Student thesis series INES nr 379

Organic farming’s role in adaptation to and ! ! mitigation of climate change ! - an overview of ecological resilience and ! ! a model case study ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! Gusten Brodin

2016

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U"! ! TABLE OF CONTENTS

ABSTRACT ...... IV SAMMANFATTNING ...... V LIST OF ABBREVIATIONS ...... VIII 1 INTRODUCTION ...... 1 1.1 BACKGROUND ...... 1 1.2 AIMS ...... 3 1.3 RESTRICTIONS ...... 3 2 EFFECTS OF ORGANIC FARMING ...... 4 2.1 DEFINITIONS AND EXPLANATIONS ...... 4 2.2 A QUESTION OF YIELD? ...... 5 2.3 RESILIENCE ...... 6 2.4 SOIL ORGANIC CARBON ...... 7 2.5 BIODIVERSITY ...... 9 2.6 FARMING PRACTICES AND GREENHOUSE GASES ...... 11 3 METHODS ...... 13 4 MODEL RESULT ...... 16 4.1 COMPARISON WITH FIELD TRIAL ...... 16 4.2 LONG TIME EFFECT ...... 18 5 DISCUSSION ...... 23 5.1 EFFECTS OF ORGANIC FARMING ...... 23 5.1.1 A question of yield? ...... 23 5.1.2 Resilience ...... 23 5.1.3 Soil organic carbon ...... 24 5.1.4 Biodiversity ...... 24 5.1.5 Farming practices and greenhouse gases ...... 25 5.1.6 Summation ...... 25 5.1.7 Comparison with field trials ...... 26 5.1.8 Long time effect ...... 27 5.1.9 Errors and improvements ...... 27 5.1.10 Future use of models in agriculture ...... 28 6 CONCLUSION ...... 29 7 REFERENCES ...... 30

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U"""! ! Organic farming’s role in adaptation to and mitigation of climate change

1 Introduction 1.1 Background

The main drivers of global environmental changes today are caused by anthropogenic activities (Steffen et al. 2007). We have already transgressed at least three out of nine planetary boundaries, defined as safe operating spaces for humanity by Rockstrom et al. (2009), which are the boundaries of climate change, rate of biodiversity loss and rate of interference with the nitrogen cycle. To be able to safely stay inside the planetary boundaries we have to change our ways of managing the earth into practises that do not compromise our future.

Since the industrial revolution global food yields have increased substantially, mainly due to new cultivars and an increase in the use of agrochemicals, such as pesticides and synthetic fertilizer, but also to a lesser extent due to more area used for agriculture (IAASTD 2009; FAO 2010). This rise in available food has set the conditions for the rapid rise in population that took off around the middle of the 20th century. In year 1800, the estimated global population was 0.98 billion and in year 1900, 1.7 billion (United Nations population division 1999). Today the population of Earth is 7.3 billion, with future predictions for 2050 and 2100 of 9.7 and 11.3 billion, respectively (United Nations population division 2015). Today, almost 800 million people or close to 11% of the global population are undernourished (FAO 2015). Agricultural land takes up 33% of the total land area, of which 10% is arable (UNEP 2014). According to FAO (2014a), during the period 2001-2010 agriculture, forestry and other land uses made up 21% of the world’s greenhouse gas (GHG) emissions, of which 11% was directly from agriculture. In the same report, the agricultural emissions are projected to rise by 30% in the year 2050.

However, as global production has increased there has also been an increase in the awareness of the negative effects caused by agriculture. Tilman (1998) states that “It is not clear which are greater – the success of modern high intensity agriculture or its shortcomings”. For instance, the widespread use of large monoculture systems may increase environmental risks e.g. by reducing levels of biodiversity, and could be very sensitive to climate change (IAASTD 2009). Another problem is soil erosion and loss of soil organic matter (SOM), a problem which Gomiero et al. (2011) claim is the most important and most studied consequence of agriculture, affecting the future possibilities of global crop production. Furthermore, Lal (2010) states that improving soil quality and in particular soil organic carbon (SOC) is necessary to address food security. A third risk is the dependence on high energy inputs, especially in the form of fossil fuels and synthetic fertilizer (FAO 2011a), a problem which has to be solved if we want to eliminate our GHG emissions. !

There is therefore a clear and urgent need for different and more sustainable ways of agriculture than those dominating today (IAASTD 2009; The Royal Society 2009; FAO 2010, 2014b). Agroecological practices, such as organic farming, have been proposed as a sustainable alternative to the more widespread and industrialized agriculture that is conventional today, both by scientists (Badgley et al. 2007; Scialabba and Mueller- Lindenlauf 2010; Horlings and Marsden 2011; Ponisio et al. 2015), agencies (FAO 2007, 2010, 2013b) and NGOs (IFOAM 2006; Naturskyddsföreningen 2013). In a recent review of published scientific studies of organic agriculture Reganold and Wachter (2016) conclude that organic farming, though it often results in lower yields, is nevertheless more profitable

! 1! Organic farming’s role in adaptation to and mitigation of climate change and environmental friendly than conventional farming, delivers higher levels of ecosystem services and social values, and could play a key role in feeding the planet in the future.

Total sales of organic food in Sweden have greatly increased in recent years (e.g. 38 and 39% for 2013-2014 and 2014-2015 respectively) and the total share of the market is now 7.7%, second to the percentage of Denmark (8.3%) which has the highest percentage of sales of organic food in the world (Ryegård and Ryegård 2016). On the global scale, all countries for which data (from 2014) was available showed an increase in market sales of organic food out of which the Swedish increase was the biggest (FIBL and IFOAM 2016). Some municipalities of Sweden have goals of increasing the amount of bought organic products over time. For example, the municipality of Lund has goals that state that in 2016, 70% of the total purchase amount for municipality use (e.g. school food or coffee in the municipality offices) should be organic food, rising to 100% in 2020 (Lunds Kommun 2014). In 2014, 96 municipalities, regions and counties in Sweden had an organic share of 25 % (Ryegård and Ryegård 2016). On average, 1 % of the global agricultural land is put under organic farming but the ratio differs greatly between countries. The Falkland Islands has the highest share or organic land (34 %) and Sweden the fourth highest (16 %) while Europe and Oceania has the highest share for whole continents with 2.4 and 4.1 % respectively (FIBL and IFOAM 2016).

Furthermore, if the increase in global average temperature is to be limited to “well below 2 °C above pre-industrial levels and pursuing efforts to limit the temperature increase to 1.5 °C above pre-industrial levels” as stated and agreed to in Paris last year (UNFCCC 2015) great measures have to be taken. The emissions of GHG have to be reduced vastly and even reach negative emissions (IPCC 2014). A possible method of mitigating the changes at the same time as increasing soil fertility would be to increase the sequestration of carbon in soils (Lal 2004; FAO 2009; Han et al. 2013; Paustian et al. 2016; Smith 2016). The amount of SOC stored in the world’s soils is hard to assess but Scharlemann et al. (2014) estimates it to be around 1500 Pg carbon (C), which is about three times as much as the amount in the atmosphere (IPCC 2013). Several studies have shown that organic farming practices lead to higher SOC stocks (Gattinger et al. 2012; Aguilera et al. 2013) which might indicate that organic farming can play a role as a way of mitigating climate change (FAO 2009, 2011c). An concrete example of where organic farming (OF) has led to increased SOC is in California, where a plot with maize-tomato rotation experienced changes from 17 to 23 Mg C ha-1 between 1993 and 2003 (Kong et al. 2005). Another example is in Indonesia, where the SOC rose from 3.4 to 6.2% in a potato plot and from 2.3 to 3.8% in a cabbage plot (Moeskops et al. 2010).

Increasing the adaptation capacity to climate change in agriculture in the form of resilience is highly important in the face of food security issues and climate change (FAO 2010). Organic farming has the potential to increase resilience in agriculture by different means such as heightened biodiversity and improved soil quality (Milestad and Darnhofer 2003; FAO 2013b).

By using models, effects of different management practices can be studied in other ways than by only conducting field trials. Some of the uses include changing scales (e.g. from local to global), reproducing field trials or investigating the importance of individual factors. In order to test how well organic farming can be modelled, the model LPJ-GUESS (Smith et al. 2014) was used to replicate a field trial comparing organic and conventional farming in Norway (Eltun et al. 2002; Riley et al. 2008). The site was mainly chosen due to its proximity to Sweden and due to the observed field trial result that shows a loss of soil C in both systems,

! /! Organic farming’s role in adaptation to and mitigation of climate change which contradicts the increases in soil C as a result of organic farming as presented by Gattinger et al. (2012).

1.2 Aims

The aim of this study is to investigate the potential role of organic farming regarding adaptation to and mitigation of climate change. As a way of adaptation, resilience aspects will be studied and as a way of mitigation, emissions of GHG and carbon sequestration. This will be conducted by answering the following questions:

• In what ways might organic agriculture be more resilient to climate change? • How and in what ways does organic agriculture influence the levels of soil organic carbon and how do emissions of GHG compare to conventional farming? • How does modelled organic and conventional farming compare with field trials and what is the difference when managed during a longer time?

The first two questions will be addressed by reviewing available literature and is presented in Section 2, Effects of organic farming. The third question will be addressed with a model case study and the results will be presented in Section 4, Model result.

1.3 Restrictions

Due to the vast scope of the research questions and limited time available, this study will mainly focus on natural resilience and functions of agroecosystems, even though they are often interdependent on the socio-economic resilience of the area. However, since they are so closely interlinked some key aspects, such as food availability and sovereignty will be discussed as well. The main studied aspects affecting adaptation and mitigation potential will be biodiversity, SOC and how the two systems compare in terms of GHG dynamics.

The modelling will be restricted to one location in Norway, focusing on the conventional and organic farming test conducted there. The model of both CF and OF will also be limited compared to the field trials in several ways due to the complexity of replicating all aspects of the field trial in the model.

!

! `! Organic farming’s role in adaptation to and mitigation of climate change

2 Effects of organic farming

This chapter starts with a section explaining central terms for the following text (2.1 Definitions and explanations) and will then highlight some common arguments for and against OF, mainly focusing on the yield aspect (2.2 A question of yield?). The text will then continue to examine the resilience aspect (2.3 Resilience), where the factors regarding resilience in an agroecosystem and whether these are more common in OF is addressed. Apart from physical resilience, some socio-economic aspects will be discussed as well. This section sets the base for the next two sections, 2.4 Soil organic carbon and 2.5 Biodiversity, which covers the functions and importance of SOC and the effects of biodiversity for agriculture respectively. The whole chapter is then finished by 2.6 Farming practices and greenhouse gases, where GHG emissions, life cycle assessments and carbon sequestration are discussed.

2.1 Definitions and explanations

Key terms that are needed for the further understanding of the thesis questions, namely organic-, sustainable- and conventional agriculture/farming, agroecology and resilience must first be explained and if possible, defined.

Organic agriculture can mean different things in different parts of the world but the International Federation of Organic Agriculture Movements (IFOAM), an international umbrella organization consisting of around 800 affiliates, defines it in the following way: “Organic Agriculture is a production system that sustains the health of soils, ecosystems and people. It relies on ecological processes, biodiversity and cycles adapted to local conditions, rather than the use of inputs with adverse effects. Organic Agriculture combines tradition, innovation and science to benefit the shared environment and promote fair relationships and a good quality of life for all involved." (IFOAM n.d.). While outlining which principles that govern OF, the definition by IFOAM does not clearly state the differences with conventional farming (CF). An easier way to define OF in relation to CF would be to describe what is not allowed if the products are going to be certified. To be certified with the EU-standard for organic products, this would in short mean no use of synthetic fertilizer, synthetic pesticides or genetically modified organisms (Jordbruksverket 2016). The definition of OF leads to the question of what it is that defines CF. This is not as easy to define but since the regulations for OF are derived from what is used in CF, the revocation of said regulations could outline which processes are used in CF. The distinctions between CF and OF are not mutually exclusive, and in reality it is more like a gradual spectrum, e.g. some conventional farmers utilize large quantities of pesticides on vast monocultural fields while some basically use organic practices and rarely use pesticides or synthetic fertilizers. On the other hand, growing demand for organic products can also lead to a new type of large scale OF, lacking the ideals of improving e.g. soil quality and instead only following what must be done according to certification standards, with a lesser possibility to create resilient farming systems (Milestad and Darnhofer 2003). Ponisio et al. (2015) means that a more accurate way of defining both OF and CF would be to describe them as biologically diversified or chemically intensive systems. This viewpoint highlights the core differences between the practices and also how they handle complications, such as the need for nutrients or pest outbreaks.

The FAO (2014b) means that a sustainable agriculture should incorporate a maintenance and conservation of ecosystem and ecosystem functions, as well as the ability to provide food and

! a! Organic farming’s role in adaptation to and mitigation of climate change goods both now and for future generations. It should also give people the possibility to take part in economic development, to have control of their livelihoods and have an equitable access to resources.

Resilience, or ecological resilience, was first defined by Holling (1973) as the persistence of relationships in a system and measures the ability of the system to absorb changes and still persist. In the same paper the term is compared to stability, which is defined as the ability of a system to return to equilibrium after a disturbance. This was further defined in 2004 as “the capacity of a system to absorb disturbance and reorganize while undergoing change so as to still retain essentially the same function, structure, identity, and feedbacks” (Walker et al. 2004). In the context of agriculture, the FAO (2010) lists increasing resilience as a key topic regarding food security in the face of climate change, especially in developing countries. In the same report it is also mentioned that practices that focus on increasing resilience also often has the potential for being low emissive of GHG as well.

The term agroecology can be described either as a scientific discipline, a movement or as a practice, according to Wezel and Soldat (2009). They further describe the discipline as including topics such as sustainable agriculture and the concept of agroecosystems, with scales ranging from individual fields to whole food systems incorporating factors such as society and politics. Agroecology has also been described as the science of sustainable agriculture, which relies on management rather than external inputs and is knowledge intensive rather than capital intensive (Altieri 1995). Agroecology has further been described as the scientific basis of sustainable OF by Naturskyddsföreningen (2013). However, while agroecology encompasses OF and describes most of the concepts and methods used, it does not necessarily share the same restrictions as the latter. An example might be the utilization of synthetic fertilizer which is not allowed in OF, but which might occasionally be used if implementing agroecology as a practice, though it is not seen as the preferable source of nutrients. Even though OF tends to incorporate more agroecological methods than CF, both systems can be managed with different levels (Altieri 1995).

2.2 A question of yield?

The most commonly used argument against organic farming is that it lacks the capability to supply the world with the amount of food needed (Trewavas 2002; Connor 2008; Kirchmann et al. 2016). The typically lower yield has also been shown in several studies (de Ponti et al. 2012; Seufert et al. 2012; Ponisio et al. 2015) but all of them also state that the differences are not uniform and vary greatly between different crop types and sites. Furthermore, Badgley et al. (2007) shows that the differences in yield also differ between developed and developing countries, where developed countries generally showed lower yield for OF compared to CF (OF:CF of 0.9) and developing countries showed higher yields (OF:CF of 1.8). The possibility of higher yield due to OF practises has also been confirmed in developed countries. In an ongoing field project of the Rodale Institute (USA) which has run since 1981, it has been shown that after an initial decline of yield in the first years after conversion to organic farming, the yield of OF has matched the CF and even outperformed it in years of drought (Moyer 2013; Rodale Institute n.d.). Apart from reporting an average of 19% less yield in OF, Ponisio et al. (2015) found that diversification techniques such as crop rotation and multi cropping could limit the difference to less than 10%. They further claimed to detect a bias in the published research towards showing higher yield ratios in CF, which would mean that their estimate of the yield gap could be overestimated and that the yield gap is in fact smaller than reported.

! :! Organic farming’s role in adaptation to and mitigation of climate change

There are also discussions regarding how much food is actually needed, both for today and for the future. Many reports and refereed scientific papers state that we need to increase our food production, especially in face of a future population increase (IAASTD 2009; The Royal Society 2009; Godfray et al. 2010). Some also state that we already produce more than enough food, at least for today’s use, and it is rather a question of making it available rather than increasing the absolute yield (Holt-Giménez et al. 2012). Today there are about 0.8 billion undernourished people globally (FAO 2015) and as a comparison it can be said that there are almost 1.5 billion people who are overweight, out of which 0.5 billion are obese (Finucane et al. 2011). The Nobel Prize winner in economic sciences of 1998 Amartya Sen worded the problem regarding food availability in the following way: “Starvation is the characteristic of some people not having enough food to eat. It is not the characteristic of there being not enough food to eat” (Sen 1981). Furthermore, roughly a third of the total global food production is lost along the food chain and is never consumed (FAO 2011b), which indicates that there is a huge potential to increase the available and used food without the need to increase production. Also, 70% of agricultural land is used for livestock production and out of all arable land, 33% is dedicated to feed crop production for livestock (FAO 2006). This is important in the context of diets, since it would be possible to use more of the area now used for feed crop production directly for human food production instead. Springmann et al. (2016) recently showed that by shifting diets, either to a “healthy diet” (e.g. less meat and only the necessary amount of calories), vegetarian or vegan diets the expected rises in food related GHG emissions in 2050 could be mitigated with 29% for the “healthy diet” and 63-70% for the vegetarian diets. These mitigations are primarily explained by less emission from livestock production, which makes up 80% of total agricultural GHG emissions (FAO 2006).

Even though advances in science and technology and an intensification of agriculture has provided us with a great increase in food supply during the last century, this might not be enough for a continued supply for a growing population, according to Smith (2015). Instead Smith (2015) list primarily changes in demand, in particular less demand for livestock products, and food waste reduction as main factors for being able to feed a growing population.

2.3 Resilience

Organic farming has been proposed as a more climate change resilient alternative to CF (Altieri 1995; Milestad and Darnhofer 2003; Scialabba and Mueller-Lindenlauf 2010; FAO 2013b) and concepts central to OF, such as promotion of biodiversity in agriculture, the viewing of agriculture as an ecosystem and improvement of soil health have also been listed as key factors for a resilient agriculture, whether classified organic or not (Tscharntke et al. 2005; IAASTD 2009; FAO 2010; Lin 2011; Mijatovi! et al. 2013; FAO 2014b; Altieri et al. 2015). Biodiversity, with a scale ranging from genes to ecosystems, is important in agricultural stability and for resilience since high diversity means a high possibility to resist or recover from deterministic or stochastic events (Chapin et al. 2000; Millenium Ecosystem Assessment 2005) which in agriculture could be such stresses as pest outbreaks, droughts or changes in growing season (Altieri et al. 2015). Regarding agriculture, intensification, fragmentation and specialisation has led to large biodiversity losses globally, although a lot of biodiversity is also dependent on certain agricultural practices (Tscharntke et al. 2005).

Resilience in an agroecosystem is not only dependent on local physical and ecological characteristics such as biodiversity or SOC but also on external factors. These factors can

! 2! Organic farming’s role in adaptation to and mitigation of climate change have both social and/or economic origins, often overlapping with topics such as food security and food sovereignty. An example of problems in agriculture of a socio-economic origin is that of increasing levels of enclosure of seeds, lands and market described by Holt-Giménez and Altieri (2013), with implications such as increasing global hunger and less agroecosystem resilience. Intellectual properties of cultivars, which is very common in genetically modified (GM) crops, and its implications for seed trade/exchange and for farmers producing their own seeds are outlined as a topic of concern by the IAASTD (2009) as well. Both the FAO (2014b) and the IAASTD (2009) state that in a sustainable and resilient agriculture more focus has to be put on the total resilience of the agroecosystem, which is a product of both physical and socio-economic resilience.

Another aspect of agroecosystem resilience is the need for external inputs, mainly in the form of energy (such as fossil fuels) or in the form of agrochemicals (such as pesticides or synthetic fertilizer) and by limiting the need for external inputs, the resilience of a farm can be strengthened in the face of economic fluctuations, new policies or lack of resources (FAO 2013a). A specific but crucial problem for agriculture that relates to the external input resilience question and which is sometimes overlooked today is that of the availability of phosphorus (P). P is a limited resource, which is essential for plants. Today, it is mostly distributed as synthetic fertilizer, originating from mined phosphate rock in a few locations. Cordell et al. (2009) estimated that the global P production could peak around 2030, with all known reserves depleted within this century. Cordell et al. (2009) further conclude that if nothing is changed in modern agriculture, its dependence on non-renewable cheap P fertilizer will drastically compromise future yields as the availability of P declines.

2.4 Soil organic carbon

Carbon (C) in soils has two sources, either as a result of weathering processes or as a result of photosynthetic fixation of atmospheric C. A major part of the fixated C is directly emitted due to respiration, but a smaller part will stay in the form of living tissue, SOM, inorganic carbon phases or dissolved organic matter (Chadwick et al. 1994). As mentioned previously, soils hold a large pool of C but land use changes, particularly changes from native vegetation to agriculture and pasture, has often led to diminishment of the pool (Scharlemann et al. 2014). Carbon leaves the soil either as a respiratory product (such as CO2 or CH4), via soil erosion or by hydrological processes (such as leaching of dissolved organic C) (Dawson and Smith 2007). The amount of C a soil holds is mainly dependent on four factors according to Johnston et al. (2009). These are listed as: input amount and oxidation rate of organic material, rate of decomposition in existing material, soil texture and climate. These factors will, if changed, induce changes in the soil C content towards a new equilibrium (Johnston et al. 2009). The two first factors are dependent on management, and the two others are dependent on spatial location. Plant uptake of N depends on many things, out of which the ratio N:C is important for the decomposition rate of organic matter and N mineralization.

Maintaining optimal SOC levels is important for many different soil functions such as: holding capacity of water and nutrients, erosion and degradation resistance, maintaining and improving soil structure and to provide microorganisms with energy (Lal 2004). It is also vital for ecosystem resilience (Grandy et al. 2012) and with all these factors combined, SOC is a crucial determinant of yield, yield stability and in this connection, a sustainable agriculture (Bot and Benites 2005; Lal 2010).

! b! Organic farming’s role in adaptation to and mitigation of climate change

An overview of how different management practises affect SOC in Europe is given by Freibauer et al. (2004). Amongst others, they list application of organic amendments, such as manure, use of cover crops, mulch farming and the use of leys as improving C sequestration and conclude with listing the most promising policies for enhancing sequestration rates in agricultural soils. These include restricting the drainage of agricultural peatlands, promotion of OF, promotion of increased organic inputs, and permanent revegetation of arable land. Diacono and Montemurro (2010) also list the addition of organic amendments as important for SOC and conclude that repeated applications increases the soil N pool and lowers the risk of N leaching, which means that the N can then be used by crops during following seasons.

In a meta-analysis of studies comparing OF and CF, Gattinger et al. (2012) found that both the stocks of C and the C sequestration rate was higher in OF, though the method and results were debated (Gattinger et al. 2013; Leifeld et al. 2013). In another meta-review, Leifeld and Fuhrer (2010) also concluded that the SOC rises under OF practices, but continued with stating that it was due to the higher application of organic fertilizer in OF and as such, not dependent on the practice itself. In a third review, Mondelaers et al. (2009) confirmed an increase in SOM in OF.

Some of the effect SOC has on the physical qualities of a soil is increased resistance to erosion, but a lot of other management dependent factors contribute to the erosion susceptibility of a soil as well. These factors include methods such as the use of cover crops and the addition of organic matter (Erhart and Hartl 2009). When comparing winter wheat under CF and OF where the OF had a higher SOC content, Reganold et al. (1987) found that the OF had a fourth of the erosion of the CF (8 compared to 32 t ha-1). The difference was mainly explained by different crop rotation schemes, where the OF included a green manure legume crop and also by less tillage in the OF. Mechanical weed management, which is common in OF, and tillage increases erosion rates but according to Erhart and Hartl (2009) the negative aspect of more mechanical soil disturbance is outweighed by the measures that reduce erosion in OF.

The amount of SOC is also one of the factors that determine how much plant available water a soil can hold, along with factors such as texture and porosity. The amount of SOC is positively correlated with the water holding capacity, and an increase in SOC will heighten soil aggregate formation and stability as well as the porosity which also enhances infiltration (Tom 2007). A higher level of infiltration also leads to less surface runoff and less erosion, and recharges the local groundwater (Bot and Benites 2005). Higher yields in OF compared to CF during drought years are mainly explained by the higher SOC content and the larger amount of plant available water (Pimentel et al. 2005).

A term that is often mentioned alongside soil carbon sequestration or negative emission techniques is that of biochar (Paustian et al. 2016; Smith 2016). Biochar is a concept which is based on a type of anthropogenic soil found in certain places in the Amazon, Terra Preta, which had its quality enhanced by organic amendments over a long period of time (Glaser and Birk 2012). In a study comparing sites with and without Terra Preta, Doughty et al. (2013) found that trees growing in these soils had a greater productivity and carbon storage efficiency than those of a control plot. This is important both in the context of climate change and food security since the possibilities of the technique could contribute both to mitigation in the form of C storage as well as soil quality (Woolf et al. 2010). The effects of biochar on soil biota, and in connection soil quality can be explained due to the chemical properties as well as the physical properties of the charcoal (Lehmann et al. 2011). All of the effects are

! c! Organic farming’s role in adaptation to and mitigation of climate change not yet fully understood, but is has been shown that the effects include increases in net production, nutrient retention capacity, water holding capacity and soil microbial life, enhanced soil structure and erosion resistance (Lehmann et al. 2011; Barrow 2012), as well as providing higher yields and a high rate of C sequestration (Smith 2016).

2.5 Biodiversity

Bengtsson et al. (2005) concluded in a meta-analysis that OF gives an average of 30% higher biodiversity compared to CF but that differences varied between species groups. E.g., both weed and predatory species showed a higher abundance in OF, while non-predator and pests showed no changes or higher abundance in CF. These results have also been confirmed in other studies (Mader et al. 2002; Hole et al. 2005; Rahmann 2011; Winqvist et al. 2012; Tuck et al. 2014) and it is further said that the processes inducing changes in the level of biodiversity are the result of many different factors such as landscape homogeneity, the amount and type of applied pesticides or tilling practises. The concept of levels of biodiversity is very important for an ecosystem, or in this context, an agroecosystem, in many ways influencing aspects such as yields, yield stability, resilience and amount of management needed.

Regarding biodiversity within species, or genetic biodiversity, Dempewolf et al. (2014) state that landrace species (i.e. traditional and local adapted cultivars (Villa et al. 2005)) and wild relatives to modern cultivars will be increasingly important as a source of genetic material when adapting crops to climate change. This view is also shared by Burke et al. (2009) who state that increased cooperation and distribution of genetic material from local landrace species across borders will be crucial when adapting crops to a new climate or to changes in the growing season in Africa. A proposed solution for both food security and climate change resilient crops is to utilize genetic modification techniques to create new variants of cultivars with new qualities, such as increased drought resistance or resistance to a particular pesticide (Borlaug 2000; Trewavas 2002). This view, however, is not the only one regarding the techniques. Jacobsen et al. (2013) state that the claim of GM crops as necessary for feeding the world is not driven by demand but instead by corporate interests. Instead, Jacobsen et al. (2013) stress that we should focus on maintaining and improving existing agrobiodiversity to secure food production. The IAASTD (2009) states that no matter how big yields modern biotechnology can produce with GM crops, it cannot replace traditional breeding and distribution of seeds. They also outline arising problems, such as the increase of pesticide resistant weeds and insects and the spreading of genes to wild plants and conclude with stating that even though GM crops can give certain advantages, the environmental effects are not studied enough and that current risk assessment concepts and programs are incomplete and need improvement in the face of this new technology.

An extensive test of how increased biodiversity within species affected pest resilience in rice in China was conducted by Zhu et al. (2000) in 1998-99. Before the test was conducted, two cultivars were farmed in monocultures in the areas, one hybrid with high resilience to blast disease and one with lower resilience and lower yield but with a higher market price. The experiment consisted of mixing the two cultivars in one field, with one row of the less resilient variety followed by four rows of the other. The low resilient variety showed 89% greater yield and 94% less severe blast disease compared to areas where it was still grown in monocultural fields. The other cultivar benefited slightly as well, with lower damages caused by the blast disease. In the second year of the experiments use of the former primary control of the pest, foliar fungicides, was not deemed necessary. In 2000, the diversified practice has

! ^! Organic farming’s role in adaptation to and mitigation of climate change expanded to 40000 ha (Zhu et al. 2000). The rice was not farmed under strict OF practices, but diverse crops and crop systems is a cornerstone in organic farming (IFOAM n.d.) and are extensively used in OF and often seen as a main factor for increased resilience (FAO 2007; Scialabba and Mueller-Lindenlauf 2010).

A concrete and current example of biodiversity problems associated with farming practices might be changes in levels of pollinators, since they are necessary for yield in many crop types. After studying bee abundance in OF and CF, Holzschuh et al. (2007) concluded both that the abundance of bees was higher in organic fields and also that farming practices had a bigger impact on the abundance than the landscape structure.

Another example might be the abundance of earthworms in the soil. Earthworms contribute tremendously to the soil structure and soil quality, e.g. by transporting and decomposing litter from the surface, increasing both aggregate stability and soil porosity (Blouin et al. 2013). In a 21 year long study in Switzerland comparing organic and conventional farming Mader et al. (2002) found that there was a higher abundance of earthworms in organic systems by a factor of 1.3 to 3.2, compared to the conventional. Higher abundance of earthworms in organic farms has also been confirmed in other studies (Blakemore 2000; Pelosi et al. 2015). Apart from effects on the soil quality, earthworm abundance also affects the yield with possible increases of up to 25 % when abundance is high, according to a meta-analysis made by van Groenigen et al. (2014). This increase is further explained mainly as a result of higher N mineralization caused by the earthworms, which is of extra importance in farming practices where external N input is limited, such as organic farming.

A third aspect of diversity is that of soil biodiversity. In CF, soil biodiversity is seldom considered beyond selection of plant species and maybe some microorganisms such as N fixating bacteria (Cavigelli et al. 2012). In contrast, one of the goals in OF is to increase and maintain soil health and soil biodiversity (Lockeretz 2007). Also, the choice of crops and the choice of cultivars, has a direct effect on soil biodiversity by the means of e.g. competition of nutrients or influence on the levels and type of mycorrhiza (Cavigelli et al. 2012) regardless of the managing practice.

Mycorrhiza symbiosis is determinant for ecosystem variability, productivity and plant diversity (van der Heijden et al. 1998) and arbuscular mycorrhiza (a common type of mycorrhiza) form symbiosis with more than 80% of all land species, including many crop species (Gosling et al. 2006). An abundance of mycorrhiza benefits crops in many ways, such as an easier uptake of nutrients (particularly P), improving soil structure (Smith et al. 1997), or increased plant disease resistance (Whipps 2004). However, many of the practices associated with CF are detrimental for mycorrhiza, practices that Gosling et al. (2006) list as the use of easily water-soluble fertilizer, pesticides, monocultural cropping systems, growth of non-mycorrhizal crops and extensive tillage and mechanical weed control. Gosling et al. (2006) continue by stating that common OF practices, though not exclusively limited to OF, usually promote growth of mycorrhiza both by the exclusion of synthetic fertilizer and pesticides and by the extensive use of crop rotation with the inclusion of ley. Several studies have shown that both abundance of biomass and species of arbuscular mycorrhiza is greater in OF than in CF, which is mainly explained by the use of water soluble pesticides and easily accessible P contents in CF on one hand and the active promotion of soil diversity in OF on the other hand (Ryan and Ash 1999; Mader et al. 2000; Bending et al. 2004). The positive effects of a well established mycorrhiza community are often seen as an important topic for

! 10! Organic farming’s role in adaptation to and mitigation of climate change agroecological agriculture in general and OF in particular (Johansson et al. 2004; Oehl et al. 2004; Gosling et al. 2006; Antunes et al. 2012).

2.6 Farming practices and greenhouse gases

As mentioned above, agriculture, forestry and other land uses make up a big part (21%) of the total GHG emissions (FAO 2014a). The IPCC (2013) give examples of four mitigation strategies for this sector, namely emission reduction, sequestration, substitution and demand- side measures. Emission reduction can be the preservation of C in soils and vegetation or reducing the emission of methane and nitrous oxide. Sequestration is to increase the existing C pools (e.g. in soils), substitution is the replacement of fossil fuels with e.g. biological products and demand side measures can be changes in diets, reduction of waste or changes in wood consumption. Out of these examples, sequestration is the only one that has the possibility to reduce the total C content in the atmosphere while the other examples only are means to reduce the increase of C emissions. If the temperature rise is to be limited in accordance with the UNFCCC (2015) it is not enough to only reduce the current emissions, but instead it is necessary to achieve net negative emissions (IPCC 2014).

Mondelaers et al. (2009) conclude in a meta-analysis that OF emits less GHG than CF per unit area, but that the result for emission per yield shows no difference. In another meta- review regarding soil derived emissions of non-CO2 GHG in OF and CF, Skinner et al. (2014) found similar results; that OF emitted less N2O than CF when measuring emissions per area, but the opposite when measuring emission per yield. This is explained by the observed yield difference of 26%. Skinner et al. (2014) further note that if the yield difference were less than 17%, OF would have lower N2O emissions per yield as well. Considering both GHG emissions and energy efficiency, OF seems to outperform CF both regarding to area and yield (Lotter 2003; MacRae et al. 2010). These differences are primarily explained by the use of synthetic fertilizer and pesticides in CF, for which the production process is very energy demanding. A study in eastern China comparing the effects of synthetic fertilizer and manure on GHG emission reported that when using synthetic -1 -1 fertilizer, the site acted as a net source of GHG with 2.7 t CO2-eq. ha year and when using -1 -1 manure, as a sink with -8.8 t CO2-eq. ha year . At the same time, the yield difference between OF and CF was insignificant. The major part of the OF emissions were from enteric fermentation by cattle, and as described earlier, the major part in CF from the production of synthetic fertilizer (Liu et al. 2015).

Life cycle assessments are common tools for evaluating GHG emissions for a certain product, which try to take all possible sources of emissions into account. In the context of agriculture, it can be the inclusion of aspects such as a conversion of forest to arable land, fuel type for machinery, production of fertilizer or the transport to a store. When comparing the global warming potential for 1 kg wheat bread in the USA, Meisterling et al. (2009) found that the bread baked with organic flour resulted in about 16%, or 30 g, less CO2 equivalents than bread baked with conventional flour. The larger emission from the conventional flour was mainly explained by the production and transportation of synthetic fertilizer used in CF. Meisterling et al. (2009) further explained that the potential for soil carbon storage was assumed to be equal in the analysis, but a higher sequestration rate in OF would mean a bigger difference of the global warming potential. Life cycle assessments are however not always without problems and comparable with each other, since they often set the borders in different ways. Specific problems comparing CF and OF are outlined by Meier et al. (2015).

! 11! Organic farming’s role in adaptation to and mitigation of climate change

The topic of soil carbon sequestration as a way of mitigating climate change has seen a rapid increase of study interest during the last decade (Powlson et al. 2011) and many studies regarding the mitigation potential and means to achieve higher sequestration have been conducted (Freibauer et al. 2004; Smith 2004; Paustian et al. 2016). A common finding is that the lessening of atmospheric C is not the only positive outcome from increased sequestration, but that the soil also experiences benefits in terms such as soil fertility and erosion resistance (Lal 2004; Powlson et al. 2011; Grandy et al. 2012). Organic farming has frequently been proposed as a more climate smart management practice than CF, both because of overall less GHG emissions and because of the greater possibilities of sequestering C (FAO 2009; MacRae et al. 2010; FAO 2011c, a; Goh 2011; Han et al. 2013). The claimed effect of a hypothetical global conversion to OF varies, but Gattinger et al. (2012) state that it could sequester 0.4 Gt C annually (3% of annual global GHG emissions). The Rodale Institute (2014) goes as far as claiming, in a white paper, that while maintaining yields, “regenerative organic farming” has the potential to sequester more than 100% of annual global GHG emission.

However, soil carbon sequestration is not a universal long term solution, since soils only are able to accumulate a certain amount of C before the concentration stabilize in a new equilibrium (Lal 2004). Even so, the potential is great, not only because vast areas have experienced C loss previously but also because many soils have not yet reached their full saturation point (Lal et al. 2007). Another way of increasing the soil carbon pool, beyond the mentioned equilibrium, would be by the addition of biochar to soils. This would be possible since the C stored as biochar and the C stored as SOC is different in many aspects, but especially in terms of decay rate. While SOC normally has a relatively short life length, biochar has a potential life length of several thousands years (Glaser 2007). Also, as discussed in the previous chapter, biochar can enhance the soil quality with benefits for food security and productivity. According to Woolf et al. (2010), the benefits of biochar in terms of C sequestration is three-fold: by substituting fossil fuels, by avoiding N2O and CH4 from decaying biomass and by sequestering C as biochar. Woolf et al. (2010) continues with an estimate of the potential of biochar implementation and concludes that net emission of CO2 could be reduced with 6.6 Pg CO2 equivalents, or 12% of the anthropogenic emission, each year and over the next century 477 Pg. When reviewing different techniques for C sequestration in soils, Paustian et al. (2016) estimate the mitigation potential to be 8 Pg CO2 equivalents annually, compared with the 49 CO2 equivalent anthropogenic GHG that was emitted in 2010 (IPCC 2013).

The leaching of nutrients from agriculture and the resulting eutrophication is not only a major environmental problem with implications in ecosystems all the way between the source and the endpoint (Swedish Environmental Protection Agency 2016). Leaching of N from agriculture also gives rise to indirect GHG emissions (IPCC 2000). When reviewing differences between OF and CF, Mondelaers et al. (2009) found that the leaching of N was lower in OF when looking at leaching per area and lower but insignificant when looking at leaching per yield. The higher leaching per area in CF is further explained by larger application of fertilizer, lower use of cover crops, higher livestock density and a lower C:N ratio. These results are partly confirmed by Tuomisto et al. (2012), giving the same result for leaching per area but a substantially higher leaching per yield in OF.

! 1/! Organic farming’s role in adaptation to and mitigation of climate change

3 Methods

The third research aim was addressed with a limited model study. The model used was the dynamic global vegetation model LPJ-GUESS version V (Smith et al. 2014), with added functions by Lindeskog et al. (2013) to expand the supported land types to managed land, and Olin et al. (2015a) to include carbon-nitrogen (C-N) interactions on managed land. A schematic illustration of the different parts of the model is shown in Figure 1. Main outputs relating to the questions of the thesis are the SOM and the vegetation part, as well as primary production & growth. The model use climate and CO2 as drivers, along with values of N deposition and soil information, and simulate vegetation dynamics in daily steps through competition based on light, water and N availability (Olin et al. 2015a; Olin et al. 2015b). Soil C and soil N dynamics in LPJ- GUESS are based on the model CENTURY (Parton et al. 1993), where different C:N ratios and decay rates, along with soil temperature and soil water content, determines how the SOM pool behaves (Olin et al. 2015b). Allocation of N and C within the crops (e.g. C allocation from leaves to roots) takes place on a daily scale and is based on daily net primary production and in which developing stage the crop is (Olin et al. 2015b), as opposed to the yearly allocation described by Smith et al. (2014). The amounts of applied manure is derived from the historical N application rate, and to simulate the different impacts on soil ecology of the two types of fertilizer, the N is added to the SOM pool instead of to the mineral N pool, with extra C added as well to Figure 1: Illustration of the different parts of LPJ- replicate the composition of manure (Olin et GUESS (Department of Physical Geography and al. 2015a). Ecosystem Science - Lund University n.d.)

The chosen field trial for comparison was a trial conducted by the Norwegian Crop Research Institute, located in Apelsvoll, southeast Norway (60°42´ N 10°51´ E), where different farming systems have been compared since 1990 (Eltun et al. 2002; Riley et al. 2008). The field trial consists of 12 plots, out of which the conventional arable and the organic arable plots were chosen (OF corresponds to cs3 or ECO-A and CF to cs1 or CON-A in Eltun et al. (2002) and Riley et al. (2008)).

Due to time limitation and due to the complexity involved in replicating all aspects of the field trial, the modelled scenarios differed in several ways compared to the field trials. The differences between the field trials and the modelled scenarios are summarized in Table 1. All modelled scenarios include grass intercrops, and the organic scenarios also include N fixating intercrops. In the model, intercrops are grown temporally between the main crops of different years.

!

! 1`! Organic farming’s role in adaptation to and mitigation of climate change

Table 1: Differences between field trials and modelled scenarios.

Field trial Modelled Field trial Modelled Aspect Conventional Conventional Organic farming Organic farming farming farming Crop/crop 4 year rotation, cereals and Wheat and N rotations 4 year rotation, Wheat and grass potato. Each fourth year, ley fixating inter (Eltun et al. cereals and potato intercrop with legumes crop 2002) Tillage 1/year, no tillage during ley (Eltun et al. 1/year 1/year 1/year years 2002) Fertilizer Synthetic Organic Synthetic Organic

The model uses historical land use for the calculations, in which the crops at the location are represented by either temperate winter or summer wheat or irrigated variants (Olin et al. 2015a). The model also provides historical fertilization rates, and uses gridded climate data as the main drivers.

The model is first run for 500 years using the climate and management of the years 1901- 1930 for the closest gridcell centred at 60°75´N 10°75´E to establish equilibrium soil properties (C and N pools) and vegetation. The model then continued to run with historical management and climate until 1990, when the field trial started. A series of model runs were then performed to investigate different OF management practises until the end of the historical data in 2006. To investigate how much the C in the manure (i.e. Organic fertilizer in Table 1) affected the soil C pools, three scenarios of different manure type were run as well. The difference between the modelled scenarios is presented in Table 2.

Table 2: Differences between the modelled practices of the comparison with the field trial (chapter 4.1). Changes relative to CF since the year stated

Conventional Organic Manure Manure Manure Treatment farming farming (C+N) (C) (N) (CF) (OF, 1990) (1990) (1990) (1990) Tillage 1/year 1/year 1/year 1/year 1/year Manure Manure Fertilizer Synthetic Manure Manure (C only) (N only) N fixing No Yes No No No intercrop

To investigate long term effects of OF, scenarios where OF started in 1950 were modelled in addition to the 1990 experiments. When soil C increases, the soil type gradually changes towards an organic soil with different properties. Therefore, a scenario with organic soil type and OF was conducted to investigate the differences. Since no tillage agriculture is often proposed as a way to increase sequestration of C, a scenario of no tillage OF was also conducted. In the model, tillage is modelled by increasing the decomposition rate of organic matter (Olin et al. 2015a). The long term scenarios, as well as the 1990 OF scenario, are presented in Table 3.

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! 1a! Organic farming’s role in adaptation to and mitigation of climate change

Table 3: Differences between the modelled practices of the long time effect (chapter 4.2). Changes relative to CF since the year stated

Conventional Organic Organic Organic Organic Treatment farming farming farming farming farming (CF) (OF, 1950) (OF-OS, 1950) (OF, 1990) (OF-NT, 1950) Tillage 1/year 1/year 1/year 1/year No Fertilizer Synthetic Manure Manure Manure Manure N fixating No Yes Yes Yes Yes intercrop Soil type Coarse Coarse Organic Coarse Coarse

The model outputs that main focus will be put on are:

• Crop yield • Soil carbon pool • Carbon net ecosystem exchange • Soil nitrogen pool • Nitrogen leaching

Notes regarding the comparison

Comparison of yields: To compare the modelled yields of OF since 1990 with the observed values of the trials, the modelled yield values were factored by 0.75 to accommodate for ley years, which was already taken into account in the reported trial yields (Eltun and Nordheim 1999; Korsaeth 2008). The output of the model was temperate winter wheat and irrigated temperate winter and summer wheat, which were compared to the average yields of wheat during 1990-97 from Eltun and Nordheim (1999), and of wheat during 2001-04 from Korsaeth (2008). Both reported field trial yields were reported with a water content of 15%, and the values were multiplied by 0.85 to acquire yield in dry weight.

Comparison of SOC: Since the field trial values of SOM were given in percentage of volume (Riley et al. 2008), and the modelled result as kg C m-2, a conversion from SOM (volume %) to soil C m-2 was made. SOM was converted to SOC (%) by dividing the values by a factor of 2 according to Pribyl (2010). The values were then multiplied with the corresponding soil bulk density (Riley et al. 2008) and the same soil depth as the model uses (1.5m), with the resulting values kg C m-2.

Comparison of N leakage: Surface run-off and drainage run-off of N from Korsaeth and Eltun (2000) were added and treated as total N leakage.

Notes regarding the long time modelling

Comparison of plant available water: Plant available water values in LPJ-GUESS (given as fraction of available water-holding capacity) for the months in the growing season (May- September) for both upper (0-50 cm) and lower (50-150 cm) soil were averaged. These values were then multiplied with the water holding capacity of different soil types given by the model, which was 55 (mm water per m soil depth) for the coarse soil corresponding to the field trial and 150 mm for organic soil respectively, giving the result in modelled plant available water (mm m-2).

! 1:! Organic farming’s role in adaptation to and mitigation of climate change

4 Model result 4.1 Comparison with field trial

The modelled yield of CF and OF for the site in Norway is shown in Figure 2, along with observed average yields for the periods 1990-1999, 0.54 and 0.32 kg dry weight (DW) m-2 respectively (Eltun and Nordheim 1999) and 2001-2004, 0.43 and 0.17 kg DW m-2 (Korsaeth 2008). The average yield difference (as a ratio of CF yield) in 1990-1999 was 0.59 in the field trials and in the modelled results 0.37. For the period 2001-2004, the difference was 0.40 and 0.46 respectively. The yields seems to decline over time in the modelled CF and increase in OF, but in the observed data both decline.

Figure 2: Modelled yield of conventional (CF) and organic (OF) farming compared to observed field trials averages for conventional (CF-FT) and organic (OF-FT) farming. The modelled yield was factored (75%) to simplify comparison with the field trial yields, which were reported with 15% water content. The comparison of soil C is given in Figure 3. The field trial values was 4.47 kg C m-2 for CF and 4.51 for OF in 1988 and 3.28 and 4.01 respectively in 2003 (Riley et al. 2008). Both modelled CF and OF soil C increase with time, though CF does so very slow compared to OF. While both the modelled practices raised the soil C content, both field trials observed a reduction in soil C content during the period. The observed reduction of soil C was greater in CF than in OF. The ratio CF:OF between modelled soil C in 2003 is 0.77 and the corresponding field trial ratio is 0.82.

! 12! Organic farming’s role in adaptation to and mitigation of climate change

Figure 3: Comparison between modelled soil carbon in conventional (CF) and organic (OF) farming compared to field trial values of conventional (CF-FT) and organic (OF-FT) farming Leaching of N from the modelled results and the field trials are shown in Figure 4. Average values in the field trials for the period 1990-97 were 34.7 and 28.8 kg N ha-1 year-1 for CF and OF respectively (Korsaeth and Eltun 2000). The average ratio of leaching between 1990-97 was lower in OF, with a ratio to CF of 0.64 in the modelled result and 0.83 in the field trial. While the leaching in CF seems to decrease, it seems to increase in OF. The fluctuations in OF seems to be less than in CF.

Figure 4: Comparison between modelled N leakage in conventional (CF) and organic (OF) farming compared to field trial N leakage of conventional (CF-FT) and organic (OF-FT) farming The impact of different types of fertilizer on soil C is shown in Figure 5. If only applying synthetic fertilizer (CF) the soil C rises but at very slow pace. If only applying the N part of manure the rise is even less prominent. When applying manure with only C, the rise is greater and applying manure with both C and N gives the highest soil C.

! 1b! Organic farming’s role in adaptation to and mitigation of climate change

Figure 5: Comparisons of different fertilizer types effect on soil carbon. Conventional farming (CF) represents synthetic fertilizer, and organic farming uses Manure (C+N). Manure (C) and Manure (N) are theoretical fertilizers in this model experiment that only contain the respective element. 4.2 Long time effect

Total yield of CF, OF and OF with organic soil (OF-OS) is shown in Figure 6. The yield of CF rises gradually from 1930, but seems to peak around 1980. Both OF-OS 1950 and OF 1950 show sharp declines when converted from CF, almost to the levels in the start of the century. After the decline, both increase again gradually. OF 1950 seems to level out around 1990, but OF-OS 1950 does not show the same pattern, instead continuing to rise. The fluctuations of yield between years seems bigger in both CF and OF 1950 compared to OF- OS 1950. The practice presented in the previous section, OF since 1990, also shows a sharp drop when converting from CF, with a much larger difference than the drops showed by OF and OF-OS since 1950.

Figure 6: Modelled yield of conventional (CF) and different variants of organic (OF) farming. OF, 1950 shows the yield if converted in 1950 and OF, 1990 if converted 1990. OF-OS, 1950 is OF since 1950 but with organic soil.

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! 1c! Organic farming’s role in adaptation to and mitigation of climate change

The modelled change in soil C is shown in Figure 7. The soil C in CF rises slowly from 3.3 in 1950 to 3.7 kg C m-2 in 2006 while the soil C in the organic practices rises more rapidly, achieving values of 5.7, 5.4 and 4.9 kg C m-2 for OF 1950, OF-OS 1950 and OF 1990 in the year 2006, respectively. Both organic practices from 1950 seem to level or peak around 1990, while the OF 1990 is still rising in 2006. OF 1950 has a general higher soil C content than OF-OS 1950. The rise in OF 1990 when converted seems faster than the rise of the organic practices in 1950.

Figure 7: Modelled soil carbon of conventional (CF) and different variants of organic (OF) farming. OF, 1950 shows the rate if converted in 1950 and OF, 1990 if converted 1990. OF-OS, 1950 is OF since 1950 but with organic soil. A comparison between modelled ecosystem C exchange, NEE, is given in Figure 8. Negative values mean a net flow of C from the atmosphere to the soil. Over the whole period, CF acts as a very small sink (0.004 kg C m-2 year-1) while all the OF practices act as sources. Since the OF practices increased soil C more than the CF (Figure 7), the difference is probably due to the applied organic fertilizer in OF. The organic fertilizer does not count as an uptake in the model but it provides the soil with more organic matter out of which some will be decomposed, leading to increased releases of C to the atmosphere compared to CF.

! 1^! Organic farming’s role in adaptation to and mitigation of climate change

Figure 8: Modelled net ecosystem exchange (NEE) of conventional (CF) and different variants of organic (OF) farming. OF, 1950 shows the rate if converted in 1950 and OF, 1990 if converted 1990. OF-OS, 1950 is OF since 1950 but with organic soil. The modelled N pool is given in Figure 9. All practices lead to increased soil N, but while the pool in CF only increases slightly the pools in OF rises faster and to a greater extent.

Figure 9: Modelled soil nitrogen pool of conventional (CF) and different variants of organic (OF) farming. OF, 1950 shows the rate if converted in 1950 and OF, 1990 if converted 1990. OF-OS, 1950 is OF since 1950 but with organic soil. The leakage of N is shown in Figure 10. The leaching of N in CF is rather stable until 1950, where it begins to rise, until it peaks around 1980 after which it diminishes again. Both OF practices increase the leakage over time and does not seem to peak like CF. This might be due to the higher total level of soil N in OF (Figure 9). As seen both in Figure 6 and Figure 8, the OF-OS 1950 has less variation than the OF 1950 and the CF.

! /0! Organic farming’s role in adaptation to and mitigation of climate change

Figure 10: Modelled nitrogen leaching of conventional (CF) and different variants of organic (OF) farming. OF, 1950 shows the rate if converted in 1950. OF-OS, 1950 is OF since 1950 but with organic soil. As soil carbon increases, the soil type gradually changes towards a more organic soil with different soil characteristics such as a higher water holding capacity and a different thermal diffusivity. To illustrate the difference between an organic soil and a soil with low organic content, modelled plant available water (May-September) is presented in 11. OF-OS has almost three times as high average during 1950-2006 as CF, 238 and 86 mm m-2, respectively. The difference between OF and CF is much smaller, but OF has an average of 1.5% more plant available water (ca 86 and 84 mm m-2) during the same period.

Figure 11: Modelled plant available water in conventional (CF) and different variants of organic (OF) farming. OF, 1950 shows the rate if converted in 1950. OF-OS, 1950 is OF since 1950 but with organic soil. OF, 1950 is barely visible behind CF. A comparison between tilled and non tilled OF and CF regarding yield and soil carbon is given in Figure 12 and Figure 13 respectively. The non tilled organic farming (OF-NT) gives lower yields than the OF, with an average ratio of 0.89 against OF for the period 1950-2006 and 0.93 for the period 1996-2006 (Figure 12). When comparing soil C, OF-NT has a higher value than OF with a ratio of 1.04 for the period 1950-2006 and 1.07 for the period 1996- 2006 (Figure 13).

! /1! Organic farming’s role in adaptation to and mitigation of climate change

Figure 12: Comparison between modelled yield of conventional (CF), organic (OF) and organic no till (OF- NT) farming

Figure 13: Comparison between modelled soil carbon in conventional (CF), organic (OF) and organic no till (OF-NT) farming

! //! Organic farming’s role in adaptation to and mitigation of climate change

5 Discussion 5.1 Effects of organic farming

5.1.1 A question of yield?

The role of OF in feeding the world both now and in the future is a subject of debate, where one side claims that OF simply does not yield enough to be able to support a growing population with changing dietary demands. The other side claims that yield is not the main question we should focus on when addressing food related issues, instead emphasising the need to make more of the food that is produced available, reduce losses in the production chain and rearrange diets as a way forward. The actual yield gap has also been showed to be less than what was previously thought, and also that there is potential to increase the productivity of OF, especially in developing countries. When speaking about food security, pure yield is also not the only aspect since yield stability and food sovereignty also plays large parts, especially in the face of climate change (FAO 2013a). Though there has been many calls for increased productivity and yields in agriculture (The Royal Society 2009), increased productivity also needs to take total sustainability into account (Reganold and Wachter 2016) as well as mitigation of GHG (FAO 2014b). Whether agricultural production is seen as decoupled from ecosystems or dependent on them will probably influence how agriculture will progress in the future. The summation of agricultural knowledge presented by the IAASTD (2009), stresses the need for ecosystem maintenance as necessary for long term food production and calls for management systems that maximize production without compromising sustainability.

5.1.2 Resilience

Resilience aspects of agriculture will be increasingly important with climate change. The total resilience of local, regional and global agriculture is not only dependent on physical resilience against such things as droughts or changes in growing season, but also depends on socio-economic factors and even though addressing physical resilience is the most important action towards increasing resilience in some cases, addressing social or economic issues could be more effective in other cases. OF could be more resilient than CF against climate change either because of heightened physical resilience – by utilizing more diverse agroecosystem and building soil quality or by being less dependent on external inputs, such as synthetic fertilizer or pesticides. It is very important, however, to state that even though OF utilizes and relies on practices that often heighten resilience, these practices are not limited to OF and a lot of them are commonly utilized in CF as well. While OF is often limited by definitions and certificate regulations, different CF practices have a greater span of practices and can in turn be more or less resilient. As discussed in the Definitions and explanations chapter, the main difference between an OF practice and a CF practice is how resilience is managed (if they are biologically diversified or chemically intensive). Whereas OF strives to prevent the need for direct measures, e.g. by building an agroecosystem with internal biological control of insects, CF relies on direct measures, such as pesticides, as a way of directly affecting outbreaks.

As briefly mentioned in the resilience chapter, the availability of cheap P for agricultural use will probably greatly diminish during this century. The implications will affect global agriculture in many ways, and farms relying on external inputs might have a harder time adapting to the changes. Maintenance of the current soil P pools will probably be increasingly

! /`! Organic farming’s role in adaptation to and mitigation of climate change important and since P leaches as particles via soil erosion or drainage, factors that reduces these, such as increased SOC, will probably be even more important in the future.

5.1.3 Soil organic carbon

Soil carbon sequestration is recognized both as a climate change mitigation strategy and as an important factor for soil restoration and improvement. The level of soil C in agricultural soils is mainly dependent on the management practices though it is also dependent on climate and soil texture. The amount of SOC is directly linked to many resilience aspects, such as holding capacity of nutrients and water, resistance to erosion or the presence of a diverse soil biota. Many of the discussed practices that increase SOC, such as the use of organic instead of synthetic fertilizers, use of legume based leys and cover crops, are used to a wider extent in OF than in CF and are thus the main explanations as to why OF could increase SOC.

Though it seems like SOC carbon on average rises during OF, it is not always the case and several studies in the above-mentioned meta reviews show the opposite e.g. the field trial in Apelsvoll, where both CF and OF led to decrease in SOC (Figure 3). As observed by Leifeld and Fuhrer (2010) it is also important to not equate C sequestration in agricultural fields directly to net uptake of C from the atmosphere. This would mean that if the SOC in OF rises only due to the C in the applied organic fertilizers, the net C for the production of the manure has to be taken into account as well. If the land where the manure-producing animals graze or where the fodder is cultivated loses SOC over time, it is simply a rearranging of existing soil C pools and no net sequestration. If, however, the area where the animals’ food originates from does not lose soil C or if the contents are stable, there is a net uptake and a net sequestration of C.

When speaking about soil carbon sequestration and improvement of soil health, biochar is a topic that is receiving more and more attention and was thus described alongside SOC since they influence the soils in similar ways. By applying biochar the soil C can increase faster than if only changing management practices, and since it is more recalcitrant than average SOC it can play a major role as a C sequestering technique. Since biochar could e.g. increase the effect of applied fertilizers (Glaser et al. 2015) and favour mycorrhiza abundance (Warnock et al. 2007), biochar might have the possibility to improve both OF and CF.

5.1.4 Biodiversity

The expansion and intensification of agriculture has led to large losses of biodiversity on all scales (Millenium Ecosystem Assessment 2005). Many of the problems are associated with large scale monocultures, farm specialization and pesticides, according to the (IAASTD 2009). They further address the need for biodiversity maintenance as a crucial topic for a sustainable agriculture. Biodiversity is important for the resilience of an ecosystem and higher biodiversity in OF is one of the reasons given to explain why OF might be more resilient than CF. Since biodiversity is a key aspect for agroecosystem management in OF it is usually promoted in several ways (IFOAM n.d.). These include practices such as both temporal and spatial crop rotations, leys, intercropping and the use of cultivars with wide gene pools. The lack of use of synthetic fertilizer and synthetic pesticides are also listed as key factors for promoting biodiversity.

! /a! Organic farming’s role in adaptation to and mitigation of climate change

5.1.5 Farming practices and greenhouse gases

The agricultural sector is a large emitter of GHG but one that also has a large potential to mitigate emissions. Whether OF or CF is more climate smart regarding emissions is not clear. The emissions per area are almost always lower in OF but regarding emissions per product, the results tend to differ. The comparison of non-CO2 GHG reported by Skinner et al. (2014) is very interesting since they state that although the emission per product was higher in OF due to yield differences, a reduction of the yield to less than 17% would mean that the emission per product would be lower as well.

Regarding the question of whether indicators (such as GHG emission or eutrophication) per yield or indicators per area is the best measure to estimate the effects of agriculture, Mondelaers et al. (2009) emphasise that both have their respective places. The area aspect is important when addressing the impacts on local ecosystems, since the caused effects are based on absolute values (e.g. leached N per area). The product aspect is important when addressing total efficiency regardless of local effects.

The production of synthetic fertilizer in CF is a large contributor to GHG emission, and the mentioned experiment comparing synthetic and organic fertilizer by Liu et al. (2015) is noteworthy since it showed that the emissions of synthetic fertilizer based agriculture were higher than manure based agriculture, although enteric fermentation and methane emissions were taken into account.

According to a simple estimate by Gattinger et al. (2012), global OF could sequester 0.4 Gt C yr-1. Lal (2004) lists the potential of soil carbon sequestration to be between 0.4 and 1.2 Gt C yr-1 and Smith (2016) estimates that soil carbon sequestration and biochar could mitigate 0.7 Gt C yr-1 each. When optimizing land management in LPJ-GUESS for carbon sequestration, Olin et al. (2015a) found the global potential to be 0.08 Gt C yr-1 compared to the standard modelled values. These findings suggest that C sequestration in soils has the potential to mitigate climate change. According to Wollenberg et al. (2016), the agricultural sector should aim to mitigate emissions by between 0.25 and 0.37 Gt C yr-1 up to 2030 to stay within the stated 2°C goal, corresponding to 4-5% of the total mitigation needed. They continue with stating that without taking soil C sequestration into account but implementing mitigation strategies available today, agriculture could mitigate between 0.06 and 0.11 Gt C yr-1 up to 2030, or 20-40% of their set goal. This indicates that soil C sequestration will probably play a major role when addressing agricultural mitigation of GHG. Indeed, when including more agricultural related potential mitigation aspects, such as soil C sequestration and reducing land use change, and decreasing food loss and waste and shifting diets, Wollenberg et al. (2016) estimated the total mitigation potential to be between 1.36 and 2.45 Gt C yr-1, or 27% of the mitigation needed across all sectors.

5.1.6 Summation

With three planetary boundaries passed and more approaching (Rockstrom et al. 2009), societies will have to adapt in several ways. Both the IAASTD (2009) and the FAO (2013a) state that the world’s agriculture today stands before an important choice of paths and that substantial changes have to be made to create a truly sustainable agriculture that can continue to provide ecosystem services. More focus on ecosystem management will be needed and agroecological practices are presented as a way to create a more resilient and climate smart agriculture.

! /:! Organic farming’s role in adaptation to and mitigation of climate change

Resilience against climate change in agriculture is complex and encompasses physical resilience as well as economic and social resilience. It is thus hard to separate one aspect, but since they are interconnected a positive change in one part might lead to positive changes elsewhere as well.

OF has been presented as a practice that increases agricultural resilience, not only physical but social and economic as well. It is crucial, however, to stress that the individual factors presented in this thesis that increase resilience, such as the increase of SOC or less reliance on external inputs, is not limited to OF and that many of them are utilized in CF as well. Agriculture management practices are neither black nor white. The greatest benefit of OF, according to Peter Borring, a Swedish farmer that practises both OF and CF, is that it creates a benchmark for all agriculture that CF always has to compare itself with, leading to developments in both (Casserlöv 2016).

The market sale of organic food and products has seen sharp rises during the last years and the rise is projected to continue. Although the area used today for OF is small globally, it will likely increase with increasing demand of products and incentives from municipalities or states. It is therefore important to assess the different environmental impacts of different management practices to evaluate whether the claimed benefits are true, if the practices are scalable and what the effects of large scale utilization would be. An example of a scale related problem is the reliance in OF on livestock manure. Since OF relies on manure to a greater extent than CF, it raises the question of how a potential global conversion to OF might influence the utilization of livestock, if we at the same time need to limit our consumption of meat as outlined earlier in the report (Smith 2015; Springmann et al. 2016).

5.1.7 Comparison with field trials

The modelled yields were generally higher than the field trial yields, except in the case of OF during 1990-99 (Figure 2). The difference in yield in the field trials (0.59) and in the modelled yields (0.37) for 1990-99 can be compared to the average difference of wheat yields of 73% with a spread of 40-130% reported by Ponisio et al. (2015). The average yield gap is larger than that reported by Badgley et al. (2007), but Ponisio et al. (2015) state that the observed yield gap between OF and CF is largest in cereals. In relation to this, both modelled and a field trial differences seems to be plausible.

Both modelled CF and OF leads to increase of soil C (Figure 3) but the field trials report losses for both systems. This could either indicate that the model is too general for mimicking the field trial and needs more factors taken into account, that the model experiment did not resemble the field trial closely enough (Tables 1 & 2), or that the management of the field trial is not representative for the location. Since the model uses historical values for most of the variables, a calibration against field properties (e.g. soil texture, SOC content) before the start of the model might improve the results. Even though the field trial and the model yielded different results, there is an interesting connection between them. In the modelled results, soil C increased more in OF than in CF and in the field trial soil C in OF decreased less than in CF, which could indicate that OF might promote accumulation of soil C in some cases and lessen the loss rate in other cases.

The results of examining different types of fertilizer presented in Figure 5 is very interesting since it relates to the question whether C sequestration in OF is mainly caused by added C from manure, as described by Leifeld and Fuhrer (2010). Since the manure (C+N) results in

! /2! Organic farming’s role in adaptation to and mitigation of climate change the highest soil C rate, it seems plausible to assume that although a large part of the soil C does originate from the manure (as showed by manure (C)), the application of manure also enhances sequestration rates compared to synthetic fertilizer. Whether the accumulation of soil C represents an overall net uptake is dependent, as mentioned earlier, on whether the areas used for grazing/fodder production releases or accumulates C.

5.1.8 Long time effect

The modelled long term yields presented Figure 6 shows interesting results. One is that the yield drops substantially when the management practice is switched to OF, although it quickly starts to rise again. This switch induced yield drop followed by gradual increase has also been seen e.g. in field trials conducted by the Rodale Institute (Pimentel et al. 2005; Rodale Institute n.d.) The drop and increase is outlined as a result of gradual build up of biological soil health by MacRae et al. (1990). However, Martini et al. (2004) rejected this idea and instead claimed that the inability to produce with full potential the first year after such a CF to OF transition might be due to a lack of OF knowledge in the part of the farmer. Since the modelled yield does not take management knowledge into account, the drop and following increase might instead be explained by changes in soil chemistry, particularly changes to the C:N ratio, and the slower release of nutrients from organic fertilizer compared to synthetic.

The soil C levels in Figure 7 are important since they could indicate saturation rates depending on practices. The CF seems to be stable in terms of soil C, and the OF that started in 1950 seems to level out around 1990, thus indicating that the maximum sequestration potential for this site with these management practices has been achieved. If so, it took 40-50 years from the start of the management to the saturation point, which can be compared to the estimates of 20-100 years reported in a study by Freibauer et al. (2004).

The NEE presented in Figure 8 shows that the CF is, at farm level, neither a clear source nor a sink of C while the OF emits more C compared to the uptake. As already stated, the C in the organic fertilizer is not counted as an uptake in the model, but results in more C available for decomposition in the soil. To investigate the NEE further, the origin of the C in the manure has to be taken into account as well.

The leakage of N presented in Figure 10 is not consistent with the discussion in the chapter regarding GHG emission, where it was stated that the leakage per area was lower in OF. This might be due to lack of implemented factors in the model, such as crop rotations in both CF and OF or the use of leys in OF.

Regarding the difference between tilled and non tilled OF presented in Figure 12 and Figure 13, it is interesting to note that no tillage seems to promote soil C sequestration while at the same time depress yields. No tillage agriculture is usually regarded as a way of increasing soil C since tillage increases microbial decomposition of C. As described in the Method chapter, this is how tillage is treated in LPJ-GUESS (Olin et al. 2015a). Lower decomposition rates lead to a higher equilibrium point and a bigger sequestration potential.

5.1.9 Errors and improvements

It is hard to assess how accurate the model is when comparing with only one field trial, but overall the result seems similar. The exception is the soil C dynamics, were the model

! /b! Organic farming’s role in adaptation to and mitigation of climate change indicates an increase of C, particularly in OF, but the field trials reported losses in both systems.

As described in the Methods chapter, the modelled practices were greatly simplified compared to the field trials (see Table 1 & 2). An incorporation of conducted crop rotations (with more crop functional types) with the corresponding fertilizer amount would likely refine the model output, as would implementation of the local climate and soil characteristics. However, since the LPJ-GUESS is mainly a global model, and these implementations are very fine scale and vary greatly with location, a wider implementation (e.g. smaller cell size of climate and soils) would likely be both very complex to incorporate and result in a computationally heavy model. Some key aspects that could maybe be implemented however, are typical crop rotations and in particular, crop rotations with legume base leys. Crop rotations are vital to OF, but they are used in CF as well, though not as extensively and affect the soil properties in several ways.

Since OF might be more reliant on soil health and soil biodiversity (e.g. earthworm or mycorrhiza abundance) than CF, it would be interesting to compare the results of LPJ- GUESS, which is a large scale general model, with a soil process model at plot scale to see if there are differences in outcome. The role of mycorrhiza in agriculture and how different management practices might affect it (e.g. tillage and synthetic fertilizer) could be an interesting implementation of this.

5.1.10 Future use of models in agriculture

With climate change and an increasing population there are escalating needs to assess strategies that on one hand provide for different human needs while on the other hand can minimize environmental and climate change damages. By using models, the impacts of different scenarios can be tested and evaluated against each other and thus provide basis for policy, implementations and mitigation measures.

An interesting thought would be to incorporate models of different complexity (from soil process models up to a DGVM such as LPJ-GUESS) with social and economic models with the goal of modelling total agroecosystem resilience. Since these would be both extremely complex and also very site specific, the main goal would not necessary be to quantify resilience globally but to investigate were focus is needed at the local or regional scale. At some places the main focus may need to be put in soil health and in other places it might be needed in managing seed policies. By not only doing qualitative assessments but also modelling quantitative effects, agroecosystem models that also take socio-economic aspects into account could provide better understanding of the relationships between physical and socio-economic agroecosystem resilience against climate change.

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! /c! Organic farming’s role in adaptation to and mitigation of climate change

6 Conclusion

Organic farming shows many of the qualities that are important for a resilient and sustainable agriculture while the most widespread forms of conventional farming generally have higher environmental costs and lower resilience. Organic farming might also be more climate smart than conventional due to its lower emissions and a higher possibility to sequester carbon. The factors that increase resilience, however, are not limited to organic farming and are used to varying degrees in conventional farming as well. Climate change resilience in agriculture is intricate and what is most important in some contexts might be less important in others. By using models, different management practices can be scaled and individual measures can be assessed, thus creating support for or evidence against proposed policies and measures. In order to create agriculture systems more suitable for the future in terms of climate change and food security, a higher focus has to be put on the management of agroecosystems, with a greater acknowledgement of all the ecosystem services provided by agriculture.

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! /^! Organic farming’s role in adaptation to and mitigation of climate change

7 References

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organic management - A global meta-analysis. Science of the Total Environment, 468: 553-563. DOI: 10.1016/j.scitotenv.2013.08.098 Smith, B., D. Wårlind, A. Arneth, T. Hickler, P. Leadley, J. Siltberg, and S. Zaehle. 2014. Implications of incorporating N cycling and N limitations on primary production in an individual-based dynamic vegetation model. Biogeosciences, 11: 2027-2054. DOI: 10.5194/bg-11-2027-2014 Smith, P. 2004. Carbon sequestration in croplands: the potential in Europe and the global context. European Journal of Agronomy, 20: 229-236. DOI: 10.1016/j.eja.2003.08.002 Smith, P. 2015. Malthus is still wrong: we can feed a world of 9–10 billion, but only by reducing food demand. Proceedings of the Nutrition Society, 74: 187-190. DOI: doi:10.1017/S0029665114001517 Smith, P. 2016. Soil carbon sequestration and biochar as negative emission technologies. Global Change Biology, 22: 1315-1324. DOI: 10.1111/gcb.13178 Smith, S. E., D. J. Read, and J. L. Harley. 1997. Mycorrhizal symbiosis. San Diego, Calif.: Academic Press. Springmann, M., H. C. J. Godfray, M. Rayner, and P. Scarborough. 2016. Analysis and valuation of the health and climate change cobenefits of dietary change. Proceedings of the National Academy of Sciences, 113: 4146-4151. DOI: 10.1073/pnas.1523119113 Steffen, W., P. J. Crutzen, and J. R. McNeill. 2007. The Anthropocene: Are humans now overwhelming the great forces of nature. Ambio, 36: 614-621. DOI: 10.1579/0044- 7447(2007)36[614:taahno]2.0.co;2 Swedish Environmental Protection Agency, 2016. The environmental objectives: Annual review of Sweden's environmental quality objectives and milestones in 2016. Report 6707. (In Swedish). The Royal Society, 2009. Reaping the benefits: Science and the sustainable intensification of global agriculture. Report. Tilman, D. 1998. The greening of the green revolution. Nature, 396: 211-212. DOI: 10.1038/24254 Tom, G. H. 2007. Available Water Capacity and Soil Organic Matter. In Encyclopedia of Soil Science, Second Edition, 139-143. Taylor & Francis. Trewavas, A. 2002. Malthus foiled again and again. Nature, 418: 668-670. DOI: 10.1038/nature01013 Tscharntke, T., A. M. Klein, A. Kruess, I. Steffan-Dewenter, and C. Thies. 2005. Landscape perspectives on agricultural intensification and biodiversity - ecosystem service management. Ecology Letters, 8: 857-874. DOI: 10.1111/j.1461-0248.2005.00782.x Tuck, S. L., C. Winqvist, F. Mota, J. Ahnstrom, L. A. Turnbull, and J. Bengtsson. 2014. Land-use intensity and the effects of organic farming on biodiversity: a hierarchical meta-analysis. Journal of Applied Ecology, 51: 746-755. DOI: 10.1111/1365- 2664.12219 Tuomisto, H. L., I. D. Hodge, P. Riordan, and D. W. Macdonald. 2012. Does organic farming reduce environmental impacts?--a meta-analysis of European research. J Environ Manage, 112: 309-320. DOI: 10.1016/j.jenvman.2012.08.018 UNEP, 2014. Assessing global land use: Balancing consumption with sustainable supply. UNEP, Report. UNFCCC, 2015. Paris Agreement. UNFCCC, Report. United Nations population division, 1999. The World at Six Billion. Report. United Nations population division, 2015. World Population Prospects 2015. Report.

! `b! Organic farming’s role in adaptation to and mitigation of climate change van der Heijden, M. G. A., J. N. Klironomos, M. Ursic, P. Moutoglis, R. Streitwolf-Engel, T. Boller, A. Wiemken, and I. R. Sanders. 1998. Mycorrhizal fungal diversity determines plant biodiversity, ecosystem variability and productivity. Nature, 396: 69-72. van Groenigen, J. W., I. M. Lubbers, H. M. J. Vos, G. G. Brown, G. B. De Deyn, and K. J. van Groenigen. 2014. Earthworms increase plant production: a meta-analysis. Scientific Reports, 4: 6365. DOI: 10.1038/srep06365 Villa, T. C. C., N. Maxted, M. Scholten, and B. Ford-Lloyd. 2005. Defining and identifying crop landraces. Plant Genetic Resources: characterization and utilization, 3: 373- 384. DOI: 10.1079/pgr200591 Walker, B., C. S. Holling, S. R. Carpenter, and A. P. Kinzig. 2004. Resilience, Adaptability and Transformability in Social-ecological Systems. Ecology and Society, 9. Warnock, D. D., J. Lehmann, T. W. Kuyper, and M. C. Rillig. 2007. Mycorrhizal responses to biochar in soil - concepts and mechanisms. Plant and Soil, 300: 9-20. DOI: 10.1007/s11104-007-9391-5 Wezel, A., and V. Soldat. 2009. A quantitative and qualitative historical analysis of the scientific discipline of agroecology. International Journal of Agricultural Sustainability, 7: 3-18. DOI: 10.3763/ijas.2009.0400 Whipps, J. M. 2004. Prospects and limitations for mycorrhizas in biocontrol of root pathogens. Canadian Journal of Botany-Revue Canadienne De Botanique, 82: 1198- 1227. DOI: 10.1139/b04-082 Winqvist, C., J. Ahnstrom, and J. Bengtsson. 2012. Effects of organic farming on biodiversity and ecosystem services: taking landscape complexity into account. In Year in Ecology and Conservation Biology, eds. R. S. Ostfeld, and W. H. Schlesinger, 191-203. Wollenberg, E., M. Richards, P. Smith, P. Havlík, M. Obersteiner, F. N. Tubiello, M. Herold, P. Gerber, et al. 2016. Reducing emissions from agriculture to meet the 2°C target. Global Change Biology. DOI: 10.1111/gcb.13340 Woolf, D., J. E. Amonette, F. A. Street-Perrott, J. Lehmann, and S. Joseph. 2010. Sustainable biochar to mitigate global climate change. Nature Communications, 1: 1. DOI: 10.1038/ncomms1053 Zhu, Y., H. Chen, J. Fan, Y. Wang, Y. Li, J. Chen, J. Fan, S. Yang, et al. 2000. Genetic diversity and disease control in rice. Nature, 406: 718-722. DOI: 10.1038/35021046

! `c! Institutionen för naturgeografi och ekosystemvetenskap, Lunds Universitet.

Student examensarbete (Seminarieuppsatser). Uppsatserna finns tillgängliga på institutionens geobibliotek, Sölvegatan 12, 223 62 LUND. Serien startade 1985. Hela listan och själva uppsatserna är även tillgängliga på LUP student papers (https://lup.lub.lu.se/student-papers/search/) och via Geobiblioteket (www.geobib.lu.se)

The student thesis reports are available at the Geo-Library, Department of Physical Geography and Ecosystem Science, University of Lund, Sölvegatan 12, S-223 62 Lund, Sweden. Report series started 1985. The complete list and electronic versions are also electronic available at the LUP student papers (https://lup.lub.lu.se/student-papers/search/) and through the Geo-library (www.geobib.lu.se)

350 Mihaela – Mariana Tudoran (2015) Occurrences of insect outbreaks in Sweden in relation to climatic parameters since 1850 351 Maria Gatzouras (2015) Assessment of trampling impact in Icelandic natural areas in experimental plots with focus on image analysis of digital photographs 352 Gustav Wallner (2015) Estimating and evaluating GPP in the Sahel using MSG/SEVIRI and MODIS satellite data 353 Luisa Teixeira (2015) Exploring the relationships between biodiversity and benthic habitat in the Primeiras and Segundas Protected Area, Mozambique 354 Iris Behrens & Linn Gardell (2015) Water quality in Apac-, Mbale- & Lira district, Uganda - A field study evaluating problems and suitable solutions 355 Viktoria Björklund (2015) Water quality in rivers affected by urbanization: A Case Study in Minas Gerais, Brazil 356 Tara Mellquist (2015) Hållbar dagvattenhantering i Stockholms stad - En riskhanteringsanalys med avseende på långsiktig hållbarhet av Stockholms stads dagvattenhantering i urban miljö 357 Jenny Hansson (2015) Trafikrelaterade luftföroreningar vid förskolor – En studie om kvävedioxidhalter vid förskolor i Malmö 358 Laura Reinelt (2015) Modelling vegetation dynamics and carbon fluxes in a high Arctic mire 359 Emelie Linnéa Graham (2015) Atmospheric reactivity of cyclic ethers of relevance to biofuel combustion 360 Filippo Gualla (2015) Sun position and PV panels: a model to determine the best orientation 361 Joakim Lindberg (2015) Locating potential flood areas in an urban environment using remote sensing and GIS, case study Lund, Sweden 362 Georgios-Konstantinos Lagkas (2015) Analysis of NDVI variation and snowmelt around Zackenberg station, Greenland with comparison of ground data and remote sensing. 363 Carlos Arellano (2015) Production and Biodegradability of Dissolved Organic Carbon from Different Litter Sources 364 Sofia Valentin (2015) Do-It-Yourself Helium Balloon Aerial Photography - Developing a method in an agroforestry plantation, Lao PDR 365 Shirin Danehpash (2015) Evaluation of Standards and Techniques for Retrieval of Geospatial Raster Data - A study for the ICOS Carbon Portal 366 Linnea Jonsson (2015) Evaluation of pixel based and object based classification

methods for land cover mapping with high spatial resolution satellite imagery, in the Amazonas, Brazil. 367 Johan Westin (2015) Quantification of a continuous-cover forest in Sweden using remote sensing techniques 368 Dahlia Mudzaffar Ali (2015) Quantifying Terrain Factor Using GIS Applications for Real Estate Property Valuation 369 Ulrika Belsing (2015) The survival of moth larvae feeding on different plant species in northern Fennoscandia 370 Isabella Grönfeldt (2015) Snow and sea ice temperature profiles from satellite data and ice mass balance buoys 371 Karolina D. Pantazatou (2015) Issues of Geographic Context Variable Calculation Methods applied at different Geographic Levels in Spatial Historical Demographic Research -A case study over four parishes in Southern Sweden 372 Andreas Dahlbom (2016) The impact of permafrost degradation on methane fluxes - a field study in Abisko 373 Hanna Modin (2016) Higher temperatures increase nutrient availability in the High Arctic, causing elevated competitive pressure and a decline in Papaver radicatum 374 Elsa Lindevall (2016) Assessment of the relationship between the Photochemical Reflectance Index and Light Use Efficiency: A study of its seasonal and diurnal variation in a sub-arctic birch forest, Abisko, Sweden 375 Henrik Hagelin and Matthieu Cluzel (2016) Applying FARSITE and Prometheus on the Västmanland Fire, Sweden (2014): Fire Growth Simulation as a Measure Against Forest Fire Spread – A Model Suitability Study – 376 Pontus Cederholm (2016) Californian Drought: The Processes and Factors Controlling the 2011-2016 Drought and Winter Precipitation in California 377 Johannes Loer (2016) Modelling nitrogen balance in two Southern Swedish spruce plantations 378 Hanna Angel (2016) Water and carbon footprints of mining and producing Cu, Mg and Zn: A comparative study of primary and secondary sources. 379 Gusten Brodin (2016) Organic farming’s role in adaptation to and mitigation of climate change - an overview of ecological resilience and a model case study