations, Sensitivity Analysis „Knowing what you can not do is more important than knowing what you can do." [Lucille Ball] L 5.2.6.1 Accuracy of the budgets The data used to calculate annual C and N flows have varying uncertainties associated with them and in many cases it is difficult to evaluate the estimates from a statistical viewpoint. C-Balance • C content in subsoils: more information is needed about changes in SOC with depth • dependency of carbon flows on various environmental factors: For example, assimilation is chiefly controlled by light, carbon dioxide concentration, and nutritive availability, while respiration is largely a function of temperature (WBGU, 1998). -> changes through higher atmospheric carbon dioxide concentrations (carbon dioxide fertilisation) -> changes through climatic changes • absence of systematic surveys of the carbon dynamics of ecosystems as a function of their intensity and form of use (WBGU, 1998). 62 N- Balance There are still knowledge gaps as to the fate of all N entering pastures. This greatly hampers the derivation of precise emission factors for nitrate leaching, denitrification and NH 3 volatilisation (Wagenetand Hutson, 1989; Hutson and Wagenet, 1991). The static N model provides useful estimates of potential nitrate leaching losses even though it relies on some major assumptions. A major uncertainty is atmospheric deposition of ammonia volatilised from on-farm sources. There is little data on ammonia losses and redistribution via the atmosphere. 5.2.6.2 Sensitivity Analyses Sensitivity analyses have been conducted for the static models, changing each parameter by 10 % and looking at the changed outcome (see section on results). For ICBM sensitivity analyses have been performed by Katterer and Andren (1997, 1999). Results showed, that initial soil C mass, present C inputs and abiotic conditions, such as soil temperature and moisture, are the deciding factors in whether C stocks decline or increase. 5.2.6.3 Limitations of simulation models In choosing a model suited to a certain need, a user often has to face the problem of selecting the most appropriate model to obtain the level of detail required. The next task is to obtain the necessary data on the various parameters to run the model. A user must recognise that model output or predictions will only be as reliable as the data input. In general, models are recommended only for comparing relative effects of management strategies (Hatfield and Karlen, 1994). 63 Results First, the results from the British Columbia farm are presented. This is followed by the conventional farm in Austria and the organic farm. Then the results are compared. 5.3 Results - Fort Langley Conventional Dairy Farm 5.3.1 Collected data The farm data collected for the British Columbia farm is summarised in Table 5.3-1 below. Table 5.3-1: Dairy Farm Questionnaire - Fort Langley dairy farm I Dairy Farm Questionnaire - Fort Langley Fields field number 1 2 3 4 Sum size (ha) 12 10 10 8 40 usage in general intensive: 4 or more cuts, > 2 manure additions, mineral fertiliser Less intensive: 2-3 cuts, 2 manure additions years under same crop type seeded with grass 4 - 5 years ago crop type (fescue, orchard grass, clover,....) orchard/fescue mix Cattle and calves number of animals mi lk ing cows dry cows heifers, 6 months & older calves, under 6 months 41 10 30 10 number of animals -history at start o f operation (1994) 30 mi lk ing cows planned 60 - 65 mi lk ing cows housing free stall - tie stall waste handling scraper - flushing - dropping (slotted floor) - other Manure data manure production per year (any units) ± 300 tank loads at 1500 gallon/tank manure imported or exported ? solid manure from calf barn exported manure storage facility type earth/ concrete - uncovered/covered storage capacity (months or other units) ±3 .5 months physical dimensions (any units) 1.2 mi l l ion gallon 64 manure application: spreading practice Splash plate - mechanical - irrigation - other Irrigation yes - no Import of feed (type, approx. Amount) ± 15 metric tons textured feed per month Export of feed ± 4000 bales of hay (25 kg each) Pesticides (type, frequency) none The management scheme 1999 for the British Columbia farm is listed in the Appendix (Table 8.4-2). Relation of the study farm to typical farms in B.C. The average large Langley1 dairy farm has about 56 cows and 45.5 ha of forage crops (Brisbin, 1995). The Fort Langley study farm has 51 cows and 42 ha grassland. Thus it can be seen as a typical large Langley dairy farm. Soil carbon content (Leco method) It was decided to sample after the end of the growing season (Dec 2, 1999). Sample Depths: 0 - 10 and 10 - 20 cm. The location of the sampling sites and the results of the analyses are shown in the Appendix (Figure 8.4-1, Figure 8.4-2). The average C content was estimated to be 6.56 %. Thus the soil organic carbon for the top 20 cm is 124640 kg/ha. In this context "Langley" is defined as the Langley waste management zone and "large farm"as a farm with annual gross farm receipts > $40,000 (Brisbin, 1994). 65 5.3.2 Carbon Balance 5.3.2.1 Field Scale Carbon Balance with the Static Model For the methodology see chapter 3.2.4.2.(Carbon Static Model Methodology). Table 5.3-2 Carbon balance for all fields (40 ha) of the Fort Langley dairy farm Input flows [kg C/yr] [kg C/ha/yr] producing roots GRASS [kg C/yr] Grassland area [ha] 40 136080 3402 Yield [kg dry mass/ha/yr] 9000 Carbon content [kg C/kg DM] 0.45 Shoot/root ratio [Index] (intensive farming) 0.84 producing grass litter GRASS [kg C/yr] See above 162000 16200 405 Producing litter fraction [Index] (part of shoot which remains as litter) 0.1 spreading manure MANURE [kg C/yr] Livestock units [LU] (Table 5.3-3) 75 46950 1174 Manure-C production rate [kg C/LU/yr] (Leithold and Hiilsbergen, 1998) 626 sum 199230 4981 Output flows decomposing of old soil organic matter to CO2 SOC [kg C] Grassland area [ha] 40 74784 1870 SOC [kg C/ha] (Sampling and analysis) 124640 Decomposition rate of SOC [/yr] (Buyanovsky, 95) 0.015 decomposing of manure to C0 2 SPREAD MANURE [kg C] 46950 42255 1056 Decomposition rate of manure [/yr] (Buyanovsky, 95) 0.9 Decomposing of roots and grass litter to C0 2 ROOTS and LITTER [kg C] 152280 95936 2398 Decomposition rate of plant residues [/yr] (Buyanovsky, 95; timothy) 0.63 leaching of soc Grassland area [ha] 40 800 20 Leaching [kg C/ha/yr] (Moore, 1997) 20 sum 213775 5344 ANNUAL SURPLUS/DEFICIT -14545 -364 INPUT/OUTPUT RATIO 0.93 0.93 Estimation of grass yield Grass cutting has a significant influence on the pattern of sward growth for it removes the flowering head and causes reproductive growth to cease. Factors such as the height, frequency and timing of cutting therefore determine the character of the growth curve and 66 frequency and timing of cutting therefore determine the character of the growth curve and the ultimate yield of the crop (Briggs and Courtney, 1985). According to LBL (1993) the yield of the 2. cut makes about 35 % of the annual yield. As for the study dairy farm the 2. cut yielded 3.125 t drymass/ha, the annual yield is calculated to be about 8.93 t drymass/ha. Another method to estimate the yield is in an indirect way based on the number of livestock units (grass demand). With this method the annual yield is calculated to be about 9 t drymass/ha. Calculation of livestock units Table 5.3-3: LU - Fort Langley dairy farm Comment --r^ f.-^ ;-- dairy cow i / 'dairy heifer :'f^-:fpf:^g, itfairyxalf-C?:-;^!f: ;sum>"'-'--'••'•'r-:-;' 1 L U 1 0.73 L U 0.2 L U Number of animals 51 30 10 I n L U 51 22 2 75 5.3.2.2 Steady state carbon input with ICBM "us was calculated to be 5600 kg/ha/yr (Table 5.3-4). Table 5.3-4: ICBM data for Fort Langley farm Input parameters parameter for pool of total soil C 124640 parameter for external influences: r e 1.1 (treatment group E) x 1.2 (correction for latitute) 1.32 parameter for humification: h weighted according to proportions of C input via manure (hm = 0.31) and crop-derived C sources (he = 0.125) 0.168 decay constant young soil C: k y rate constant for decomposition 0.800 decay constants old soil C: k o rate constant for decomposition 0.006 Output parameters steady-state carbon input: i ss [kg/ha/yr] 5600 67 5.3.3 Nitrogen Balance 5.3.3.1 Field Scale Nitrogen Balance Table 5.3-5 Nitrogen balance for all fields (40 ha) of the Fort Langley dairy farm Input flows [kg N/yr] [kg N/yr] [kg N/ha/yr] spreading Grassland area [ha] 4 0 5 0 8 0 1 2 7 mineral fertilizer Fertilizer application rate [kg N/ha/yr] (average for all fields) 1 2 7 adding from Grassland area [ha] 4 0 1 6 0 0 4 0 atmosphere Addition rate [kg N/ha/yr] best estimate for study region (Belzer et al, 97 in Zebarth,98) 4 0 spreading MANURE Livestock units [LU] 7 5 4 3 2 5 1 0 8 manure [kg N/yr] Manure-N production rate [kg N/LU/yr] 9 3 Manure loss rate [Index] Table 3.2-11 0 . 6 2 N fixing (through Grassland area [ha] 4 0 4 0 0 1 0 micro- N fixation rate [kg N/ha/yr] (Wieser, 10 organisms) 1997) sum 1 1 4 0 5 2 8 5 Output flows [kg N/yr] removing Grassland area [ha] 4 0 9 0 0 0 2 2 5 grasses Yield [kg dry mass/ha/yr] 9 0 0 0 N content [kg HI kg dry mass] (BCAFF Guidelines, south coast) 0 . 0 2 5 losing through Applied N [kg N/yr] 9 4 0 4 . 5 9 4 0 2 4 denitrification Denitrification rate [Index] 0.1 sum 9 9 4 0 2 4 9 ANNUAL SURPLUS/DEFICIT [kg N/yr] calculating surplus/deficit Input flows -N/yr] output flows [kg 1 4 6 4 3 7 leaching ANNUAL SURPLUS [kg N/yr] 1 4 6 4 3 7 Leaching rate [Index] 0 . 3 4 3 9 11 68 5.3.3.2 Farm Scale Nitrogen Balance Table 5.3-6; Farm scale nitrogen-balance for the Fort Langley farm (in kg N) Input components Output components Mineral fertilizer 5080 0 Cattle export Imported feed 18000 1900 Milk (7600 I) Cattle import 0 2500 Plant products Atmos. Additions 1600 940 Gaseous losses Biol. N fixation 400 1000 Leaching Sum Input: 25080 6400 Sum Output Balance = + 467 kg N/ha/year 69 5.4 Results - Austrian conventional dairy farm 5.4.1 Collected data The farm data collected for the Austrian'conventional farm is summarised in Table 5.4-1. Table 5.4-1: Dairy Farm Questionnaire - Austrian conventional dairy farm Dairy Farm Questionnaire - Austria Fields field number 1 sum size (ha) 1999 15 11 26 Usage general in medium intensive: 3-4 cuts, > 2 manure additions, mineral fertiliser Less intensive: 2-3 cuts, 2 manure additions years under same crop type >20 crop type (fescue, orchard grass, clover,....) Weidegrasmischung Cattle and calves Number of animals milking cows dry cows heifers, 6 months & older calves, under 6 months 13 26 11 housing free stall - tie stall waste handling scraper - flushing - dropping (slotted floor) - other Manure data manure imported or exported ? no manure storage facility type earth/concrete - covered /uncovered manure application: spreading practice splash plate (Miststreuer, VakuumfaB) Irrigation yes - no Import of feed (type, approx. Amount) 10000 kg Export of feed no Pesticides (type, frequency) "Round up", if necessary 70 Soil Analyses The average C content was estimated to be 5.1 %. Thus the soil organic carbon for the top 20 cm is 110160 kg/ha (based on a bulk density of 1.08). The location of the sampling sites and the results of the analyses are shown in the Appendix (Table 8.4-4, Figure 8.4-3). 5.4.2 Carbon Balance 5.4.2.1 Field Scale Carbon Balance with the Static Model For the methodology see chapter 3.2.4.2.(Carbon Static Model Methodology). Table 5.4-2 Carbon balance for the Austrian conventional dairy farm [kg C/yr] Input flows [kg C/yr] [kg C/ha/yr] producing roots GRASS [kg C/yr] Grassland area [ha] 26 72248 2779 Yield [kg dry mass/ha/yr] 6500 Carbon content [kg C/kg DM] 0.45 Shoot/root ratio [Index] (semi-intensive farming) 0.95 producing grass litter GRASS [kg C/yr] See above 76050 7605 293 Producing litter fraction [Index] (part of shoot which remains as litter) 0.1 spreading manure MANURE [kg C/yr] Livestock units [LU] ( Table 5.4-3) 34.18 21397 823 Manure-C production rate [kg C/LU/yr] (Leithold and Hulsbergen, 1998) 626 sum 101249 3894 [kg C/yr] Output flows Decomposing of old soil organic matter to CO2 SOC [kg C] Grassland area [ha] 26 34370 1322 SOC [kg C/ha] (Sampling and analysis) 110160 Decomposition rate of SOC [/yr] (Buyanovsky, 95) 0.012 Decomposing of manure to C0 2 SPREAD MANURE [kg C] 21397 19257 741 Decomposition rate of manure [/yr] (Buyanovsky, 95) 0.9 Decomposing of roots and grass litter to C0 2 ROOTS and LITTER [kg C] 79853 50307 1935 Decomposition rate of plant residues [/yr] (Buyanovsky, 95; timothy) 0.63 leaching of SOC Grassland area [ha] 26 520 20 Leaching [kg C/ha/yr] (Moore, 1997) 20 sum | 104454 4017 ANNUAL SURPLUS/DEFICIT -3205 -123 INPUT/OUTPUT RATIO 0.969 0.969 71 Table 5.4-3: L U - Austrian conventional dairy farm comment dain cow dain lurfi-i (lain call sum 1 LU j 0.73 LU 0.2 LU number of animals 13 j 26 11 LU 13 | 18.98 2.2 i 34.18 5.4.2.2 Steady State Carbon Input with ICBM iss was calculated to be 4970 kg/ha/yr. Table 5.4-4: ICBM data for the Austrian conventional farm Input parameters parameter for pool of total soil C 110160 parameter for external influences: re 1.1 (treatment group E) x 1.2 (correction for latitute) 1.32 parameter for humification: h weighted according to proportions of C input via manure (hm = 0.31) and crop-derived C sources (he = 0.125) 0.168 decay constant young soil C: k y rate constant for decomposition 0.800 decay constants old soil C: ko rate constant for decomposition 0.006 Output parameters steady-state carbon input: i ss [kg/ha/yr] 4970 72 5.4.3 Nitrogen Balance 5.4.3.1 Field Scale Nitrogen Balance Table 5.4-5 Nitrogen balance for the Austrian conventional dairy farm Input flows [kg N/yr] [kg N/yr] [kg N/ha/yr] spreading mineral fertilizer Grassland area [ha] 26 780 30 Fertilizer application rate [kg N/ha/yr] (average for all fields) 30 adding from atmosphere Grassland area [ha] 26 468 18 Addition rate [kg N/ha/yr] best estimate for study region (Wieser) 18 spreading manure MANURE [kg N/yr] Livestock units [LU] 34.18 1971 76 Manure-N production rate [kg N/LU/yr] 93 Manure loss rate [Index] Table 3.2-11 0.62 N fixing (through micro-organisms) Grassland area [ha] 26 390 15 N fixation rate [kg N/ha/yr] (Wieser) 15 sum 3609 139 Output flows [kg N/yr] removing grasses Grassland area [ha] 26 3380 130 Yield [kg dry mass/ha/yr] 6500 N content [kg N/ kg dry mass] (Wieser) 0.02 losing through denitrification Applied N [kg N/yr] 1971 197 8 Denitrification rate [Index] 0.1 sum 3577 138 ANNUAL SURPLUS/DEFICIT [kg N/yr] calculating surplus/deficit Input flows - output flows [kg N/yr] 32 1 leaching ANNUAL SURPLUS [kg N/yr] Leaching rate [Index] 73 Table 5.4-6: Farm scale nitrogen-balance for the Austrian conv. dairy farm (in kg N) Input components Output components Mineral fertilizer 780 208 Cattle export Imported feed 676 182 Milk Cattle import 0 26 Plant products Atmos. Additions 468 208 Gaseous losses Biol. N fixation 390 Leaching Sum Input: 2314 624 Sum Output Balance =+ 1690 kg N/a or + 65 kg kg N/ha/a 5.5 Results - Austrian organic dairy farm 5.5.1 Collected data The farm data collected for the Austrian organic farm is summarised in Table 5.5-1 below. The management scheme 1999 for the Austrian organic farm is listed in the Appendix (Table 8.4-5). Relation of the study farm to typical farms in Austria Typical organic farms in Austria are small and medium-scale (on average between eleven and eighteen dairy cows), and the average size is approximately fourteen hectares. Thus the study farm can be seen as a typical organic dairy farm. Soil Analyses Sample Depths: 0 - 1 0 and 10 - 20 cm (Sampling Strategy: see chapter 3.2.3.1). The results of the analyses are shown in the Appendix (Figure 8.4-4, Table 8.4-5) The average C content was estimated to be 5.5 %. Thus the soil organic carbon for the top 20 cm is 96800 kg/ha (based on a bulk density of 0.88). 74 Table 5.5-1: Dairy Farm Questionnaire - Austrian dairy farm Dairy Farm Questionnaire - Austria Fields field number 1 2 3 sum size (ha) 1999 11.82 2.7 1.57 16.1 size (ha) 1994 10.82 1.2 1.57 13.6 Usage in general medium intensive: 3-4 cuts, > 2 manure additions Less intensive: 2-3 cuts, 2 manure additions Extensive: only one cut, no manure addition years under same crop type 7 (Umstellung auf organisch 92) crop type (fescue, orchard grass, clover,....) Frauenmantel-Glatfhaferwiese Cattle and calves Number of animals 1999 milking cows dry cows (Kalbinnen) heifers, 6 months & older calves, under 6 months 11 2 5 1 Number of animals 1994 milking cows dry cows (Kalbinnen) heifers, 6 months & older calves, under 6 months 9 2 5 1 housing free stall - tie stall waste handling scraper - flushing - dropping (slotted floor) - other Manure data manure imported or exported ? no manure storage facility type earth/concrete - covered /uncovered storage capacity (months or other units) or physical dimensions (any units) 5 months (Rottezeit) manure application: spreading practice splash plate (Miststreuer, Vakuumfafi) Irrigation yes - no Import of feed (type, approx. Amount) about 2500 kg Export of feed no Pesticides (type, frequency) None 75 5.5.2 Carbon Balance 5.5.2.1 Field Scale Carbon Balance with the Static Model For the methodology see chapter 3.2.4.2.(Carbon Static Model Methodology). Table 5.5-2 Carbon balance for the Austrian organic dairy farm [kg C/yr] Input flows [kg C/yrl [kg C/ha/yr] producing roots GRASS [kg C/yr] Grassland area [ha] 16.1 50715 3150 Yield [kg dry mass/ha/yr] 7000 Carbon content [kg C/kg DM] 0.45 Shoot/root ratio [Index] (organic farming) 1 producing grass litter GRASS [kg C/yr] See above 50715 5071,5 315 Producing litter fraction [Index] (part of shoot which remains as litter) 0.1 spreading manure MANURE [kg C/yr] Livestock units [LU] (Table 5.5-3) 16.85 10548 655 Manure-C production rate [kg C/LU/yr] (Leithold and Hiilsbergen, 1998) 626 sum 66335 4120 [kg C/yr] Output flows Decomposing of old soil organic matter to CO2 SOC [kg C] Grassland area [ha] 16.1 15585 968 SOC [kg C/ha] (Sampling and analysis) 96800 Decomposition rate of SOC [/yr] (Buyanovsky, 95) 0.01 Decomposing of manure to C0 2 SPREAD MANURE [kg C] 10548 9493 590 Decomposition rate of manure [/yr] (Buyanovsky, 95) 0.9 Decomposing of roots and grass litter to C0 2 ROOTS and LITTER [kg C] 55787 35145 2183 Decomposition rate of plant residues [/yr] (Buyanovsky, 95; timothy) 0.63 leaching of SOC Grassland area [ha] 16.1 322 20 Leaching [kg C/ha/yr] (Moore, 1997) 20 sum 60546 3761 ANNUAL SURPLUS/DEFICIT 5789 360 INPUT/OUTPUT RATIO 1.10 1.10 Table 5.5-3: L U - Austrian organic dairy farm 76 Table 5.5-3: L U - Austrian organic dairy farm comment - dairy cow dairy heifer dairy calf „ 1 LU 0.73 LU 0.2 LU number of animals 13 5 1 LU 13 3.65 0.2 16.85 5.5.2.2 Steady State Carbon Input with ICBM iss was calculated to be 4160 kg/ha/yr (Table 5.5-4). Table 5.5-4: ICBM data for the Austrian organic farm Input parameters parameter for pool of total soil C 96800 parameter for external influences: r e 1.1 (treatment group E) x 1.2 (correction for latitute) x 0.9 (organic f) 1.2 parameter for humification: h weighted according to proportions of C input via manure (hm = 0.31) and crop-derived C sources (he = 0.125) 0.16 decay constant young soil C : k y rate constant for decomposition 0.800 decay constants old soil C: ko 0.006 Output parameters steady-state carbon input: i ss [kg/ha/yr] 4160 77 5.5.3 Nitrogen Balance 5.5.3.1 Field Scale Nitrogen Balance Table 5.5-5 Nitrogen balance for the Austrian dairy farm Input flows [kg N/yr] [kg N/yr] [kg N/ha/yr] spreading mineral fertilizer Grassland area [ha] - -Fertilizer application rate [kg N/ha/yr] (average for all fields) adding from atmosphere Grassland area [ha] 16.1 290 18 Addition rate [kg N/ha/yr] best estimate for study region (Wieser) 18 spreading manure MANURE [kg N/yr] Livestock units [LU] 16.85 972 60 Manure-N production rate [kg N/LU/yr] 93 Manure loss rate [Index] Table 3.2-11 0.62 N fixing (through micro-organisms) Grassland area [ha] 16.1 402.5 25 N fixation rate [kg N/ha/yr] (Wieser) 25 sum 1664 103 Output flows [kg N/yr] removing grasses Grassland area [ha] 16.1 2254 140 Yield [kg dry mass/ha/yr] 7000 N content [kg N/ kg dry mass] (Wieser) 0.02 losing through denitrification Applied N [kg N/yr] 971.571 97 6 Denitrification rate [Index] 0.1 sum 2351 146 ANNUAL SURPLUS/DEFICIT [kg N/yr] calculating surplus/deficit Input flows - output flows [kg N/yr] -687 -43 leaching ANNUAL SURPLUS [kg N/yr] - -Leaching rate [Index] 78 5.5.3.2 Farm Scale Nitrogen Balance Table 5.5-6: Farm scale nitrogen-balance for the Austrian organic farm (in kg N) Input components Output components Mineral fertilizer 0 48 Cattle export Imported feed 170 174 Milk Cattle import 0 0 Plant products Atmos. Additions 290 94 Gaseous losses Biol. N fixation 400 Leaching Sum Input: 860 316 Sum Output Balance = 544 kg N/year + 34 kg N/ha/year 79 5.6 Comparison of the results 5.6.1 Field scale carbon balances Results (Table 5.6-1 and Figure 5.6-1) show that the amount of C entering the fields is largest for the B.C. conventional farm and smallest for the Austrian conventional farm. However, looking at the output side a different order occurs: again the output flow is largest for the B.C. conventional farm, but smallest for the Austrian organic farm. As seen when comparing conventional and organic management, only the organic system has a positive balance. The negative C balances (C deficit) for the conventional farms indicate net C 0 2 emissions. Table 5.6-1: Comparison of the C-balances (summary) [kg C/ha/yr] B.C. conventional farm Austrian conventional farm Austrian organic farm C input 4981 3894 4120 C output 5345 4017 3727 Surplus/deficit -364 -123 393 Input/output ratio 0.93 0.97 1.1 DEFICIT indicates net C 0 2 emissions DEFICIT indicates net C 0 2 emissions S U R P L U S Figure 5.6-1: Comparison of the C-balances 80 4000 3000 2000 1000 kg C/ha/yr -1000 •2000 -3000 -B.C. conventional farm Austrian conventional farm Austrian organic farm • producing roots 3402 2779 3150 • producing grass litter 405 293 315 B spreading manure 1174 823 655 B decomposing of old soil organic matter to C02 -1870 -1322 -935 ^decomposing of manure to C02 -1056 -741 -590 • decomposing of roots and grass litter to C02 -2398 -1935 -2183 E leaching of SOC -20 -20 -20 ^deficit/surplus -364 -123 393 8 1 5.6.2 Steady state carbon inputs The results (Table 5.6-2) suggest, that only the actual C input flow of the Austrian organic farm is close to the calculated (SOM modelling) steady-state input flow, whereas this is not the case for the conventional farms. Table 5.6-2: Comparison of the C input flows [kg C/ha/yr] B.C. conventional farm Austrian ' : conventional farm Austrian organic farm Actual input 4981 3894 4120 Steady-state input 5600 4970 4160 5.6.3 Field scale nitrogen balances Results (Table 5.6-3 and Figure 5.6-2) show the different intensity of usage: The fields of the B.C. conventional farm are used intensively with high rates of mineral fertiliser and manure additions. The fields of the Austrian conventional farm are used semi-intensively. Only little mineral N is used. The fields of the organic farm are used less intensively to extensively. No mineral N is added, but the N input due to N fixing microorganisms is rather high (High biodiversity on less intensively used fields). Still the sum of the output flows exceeds the sum of the input flows. Thus a negative balance results: More N was removed than supplied. However, as N in soils is subject to many transformations and interactions, a recommendation for additional fertilization is not necessary. Organic farmers use only organic amendments. Thus they 'feed the soil organisms' rather than the plant and thereby reduce nitrogen losses to the environment (van Faassen et Lebbink, 1994).Organic farmers point out that the large inputs of chemicals to the soil-plant system, used by modern intensive agriculture, upsets a natural ecosystem which ought to be disturbed as little as possible (Addiscott, 1991). 82 Table 5.6-3: Comparison of the N-balances at field scale (summary) [kg N/ha/yr] B.C. conventional farm Austrian conventional farm Austrian organic farm Sum input flows 285 139 103 Sum output flows 249 138 146 Surplus/deficit 37 1 -43 leaching 11 S U R P L U S indicates nitrate leaching B A L A N C E D DEFICIT 83 Figure 5.6-2: Comparison of the N-balances at field scale kg N/ha/yr I spreading mineral fertilizer • adding from atmosphere I spreading manure • N fixing (through micro-organisms) I removing grasses IM losing through denitrification B.C. conventional farm 127 40 108 10 -225 -24 Austrian conventional farm 30 18 76 15 -130 Austrian organic farm 18 60 25 •140 -6 5.6.4 Farm scale nitrogen balances Results (Table 5.6-4, Figure 5.6-3) show drastic differences between the individual farm balances: Whereas for the B.C. conventional farm biological N fixation is an unimportant input flow (1.6 %), it contributes to nearly 50% of the total input of the Austrian organic farm. Also the portion of imported N (mineral fertiliser and imported feed) is rather different for the three study farms: 92 % for the B.C. conventional farm, 63 % for the Austrian conventional farm, and only 20 % for the Austrian organic farm!! Table 5.6-4; Comparison of the farm scale nitrogen-balances (summary) 84 B.C. conv. farm Austrian conv. farm Austrian organic farm k g N kg N/ha kg N kg N/ha kg N kg N/ha Sum Input: 25080 627 2314 89 860 54 Sum Output 6400 160 624 24 316 20 Balance N/ha/year + 467 kg + 65 kg + 34 kg Figure 5.6-3: Comparison of the farm scale nitrogen-balances kg N/ha/yr •100 B.C. conventional farm Austrian conventional farm Austrian organic farm • Mineral fertilizer 127 30 0 • Imported feed 450 26 11 • Cattle import 0 0 0 MAtmos. Additions 40 18 18 • Biol. N fixation 10 15 25 • Cattle export 0 -8 -3 M Milk -47 -7 -11 M Plant products -62 -1 0 FJ Gaseous losses -23 -8 -6 M Leaching -25 85 5.7 Sensitivity Analyses Sensitivity analyses have been conducted for the static models, changing each parameter by 10 % and looking at the changed outcome (For details see Appendix). Figure 5.7-1 shows the results of the sensitivity analyses for the carbon model. Results showed, that especially root production (i.e. yield and root/shoot ratio), but also plant residue decomposition and soil organic matter decomposition are the deciding factors in whether the C input/output ratios decline or increase. Figure 5.7-1: Sensitivity analyses for the carbon model Sensitivity Analysis - C model 4 n a> - 8 J parameters Table 5.7-1 shows that the deciding factors for the carbon model are associated with high uncertainties. Thus the most urgent goals for future research are: • To improve further the estimates of C02 release due to decomposition. • To understand better how climatic changes influence C02 emissions 86 Table 5.7-1: Carbon model - Sensitivity and uncertainty Effect of single parameter change Effect on C02 emissions2 influence due to farm managment Uncertainty in estimation Urgent need for more research plant residue decomposition fr small high X soil organic matter decomposition ft small high x root production u medium medium manure decomposition t small high livestock per grassland area i large minimal Effect of combined parameter change Climate change favouring decomposition ft minimal high X Soil type change favouring decomposition ft minimal medium Figure 5.7-2 shows the results of the sensitivity analyses for the nitrogen model. Results showed, that especially plant N removal (i.e. yield and plant N content), but also grassland area, mineral fertiliser rate, and livestock numbers are the deciding factors in whether N surpluses decline or increase (or even become deficits). Size of arrows approx. equivalent to magnitude of effect; up-arrow = positive correlation; down-arrow = negative correlation 87 Figure 5.7-2: Sensitivity analysis for the nitrogen model Table 5.7-2 shows that the deciding factors for the nitrogen model are associated with small uncertainties. However, a major uncertainty is atmospheric deposition of ammonia. Thus future research should include studies on this parameter. Table 5.7-2: Nitrogen model - Sensitivity and uncertainty Effect of single Effect on influence due to Uncertainty in Urgent need parameter change nitrate farm estimation for future leaching3 management research plant N removal medium small mineral fertiliser rate U large minimal livestock per grassland ft large minimal area atmos. additions t minimal high X denitrification I minimal high N fixation t small medium Size of arrows approx. equivalent to magnitude of effect; up-arrow = positive correlation; down-arrow = negative correlation 88 5.8 Discussion of the results from the case studies 5.8.1 General remarks As too many budget items are not directly measured, the budget calculations performed give general ideas of C & N turnover at the study sites, but cannot be used to reliably assess the exact C & N statuses of the systems. However, the budget items • serve as indicators on the magnitude of flows • help to determine the relative importance of system components • help to assess the influence of management and fertiliser treatments 5.8.2 Comparison with related findings 5.8.2.1 Carbon Balances Only one C budget for a managed grassland system - Sweden, conventional (Paustian, 90) -could be found in literature. It is different from the systems analysed in this thesis, as no manure was applied. However, Table 5.8-1 shows that the individual C flows are comparable. It is interesting to notice that the Swedish system is accumulating C, although it is managed conventionally. This might be due to the higher root production and smaller root decomposition (colder climate). 8 9 Table 5.8-1: Carbon balances [kg C/ha/yr] : comparison with grassland systems from literature [kg C/ha/yr] B.C., conventional (this thesis) Austria, conventional (this thesis) Austria, organic (this thesis) Sweden, conventional (Paustian, 90) producing roots 3402 2779 3150 3870 producing grass litter 405 293 315 640 spreading manure 1174 823 655 0 4981 3894 4120 4500 Decomposing of old soil organic matter to C 0 2 1870 1322 935 2400 Decomposing of manure to C 0 2 1056 741 590 0 Decomposing of roots and grass litter to C 0 2 2398 1935 2183 1900 leaching of SOC 20 20 20 5345 4017 3728 4300 Surplus/deficit -364 -123 393 200 Input/output ratio 0.93 0.97 1.1 1.05 DEFICIT DEFICIT S U R P L U S S U R P L U S indicates net indicates net C 0 2 C 0 2 emissions emissions 5.8.2.2 Field Scale Nitrogen Balances Only N budgets for conventionally managed grassland systems could be found in literature (Table 5.8-2). The results for the study dairy farm in Fort Langley, B.C. match with the results for the Dutch farm. Both are high input systems and show a N surplus. The Swedish system is different from the systems analysed in this thesis, as no manure was applied. Thus its balance is negative. 90 Table 5.8-2: Field Scale Nitrogen balances [kg N/ha/yr] : comparison with grassland systems from literature [kg N/ha/yr] B.C., conventional (this thesis) Austria, conventional (this thesis) Netherlands, conventional (in: Smaling and Oenema, 97) Sweden, conventional (Paustian, 90) spreading mineral fertilizer 127 30 5 2 2 0 0 adding from atmosphere 4 0 1 8 4 9 5 spreading manure 1 0 8 7 6 2 3 0 N fixing (through micro-organisms) 10 1 5 12 Sum input flows 2 8 5 1 3 9 3 4 3 2 0 5 removing grasses 2 2 5 1 3 0 2 6 0 2 4 1 losing through denitrification 2 4 8 3 6 1 0 Sum output flows 2 4 9 1 3 8 2 9 6 2 5 2 Surplus/deficit 3 7 1 4 7 - 4 7 S U R P L U S B A L A N C E D S U R P L U S DEFICIT i n d i c a t e s i n d i c a t e s n i t ra te n i t ra te l e a c h i n g l e a c h i n g 91 5.8.2.3 Farm Scale Nitrogen Balances As seen when comparing conventional and organic management in Austria, the N surplus is much higher in the conventional system. Also Swedish research on nutrient flows on dairy farms (Cederberg and Mausson, 2000) has shown a significantly greater surplus per ha land in conventional milk production. Table 5.8-3: Farm Scale Nitrogen Balances [kg N/ha/yr] : comparison with grassland systems from literature kg N/ha B.C., conventional (this thesis) Austria, conventional (this thesis) Austria, organic (this thesis) Sweden conventional (Cederberg and Mausson, 2000) Sweden organic (Cederberg and Mausson, 2000) Netherlands conventional4 (Smaling and Oenema, 1997) Mineral fertilizer 127 30 0 86 0 52 Imported feed 450 26 11 134 29 82 Cattle import 0 0 0 1 Atmos. Additions 40 18 18 10 10 49 Biol. N fixation 10 15 25 15 46 12 Sum Input: 627 89 54 245 85 196 Cattle export 0 8 3 47 20 11 Milk 47.5 7 11 65 Plant products 62.5 1 0 35 Gaseous losses 23.5 8 6 64 25 60 Leaching 25 32 19 50 Sum Output 160 24 20 144 64 221 Balance N/ha/year 467 65 34 101 21 experimental dairy farming system De Marke 92 5.9 Discussion of the hypotheses 5.9.1 Hypotheses for conventional vs. organic comparisons in Austria On page 44 it was hypothesised that organic farm management, compared to conventional farm management, • enhances soil organic matter (carbon) storage [HYPOTHESIS 1] • has a positive C balance = no net C 0 2 emissions [HYPOTHESIS 2] • has a negative N balance = no nitrate leaching [HYPOTHESIS 3] Hypotheses 1 and 2 were tested by comparing input and output flows of the soil C balances calculated for the Austrian study farms. Results (Table 5.9-1) show that - for the conventional farm the carbon output is exceeding the carbon input. Thus it seems reasonable to expect the fields of the conventional farm to be carbon sources. - the amount of C entering the fields of the organic farm annually is exceeding the amount of decomposed C. Thus it seems reasonable to expect this system to be a carbon sink. Table 5.9-1: outcome for the C balances regarding conventional vs. organic comparisons in Austria [HYPOTHESES 1 + 2] conventional farm management organic farm management input < output -> net C 0 2 emissions input > output -> no net C 0 2 emissions Hypothesis 3 was tested by comparing input and output flows of the soil N balances calculated for the Austrian study farms. Results (Table 5.9-2) show, that only for the organic farm management the N output is exceeding the N input. Thus it seems reasonable to expect organic farm management to prevent nitrate leaching. 93 Table 5.9-2: outcome for the N soil balances regarding conventional vs. organic comparisons in Austria [HYPOTHESIS 3] conventional farm management organic farm management input > (=) output input < output -> no nitrate leaching 5.9.2 Hypotheses for BC vs. A comparisons in conventional farms On page 44 it was hypothesised that farm management in B.C., compared to farm management in Austria, • causes more net C02 emissions [HYPOTHESIS 4] • uses higher inputs of conventional sources of nitrogen (such as mineral fertilizer, imported feeds) [HYPOTHESIS 5] • imports much more nitrogen than it exports [HYPOTHESIS 6] Hypothesis 4 was tested by comparing carbon deficits calculated for the conventional study farms. Results (Table 5.9-3) show, that the farm management in B.C. causes more net C02 emissions. Table 5.9-3: outcome for the C balances regarding BC vs. A comparisons in conventional farms [HYPOTHESIS 4] B.C. Austria Deficit [kg C/ha/yr] -364 -123 Input/output ratio 0.93 0.97 input < output Hypotheses 5 and 6 were tested by comparing the N farm balances calculated for the conventional study farms. 94 Table 5.9-4: outcome for the N farm balances regarding BC vs. A comparisons in conventional farms [HYPOTHESIS 5 + 6] N farm balances B . C . Aust r ia Sum Input 627kg N/ha 89 kg N/ha imports (mineral fertiliser, feeds) 577 kg N/ha 56 kg N/ha Sum Output 160 kg N/ha 24 kg N/ha export (cattle, milk, plant products) 110 kg N/ha 16 kg N/ha HYPOTHESIS 5 I n p u t » ou tpu t 5 High input of conventional sources of nitrogen (mineral fertiliser, imported feeds), losses to the environment (see Text Box) input > output Low to medium input of conventional sources of nitrogen, efficient nitrogen utilisation HYPOTHESIS 6 imports » exports smaller amounts imported and exported Text box 1: British Columbia - Agrochemicals in groundwater • Aquifers in southern B.C. at moderate-to-high risk of agrochemical contamination, particularly in areas of high rainfall (lower mainland) • Abbotsford-Sumas aquifer in lower Fraser Valley highly susceptible to agrochemical contamination; nitrate contamination mainly from heavy field application of manure from local high-density poultry and livestock production • Nitrate levels greater than Canadian safe limit for drinking water are found in groundwater supplies of Fraser and Okanagan valleys output in this context does not include nitrate leaching 95 6 Summary, Conclusion With the progressive growth of the world population and the increase in prosperity in the developed countries the demand for food increases also progressively and thus the pollution of air, water and soil caused by agriculture. The interest in environmental impacts of conventional agricultural practices - especially the contribution to greenhouse gas emissions and water pollution - has intensified, and with it has the need for studying carbon and nitrogen cycling in soils (Paustian et al., 1990, Vitousek et al, 1997). Globally, agricultural activities are responsible for about 20% (Watson, 1996) of total anthropogenic emissions of greenhouse gases, the estimate for both Canada and Austria is 10 % (AAFC, 1998; Dersch and Bohm, 1997). Carbon dioxide, the most prominent greenhouse gas, is emitted because of initial cultivation of soils, management of existing fields, and the use of fossil fuels to produce fertilisers and drive farm machinery. In B.C. as well as Austria the specialisation and intensification in agricultural production have contributed to degradation of organic carbon on agricultural land. However, topsoils are still an important carbon reservoir, which must be preserved by competent and sustainable soil cultivation (Dersch and Bohm, 1997). Considering recent research (Some climate models suggest a rise in average temperature over the next 100 years of 2 to 4 °C in southern Canada, and even higher in the North. BCMEPR and BCMELP, 1995) it must be realized that a certain climate change will be inevitable.The consequences will be an outstanding challenge for agriculture around the world. For south coastal B.C., increased crop production along with increased crop damage by pests may be expected (Zebarth et al., 1997). For Austria predictions include lower yields, reduced vegetation density, diminished soil carbon input and increased danger of erosion (FMEYF, 1997). Besides global warming, nitrate leaching from agricultural soils has also become a serious environmental problem in Europe and N-America (Addiscott, 1991). For example, results from two studies on the Abbotsford Aquifer in B.C. (Berka and Schreier, 1996; Zebarth et al., 1998) show, that intensive agricultural production is a primary contributor to elevated nitrate concentrations in the aquifer (nitrate concentrations measured from one well increased from less than 10 mg/l in 1970 to an average of 19.5 mg/l between 1990 and 1995; Zebarth et al., 1998). 96 Results from a comprehensive groundwater analysis for the whole of Austria (conducted between 1995 and 1997; UBA, 1998) showed that 16% of the samples contained nitrate concentrations higher than 50 mg/l (threshold value for drinking water). Nutrient turnover in agroecosystems consists of the continuous cycling between organic forms of carbon and nitrogen & inorganic forms. Mass balance calculations for carbon and nitrogen in agroecosystems can provide information about their turnover in relation to crop demand and potential losses to the environment (van Faassen et Lebbink, 1994). It was the aim of this project to use such calculations to analyse the influence of different farm management practices on C and N dynamics of typical dairy farms in B.C. and Austria. The dairy farms - two conventionally managed farms (B.C. and Austria) and one organically managed farm (Austria6) - were selected to be somewhat comparable between Austria and British Columbia in terms of climatic conditions and soil parent material. However, differences existed regarding management practices: The fields of the B.C. conventional farm were used intensively with high rates of mineral fertiliser and manure additions. The fields of the Austrian conventional farm were used semi-intensively. Only little mineral N was used. The fields of the organic farm were used less intensively to extensively. No mineral N was added. Results for the C balances of the Austrian farms show that organic management, compared to conventional management, has a positive balance (393 kg C/ha/yr) and thus contributes to soil storage of carbon. This can be explained by the increased root production in the organic fields, as organic farmers try to maintain high biodiversity and do not specialise on high yielding varieties that can be associated with smaller root production (BMUJF, 1997). For the Austrian conventional fields the C output is exceeding the C input. The resulting negative balance (-123 kg C/ha/yr) indicates net C02 emissions. The C balances comparison of the conventional farms (B.C. vs. Austria) show, that the farm management in B.C. causes more net C02 emissions (-364 vs. -123 kg C/ha/yr, respectively) and this is attributed to more intensive management. Sensitivity analyses for the carbon balance model show that the deciding factors (decomposition of plant residues/soil organic matter and climatic changes) are associated with high uncertainties. Thus the most urgent goals for future research are (i) to improve A comparable organically managed farm in B.C. could not be found. 97 further the estimates of C02 release due to decomposition and (ii) to understand better how climatic changes influence changes in soil organic matter. Results for the N balances of the Austrian farms show that organic management, compared to conventional management, has a negative N balance (- 43 vs. 1 kg N/ha/yr, respectively). This can be explained by the sole use of manure fertilisation in the organic fields, whereas mineral N (30 kg N/ha/yr) was applied to the conventionally managed farm. The N balances of the conventional study farms were used to compare the different national management practices (B.C. vs. Austria). Results show that for the B.C. farm management the N input (mineral N addition alone was 127 kg N/ha/yr) is significantly exceeding the N output. Due to the large N surplus (37 kg N/ha/yr) it seems reasonable to expect this management to cause nitrate leaching. In contrast, the Austrian fields input and output flows are balanced. Thus it can be assumed that the Austrian farm management does not contribute significantly to nitrate pollution. Sensitivity analyses for the N balance model show that the deciding factors (mineral fertiliser rate, plant N removal, and livestock density) are associated with small uncertainties. However, a major uncertainty is atmospheric deposition of ammonia. Thus future research should include studies of this issue. Summary of important findings: • Nitrogen fertilisation should be more closely adjusted to crop requirements (Austrian conventional farm) and suited to the environmental conditions to prevent nitrogen losses. • Organic dairy farming has a higher C- and N-efficiency than conventional dairy farming. The possibilities to reduce C- and N-loss by conversion to organic dairy production therefore appear to be promising. Also better management of organic matter in conventional farms should be encouraged. 6.3.1 Options and Recommendations Agricultural policies directly influence how land is used (Text box 2). For example, the U.S. National Research Council Committee concluded that in North America laws and policies 98 governing agriculture, are among the major culprits interfering with alternative methods of production. Text box 2: Part of a speech by John Miller, an Iowa farmer (Hatfield and Karlen, 1994, p 11) "A farmer is always making decisions... often... decisions on... decisions. Government may have more influence on these ,„ than either research or education. Research and education are optional when compared to policy. I can choose to respond to research by adopting it as an innovator, or I can ignore it altogether. ...education is ... effective if I choose to be receptive. But failure to pay heed to policy can cause me financial hardship, it might even break me " Various already existing policy measures can be used or adapted to reduce C- and N-losses from agroecosystems. Information on best agricultural practices can be extended to include advice on how to minimise C 0 2 emissions. Also programs to encourage the adoption of organic-farming techniques could be strengthened. Table 5.9-1 presents a summary of possible measures that can be used to reduce C- and N- losses from agroecosystems. Table 5.9-1: Policy instruments and measures that influence C - and N- losses from agriculture (adapted from Storey and McKenzie-Hedger, 1997) E c o n o m i c inst ruments Se t -as i de payments C r o s s - c o m p l i a n c e s c h e m e s S u b s i d i e s for conver t ing to organ ic agr icul ture Reduct ion / re form of agricul tural subs id ies - Incent ives to forestry Jur id ica l inst ruments International agreements and conventions Regu la t ion and legislat ion (S tandards , L imi ts, Rest r ic t ions , Requ i rements ) Complementary instruments Information and educat ion (Information on w a y s to improve agricultural productivity, C o d e s of good agr icul tural pract ice) R e s e a r c h and deve lopmen t (on the uptake and loss of ca rbon in forests, on the product ion and recovery of energy f rom was te ) Vo luntary a p p r o a c h e s with farmers (to reduce the u s e of fert i l izers) The different instruments can be, and often are, employed simultaneously and have international, regional and local dimensions. 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B C M E L P AND ENVIRONMENT CANADA, 1997 8 Appendix 8.3 Ad Chapter 4 Table 8.3-1: Figures on organic farming in Europe and Canada (http://www.ifoam.de/statistics) 1 GMIIIIBI i 1 20 .207 Aus t r ia 8,94 287 .900 8,4 9 /1999 F in land 5.200 6,1 137.000 6,3 end 1999 D e n m a r k 3 .029 5,2 160.369 6,6 31 .12 .1999 S w e d e n 3.251 3,7 154.000 5,5 31 .12 .1999 G e r m a n y 9.209 1,8 416 .318 2,4 31 .12 .1998 Italy 43 .698 1,8 788 .070 5,3 31 .12 .1998 Ne ther lands 1.216 1,2 22 .997 , 1,2 1.1.2000 L u x e m b o u r g 29 1,1 1002 1 0,8 1/2000 F r a n c e 8.140 1,0 316 .000 1,1 31 .12 .1999 Be lg i um 550 0,9 18.572 1.4 end 1999 S p a i n 11 .773 0,9 352.164 j 1,4 31 .12 .1999 U K 1.356 0,7 240 .000 1,2 Apr i l 1999 Ireland 1058 0,7 32.478 0,7 31 .12 .1999 G r e e c e 4.231 0,48 15.849 0,47 31 .12 .1998 Por tuga l 750 0,2 47.974 1.2 31 .12 .1999 E U 113.697 1,45 2.990 .702 2,2 -C a n a d a 1830 0,7 1.000.000 1,34 1997 106 8.4 Ad Chapter 5 Table 8.4-1: Manure-N production rate Weight in kg u u i i y w v v u u i i y UUII Livestock units 1 LU 0.73 LU 0.2 LU Sutton et al., liquid manure pit 93 kg N/yr 48 kg N/yr 10 kg N/yr Brisbin, 1995 116 kg N/yr 42 kg N/yr 20 kg N/yr Manure-N production rate 93 kg N/LU/yr 66 kg N/LU/yr 100 kg N/LU/yr 93 kg N/LU/yr 8.4.1 Additional Farm Data: Fort Langley dairy farm Table 8.4-2: Management scheme 1999 - Fort Langley dairy farm Dale Field 1 Field 2 Field 3 Field 4 Usage in intensive: Less intensive: general 4 or more cuts, > 2 manure additions, mineral fertiliser 2-3 cuts, 2 manure addit. mid march 30 tank loads manure 60 tank loads manure 29 mar cut for cows 250 lbs/acre of 28-10-10 14 april cut for cows 28apr cut for cows end april 20 tank loads manure 40 tank loads manure mid may cut for silage mid may 250 lbs/acre of 28-10-10 15 may cut for cows 30 may cut for cows 150 lbs/acre of 40-0-0 20june cut for cows 5 jul cut for cows early July cut: hayed 2500 bales (25 kg each) 150 lbs/acre of 40-0-0 mid July Cut for silage end July 40 tank loads manure 22 jul cut for cows 150 lbs/acre of 40-0-0 15 aug cut for cows 107 mid aug cut: hayed ± 3750 bales (25 kg each) 10 sept cut for cows 30 sept cut for cows end sept cut for silage oct cut for cows sept - nov Adding manure rest (100 loads) Figure 8.4-1: Location of the sampling sites - Fort Langley dairy farm gravel road w i l l > r o a d ^ ^ o o o 0 \ s 0 0 \ 11 0 \ 1 0 0 0 0 0 ^ ditch ^ O 0 IV 1 1 b u i l d i n g s / ^ 108 Figure 8.4-2: Results Soil Carbon (Fort Langley) Sample Depths: 0 - 10 and 10 - 20 cm Results (Leco Carbon for 0 - 10 cm depth) and their spatial distribution: Field I Field 3.86 5.14 6.5 3.15 3.91 5.8 Field II A 1.33 8.51 7.17 3.23 9.01 7.73 7:94 8 M 6.96 Field IV Results showed that the C content of the 10 - 20 cm depth samples was about 92 % of the C content of the 0 - 10 cm depth samples. a v e r a g e s Fairf ield H a z e l w o o d T o t a l 3.86 8.54 6 . 5 6 Water Analyses Water samples were taken from 5 different points of the farm ditch. Results (Table 8.4-3) over time for nitrate: increase from August ( 0 0.3 ppm) to September ( 0 0.58 ppm), then a small decrease from September to October ( 0 0.42 ppm). Table 8.4-3: concentrations [ppm] of nitrate, ammonium, DOC, TOC - farm ditch water (neutral pH) K ? S H H B mm A u g u s t 16, 9 9 9 (af ternoon, w a r m and sunny) N 0 3 " , ppm .031 .035 .033 .023 .029 0.30 N H 4 + , p p m .027 .099 .000 .095 .312 0.1 D O C T O C S e p t e m b e r 1, 1999 (noon, w a r m and sunny) N 0 3 " , p p m .054 .060 .083 .037 dry 0.58 N H 4 + , p p m .033 .010 .113 .000 dry 0 .039 D O C T O C O c t o b e r 1, 1999 (noon, wa rm and sunny) N 0 3 " , ppm .038 .046 dry 0.42 N H 4 + , p p m .31 .204 dry 0 .25 D O C T O C 109 8.4.2 Additional Farm Data: Austrian conventional dairy farm Table 8.4-4: Management scheme - Austrian conv. dairy farm fields 1 2 Usage in general medium intensive: 3-4 cuts, > 2 manure additions, mineral fertiliser Less intensive: 2-3 cuts, 2 manure additions Figure 8.4-3: Results Soil Carbon (Austrian conventional farm) Sample Depths: 0 - 10 and 10 - 20 cm Results (for 0 - 10 cm depth) and their spatial distribution: 5.5 Field I 5.1 Field II Fields 1 2 SOC (%)0- 10 cm 5.5 5.1 SOC (%)10-20 cm 5.2 4.8 110 8.4.3 Additional Farm Data: Austrian organic dairy farm Table 8.4-5: Management scheme - Austrian organic dairy farm fields 1 2 3 Usage in general medium intensive: 3-4 cuts, > 2 manure addit. Less intensive: 2-3 cuts, 2 manure addit. Extensive: only one cut, no manure addition Management scheme (kg N/ha) (M...manure, L...liquid manure) march/apr 33 asM mid/end may cut for hay and silage cut for hay begin June 53 asM 26 asM begin Jul cut for hay mid July cut for hay cut for hay aug 20 asL sept cut for silage lOasL rest 14asL sum 120 36 0 Average rate: 97 kg N/ha Figure 8.4-5: Results Soil Carbon (Austrian organic farm) Sample Depths: 0 - 10 and 10 - 20 cm Results (for 0 - 10 cm depth) and their spatial distribution: Field III I I Field II 5.8 5.6 Fields 1 2 3 SOC (%)0- 10 cm 5.8 5.6 4.5 SOC (%)10-20 cm 5.7 5.8 3.1 I l l .4.4 S e n s i t i v i t y A n a l y s e s Sensitivity analysis: C model/B.C. conv. 

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