What is intensification?
What is Sustainable Intensification?
Domains of Sustainable Intensification
The need for Sustainable Intensification
UK indicators of GHG emissions
Contribution of the agricultural sector to GHG emission
Impact of GHG on crop farms
Impact of GHG on livestock
Case against Sustainable Intensification
Studies on sustainable intensification
Intensification can be defined as the production of more output units per input units and through any possible combination of inputs and innovation. Agricultural intensification can also be explained as maintaining a certain level of agricultural output while decreasing the use of inputs (FAO 2004).
Intensification is all about improving the relation between the inputs and outputs and increasing production through an efficient usage of physical inputs such as land, labour, machinery, capital and fertilizer and pesticide use. Intensification which results in the increase in the production of the food is of detrimental value as it is critical to increase the food supply with the rapidly growing population.
The results of intensification are given in outputs which can be measures in terms production, income or nutrition.
When we measure intensification in terms of production, we are looking at the increase in the yield of food per unit input. Intensification can also be measured in terms of net income generated per unit of input. The third way is through the human consumption of nutrients per unit of input.
Most of the literature focus on agricultural intensity though either the increase in production or through the increase in income.
The inputs for an agricultural process could be either direct or indirect. Direct inputs used in a farm are mainly labour, water, fertilizers and animal feed whereas the indirect inputs used to facilitate the farm are capital, technology, infrastructure and knowhow of the workings of a farm. Greater intensification is achievable though the increase in use of inputs, by including or a new input or by using the existing inputs in new ways.
(van Apeldoorn et al. 2013)
Van used the increase of milk production as a sign of intensification of production in Dutch dairy farms. They hypothesized that the agricultural intensification is heavily dependent on the landscape of the area.
Centuries ago, before the industrial revolution, agriculture was based on the household units, where individuals used to grow a crop or keep livestock for their personal consumption. So, the production, the processing, and the consumption were all done by a single unit. With the advancement of technology and improvement of farming techniques over time, there was a farming surplus where the individual’s units were producing more than they could consume. With the surplus of food, the reluctant farmers could purchase the food from the markets and were able to do something else for a living.
With the advancement in technology, the fertilizers and pesticides used became more potent, yielding a high output. Moreover, selective breeding improved the quality as well as the quantity of meat. Hence through the ‘green revolution’, the world saw an increase in food production which was more than that of the population growth. (Bos et al. 2013)
The recent farming practices, such as intensive agriculture has become a threat to the traditional farming practices and the traditional landscape which had evolved for centuries. With the advancement in technology, the traditional landscapes have become rare and have been turned into modern landscape which lacks personality (Antrop 1997).
The change in landscape has not only been attributed to the advancement in technology. Other forces that derive the change in landscape is accessibility, urbanization, globalization and calamity (Antrop 2005). The areas which are not easily accessible have more of a natural landscape as people have difficulty getting there. As soon as the infrastructure is built for transportation, a change in landscape can be seen immediately. Urbanization and globalization are driving forces of economic growth.
The intensification of the production system is very important but it also needs to be sustainable so that these processes can fulfil the current demand and still are able to provide for the future generations. The term sustainable intensification has been around for a couple of decades and was mostly used in the context of African agriculture where the output is low and environmental degradation is high. Sustainable intensification simply is increasing productivity while reducing the harm to the environment. It is an aspiration of what needs to be achieved. Sustainable Intensification is still a fairly recent concept so it is hard to say what it might look like or how it would be different from the production systems currently in play. However, it should be mentioned here that the framework that sustainable intensification provide, needs to be specifically tailored for the respective area or industry. Sustainable intensification cannot be achieved globally by applying the same framework to every area.
The Montpellier panel report (2013) explained Sustainable Intensification as:
“Sustainable Intensification offers a practical pathway towards the goal of producing more food with less impact on the environment, intensifying food production while ensuring the natural resource base on which agriculture depends is sustained, and indeed improved, for future generations.”
The World Commission on Environment and Development (WCED) defined sustainable development as
“Development, which meets the needs of the present without compromising the ability of future generations to meet their own needs”. (WCED 1987)
Although consensus has not been made on the accurate definition and description of sustainable intensification, all researchers agree that sustainable production systems should show certain attributes:
- A sustainable production system should avoid an unnecessary use of inputs
- A sustainable production system should minimize the extra use of technology which harms human and animal health and the environment.
- The production should minimize externalities such as GHG, biodiversity and clean water.
The agricultural systems who possess these attributes are diverse systems which not only focus on the increase in production of food source but also work towards contributing to social welfare. Organic farms do have some of the qualities needed for a sustainable agricultural practice. These farms have low yield per area so that they can reduce the use of land. (Pretty and Bharucha 2014). They reuse and recycle the farming inputs and outputs and their reliance on synthetic fertilizers and pesticides is minimal. Organic farms aim to maintain the fertility of the soil and biodiversity in the farm. These farms may be able to be classified under sustainable farms but they cannot be intensive farms as their output is pretty low. With the improvement in management systems and changes to the factors of production, these farms may be able to achieve the stamp of being intensively sustainable.
According to the literature, the indicators of sustainability intensification can be categorized into five key domains(Smith et al. 2017)
The productivity domain captures the productivity of crop and the livestock output. This domain includes indicators such as yield, fodder production, yield gap and yield variety. The indicators for productivity make it clear that the most important input in increasing productivity is land. An increase in productivity is one of the goals of SI. The second domain is of economics which looks the profitability, costs and the return to the factor of production. In many kinds of literature, the domain of productivity and economic indicators are one and the same however for our analysis, I would be separating them both. Here, the productivity domain is specifically dealing with the increase in productivity form only land as an input whereas the economic domain includes the remaining inputs like labour and capital. Economic domain deals mostly with the profitability of the agricultural system where the farmers’ decision to grow crop and allocation of resources strictly depends on the demand of produced commodity in the market.
The third domain is environmental in which focus is given to the plant diversity, nutrient balance, GHG emissions and soil and water quality. The environmental domain is one of the key pillars of SI where the focus is not only on the improvement in output but also on protecting the environment. The fourth domain examines the individual. It focuses on the human conditions and their accessibility to proper nutrition, health and education. The last domain is the social aspect which looks at gender equality, social coercion and collective action.
To monitor the progress of sustainable development (thereafter referred to as SD), it is first important to identify the indicators which will measure the environment, economic and income variables. Even the United Nations emphasised on the development and identification of these indicators in a conference on environment and development and urged the government and non-government organizations to” develop and identify indicators of sustainable development in order to improve the information basis for decision-making at all levels”(UNCED 1992).
The initial program on the indicators of sustainable development came forward with the list of 134 indicators which was later shortened and divided into 14 sections: poverty, governance, health, education, demographics. Natural hazards, atmosphere, land, ocean, seas and costs, biodiversity, economic development, global economic partnership and consumption and production patterns.
Health care delivery
Health status and risk
|Natural Hazard||Vulnerability to natural hazards
Disaster preparedness and response
Ozone layer depletion
|Land||Land use and status
|Oceans, seas and coasts||Costal zone
|Economic development||Macroeconomic performance
Sustainable public finance
Information and communication technologies
|Global economic partnership||Trade
|Consumption and production patterns||Material consumption
Waste generation and management
The main driver of the agriculture process is the use of land and according to the report by FAO, we have seen only 11% increase in agricultural land from 1961 to 2007. Same time period, the world’s population has grown 123%. Furthermore, the agricultural area in industrialized country has decreased and as the cities grow with the growing population, less emphasis is placed in maintaining agricultural land. This is placed a heavy burden on the agricultural system who need to drastically improve their productivity to cater to the growing masses.
There are certain constraints on the production of food which vary from region to region. However, there are certain factors which contribute to the reduced limit of food production. Climate change is a result of burning fossil fuels which impact earth’s temperature, precipitation and the quality of soil. It also results in an increase in CO2
levels. Changes to the temperature and water highly impacts agriculture. An increase in temperature and changes in the patterns of precipitation affect the growth of crops. A higher CO2 level also affects the yield and the quality of the crop. A rise in temperature and lack of precipitation leads to drought and causes the soil to become dry. This, in turn, prevents the farmers to produce optimal yield. In some places, it is possible that this problem can be managed by an increase in irrigation, but this cannot be said for regions that lack in capital and resources. Even though less than 20% of the world’s croppable area is irrigated, it produces about 50% of the world’s food (Döll and Siebert 2002). The irrigation systems are quite beneficial to the crop production, they also cause a threat to the general environment. An increase irrigation system lead to a reduction in river flows which degrades the environment and causes the acceleration of desertification (Ma et al. 2003).
Warmer temperature and wetter climates also lead to an increase in pest, fungi and weed which thrive under these conditions and disease the crops. Changes in the pattern of temperature and precipitation also leads to degradation of the quality of soil. Soil is a non-renewable resource which is fundamental for the crop production. A loss in the nutrients provided by the soil would lead to a decrease in the yield. It should be mentioned here that climate change is not the only factor for soil degradation. With the increase in industrialization, the waste material from production has also increased. It is costly to manage waste so many of them dump their waste into the water bodies close by or dump it directly onto the land. These pollutants from the factories seep into the soil and pollute it. Regulations have made to stop these practices so that the environment can be protected but it is extremely difficult to implement these rules especially in the developing countries (Solazzo et al. 2016).
Burning of fossil fuel is not the reason for the change in climate. Agriculture is also a contributing factor to climate change. The agricultural processes produce GHG which also cause the climate to change. In 2013, agriculture contributed to a total of 10% of
emissions, 54% of
and 79% of
emissions in the EU area (EEA 2015).
The UK government have created a framework to reduce GHG emissions. There are 10 key indicators which assess the GHG emissions outcome. The indicators range from the attitude of the farmers to the nitrogen balance in the soil (DEFRA 2017). The indicators are also sector specific so that the GHG emissions from different agricultural process can be mapped accurately.
The first indicator is of attitude and knowledge of the farmer. It is difficult to measure the attitude and awareness of the farmer as the data available is limited and this indicator would assess change in the long term. Studies suggest that the farmer’s understanding of the sustainability practices help to reduce GHG emissions as he is much more likely to make decisions which would positively affect the environment. The actions of farmer include him improving the efficiency of energy by reducing the usage of fuel or by producing energy on the farm. The farmer can also recycle waste from livestock to be used a fertilizer.
Another indicator is of the uptake of mitigation methods. This indicator measures the change in farm practice adopted to reduce the GHG emissions and to achieve a sustainable agricultural production. Soil nitrogen balance is another very important indicator. It measures the value of the nitrogen content in the soil. Nitrogen balance in the soil is essential to the growth of crops. Little amount of nutrients in the soil would limit the growth of the crops and excessive nutrients in the soil causes a serious environmental harm. So it is important to have balance nitrogen in the soil. This indicator measures the nitrogen surplus and aims to minimize it.
The above three indicators are general indicators which are applicable to all type of agricultural systems. The remaining indicators are specific to their sector. The indicator for the pig sector is feed conversion ratio for finishing herd. This ratio measures the amount of feed required to produce 1 kilogram of pig’s live weight. The indicator for beef and sheep farms is the grazing livestock sector which measures the estimating breeding value (EBV). EBV is the measure of genetic merit an animal possess for a given trait. This indicator is a proxy measure of GHG emissions by measuring the percentage of the farms that are using livestock that has high EBV.
The GHG emission indicator for the dairy sector is the ratio of the dairy cow feed production to milk production. This indicator uses the ratio as a proxy to the GHG emissions and looks towards the decrease in the ratio as the decrease in the usage of feed suggesting an improvement in the emissions though milk intensity.
The indicator for poultry sector is the feed conversion ratio for table birds. The feed conversion ratio (FCR) is measure of the amount of feed required to produce 1 kilogram of poultry meat. The rationale behind it is that the efficient use of feed might potentially help in the reduction of GHG emissions.
There are also certain indicators which are applicable to the crop farms. One such indicator for the cereal and other crops is of the application of manufactured fertilizer. The fertilizer application indicator is measured by taking the ratio of the weight of the crop produced to the weight of the fertilizer applied. This is also a proxy to the GHG emissions intensity as the efficient use of fertilizer would potentially help to reduce the nitrogen input. Another important indicator is application of the organic fertilizer as many studies show that the timing and the method of the application of the fertilizer has a positive effect on the reduction of GHG emissions. The last indicator is for management of manure and slurry as it affects both air and water. This indicator deals with the mitigation methods relating to the storage and handling of slurry and manure.
The livestock sector contributes heavily to the GHG emissions. The main gases produced by livestock farming are carbon dioxide
and nitrous oxide
. European studies suggest that the production of meat and dairy products accounts to almost half of the GHG production.
The impacts of the GHG emissions are serious and they need to be reduced but it does not mean that we do not consume dairy or meat products. Some might argue that that focus should be placed on exploring alternate sources of food. However, one can argue that to find alternative source of food would be costly, and not just in terms of money but also in terms of time and energy. Furthermore, GHG are still going to be emitted when producing any kind of food and especially when the agricultural process has not been refined through years of application.
Although livestock farming does contribute heavily to the GHG production, we cannot stop producing livestock. A better option is to examine the inputs and use them in such a way that they produce less GHG. We can take a closer look at the important inputs in livestock farming. The main inputs can be categorized under the energy used, feed and the land for grazing. The energy input is the use of fuel in farming. The use of fuel leads to the emissions of carbon dioxide. Although the use of energy is less in the livestock farming as compared to the crop farming, it still remains an important input. The energy is sued to fuel the machinery, for heating and lighting and other processes.
Another important input is the feed used on the farm as a food source for animals. The production of feed
Sustainable intensification is only for one specific type of agriculture
Sustainable intensification is going to be overshowed by a need to increase the production of the food
In the term sustainable intensification, much more weight is going to be given the term intensification as compared to the equal weight being given to the sustainable side. (Garnett and Godfray 2012)
Case against intensification :
HOW TO MEASURE SUSTAINABLITY
NITROGEN USE? (Bos et al. 2013)
Clay, Reardon and Kangasniemi (Clay et al. 1998)studied the sustainable intensification in Rwanda where the traditional system of agriculture had become ineffective due to a substantial increase in the population. Their motivation for studying the agricultural system in Rwanda was that the farming there was mainly located on the slopes of the hill where the soil erosion as well as the loss of soil fertility was extremely high. Half of the productivity was lost due to land degradation. The authors took two paths to explore the intensification in Rwanda. The first path was ‘capital led intensification’ where the increase in investment and capital could possibly lead to better productivity and the second path was of ‘labour – led intensification’ where the farms were able to speed up the production process through more help. These two pathways have previously been described in Boserup (2005).
Their analysis included four regression equations in which the dependent variables were land conservation investment, non-labour inputs such as organic and chemical inputs as well as the land use erosivity. The land use erosivity is measured through a C value which when falls, indicates a fall in land erosion. All the depended variables were a function of five independent variables, financial and psychical incentive, risk, wealth and agro-socio-economic context.
The financial incentive to invest depended on the returns form agriculture or non-agriculture activities as well as the crop prices and transaction costs. The physical incentive to invest was effected by the size of the farm, the location of the farm, its age and the annual rainfall. The risk of investment entailed the price risk and the plot use right. The plot use right was measure as binary variable where the value of 0 was given to the farmers who owned the land and 1 to the ones who rented. The wealth was depended on the cash, livestock and land holding as well as the human capital.
The data examined for the study was of 1240 farm households who were interviewed by Agricultural Statistics Division in 1991. They used Random Effect, Generalized Least Square (GLS) regression to estimate the dependent variables possibly due to the presence of autocorrelation or heteroscedasticity. Their results showed that in the case of land conservation investments, plot size and characteristic had an important role to play in the investment decision. The farmers would be more likely to make an investment in the farm its location is desirable, close to their residence and is owned by them. Furthermore the motivation of investment also depended on the slope of the farm. If the farm was situated where the slope is of medium steepness, they invested more as it would be less costly and it would less likely suffer from erosion which could, in future, lead to low yield and productivity. They also showed that the steepness of the slope also effected the decision of the farmers to use organic or chemical inputs. The farms which were situated on the steeper slope were less likely to receive the inputs. Furthermore old farms received less inputs due the loss of effectiveness of inputs because of soil erosion. The farms which were rented were less likely to receive organic or chemical input.
There was also a positive relationship between non-cropping income and the land conservation investment as well as with the use of organic inputs. If the non-cropping income was present, it provided liquidity for further investment in the farm. They also found that the small farms were more likely to invest in conservation and organic inputs because it was vital for their livelihood as opposed to large farmers. It was also found that the farmers who had more knowledge about the sustainable production practices were more likely to use organic inputs.
They concluded that the structure of land holding was important to the Rwandan farmers. The incentive to invest in intensification was widely effected by the land tenure, slope, years of cultivation and the size of the holdings. Secondly, the non-farm income also provided the household’s liquidity to invest especially where there were under developed credit markets. Furthermore the non-farm income provided the farmers a breathing space to make long term investments towards sustainable intensification. Thirdly the infrastructure played an important role in sustainable intensification. Investment in infrastructure, especially in roads would result in an increase in marketing, reduction in waste and would encourage farmers to adopt sustainable production practices.
Barnes and Poole (2012) analysed the data form 500 Scottish beef farms from 2000 to 2010. The data for the 11-year period looked at the inputs and outputs of a farm. They produced a balanced panel of 42 farms and the data includes the area for rough grazing, their farm incomes, the number of animals as well as the age of farmer and the hours worked by the farmer. The average size was of 88 cows and the mean age of ferment was 57.8 years. The income analysis of the beef farm suggested that the total profit of the business increased though the years which was mainly due to the increase in the value of the beef. They measured SI by looking at four dimensions, economic, social, ecosystem and ethical.
They started off their analysis with the measurement of intensification by taking the ratio of output to an input. Although the average stocking density fell in the ten-year period, it was found that this decrease was not significant which pointed towards having no trend in intensification. They justified this by explaining that the policies adopted by the beef sector did not promote the improvement of the intensification.
To measure the financial changes, they examined variables such as total debt, the subsidies provided,
They then used a criteria to assess the “generation of ecological habitats”. Other indicators used were the ratio of permanent to temporary grassland, output growth relative to input growth.
Jayne et al. (2004) used panel data from Kenya studied the promotion of crop intensification in light of credit, input and output marketing arrangements. Small farmers are unable to purchase the inputs which can enhance the productivity because of capital constraint. As mentioned before in the underdeveloped economies, like those in Africa, the credit markets are not well developed. According to Dorward et al. (1998) it is possible that with the right market structure, the cash crops (crops cultivated just for profit) might provide a durable relationship between farmers and firms as compared to food crops. However food crops still remain the most cultivated farm product in Africa. If a relationship is developed between the farmers and the firms, it would aid in proving credit to the farmers so that their capital condition is removed. (Jayne et al. 2004). Used the data for 825 small farm households who received interlinked credit (ILC). In Kenya ILC is the credit provided to the small farmers by the firms who are purchasing and processing their crop. These firms not only provide credit for the cash crops but also provide inputs for the food crops. The rationale behind it is that if the farmers are able to satisfy their food needs by using inputs which would boost productivity, it would leave more land for cash crops. The authors examined the spill-over effect of fertilizer on non-ILC crops by dividing the 825 into four group. The first group contained 370 households where they did not receive credit in either 1997 or 2000. The second group consisted 140 households who received ILC in 2000 only. The third group had 69 households who received ILC only in 1997 and the fourth group received ILC in both 1997 and 2000 and consisted to 246 households. They found that for the entire sample, the use of fertilizer increased 44% from 1997 to 2000 but the increase was smallest for the first group. Furthermore the results showed that when the farmers received ILC in 2000, their fertilizer used increased significantly.
They then specified a reduced form of the demand equation for the fertilizer use on non-ILC crops:
is the fertilizer use on non-ILC crop by household i in village j at time t.
is the dummy variable which takes the value of 1 is the household i has received ILC at time t.
is a vector of households and village’s characteristics and
are the unobservable household and time-invariant village characteristics, respectively. The model can suffer from an omitted variable problem as the households may have some unobservable characteristics that could be correlated with the dependent variable. Similar, different villages would have different characteristics like improved infrastructure and soil quality which would encourage the use of the fertilizer.
Next they estimated a model which explained the farmer’s participation in the ILC arrangements. To show that, they used a probit model as the variable
is a dummy variable and can only take the value of 0 or of 1:
is the price of ILC crops in the previous period and ILC village dummy is denoted by
. The instrument variable is product of the price of ILC crops in the previous period in village j(
) and the ILC village dummy,
. The reason for taking prices of ILC crops is that it reflects the availability of credit to the farmers
Talking the first difference to avoid bias problem and estimating the following using instrument variables:
The results from eq (2) showed that the probability of getting ILC increase in the next period if there was an increase in the price of coffee in the previous year. The same was true for farmers planting tea however was opposite was true for sugarcane. If the price of sugarcane increase in the previous, the probability of farmers receiving ILC decreased. This could be an indicator that the households were relying less on the sugar companies for credit. Another important result that they got was that the households which were headed by females had a 9.4% lower chance of getting ILC as compared to households where males where the head. They also found that the households received less ILC where the females were highly educated. This could be a signal that they were engaged in off-farm employment or were seeking credit from other sources.
The results from eq (3) indicated that there was a positive correlation between fertilizer uses on non-ILC corps and the credit extended to the farmers under ILC. This showed that there is a positive spill-over effect for the food crops production by the households. It was also found that the households who were participating in the ILC used more fertilizer on their cash crop which indicated that the fertilizer that they were using on the food crop did not come from the fertilizer of the cash crop. They also found that providing credit to the cash crop was more feasible as it made sure that the farmers delivered the crop directly to the firms. The problem with proving credit to the farmers for the food crop was that there are more potential buyers of the food crop and makes it more likely that the crop might not reach the firms. And so they concluded that proving credit to the cash crop is a ‘win-win’ situation as it satisfies the farmers as well as the firms and the households have the ability to increase the production of food crops hence overcoming the credit related constraint on the intensification of food crops.
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