Management Practices Assessment
Editors: Giovanni Quaranta and Rosanna Salvia <quaranta@unibas.it>
With contributions from: Constantinos Kosmas, Maria José Roxo, Francisco López Bermúdez, Jorge García Gómez, Anna Grazia Marchese, Francesco Mastroberti, Rosetta Fulco

1. Introduction

The equilibrium regulating the relationship between agriculture and environment is quite delicate. It depends particularly on the utilisation of resources (land use and agricultural practices), which should always be suited to the environmental conditions. Sustainable evaluation of this relationship it is not so easy, because it involves environmental aspects and also social and economic dimensions, both at the farm and a wider scale. With this in mind, there is a need for a tool that easily supplies, in an immediate and simple way, a synthetic judgment on agricultural management, considering reciprocal relationships that exist between cultivation practices, climate and physical-chemical-biological soil characteristics. In this way all the people working directly on the land, using resources or planning development strategies, can simulate the effects of different technical solutions, evaluating all the generated impacts. Such a tool can support a substantial distribution of sustainable techniques and technologies, appearing as a valid aid for CAP implementation, as well as acting as a useful tool to support development programmes at the wider scale. Research has highlighted that available methods used to evaluate sustainable agricultural practices are extremely complex, and often not practical. It is to answer this implicit need of simplification that we propose this useful operational tool to offer easy and immediate answers to everyone involved in land management. The method may not consider the complexity of all existing interconnections among different variables that influence sustainable processes according to indexes/indicators available for stakeholders, but it tries to keep the essence of the linkages associated with degradation. ManPrAs is a tool for Agricultural Management Practices Assessment set up within DESERTLINKS project. The objective is to suggest a method, based on the indicators list in DIS4ME, to assess the sustainability of agricultural practices through its soil conservation index (SCI) and economic results (Gross Margin-GM), and to simulate the impact on soil degradation, farm profitability and socio-economic features of alternative crops in a specific context. The tool is strongly user-orientated, and allows assessment of the environmental and economic aspects of agricultural practice, giving a powerful simulation tool to farmers and stakeholders involved in land management.

The tool is composed of two different but integrated parts:

• The first part allows the calculation of a soil conservation index (SCI), a “dynamic” indicator of soil quality combining the interaction among the physical-chemical and climatic site characteristics and the single agricultural operations. SCI considers the effects of both physical-chemical-climatic characteristics and the agricultural operations on the principal threats to soil. Each interaction among the three classes of parameters (physical-chemical-climatic; agricultural operations; soil threats) has been established taking into consideration both the literature review and stakeholder consultations. For each parameter value classes have been derived taking account of the same information.
• The second part of the tool is designed for the economic evaluation of agricultural practices. Through an algorithm it is possible to obtain the gross margin (GM) for each practice.                                                                                    

 Together, SCI and GM, provide the possibility of checking the degree of soil conservation on a farm, the tradeoff options to switch towards more or less sustainable practices, and the economic impact. The environmental and economic assessment of the identified agricultural practices reported in the ManData database and the stakeholders comments gathered during the workshops have represented the first validation of the tool. ManPrAs is intended both as a review of environmental impacts of common types of land management in the four Target Areas of the DESERTLINKS project (Agri Basin – Italy; Alentejo – Portugal; Guadalentín – Spain; Lesvos – Greece), specifically for agricultural techniques, and as an interactive tool that allows an individual assessment of land management in a specific context.

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The soil conservation index is a dynamic index. It can assess the effect of each single agricultural operation on soil quality, addressing improvements or deterioration. There are essentially two starting points:

a) Each single soil operation (technique) influences soil conservation. Every single agricultural operation can influence, to a greater or lesser extent, soil and its capability to maintain its intrinsic characteristics.

b) The final effect (direction and intensity) depends both on the modality (management) and the context characteristics (climate, physical and chemical properties, site specific). The final effect of every agricultural practice, in terms of both direction and intensity of the process, strongly depends on how this practice is carried out (i.e. on the management) and on the context in which it is adopted (climate, physical and chemical characteristics, site specific).The SCI calculation procedure requires that all the three interacting dimensions have to be specified: soil threats, climate, physical and chemical soil characteristics, agricultural practices.

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According to the following conclusions set up by the  “COMMUNICATION FROM THE COMMISSION TO THE COUNCIL, THE EUROPEAN PARLIAMENT, THE ECONOMIC AND SOCIAL COMMITTEE AND THE COMMITTEE OF THE REGIONS - Towards a Thematic Strategy for Soil Protection” (Brussels, 16.4.2002 COM(2002) 179), maintaining soil condition is essential for sustainability, due to its wide range of vital functions. However soil is under increasing threat from human activities, which are undermining its long-term availability and viability. The threats are complex and, although unevenly spread across regions in the EU and accession countries, their dimension is continental. For simplicity they are presented separately below. In real terms, however, they are frequently inter-linked.

Erosion. Erosion is a natural geological phenomenon resulting from the removal of soil particles by water or wind, transporting them elsewhere. However, some human activities can dramatically increase erosion rates. Serious erosion is generally irreversible. Erosion is triggered by a combination of factors such as steep slopes, climate (e.g. long dry periods followed by heavy rainfall), inappropriate land use, land cover patterns (e.g. sparse vegetation) and ecological disasters (e.g. forest fires). Moreover, some intrinsic features of a soil can make it more prone to erosion (e.g. a thin layer of topsoil, silty texture or low organic matter content). The results of soil erosion are the loss of soil functions and ultimately the loss of soil itself. Soil erosion can therefore be considered, with different levels of severity, an EU-wide problem.

Decline in organic matter. Soil organic matter is composed of organic material (plant root remains, leaves, excrements), living organisms (bacteria, fungi, earthworms and other soil fauna) and humus, the stable end-product of the decomposition of organic material in the soil by the slow action of soil organisms. As such, it is constantly built up and decomposed, so that carbon is released to the atmosphere as CO2 and recaptured through the process of photosynthesis.  Farming and forestry practices have an important impact on soil organic matter. Despite the importance of maintaining the organic matter content of soil, there is evidence that decomposing organic matter in the soil is frequently not sufficiently replaced under arable cropping systems, which are tending towards greater specialisation and monoculture. Specialisation in farming has led to the separation of livestock from arable production so that rotational practices restoring soil organic matter content are often no longer a feature of farming. The build-up of organic matter in soils is a slow process (much slower than the decline in organic matter). This process is enhanced by positive farm management techniques such as conservation tillage (including no-tillage cropping techniques), organic farming, permanent grassland, cover crops, mulching, manuring with green legumes, farmyard manure and compost, strip cropping and contour farming. Most of these techniques have also proven effective in preventing erosion, increasing fertility and enhancing soil biodiversity.

Soil contamination. The introduction of contaminants in the soil may result in damage to, or loss of some or several functions of soils and possible cross contamination of water. The occurrence of contaminants in soils above certain levels brings multiple negative consequences for the food chain and thus for human health, and for all types of ecosystems and other natural resources. To assess the potential impact of soil contaminants, account needs to be taken not only of their concentration but also their environmental behaviour and the exposure mechanism for human health. A distinction is often made between soil contamination originating from clearly confined sources (local or point source contamination) and that caused by diffuse sources.

• Local soil contamination. Local (or point source) contamination is generally associated with mining, industrial facilities, waste landfills and other facilities both in operation and after closure. These activities can pose risks to both soil and water. In mining the risk is associated with the storage or disposal of tailings, acid mine drainage and the use of certain chemical reagents. Industrial facilities both in operation and after closure can be a major source of local contamination.  
• Diffuse soil contamination. Diffuse pollution is generally associated with atmospheric deposition, certain farming practices and inadequate waste and wastewater recycling and treatment. Atmospheric deposition is due to emissions from industry, traffic and agriculture. Deposition of airborne pollutants releases into soils acidifying contaminants (e.g. SO2, Nox), heavy metals (e.g. cadmium, lead arsenic, mercury), and several organic compounds (e.g. dioxins, PCBs, PAHs). Acidifying contaminants gradually decrease the buffering capacity of soils leading them in some instances to surpass their critical load, resulting in a sudden massive release of aluminium and other toxic metals into aquatic systems. In addition, acidification favours the leaching out of nutrients, with subsequent loss of soil fertility and possible eutrophication problems in water and excess of nitrates in drinking water. Moreover it may damage beneficial soil micro-organisms, slowing down biological activity. Ammonia and other nitrogen deposition (resulting from emissions from agriculture, traffic and industry) cause the unwanted enrichment of soils and subsequent decline of biodiversity of forests and of high nature value pastures.  A number of farming practices can also be considered as a source of diffuse soil contamination, although their effects on water are better known than on soil. Production systems where a balance between farm inputs and outputs is not achieved in relation to soil and land availability, lead to nutrient imbalances in soil, which frequently result in the contamination of groundwater and surface water. The extent of nitrate problems in Europe underlines the seriousness of this imbalance. An additional problem relates to heavy metals (e.g. cadmium and copper) in fertilisers and animal feed. Their effects on soil and soil organisms are not clear, although studies have shown the possible uptake of cadmium in the food chain. The effects on soil of antibiotics contained in animal feed are unknown. Pesticides are toxic compounds deliberately released into the environment to fight plant pests and diseases. They can accumulate in the soil, leach to the groundwater and evaporate into the air from which further deposition onto soil can take place. They also may affect soil biodiversity and enter the food chain. With regard to waste, sewage sludge, the final product of the treatment of wastewater, is also raising concern. It is potentially contaminated by a whole range of pollutants, such as heavy metals and poorly biodegradable trace organic compounds, which can result in an increase in the soil concentrations of these compounds. Some of these can be broken down to harmless molecules by soil micro-organisms whereas others, including heavy metals, are persistent. This may result in increasing levels in the soil with subsequent risk for soil micro-organisms, plants, fauna and human beings. Potentially pathogenic organisms like viruses and bacteria are also present. However sewage sludge contains organic matter and nutrients such as nitrogen, phosphorus and potassium, of value to the soil, and the options for its use include application on agricultural land. Provided that contamination is prevented and monitored at source, the careful and monitored use of sewage sludge on soil should not cause a problem, and, indeed, on the contrary could be beneficial and contribute to an increase in soil organic matter content.

Soil compaction. Soil compaction occurs when soil is subject to mechanical pressure through the use of heavy machinery or overgrazing, especially in wet soil conditions. In sensitive areas, walking, tourism and skiing also contribute to the problem. Compaction reduces the pore space between soil particles and the soil partially or fully loses its absorptive capacity. Compaction of deeper soil layers is very difficult to reverse. The overall deterioration in soil structure caused by compaction restricts root growth, water storage capacity, fertility, biological activity and stability. Moreover, when heavy rainfall occurs, the water can no longer easily infiltrate the soil. Resultant large volumes of run-off water increase erosion risks and are considered by some experts to have contributed to some recent flooding events in Europe.

Decline in soil biodiversity. Soil is the habitat for a huge variety of living organisms. In addition, the character of all terrestrial ecosystems is heavily dependent on the soil type. Soil type determines to a great extent the ecosystems found in an area, many of them of great ecological value (wetlands, flood plains, peatlands). The largest quantity and variety of life is found in the soil itself. In a pasture, for each 1 to 1.5 tons of biomass living on the soil (livestock and grass), about 25 tons of biomass (bacteria, earthworms and so on) exist in the first 30 cm of soil underneath.  Soil bacteria, fungi, protozoa and other small organisms play an essential role in maintaining the physical and biochemical properties needed for soil fertility. Larger organisms, worms, snails and small arthropods break up organic matter which is further degraded by micro organisms, and both carry it to deeper layers of soil, where it is more stable. Furthermore, soil organisms themselves serve as reservoirs of nutrients, suppress external pathogens and break down pollutants into simpler, often less harmful components. Reductions in soil biodiversity make soils more vulnerable to other degradation processes. Therefore soil biodiversity is often used as an overall indicator of the state of soil health. One gram of soil in good condition can contain up to 600 million bacteria belonging to 15,000 to 20,000 different species. In desert soils these numbers decline to 1 million and 5,000 to 8,000 species respectively. Although the complexity of soil biodiversity dynamics is not yet fully understood, there is evidence that biological activity in soils is largely dependent on the occurrence of appropriate levels of organic matter. The inappropriate use of pesticides and in particular nematicides can have very negative effects because of their poor selectivity. Some studies suggest that some herbicides considerably suppress soil bacterial and fungal activity. Moreover, excessive use of nutrients can also seriously alter biological balances and thus reduce soil biodiversity. Organic farming has been shown to be very effective in preserving and enhancing biodiversity.

Salinisation. Salinisation is the accumulation of soluble salts of sodium, magnesium, and calcium in soils to the extent that soil fertility is severely reduced. This process is often associated with irrigation as irrigation water always contains variable amounts of salts, in particular in regions where low rainfall, high evapotranspiration rates or soil textural characteristics impede the washing out of the salts which subsequently build-up in the soil surface layers. Irrigation with water of high salt content dramatically worsens the problem. In coastal areas salinisation can also be associated with groundwater over-exploitation (caused by the demands of growing urbanisation, industry and agriculture) leading to a lower water table and triggering the intrusion of marine water. In Nordic countries the winter maintenance of roads with salts can lead to salinisation.

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2.2 Soil physical, chemical and biological variables

To calculate the SCI the following variables have been used, derived from those described within DIS4ME and from focus group workshops.

Slope gradient. Slope gradient greatly affects amount of surface water run-off and soil sediment loss. Soil erosion rates become acute when the slope angle exceeds a critical value, and then increase logarithmically. The slope gradient can have variable effect in different climatic zones, depending mainly on annual rainfall. Measurements conducted in different areas with natural vegetation in the Mediterranean region have shown that severely eroded soils prevail in semi-arid climatic conditions with slopes greater than 12%, while slightly to moderately eroded soils are found in dry sub-humid climatic zones under similar slopes.

The amount of sediment transported after each rainfall event is a function of climate, vegetation, topography and soil, which can be estimated by the equation:

S=kq(**m) L (**n)

where: S is the sediment loss (t ha-¹), k is soil erodibility, q is overland flow discharge per unit width, L is local slope gradient, and m, n, are empirical values to be determined.

As well as slope gradient, slope length is also important, affecting soil loss due to surface water runoff. Tillage erosion caused by tillage implements is greatly affected by slope gradient. As the following equation shows, soil erosion is proportionally related to slope gradient. The flux of soil in the direction of ploughing (Qs, in kg m-¹) per tillage operation can be determined by the equation:

Qs = D*BD*G*B

where, D is the ploughing depth (m), BD is the bulk density of the soil (kg m-³), G is slope gradient (tan), and B is a coefficient, corresponding to plough depth D.

The following slope gradient classes have been distinguished:

• <6 %
• 6-18 %
• 18-35 %
• >35 %

The following rainfall classes have been distinguished:

• >650 mm,
• 280-650 mm,
• <280 mm

The Aridity index (1) can be estimated by the Bagnouls-Gaussen index (BGI) using the following equation:
n
BGI = sum (2ti - Pi)*k
i=1
where: ti is the mean air temperature for month i in °C, Pi is the total precipitation for month i in mm; and k represents the proportion of month during which 2ti - Pi>0.

These benchmarks have been defined according to the Bagnouls-Gaussen method (as used in the ESI index):

• <50,
• 50-75,
• 75-100,
• 100-125,
• 125-150,
• >150

The Aridity index (2) can be also defined as the ratio between mean annual precipitation (P) and mean annual evapotranspiration- (ETP) calculated with the Penman formula.

The following classes have been used (as suggested by the UNCCD):

• >0.65 ·
• 0.5-0.65 ·
• <0.5

The following vegetation cover classes have been distinguished:

• <10%,
• 10% - 40%,
• >40%

Soil texture. Soil texture is the relative proportion of sand, silt, and clay in a soil. Sand is the 2.0 to 0.05 mm soil fraction, and according to the USDA system is subdivided into five classes (very coarse sand 2.0-1.0 mm, coarse sand 1.0-0.5 mm, medium sand 0.5-0.25 mm, fine sand 0.25-0.1 mm, and very fine sand 0.1-0.05 mm). Silt is the 0.05 to 0.002 mm soil fraction, and clay is the soil fraction that has a diameter less than 0.002 mm. Texture changes slowly with time. Soil texture profoundly affects soil drainage, water holding capacity, soil temperature, soil erosion as well as fertility and productivity. Wind erosion is a major problem when sandy soils are used for crop production in regions with dry seasons. Wind erosion is accelerated when the vegetative cover is removed. Soils are classified according to their texture in classes, and each textural class have a given range of sand, silt and clay. For practical value in agriculture 12 classes were designated.

The following soil texture classes have been distinguished:

• L, SCL, SL, LS, CL
• SC, SiL, SiCL
• Si, C, SiC
• S

Soil depth. Soil water-storage capacity and effective rooting depth are mainly related to the soil depth. The effects of soil erosion on productivity depend largely on the thickness and quality of the topsoil and on the nature of the subsoil. Productivity of deep soils with thick topsoil and excellent subsoil properties may be virtually unaffected by erosion.

The following soil depth classes have been distinguished:

• very shallow (<15 cm)
• shallow (15-30 cm)
• moderately deep (30-60 cm)
• deep (>60 cm)

The following rainfall erosivity classes have been distinguished:

• <60mm/h
• 60 - 67.5mm/h
• 67.5 - 75mm/h
• >75mm/h

The following wind speed classes have been distinguished:

• <5.4,
• 5.5-10.7,
• 10.8-18.8,
• >18.9 meters/second

The following classes have been distinguished:

• high >6.0%;
• medium 2.1-6.0%;
• low 1.1-2.0%;
• very low <1.0%

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Single crop operations have been selected according to their impact on the soil and threats to the soil.

Tillage depth. The effect of plough depth on soil displacement is especially pronounced on steep slopes where the furrow slice with shallow ploughing sometimes is not completely turned but remains at an angle usually perpendicular to the soil surface, so that soil displacement is greatly reduced. Steeper convex hillslopes greatly favour reversion and breaking down of the furrow slice. When the furrow slice is reversed in the down or up slope direction (independently of tractor travel direction), soil displacement is greater because gravity acts as an additional force displacing the soil further. Of course other parameters besides slope gradient and ploughing depth could affect reversion and breaking down of furrows, such as tractor speed, soil moisture content, soil consistence, rock fragment content, etc. The mouldboard plough with the soil displaced in the up slope direction (tractor travelling up slope) may be considered as a cultivation practice reducing land degradation of hilly areas due to tillage erosion.

The following tillage depth classes have been distinguished:

• >40 cm
• 20-40 cm
• <20 cm
• 0 cm

Optional choices are as follows:

• ploughing parallel to contour lines
• ploughing downslope

Number of tillage operations. Tillage erosion resulting from tillage operations is considered to be a major degradation process in cultivated hilly areas. Tillage erosion has a great impact on the productivity of cultivated hilly areas. Redistribution of topsoil from the upper landscape positions by the various tillage operations significantly reduces the effective soil depth and the water holding capacity which is the most serious long term loss, restricting production. Under adverse climatic conditions, such as those prevailing in the Mediterranean region, production of rainfed crops has rapidly declined and farming is no longer profitable Furthermore, tillage erosion exposes subsoil, which may be highly erodible by wind or water, and filling in ephemeral blow areas, and acting as a delivery mechanism for water erosion. The various tillage implements result in different erosion rates. For example a tandem disk may be more erosive than a mouldboard plough operation because it translocates more soil with greater variability throughout the landscape. The chisel plough may be equally erosive as the mouldboard plough. Large aggressive tillage implements, operating at excessive depths and speeds are more erosive than conventional ones.

Optional choices are as follows:

• 2 tillage operations
• 3 tillage operations
• 4 tillage operations
• >4 tillage operations

Timing of first tillage operation. Timing of first tillage operation, usually ploughing, influences erosion phenomena, decreasing organic matter and soil compaction in relation to climate conditions. In summer time the tillage operations cause an obvious organic matter (oxidation) decrease while, in winter, compaction is most evident since the soil is most damp and soft.

Optional choices areas follows:

• Spring-Autumn season
• Winter-Summer season

The principal type of fertilizer. There is a distinction among mineral and organic fertilizers. From the agronomic point of view, the latter improves soil structure, making it less prone to erosion and compaction. Soil and water contamination are associated with inappropriate mineral fertilization.

Optional choices are as follows:

• Mineral fertilization
• Mixed fertilization
• Organic fertilization

Timing of the principal fertilizers. With reference to suggestions given by the Good Agricultural Practices (Rural Development Plans) it is advisable to avoid fertilization before sowing.

Optional choices are as follows:

• Fertilization pre-seeding
• Fertilization post-seeding
  

Optional choices are as follows:

• > 100 Kg
• < 100 Kg

Total number of mechanical interventions (passages). Repeated mechanical interventions, such as fertilization, weeding etc., have affects on the soil structure, worsening the situation as the number of interventions increases.

Optional choices are the following:

• 1 mechanical interventions
• 2 mechanical interventions
• 3 mechanical interventions
• > 3 mechanical interventions

Type of pest control. This is related to soil and water contamination and effects on conservation. Integrated and organic pest control reduces the risk of soil impoverishment.

Optional choices are as follows:

• Chemical pest control
• Integrated pest control
• Organic pest control

Water quality. Poor water quality leads to land deterioration, sanitation and health problems for the population, and overall environmental deterioration, thus contributing to desertification processes.

The presence of even small concentrations of salts in irrigation water leads to salt accumulation in soils unless leached away by rain or irrigation water. Evaporation from the soil surface and transpiration from the growing plants removes water but leaves salts in the soil. The salinization problem is associated with arid and semi-arid climatic conditions.

The criteria for good water quality for irrigation are: low salinity or low ratio of Na+ to Ca²+ + Mg²+ to prevent the development of sodicity; and small concentrations of those ions which may have specific toxic effects. The index used most often to characterize the quality of irrigation water with respect to its influence on the exchangeable sodium percentage is the sodium adsorption ratio (SAR) which is defined as follows:

SAR = [Na+] /{([Ca²+] + [Mg²+])/2**(1/2).

This is the ratio of the sodium ion (Na+) concentration to the square root of the average concentration of the divalent calcium (Ca²+) and magnesium (Mg²+) ions. The concentrations are expressed in mmoles per liter.

High salinity water may have a direct effect on sensitive crops. Salts may concentrate in the root zone leading to crop damage unless salts are leached away by irrigation water. Further impacts of poor quality irrigation water are expected if water has high concentrations of Na+. The major hazard is the reduction in infiltration rate due to soil structural damage.

Thresholds are as follows:

• <0.7 ,
• 0.7-3.0,
• >3.0 dS m-¹ for salinity effects

Sodicity effects are determined by electrical conductivity and sodium adsorption rate (SAR).

Optional choices are as follows:

• Drip irrigation
• Aspersion irrigation
• Other type of irrigation  

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To highlight interaction among all the variables described, a matrix has been developed where the rows contain agricultural operations and columns contains soil threats; each cell includes the physical, chemical and biological variables that control or increase the impact of agricultural practices on the main forms of soil degradation. For example, the effect of ploughing depth on soil compaction is described by soil texture, organic matter and moisture.

As shown in the figure below, the following hypotheses has been made in order to calculate the SCI value:

1.    The relationship between different soil threats is not considered. Relationshops between agricultural operations are not considered.

2.    All variables have the same weight in the SCI

Accordingly, the classes of variable have been standardized. Standardization has been used since different variables have different numbers of classes, that could compromise the final SCI value.

For example: with the variable “ploughing depth”the classes are as follows:

• > 40 cm        class (4)
• 20-40 cm      class (3)
• <20 cm         class (2)
• 0                        class (1)

A soil depth of 25 cm correspond to class 3. It is standardized by dividing it by 4, the total number of classes. In this way a numerical value is obtained for each variable.

Mathematical correlation between variables. The Geometric mean has been used as a correlation function, in order to allow an equal variable weight distribution. For example: considering the relationship betwen “ploughing depth” and “compaction” the chemical -physical and biological variables are: soil texture, organic matter content and soil moisture. Then the relationship between “ploughing depth” and each of above variables is estimated as shown below:

1- Chosen classes

Selection of the classes for each variable:

• ploughing depth = 2
• soil texture  = 3
• Organic matter content = 2
• Soil moisture = 1

2 - Standardization

• ploughing depth  = 2/4 => 0,5
• soil texture = 3/4 => 0,75
• Organic matter content = 2/4 => 0,5
• Soil moisture = 1/6 = 0,17

3 - Geometric mean

After standardization of values, the geometric mean is calculated to quantify the interaction between the agricultural operation and each of the chemical, physical and biological variables involved (giving value X, Y, Z)

[(ploughing depth  * Soil texture)^1/2]                     [X]
[(ploughing depth * O.M)^1/2]                                 [Y]
[(ploughing depth * Soil Moisture)^1/2]                    [Z]

4 - Correlation between single interactions

making the same operation between single interaction values (X, Y, Z)

(X*Y*Z)^1/3

This procedure allows us to obtain a numerical value (between 0 and 1) for each cell, which summarises and quantifies the interactions between all involved variables.

At this stage, values obtained in the single cells are summed by row and by column as in the example shown below:

The result of the example row is:

A+B+C

In this way there is a single value summarizing the interaction between “ploughing depth” and single degradation forms.

In the same manner the sum by columns is obtained as follows:

To obtain the final SCI value, the values must be summed either by rows or by columns. The system, in fact, is developed to obtain the same value both summing rows or columns. This procedure allows us to underline both the importance of single agricultural operations or each threat in defining the degradation phenomenon.

Example: matrix

In this example the SCI has a value of 30. The SCI absolute value is, then, standardized to obtain values ranging from 0 to 1.

This value by itself cannot qualify soil conservation dynamics. It must be referred to a scale where a minimum and maximum threshold must be assigned (calculated).

Specifically the tool calculates the best and worst value for the given context. The absolute best value is obtained when all the parameters are expressed at their best conditions and viceversa for the worst. The relative maximum and minimum values are estimated when the best or worst agricultural techniques are used in that specific context. At this point it is possible to judge the value obtained scaled to these benchmarks.

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3. Gross Margin Analysis and Agricultural Practices (GMA)

3.1 Introduction

Most farmers, including those involved in sustainable agriculture, carry out a number of different enterprises (e.g. different crops and livestock) with a wide range of technologies (agricultural techniques) and often need to address one of the following questions.

• How would the returns over variable costs of my enterprises be affected by changing production practices having different effects on soil conservation /soil degradation?
• How would the returns over variable costs of an enterprise change, if the product price and/or subsidies structure and/or input costs changed?

Gross margin analysis (GMA) provides a convenient and simple way to summarize information required to address such questions and, as a result, can provide a useful tool in planning changes, also with respect to soil threats.

Gross margin is the difference between gross income and variable costs (see definitions in next section). It is convenient, because it provides a measure of returns over variable costs and is a step in the direction of measuring profit. It is simple, because it does not consider fixed costs, which can often be difficult to allocate to individual enterprises.

Users of GMA need to be aware that the simplification gained by not considering fixed costs gives rise to some limitations. Profit is often defined as returns over total costs. Therefore, one must account for both fixed and variable costs when measuring the profit of farm enterprises, even though this latter term is useless with family farms (the most common type of farm all around the world).

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3.2 Definitions

Enterprise: The production of a commodity or a group of related commodities (e.g., wheat, alfalfa, cattle).

Technology: A specific way of producing a commodity. Sometimes this is called an activity. Examples include performing or custom hiring machinery operations for wheat production, season-long grazing or management-intensive grazing of cattle, growing irrigated or dryland crops, ploughing or not ploughing (sod seeding) before sowing cereals, etc.  The distinction is important because in farm planning, farmers have to decide what to produce (i.e., enterprises) and how to produce (i.e., technology), and both decisions could affect soil conservation with equal weight.

Variable Costs: Costs that vary according to the level of production (e.g., more wheat leads to higher fertilizer costs). Variable costs are the costs of inputs, such as seed or fertilizer, that are normally used up in a short-run production period. In many cases, variable costs are associated with specific enterprises and thus are sometimes called direct costs.

Fixed Costs: Costs that have to be paid whether or not production takes place (e.g., interest payments on land). Fixed costs are the costs of inputs that are normally not used up in a short-run production period. Therefore, they are sometimes called overhead costs or common costs, because in many cases, they cannot be allocated easily to a specific enterprise. This means that expenses that do not change, no matter what enterprise(s) you implement or at what level, are fixed costs.

Gross Income: Value of production of the enterprise. It takes into account not only what is sold but also an estimated value of what as been produced but not sold during the period under consideration. The latter is in essence income, although this is not realized in cash terms until all the product is sold. Sometimes the combination of sold and unsold products is called gross product. Gross income also may be called gross revenue or gross receipts.

Gross Margin: The gross income minus the variable costs associated with an enterprise/activity. This has sometimes erroneously been referred to as gross profit.

Net Income: For an enterprise, net income is calculated by subtracting the fixed costs of the enterprise from the gross margin. Net income for a whole farm or agribusiness is calculated by adding together the gross margins of all the enterprises and subtracting the total fixed costs of the farm or agribusiness.

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3.3 Calculation of the Gross Margin

In calculating the gross margins of an enterprise, the following decisions are made.

• Time period used for calculating the gross margin: one production cycle. This varies for different enterprises but often is one year. For example, cereal and legume crops differ somewhat in the length of their production cycles. But for most enterprises in Italy (and the EU), a year is a convenient period to use.
• Standard unit: one hectare. This becomes particularly important when two enterprises are being compared. All the results are reduced to that standard unit for comparison. Gross margins are typically expressed in Euro per unit of some input. (e.g. hectare, hour of labour, or Euro of variable costs).

The steps for calculating the Gross Margin for any enterprise (used by the ManPrAs algorithm) are as follows:

1. Record the estimated value of production for the enterprise, which involves the gathering of the following information:

• Number of units (tons, head, etc.) produced.
• Number of units sold and price per unit received.
• Number of units still in stock and the estimated value per unit (i.e. what price it could get if it is sold).

The total gross income is obtained by summing all the production values.

2. Record the production costs:

• Itemize the different variable inputs used directly in the enterprise and for each input, recording the number of units used, the cost/unit, and the variable cost for each input.

The total variable costs is obtained by summing the variable costs associated with each input.

3. The Gross Margin for the enterprise by subtracting the total variable costs from the total gross income.

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Agri target area

With the purpose of assessing the functionality of ManPrAs in the Agri Basin, we conducted a first validation of the tool in some of our sample farms. ManPrAs has been used to calculate the SCI index related to different agricultural techniques in similar environmental contexts, to both verify the impact of the management variables on the index value and to compare similar agricultural techniques in different physical contexts. The validation has been made at a qualitative level, comparing the results both with the farmers judgement and by direct field observations. All the results obtained are in line with the ManPrAs conclusions both in terms of soil conservation and economic results. A second assessment of of ManPrAs was made during the DESERTLINKS workshop, held in Basilicata 21- 22th  March 2005, where DIS4Me and all its tools were presented and discussed. The involved stakeholders (farmers, extension services, researchers, representatives of the regional administration) used the tools during the workshop.

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