The SFS methodology of agricultural energy balances

In order to set the basis of a consistent methodology, we need to define the limits of the system we want to analyse and its components (section 3.1), the calculation methodology (section 3.2) and the efficiency indicators we propose (section 3.3). In the following sections, the elements that characterize the energy balances of farm systems are outlined according to the novel approach developed by the international group SFS and published in Tello et al. (2015).

3.1 Agrarian systems analysed from a social metabolism standpoint 3.1.1 Adopting a metabolic view of agroecosystems as a starting point

In their interaction with nature, and from a social metabolism point of view, farmers modify ecosystems and turn them into what we call agroecosystems. These are, therefore, ecosystems modified by the intervention of human labour with the aim to obtain products that are useful for society. At the same time, however, agroecosystems have to maintain the ecological processes so that farmers and society can take advantage of the photosynthetic fixation capacity of plants, as well as of a large array of other natural processes that have been grouped into what we call ecosystem services (Brookfield and Stocking, 1999; Gliessmann, 1998; Millenium Ecosystem Assessment, 2005).

Approaching agroecosystems from the social metabolism, i.e. from an Ecological Economics viewpoint, means to account for the various flows that occur within and beyond its limits and affect the agricultural activity. It is about quantifying those flows that circulate among the different fund elements of the farm system according to the relationship established between those who manage the agroecosystem (the Farming Community) and the different compartments thereof. Thus, we propose a basic model that identifies the various components of the agroecosystem which are self-reproducing funds, grouped into the functions they perform, in a way that allows establishing the main flows circulating among them (Figure 2.2). These funds are those ‘elements that are part of a process, which provide services for a certain period but are never physically incorporated in the product’, as defined by Georgescu-Roegen (1971). Specifically, those of biological basis which are alive (despite being organisms or living systems) are self-reproducing funds whose maintenance requires reinvesting regularly to them a certain amount of resources of the agroecosystem (Giampietro et al., 2013).

The model proposed by the SFS research project identifies five of these fund elements:

the society, the farming community, the livestock, the farmland and the farm-associated biodiversity. On the one hand, we differentiate between society and the farming community that manage directly the agroecosystem, because this allows us to identify the flows that are established between them (and, as we will see below, quantify in this way what is called the Podolinsky principle). On the other hand, the differences between the fund elements that remain within the limits of the agroecosystem are characterized by the way in which farmers’ labour takes place. While livestock or farmland are actively maintained through the flows supplied through farmers, the farm-associated biodiversity, as we will see, is partly maintained with that share of biomass produced in the agroecosystem that is not appropriated by humans.

Along the thesis, we will approach for what we call the material conditions for farm-associated biodiversity. The proposal will remain as a hypothesis, because we do not deal with empirical databases for confirming or rejecting it. But here is important to make some brief explanation on what we deem this fund is. We consider farm-associated biodiversity as all those species that are not directly planned by farmers but take part of agrarian systems, to which at to

Chapter 2. Foundations and methodological developments on Energy Balances

some extent contributes to farming activities through the ecosystem services they provide (Altieri, 1999; Tello et al., 2015). Many recent researches have pointed that a lot of species of very different taxa, could be enhanced by combining certain degrees of land cover spatial heterogeneity and appropriate levels of human disturbance, always regarding many different aspects of the landscape patterns (Bengtsson et al., 2003; Harper et al., 2005; Loreau et al., 2003; Tscharntke et al., 2012). No doubt, this farm-associated biodiversity cannot include the whole biodiversity of a given territory, because some rare highly-specialist species are unable to withstand recurring disturbances. In other chapters we will deal with the different strategies that exists for dealing with biodiversity maintenance in agroecosystems. However, it is important to keep in mind to which kind of biota are we referring when approaching this farm-associated biodiversity.

A fundamental modelling issue is where we set the limits of the agroecosystem. This decision will be key to calculating efficiency indicators, as it places the boundaries where entries and exits are observed in the system. Here we adopt what we call an agroecosystem boundary in such a way that the Farming Community and the Society are virtually separated from the other fund elements. Thus, we will consider an input all that is provided by these two funds (ASI, L and FCI, explained later), whereas we will account as output all what is received from them (FP).

3.1.2 The flows circulating in an agroecosystem

Since it is a dynamic and alive system, we also need to set a time scale in which we calculate the flows in the energy balance. Given the conditions set both by the available sources of information, and by the seasonal logic of operation of a farm system, we will take by definition an annual schedule.

As we said, the main contribution of energy flowing in an agroecosystem derives from the ability of photosynthetic fixation of plants that allows the production of biomass in the different land covers of farmland. In this methodological approach we consider the contribution of solar energy (SR) as a ‘gift of nature’, not as a cost. Once the photosynthetic process of the

Figure 2.2. Agroecosystem’s fund-flow model and boundaries. Source: Our own (Tello et al., 2015)

Chapter 2. Foundations and methodological developments on Energy Balances

autotrophic organisms (mainly plants) is fixed, this energy circulates within the agroecosystem or outside of it.

Next, the phytomass produced over a year fulfils multiple functions and can take different directions. A part can be used to feed livestock of the farm system, or to maintain soil fertility (Biomass Reused, BR). Another, may be available for non-domesticated species (Unharvested Biomass, UB), which is a fundamental flow in order to guarantee certain ecosystem services such as pollination, pest control, or other regulating, supporting and cultural services. Finally, another important part is the one that actually leaves the limits of the agroecosystem considered to go towards the Farming Community and the rest of Society (Final Produce, FP).

Inside what we consider the Total Produce of the system (TP) there is something more than what has been photosynthetically produced and is intended to be BR or FP (the Land Produce, LP). There is also the production coming from the livestock hut (Livestock Final Produce, LFP). As we shall see later in section 4.2, a part of this LP may end up losing much of its functions within the agroecosystem, when it becomes Farmland Waste (FW).

All of these are not the only flows that circulate within the agroecosystem. The Livestock fund can also return flows to the Farmland in the form of draught power and manure (Livestock Services, LS). Yet, depending on how they are managed, they can also become Livestock Waste (LW).

Regarding the Farming Community, which modifies the ecosystem to turn it into an agroecosystem, Labour (L) is always a basic flow that becomes the minimum condition for dealing with a farm system. Farmers can also provide other flows, such as domestic residues and, in some historical periods, human excreta (humanure), which we include in Farmland Community Inputs (FCI).

It was not until the so-called Green Revolution that other flows coming from the rest of the compartments of society would experience a skyrocketing increase, such as synthetic fertilizers and machinery together with the fossil fuels embodied in their production and delivery.

These are grouped into the category of Agroecosystem Societal Inflows (ASI).

All the inputs that come from outside the agroecosystem (ASI, L and FCI) are called External Inputs (EI). Then the sum of EI and BR will be all the energy costs spent in agricultural production, either internal or external, and account for the Total Inputs Consumed (TIC) by farmers. A relevant element of this model is that it calculates not only the contributions made by external inputs to the agroecosystem, but also that part of biomass products harvested that remain on it and are intended to guarantee its production over time. This involves adopting an agroecological perspective through which we show how BR cycles are indeed a cost to the farm system as such. BR could be a flow extracted from the agroecosystem, but farmers decide to reinvest it so as to ensure the agroecosystem’s reproduction.

3.2 Accounting method of energy flows

Once we defined the structure of funds and flows considered within the agroecosystem, another fundamental element we need to have a consistent methodology is to specify how we are going to account these flows.

Given that the aim is to obtain indicators of energy efficiency of agricultural activity, all biophysical flows have to be accounted in comparable units. From this standpoint we interpret these flows not as simple circulation of mass, but as energy carriers. Thus, we have to quantify them by their own energy content and taking into account as well all the energy that has been spent to reach their destination site in the agroecosystem, under the desired conditions. The main

Chapter 2. Foundations and methodological developments on Energy Balances

problem for doing this calculation is that there is no scientific consensus as to how to perform this energy valuation of flows (Brown and Herendeen, 1996). When all the TICs spent in an agricultural production are added, we have to bear in mind that biophysical flows with very different qualities and levels of energy are being merged. In fact, is not the same a flow of straw that can be buried into the soil as a flow of diesel used to fuel a tractor or other mechanical machinery. These are sources of energy of very different qualities. How can we resolve this reduction of different energy qualities into homogenous energy quantities? There are two methodological ways to address this accounting problem.

The first approach was proposed by Howard T. Odum (1984 and 2007) through emergy analysis. In his studies, Odum defined emergy as ‘an expression of all the energy used in the work processes that generates a product or service in units of one type of energy’. The solar emergy of a product is the solar energy equivalent required to generate it. Thus, we can calculate each flow as all the amount of solar energy that has been required in order to be able to find it in the conditions of arrival and functioning within the agroecosystem considered.

The second approach is the energy analysis, in which the accounted element is enthalpy.

This thermodynamic concept defines the amount of stored energy that can be converted into heat under standard conditions. Besides counting the amount of energy that a flow contains, it can also account for what is called embodied energy. In a similar way to the emergy analysis, this embodied energy adds all the energy that has been consumed, in the form of enthalpy, so that this flow reaches the agroecosystem considered. For example, synthetic fertilizers have zero enthalpy value, but in order to have them into this agroecosystem a relevant amount of energy has been spent on extracting ores, producing the fertilizer, packaging and transporting them to the point of use. The embodied energy can be accounted by the sum of the enthalpy of each of the energy carriers spent throughout these production and delivery chains.

When both approaches are compared, it is obvious that emergy analysis provides a more consistent and linear accounting way to differentiate between the different qualities of energy flows and products. However the emergy accounting also entails a major difficulty. When a process of energy conversion results in two or more products (e.g. grain and straw), the emergy methodology allocates the whole solar emergy added to both, considering that there cannot be one without the other, and both need all the previous emergy chain to be created. Then, in order to avoid double counting, emergy analysis has to select either one or another, leaving the other apart, so as to follow the emergy chain to the end. This is called the principle of ‘nonadditivity of by-product flows’ set forth by Odum (1984), and creates unsurmountable problems when dealing with systems that have feedback loops. This is the case of BR, which is an agricultural product that becomes also a necessary element for the production of FP. Yet, according to the above principle, we cannot account BR loops as costs in emergy analysis despite their vital role to keep the agroecosystem reproduction.

In the energy analysis, instead, we usually account for metabolic energies and we do not include primary energy sources. Hence, this is why we consider solar energy as a ‘gift of nature’.

This allows taking into account how the internal energy loops, which are so intrinsic to agroecosystems, can circulate and enable the farming community to get what we call an energy surplus on which they sustain the whole society. This means accounting for the Podolinsky principle, throughout the metabolic chains that turn solar energy into biomass flows up to the forms required to meet human needs (Podolinsky, 1880).

Therefore, we took the decision to use energy analysis by means of accounting enthalpy values and embodied energy flows, in order to bring to light those internal flows and loops that circulate within agroecosystems and link their fund elements. Only in this way we can find out and analyse the circular complexity of the energy processes taking place in farm systems (Ho and Ulanowicz, 2005), as a first step towards new developments of a research approach of strong sustainability science that always seeks to become more systemic, holistic and dynamic.

Chapter 2. Foundations and methodological developments on Energy Balances

However, this is not an easy task nor free from criticism (Brown and Herendeen, 1996;

Giampietro et al., 2008). It is obvious by using the same enthalpy values accounted along industrial production chains and contained by the agroecosystem biophysical flows, we do not solve the qualitative differences between different energy carriers. The inevitable reductionism of our energy efficiency indicators is something that always must be kept in mind, and pointed out in a transparent manner.

To conclude, we will account those flows that emanate from the agroecosystem for only enthalpy values, while we will calculate those that come from outside with their enthalpy value plus the entire enthalpy consumed in the production process and transport to this agroecosystem.

3.3 Energy efficiency indicators: A multi-EROI approach

One last aspect of the methodological development carried out by the SFS team on energy analysis of farm systems is that of the efficiency indicators that we can calculate from this model.

Let us take Energy Return On Investment (EROI) as a starting point, as explained in section 2.2.

In the light of the various flows and circular relationships set among different fund elements of agroecosystems, we consider that based on them we can establish different indicators in order to highlight the multidimensionality of the energy costs carried out by farmers to produce biomass useful for society. Therefore, instead of seeking a reductionist simplification with a single efficiency indicator intended to explain everything, we have adopted a multi-EROI approach by using a set of interrelated EROI indicators that may allow a deeper understanding of the different sides of an agroecosystem functioning.

Here we are interested in presenting three of them²: Final EROI (FEROI), External Final EROI (EFEROI) and Internal Final EROI (IFEROI).

The first of these, the Final EROI (FEROI), takes into account the amount of useful biomass produced by farmers (FP) in relation to all costs, internal and external, required to do so (TIC)—as seen in equation 1:

= = (Eq.1)

As we explained, TICs includes all those external flows that enter the agroecosystem coming from Society and the Farming Community (EI), together with all those internal reinvestment flows coming from the farmland harvest (BR). Therefore, we can decompose this initial FEROI into two different indicators shown in equations 2 and 3, which are the external cost to the agroecosystem biomass production (EFEROI), and the corresponding internal cost (IFEROI). While the first one is closer to the calculations usually made when accounting for conventional energy efficiency so far (without considering the internal costs), the second one is also interesting in order to bring to light the internal effort made by the Farming Community of reinvesting a part of the biomass harvested in order to maintain the agroecosystem functioning.

= (Eq.2)

= (Eq.3)

2 Although in this thesis, as will be seen, some others will be used such as the Agroecological-EROI, Actual Net Primary Productivity-EROI or the Final Energy Return on Labour (Galán et al., 2016; Guzmán and González de Molina, 2015;

Tello et al., 2015).

Chapter 2. Foundations and methodological developments on Energy Balances