Sources of organic carbon fueling carbon emissions from tropical reservoirs

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UPTEC W 16033

Examensarbete 30 hp

December 2016

Sources of organic carbon fueling

carbon emissions from tropical

reservoirs

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ABSTRACT

Sources of organic carbon fueling carbon emissions from tropical reservoirs

Gabriella Villamor Saucedo

For a sustainable energy supply, it is of importance to be aware about the environmental impacts from the different energy sources. Hydroelectric reservoirs in tropical areas have been found to emit more greenhouse gases (GHG) than reservoirs from boreal regions. Emerging economies such as Brazil, China and India have developed extensive plans for future constructions of hydroelectric reservoirs, and most of them will be built in tropical regions. Methane (CH4) release has been identified as particularly significant, because it has a much stronger greenhouse gas potential than carbon dioxide (CO2). Therefore, there is a need for a better understanding about methane production in hydropower reservoirs, to develop strategies for the mitigation of the potential impact of hydropower on the climate.

Previous research has shown that not only organic matter (OM) from impoundment (flooded trees and soil) can be a substantial source for CH4 emissions from reservoirs, but also OM from other sources. Reservoirs can offer favorable conditions for primary production by aquatic plants, both phytoplankton and macrophytes, i.e. water-living vascular plants. The sustained long-term CH4 emission from tropical reservoirs, i.e. the emission after the flooded trees and soils are decomposed, could thus to a large degree be fueled by the production of new organic carbon (OC) by aquatic plants. This project examines the relative importance of autochthonous OC (originating from inside the system, i.e. aquatic plants) and allochthonous OC (originating from outside the system, i.e. from land) as a fuel for CH4 production in tropical reservoirs. The influence on the production of CO2 and CH4 of different amounts, types, and species of autochthonous sources and one allochthonous source from reservoirs around the area of Juiz de Fora, Brazil, were studied experimentally. There was a great variability in the production of CH4 and CO2 due to the source of carbon. The allochthonous contribution to CH4 production was negligible in comparison to the autochthonous sources. However, increasing amounts of autochthonous OC did not result in equal increases in CH4 production. Further, the degradation of the macrophyte P. stratiotes produced about five times more CH4 than that of phytoplankton, even though phytoplankton is generally considered as a more labile source. Also between different macrophyte species, a great variability in the extent of CH4 production was observed. The regulation of nutrient inputs to reservoirs could help to mitigate CH4 emission. Also, regulating the growth of the invasive species P. stratiotes, which had a particularly big potential for high CH4 production, could be useful for reservoir CH4 emission management. In addition, the degradation of macrophytes on land results in less production of CO2-equivalents than in oxygen-poor bottom waters, therefore harvesting of macrophytes could be another way of reservoir emission management.

Keywords: tropical reservoirs, decomposition, autochthonous carbon, allochthonous

carbon, tropical macrophytes, methanogenesis

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REFERAT

Bidraget av olika sorters organiskt material till produktionen av växthusgaser i tropiska vattenkraftsmagasin

Gabriella Villamor Saucedo

För en hållbar energianvändning krävs det kunskaper om de olika energislagens miljöeffekter. I tillväxtekonomier såsom Brasilien, Kina och Indien finns det idag stora planer för utbyggnaden av vattenkraftverk och de flesta planeras att byggas i tropiska områden. Tropiska vattenkraftsmagasin har resulterat i att generera högre utsläpp av växthusgaser än vattenkraftsmagasin i boreala områden. Särskilt emissionen av metangas (CH4) har varit signifikant hög, vilket är problematiskt ur klimatsynpunkt då den är en kraftigare växthusgas än koldioxid (CO2). Detta gör att det blir särskilt viktigt att förstå de processer i vattenkraftsmagasinen som kan bidra till metangasproduktionen.

Tidigare forskning har visat att organiskt material (OM) annat än det OM från dämning (såsom träd och mark), kan vara betydelsefull för produktionen av CH4 i vissa magasin. Tropiska vattenkraftsmagasin kan ha hög potential för tillväxten av akvatiska växter, både växtplankton och kärlväxter (makrofyter) och nedbrytningen av växtbiomassan kan möjligen bidra till emissionen av CH4 från kraftverksmagasin. Syftet med denna studie var att förstå den relativa betydelsen av autoktont OM (som härstammar från magasinet, dvs vattenväxter) och alloktont OM (som härstammar från land) för produktionen av CH4 och CO2, där fokus främst lagts på bildning av metangas. Projektet, utfört i området omkring Juiz de Fora, Brasilien, undersökte bidraget av olika typer, arter och halter av autoktont OM för nedbrytning i olika miljöer genom oxiska/anoxiska inkuberingsexperiment.

Variabiliteten för produktionen av växthusgaser var stor mellan de olika organiska materialen. Bidraget från alloktont OM till metanproduktion var försumbart i jämförelse med autoktont OM. Skillnaden mellan de olika typerna av autoktont material, dvs mellan makrofyt och växtplankton, var stor. Makrofyten P. stratiotes producerade fem gånger högre halter av CH4 än växtplankton, trots att växtplankton generellt anses vara lättare att bryta ner. Variabiliteten i växthusgasbildning mellan olika arter av makrofyter var stor, både i anoxisk och oxisk miljö. Typen och kvaliteten av det organiska materialet har i och med detta en nyckelroll för produktionen av metangas, vilket är en direkt följd av dess näringsinnehåll och organiska materialets kemiska sammansättning. Därför kan det vara viktigt att reglera näringstillförsel till kraftverksmagasin, för att förutom undvika övergödning, även reglera tillväxt av vissa invasiva arter såsom P. stratiotes, som har stor metangaspotential. Dessutom bidrar nedbrytning av makrofyter på land med mindre produktion av CO2-ekvivalenter än i syrefattiga bottenvatten, vilket bidrar till att skördandet av makrofyter kan vara en metod för att minska klimatpåverkan från vattenkraftsmagasin.

Nyckelord: tropiska vattenkraftsmagasin, metangasproduktion, autoktont OM, alloktont

OM, tropiska makrofyter

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PREFACE

This master thesis of 30 ECTS was performed as the finishing part of the Master Program in Environmental and Water Engineering at Uppsala University (UU). It has been carried out on the behalf of the Department of Ecology and Genetics, Limnology, UU in cooperation with Laboratory of Aquatic Ecology at the Federal University of Juiz de Fora (UFJF) in the state of Minas Gerais, Brazil. The project was sponsored by the Swedish International Development Cooperation Agency (SIDA) and performed as a Minor Field Study (MFS). The project is part of a ERC funded research project HYDROCARB (“Towards a new understanding of carbon processing in freshwaters: methane emission hot spots and carbon burial in tropical reservoirs”) led by Sebastian Sobek (Dep. of Ecology and Genetics, Limnology, UU). The report has a 2-year embargo on publication. The supervisor of the project was Charlotte Grasset (Laboratory of Aquatic Ecology, UFJF) and the subject reviewer Sebastian Sobek (Dep. of Ecology and Genetics, UU). There were several people involved in the process of making this project possible. I want to give my sincere thanks to all involved. First and foremost, I would like to thank Charlotte Grasset for helping me with all preparations and effort for sampling, experiments and data analyses throughout the project. Also for the good time in Juiz de Fora and always being there to help me! I would also like to give a big thanks to Raquel Mendoça (UFJF, UU), who helped me with all practicalities in Brazil, sampling of phytoplankton and giving inputs about the project. Thanks to Sebastian Sobek for all very valuable guidance during the project! I also want to thank the working group for Tropical Ecology at Uppsala university, who through Ronny Alexanderson, Biology Education Centre, UU, awarded me the MFS-scholarship.

I want to direct my sincere gratitude to the entire team of the ERC project and the laboratory of Aquatic Ecology in Juiz de Fora (UFJF) that I have met both in Brazil and in Sweden. Being so friendly and helpful with ideas and making the process both interesting and fun! I have learned a lot.

Finally, a huge thanks to my family, especially my sister Claudia, and friends who always encouraged and believed in me during all the years at Uppsala university and wherever I found my way to end up.

Uppsala, November 2016

Gabriella Villamor

Map published with authorization of © OpenStreetMap contributors. All other figures and photos were created by the author.

UPTEC W 16033, ISSN 1401-5765. Published digitally at the Department of Earth Sciences, Uppsala

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POPULÄRVETENSKAPLIG SAMMANFATTNING

För en hållbar energianvändning krävs det kunskaper om de olika energislagens miljöeffekter. I utvecklingsländer såsom Brasilien, Kina och Indien finns det idag ett stort behov av energi i och med snabbt ökad ekonomisk tillväxt. Därför planeras en stor utbyggnad av flertalet vattenkraftverk för att klara av det framtida energibehovet. En av miljöeffekterna av vattenkraftsmagasin är utsläpp av växthusgaser. Globalt sett släpper vattenkraftsmagasin ut ungefär 4 % av de totala utsläppen av växthusgaser från alla slags vattensystem på land. Vattenkraftsmagasin i tropiska områden har visat sig generera högre utsläpp av växthusgaser än vattenkraftsmagasin i boreala områden och metangas har blivit identifierat som den växthusgas som är speciellt viktig, på grund av dess starkare klimatpåverkan jämfört med koldioxid. Detta gör att det blir speciellt viktigt att förstå de processer i vattenkraftsmagasinen som kan bidra till metangasproduktion.

Vattenkraftsmagasin är speciella eftersom det finns organiskt material sedan skapandet av dammen där stora delar land med träd och annan växtlighet har blivit översvämmat med vatten. Efter skapandet av ett vattenkraftsmagasin sker även en tillförsel av organiskt material utifrån (alloktont bidrag) från exempelvis erosion och transport av material med floder. Det sker även en produktion av organiskt material i systemet (autoktont bidrag) i och med primär produktion, tillväxten av vattenlevande växter och alger. Syftet med projektet var att förstå den relativa betydelsen av det organiska material som härstammar utifrån vattenkraftsmagasinet och det organiska materialet producerat i vattenkraftsmagasinet, som källa för produktionen av metan och koldioxid. Störst fokus lades på produktionen av metangas på grund av dess större klimatpåverkan. Även en undersökning av effekten av nedbrytning i olika miljöer gjordes under syrefria/syresatta samt våta/torra omständigheter. Material för att studera nedbrytningen och bildning av metangas samlades in från fyra olika vattenkraftsmagasin i området nära Juiz de Fora i delstaten Minas Gerais, Brasilien. Materialet bestod av sediment (som bestod av organiskt material utifrån vattenkraftsmagasinet), växtplankton samt olika arter av vattenlevande växter (producerade i vattenkraftsmagasinet). För att studera metangasproduktion av de olika organiska materialen gjordes olika behandlingar med växtplankton och vattenlevande växter med och utan sediment i syrefri miljö. Även behandlingar i syresatt miljö gjordes för att undersöka produktionen av koldioxid och metangas under våt och torr nedbrytning.

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GLOSSARY

Allochthonous Originating from outside the system, i.e. from land Autochthonous Originating from inside the system, i.e. from the reservoir Impoundment The result from damming of water such as a reservoir

GHG Greenhouse gases

OC Organic carbon

OM Organic matter

Mineralization Decomposition of organic matter to inorganic compounds Methanogenesis Anaerobic respiration from methanogens (bacteria that

produce methane)

DOC Dissolved organic carbon

DIC Dissolved inorganic carbon

TOC Total organic carbon

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TABLE OF

1. INTRODUCTION

For a sustainable energy supply, it is of importance to know about the environmental impacts from the different energy sources. One of the environmental impacts of reservoirs is the emission of greenhouse gases (GHG) and it is evident that hydroelectric reservoirs are not free from these emissions (Rosa & Schaeffer 1995; Galy-Lacaux et al. 1999; Barros et al. 2011; Fearnside 2015; Scherer & Pfister 2016). Reservoirs have been estimated to emit about 4% of the carbon emissions from all inland waters (Barros et al. 2011) and in a recent study it was estimated that reservoirs stand for 1.5% of the global anthropogenic climate impact from GHG emissions (Deemer et al. 2016). Methane (CH4) release from reservoirs has been identified as particularly significant, because it is a much stronger GHG than carbon dioxide (CO2) (Giles 2006; Demarty & Bastien 2011). Earlier measurements from hydroelectric reservoirs taken in tropical areas in Brazil have in some cases shown significant high GHG emissions (IPCC 2011). The higher emissions from tropical reservoirs in comparison to reservoirs in boreal regions have also been confirmed in a recent global estimate on carbon footprint from hydroelectric reservoirs (Scherer & Pfister 2016). Therefore, because of the climate footprint, there is a concern in the future building of hydroelectric dams and other reservoirs (Santos et al. 2005; Giles 2006). The largest source of renewable energy in the world today is hydropower. Though most developed countries have used up their potential, developing countries still have a large potential to expand their share of hydropower. Emerging economies such as Brazil, China and India have already developed extensive plans for future constructions. In tropical regions, the high temperatures favor decomposition (Cardoso et al. 2013) and potentially contribute to high methane emissions (West et al. 2012). Any management strategies to reduce GHG emissions from reservoirs are dependent on understanding the sources of organic carbon (OC) fueling the CH4 production in reservoirs (Demarty & Bastien 2011; IPCC 2011).

During impoundment of a reservoir, large areas of vegetation and soil are flooded. The organic carbon (OC) from these sources, can through different decomposition processes contribute to GHG emissions. Additional to flooded OC, both allochthonous (i.e. OC originated from outside the system) and autochthonous (i.e. OC originated from inside the system) have been shown to contribute to emissions of GHG in reservoirs (Huttunen et al. 2003; Rosa et al. 2004). It is also been presented that trophic status is the strongest regulator for methanogenesis in lakes (West, Creamer, et al. 2015) and autochthonous sources such as algae in compare to allochthonous OC has been found to be a preferred substrate by decomposing microbes (Guillemette et al. 2013). The decomposition of different OC does not occur separately in nature and could therefore influence each other. The relation between the decomposition of labile and refractory organic matter (OM) in soils and sediments is called priming effect. If there is a priming effect for methanogenesis, the allochthonous contribution of CH4 in presence of autochthonous sources (more labile) will be higher than that of the sediment decomposing on its own (the control).

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also readily degrades at anoxic conditions, it can fuel CH4 production and have a high potential for higher emissions. CH4 emission from reservoirs could to a large degree be fueled by autochthonous production of new OC and can thus be reduced by management of nutrient supply to aquatic primary production (Deemer et al. 2016). There are many invasive species of macrophytes in Brazilian reservoirs, causing problems due to expansive growth, which also can increase the amount of labile OM available for methane production. However, the decomposition condition of macrophytes, wet or dry, can be altered through different management practices. Previous studies have shown that macrophytes decomposed in moist environments decompose substantially faster than decomposition in dry environments (Enríquez et al. 1993). One can therefore hypothesize that decomposition of macrophytes in dry condition leads to less GHG production. The objective of this project was to understand the relative importance of autochthonous and allochthonous carbon fueling CH4 production in tropical reservoirs. The importance of autochthonous sources such as phytoplankton and macrophytes for fueling CH4 emissions was studied in more detail.

Q1. Are there differences in CH4 production rates between different types and amounts of autochthonous sources?

Q2. What is the relative importance of autochthonous and allochthonous OC in fueling

CH4 production in reservoirs?

Q3. Are there differences in CO2 and CH4 production rates when different macrophytes decompose under different conditions?

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2. THEORY AND BACKGROUND

2.1 PRODUCTION OF GREENHOUSE GASES IN RESERVOIRS

The gases CO2, CH4 and N2O stand for most the global GHG emissions and have a strong influence on the radiative properties of the atmosphere. Since the end of the 19th_century, emissions of these gases have increased and it has been declared to be extremely likely that it is caused by anthropogenic activities (IPCC 2013). The levels of CH4 emissions have had a global stable growth and the anthropogenic contribution stands for 50-65% of the total global amount emitted. The growth of CH4 emissions is particularly an issue because of its much stronger global warming potential (GWP) than for CO2. CH4 has a GWP of 84 times stronger than CO2 on a 20 year period and 28 times stronger on a 100 year period (IPCC 2013).

In the global carbon cycle, a significant amount of terrestrial carbon gets transported from land to fresh water systems (lakes, rivers and reservoirs) where the carbon is sequestered in sediments, released as CO2 or CH4, or transported out to the ocean (Cole et al. 2007). Humans have altered many watershed systems with the implementation of reservoirs by changing the streamflow of rivers and modifying the landscape changing the aquatic ecosystem and the carbon processes. Reservoirs differ from natural lakes because for example of the higher sediment deposition rates which can diminish the oxygen exposure time of organic particles (Mendonça et al. 2012). Decomposition, respiration, photosynthesis and other aquatic ecosystem properties are important factors determining the conversion of organic carbon to inorganic carbon or vice versa. These mechanisms can influence whether the carbon gets buried in the sediment or will be emitted as CO2 or CH4. This has a direct impact on the carbon fluxes from aquatic ecosystems as the GHG emissions per unit area could even be larger than natural emissions from the surrounding land (Cole et al. 2007). There is also an indication that fresh water systems including reservoirs and lakes contribute to more CH4 emission to the atmosphere than the oceans (Bastviken et al. 2004).

The GHG emissions from aquatic systems originate to a large degree from the degradation of OM in the water column and in the sediments. The sediment OM has three pathways: mineralization (decomposition or oxidation of OM), re-suspension into the water column, and sediment burial. Mineralization results in the production and emissions of GHG. The mineralization pathways (anaerobic or aerobic) that lead to CO2 or CH4 production, depend on the environmental conditions such as access to electron receptors, mixing regimes, thermal structure and oxygen levels (Cardoso et al. 2013). These factors influence which kind of decomposition will prevail. If there are anoxic conditions, methanogenesis can occur. According to Conrad (2009) microbial production from methanogenic archaea stands for the majority of CH4 emissions in the atmosphere. The degradation goes through several steps, were microbes degrade the substrate into smaller molecules, breaking down polymers into glucose and amino acids. Later, other bacteria take these products and convert into hydrogen (H2), CO2 and acetate (CH3COOH). In the process of methanogenesis, the methanogenic microbes use H2, CO2 and acetate producing both CH4 and CO2 (Eq. 1; Eq. 2).

CO2 + 4H2 CH4 + 2H2O Eq. 1

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The produced CH4 can also be further oxidized into CO2, both aerobically and anaerobically by reducing for example iron, sulfate or nitrate (Conrad 2009; Ferry 2010). According to Abril et al. (2005) GHG emissions mainly originate from GHG production at the bottom of the reservoir. In lakes, the deposition of readily degradable OM onto the sediment increases decomposition rates, which leads to lower oxygen levels in the bottom water due to respiration, which favors methanogenesis (Huttunen et al. 2002). Enhanced autochthonous organic input can contribute to a depletion of oxygen in freshwater systems because of increased mineralization in the water column. The increased decomposition activity, stimulating consumption of rapid dissolved oxygen in the water column, can thus result in stimulating methanogenesis (Huttunen et al. 2002; Marinho et al. 2009; Furlanetto et al. 2012). In reservoir sediments, the organic carbon mostly consists of inorganic particles originating from soil erosion, terrestrial plant litter, flooded soil, and autochthonous OM. The time period right after an impoundment of a reservoir often show high emission production because of the large amount of storage of organic matter in flooded soils, which is decomposed after flooding (Giles 2006). It is important to take the time scale of impoundment into account. The age of the reservoir has a large impact on temperature, stratification, oxygen levels, water residence time and amount of carbon (Fearnside 2002). The decomposition of flooded organic matter can be the major source of carbon even 10 years after impoundment (Abril et al. 2005), but with time, the stock of flooded biomass gets exhausted and emissions decrease (Guérin et al. 2008; Barros et al. 2011).

2.1.1 Emission pathways for methane in reservoirs

The CH4 produced in aquatic sediments can be emitted to the atmosphere through three main pathways: (i) ebullition, (ii) diffusive flux and (iii) plant emission (Bastviken et al. 2004). (i) Through ebullition, the release of gas bubbles, CH4 gets exported from the sediment directly to the atmosphere. The CH4 bubbles form in the sediment due to the low solubility of CH4, and the release rate of bubbles from the sediment is a function of hydrostatic pressure and temperature (Demarty & Bastien 2011). (ii) Through diffusive flux, CH4 is transported from the sediment to the water column. In this stage, a large part of the CH4 can get oxidized to CO2 by methane-oxidizing microbes. The CH4 left in the water column can be emitted by diffusive flux to the atmosphere from the water column. Weather conditions such as wind speed and rainfall, but also mixing events in the lake (i.e. when the stratifications, created due to temperature and density differences, break) affect the diffusive flux (Demarty & Bastien 2011). If the reservoir is stratified, CH4 can be stored in the hypolimnion (bottom water layer) and emitted under a mixing event. Also, when the water in hydroelectric dams passes through the turbines, the water goes through a large depressurization by the turbines, and the pressure drop causes an immediate release of CH4 (Kemenes et al. 2007; Fearnside 2015). (iii) Through plant-mediated emission, CH4 gets emitted through leaves, stems and flowers of emergent macrophytes, i.e. aquatic plants that are rooted in the sediment (where the CH4 is produced) and extend over the water surface (Sebacher et al. 1985).

2.2 SOURCES OF ORGANIC CARBON AND DIFFERENCES IN

DECOMPOSITION

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The OC in the sediments is dominated by particulate organic carbon (POC) while the water column it is dominated by dissolved organic carbon (DOC) (Cole et al. 2007). The decomposition of organic matter in reservoirs is related to many aquatic ecosystem functions such as source of organic matter, oxygen concentrations, pH and the quality of organic matter. Physical factors as for instance temperature and redox potential can also influence the decomposition. Temperature is especially important for the degradation of organic carbon averting carbon burial in sediments (Gudasz et al. 2010; Song et al. 2013). Increasing biomass from autochthonous sources, because of increased human nutrient input, has been shown to correlated with the production rates of CH4 and CO2 in lakes (Huttunen et al. 2002; Marinho et al. 2009; Conrad et al. 2010; West et al. 2012). The nutrient composition of carbon (C), nitrogen (N) and phosphor (P) in relation to each other (C:N:P) of the source has been shown to correlate with decomposition rates when comparing plants from different species (Enríquez et al. 1993). It is more likely that the autochthonous OM (low C:N ratio) will be degraded in the sediment than the allochthonous OM (high C:N ratio), as it has been shown that autochthonous OM is less likely to be buried in the sediments but rather fueling decomposition (Sobek et al. 2009). Differences in mineralization rates depends on both the quality and quantity of the autochthonous and allochthonous material and directly influences the carbon cycling in the aquatic ecosystem. There is a relation between differences in organic matter and differences of mineralization rates in sediments (Cardoso et al. 2013; Gudasz et al. 2015). The organic matter from autochthonous OM is more reactive than the allochthonous land based OM that is more refractory. The decomposition of these different OM does not occur separately in nature and could therefore influence each other. The relation between decomposition of labile and refractory OM in soils and sediments is called priming effect. The priming effect has been mainly studied in soil science, although there are strong suggestions that it occurs in aquatic systems too (Guenet et al. 2010). Priming effect found in aquatic systems have been mostly positive, i.e. autochthonous OM stimulates the decomposition of allochthonous OM from sediments. A previous study (Guillemette et al. 2013) showed for example that decomposition of algae OC may stimulate the incorporation of allochthonous carbon for microbial biomass. Other studies have also shown negative priming effects from experiments with phytoplankton and sediment (Gontikaki et al. 2013).

2.2.1 The role of macrophytes

Aquatic plants large enough to be observed by the naked eye are called macrophytes. These aquatic plants can be floating, emergent or submerged in the water, and their influence on the aquatic ecosystems is important for the carbon cycling. In tropical and sub-tropical systems, extensive growth of macrophytes is common (Bini et al. 1999; Santino et al. 2015) because of the high temperatures (van der Heide et al. 2006). Because of the high production of biomass, this leads to a high amount of decomposable material. The increased decomposition has direct implications by changing the ecosystem with for example lowering the oxygen level and increasing availability of nutrients (Chiba de Castro et al. 2013).

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lower oxygen levels due to increased decomposition. Macrophytes can also lower the exchange rates of oxygen from the atmosphere to the water column because of the physical barrier from the leaves (Jacobs & Harrison 2014). This directly affects the production of GHG emission by stimulating both CH4 production and oxygen consumption. The first thing that happens during the decomposition of plants is leaching, where the leaves goes through a rapid mass loss and plant biomass is extracted into the water as DOC. The leaching is continuous for substrates that are submerged under water, which influences mass loss (Padial & Thomaz 2006). Leaching is followed by microbial decomposition, and mechanical and invertebrate fragmentation (J R Webster & Benfield 1986; Chimney & Pietro 2006). To understand all aspects on decomposition of organic matter and GHG emissions in aquatic systems, the autochthonous OC from decomposed macrophytes is an important factor to take into account (Cunha-Santino & Jr 2013). According to Li et al. (2012) site conditions does not have as strong effect on macrophyte decomposition as differences in macrophyte species. The detritus quality of the plant, which is due to content of for example nutrients and cellulose, is directly coupled with plant traits, where invasive species tend to have high decomposition rates (Enríquez et al. 1993; Song et al. 2013). These traits are different between, for example, emergent, floating and submerged species, as the chemical composition and accessibility of OC varies (Santino et al. 2015). The carbon in the tissue of macrophytes is found in the cell wall as building blocks for materials such as lignocellulose and lignin. High content of N and P shows positive correlation with decomposition rates, whereas lignin, cellulose, high C/P and C/N rations, show negative correlation with decomposition rates (Enríquez et al. 1993; Chimney & Pietro 2006). The macrophyte P. stratiotes have for example a C:N:P ratio of 1:3.7:9.6 which together with low fiber content is assumed to have high detritus quality (Bottino et al. 2015), and therefore likely to have high decomposition rates. Macrophytes can sometimes decompose in a dry state, for example during a drought or falling water levels (common in hydroelectric reservoirs), or due to management practices that imply removing macrophytes from the reservoir to land. These anthropogenic influences are important factors for macrophyte decomposition, as long term droughts leave macrophytes drying in the margin of the reservoirs which changes the conditions of decomposition (Padial & Thomaz 2006). A previous study on decomposition from macrophytes has determine that moist or wet plant material decompose faster than dry material (Enríquez et al. 1993).

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These invasive macrophytes grow in most Brazilian reservoirs and have been shown to impact ecosystem services negatively. In some reservoirs in Brazil, there can be large production of macrophyte biomass which can interfere with the ecosystem service such as impediment of water flow, hindrance of transportation by boats and recreational activities. E. crassipes has been identified to affect many countries in tropical areas negatively, although it also has beneficial properties such as cleaning polluted water (Labrada et al. 1994).

2.2.2 Phytoplankton degradation

Phytoplankton production depends on interrelated factors such as sunlight for photosynthesis, nutrients, hydrological characteristics and morphological factors. The carbon from phytoplankton has been recognized as good quality substrate for decomposition (Bertilsson & Jones Jr. 2003; Hanamachi et al. 2008). Due to the generally low C:N ratio of phytoplankton, and the absence of structural tissues like lignin or cellulose, phytoplankton cells are easily degraded. Previous incubations of degrading phytoplankton suggests that the DOC from phytoplankton is immediately used by bacteria and therefore very labile (Hanamachi et al. 2008). Phytoplankton biomass quality, due to lipid content, has also been shown to enhance rates of methane production (West, McCarthy, et al. 2015). This can imply that phytoplankton is more degradable than macrophytes, but there have also been cases were macrophytes have shown higher lability than phytoplankton (Bertilsson & Jones Jr. 2003). The influence of differences in species of phytoplankton has been found to be negligible in comparison to biomass quantity for methanogenesis rates (West, McCarthy, et al. 2015).

Reservoirs in sub- and tropical system are often linked to algae blooms because of often being eutrophic (due to anthropogenic activity in the watershed), though depending on purpose and location of the reservoir. For reservoirs, residence time is an important factor for algae production because its effect on nutrient loading, OC burial and turbidity (where Figure 1. A = Eichhornia crassipies, B = Pistia stratiotes and C = Salvinia auriculata are macrophytes that often prevail in Brazilian reservoirs. Picture is taken from the hydroelectric reservoir Simplicio,

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low turbidity is beneficial). In the case of reservoirs, they tend to have bigger watersheds and higher surrounding anthropogenic activity, which also can affect higher productivity of phytoplankton. Specifically, alteration of water levels, which is common for hydropower, can also cause turbidity. Turbidity alone has been found to explain 17 % of the variance in phytoplankton biomass in Brazilian reservoirs (Rangel et al. 2012). Land use is also an important factor for nutrient dynamics and phytoplankton production, where for example the areal size of the watershed can influence the nutrient load (Wagner et al. 2011).

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3. METHOD

3.1 STUDY SITE AND SAMPLING

The sampling of material was conducted in April 2016 at four sites, all located in the subtropical area close to Juiz de Fora in the state of Mina Gerais, Brazil (Figure 2). The sampling sites were the hydroelectric dam Simplicio, the two drinking water reservoirs João Penido and Chapéau d’Uvas, and a small pond at Parque do Museu Mariano Procópio. All experiment work was conducted at the University of Juiz de Fora, Brazil.

Figure 2. The red dot presents the location in the state of Minas Gerais (MG), Brazil where all the sampling and the experiments were conducted (OpenStreetMap, 2016).

The allochthonous sediment was taken from the reservoir Chapéau d’Uvas which is an oligotrophic drinking water reservoir mainly influenced by terrestrial material due to low internal primary production. Undisturbed sediment cores were sampled with an Uwitec corer equipped with hammer device. The top layer, 3-4 cm, from the sediment cores were sliced from 3 cores and used for the experiment. Sediment was also sampled with the same method from Simplicio, Chapéau d’Uvas and João Penido for preparation of the inoculum.

The macrophytes, common in Brazilian reservoirs (Thomaz et al. 1999), were sampled from 2 reservoirs (Table 1). Only senescent leaves (semi-degraded yellow and brown leaves) were collected as these are the leaves that would normally settle onto the sediment rather than fresh produced leaves.

Table 1. The collected material from each site

Site Collected Material

Chapéau d'Uvas allochthonous sediment

Simplicio P. stratiotes, S. auriculata, E. crassipes, sediment

João Penido N. indica, P. ferrugineum, S. auriculata, sediment

Parque do Museu Mariano Procópio phytoplankton

After collection, the macrophytes were washed in tap water to remove any other organic source such as dirt and sand. As size of the material influence decomposition rate, the macrophytes where cut into 1x1 cm pieces which approximately corresponds to the size of the leaves of S. auriculata.

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The phytoplankton was sampled from a small pond at Parque do Museu Mariano Procópio in the city of Juiz de Fora (Figure 3). The phytoplankton community consisted, in order of decreasing abundance, of: Microcystis sp., Desmodesmus sp, Ankistrodesmus,

Chlorella sp., Scenedesmus sp., and Synura sp. The sample was kept refrigerated in the

dark to avoid too much degradation before incubation.

3.2 INCUBATION EXPERIMENT

The incubation experiments involved different treatments studied under anoxic and oxygenized conditions using different autochthonous sources. Experiment 1 consisted of anoxic incubations with increasing amounts of autochthonous material, phytoplankton and P. stratiotes, together with allochthonous sediment. The assumption was that the relation between increasing amount of autochthonous source and CH4 production is linear, i.e. that the added amount of autochthonous OC results in a corresponding increase in OC mineralization (CH4 and CO2 production). Experiment 2, consisted of two parts, A and B. Part A consisted of anoxic incubations with 5 different species of macrophyte, where two of these were also used for part B. In part B, there was the incubation under anoxic wet (part B1), oxygenized wet conditions (part B2) and dry conditions (part B3). O2, CO2, CH4 and TOC (total organic carbon) for the different sources of organic carbon and sediment was measured.

3.2.1 Solid phase analyses

For determination of the water content, the plant material was dried in an oven at 60 °C for more than 24 h. The weight measurements before and after drying gave the water content. The dried plant material was later grinded for analysis of total organic carbon content (TOC) in a TOC-L Series Total Organic Carbon Analyzer SSM-500A. The fresh mass mfresh [g], total organic carbon TOC [g/g] and water content k [g/g] were used to

ensure equal carbon content between source 1 and source 2 using Eq. 3. The results were used in calculation to determine how much fresh mass to add in the vials, ensuring that the vials would have equal carbon content. In Experiment 1, the TOC of the allochthonous sediment was used as a reference while in Experiment 2 it was the macrophyte P.

ferrugineum.

𝑚1,𝑓𝑟𝑒𝑠ℎ∗𝑇𝑂𝐶1

𝑘1

=

𝑚2,𝑓𝑟𝑒𝑠ℎ∗𝑇𝑂𝐶2

𝑘2 Eq. 3

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3.2.2 Incubation preparations

100 ml glass vials with 2 cm rubber stoppers and aluminum seals were used for the incubations. An artificial lake water medium was made in the laboratory to create equal aquatic environment for all incubations (Table 2). The artificial lake water medium was prepared according to Lehman (1980) with additional nutrients (KH3PO4 and NH4NO3) (Attermeyer et al. 2014). After weighing the trace elements, the flask was filled with distilled water and filtered. 10 ml of the trace element solution was then added to the artificial lake water medium.

Table 2. Content of the artificial lake water

Artificial Lake Water Medium 1000 ml water

Trace element solution (ml) 10

CaCl2·2 H2O (mg/L) 20

MgSO4·7 H2O (mg/L) 15

NaHCO3 (mg/L) 20

KH2PO4 (µg/L) 15.8

NH4NO3 (mg/L) 4.57

Trace Element Solution 1000 ml water

ZnSO4·7 H2O (g/L) 1 MnCl2 (g/L) 0 H3BO3 (g/L) 3 CoCl2·6 H2O (g/L) 2 CuCl2·2 H2O (g/L) 0.1 NiCl2·6 H2O (g/L) 0.2 Na2MoO4·2 H2O (g/L) 0.3

For preparation of the inoculum (the bacterial community to able decomposition), sediment was sampled using the top layer of the sediment and then mixed together. The inoculum was prepared from different sites to ensure that all incubations would have the same microbial communities represented from all sites where the macrophytes and allochthonous sediment were collected. When preparing the glass vials for incubation, ~ 0.03 g of inoculum was added to all treatments. 30 ml artificial lake water medium was added to both Experiment 1 and Experiment 2 A together with the autochthonous sources (Figure 4; Figure 5).

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Figure 4. The treatments in Experiment 1 with content and increasing amount of autochthonous source. Experiment 2 consisted of two parts with the aim to answer questions Q1 and Q3 presented in the introduction. In the first part A, 5 different species of macrophytes were investigated separately for between-species differences of CH4 production at anoxic conditions species (Salvinia auriculata from two different sites was also compared). For the treatments in part B, Eichhornia crassipies and Salvinia auriculata were used. The two species were incubated in both anoxic/wet (B1), oxic/wet (B2), oxic/dry (B3) (Figure 5). All treatments had 3 replicates each and were incubated for 40 days. The carbon content added was calculated in relation to TOC of 1.5 g of P. ferrugineum, such that all treatments contained the same amount of TOC. In the dry treatment, 3 ml of 10 times concentrated water medium was added for creating equivalent nutrient content for all incubations. The small amount of water evaporated during the first days of incubation, which ensured dry conditions. A control with one replicate in oxygenized condition of water medium + inoculum was also performed.

Figure 5. The treatments in Experiment 2 presenting the content of the anoxic part A and the oxic part B: anoxic/wet (B1), oxic/wet (B2), oxic/dry (B3).

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To ensure anoxic/oxic conditions, oxygen levels in one of the replicates of each treatment were also measured. To ensure oxygenized vials in Experiment 2 B, air was initially pumped into the vials. This method was not effective, because it led to that the samples dried out (which was compensated), and was therefore terminated. Although not pumping in air, the vials had high oxygen levels (>18 % O2).

3.2.3 CO2 and CH4 measurement and analysis

An Ultra-Portable Gas Analyzer (Los Gatos Research) was used for measurements of CH4 and CO2. Before the measurements, the vials were vigorously shaken to ensure equilibrium between gas- and water phase (Karlsson et al. 2007; Guérin et al. 2008). Measurements were performed taking 1 ml of gas from the headspace with a syringe through the rubber stopper and inserting the gas into the Ultra-Portable Gas Analyzer once a week. For the vials that were flushed every week (Experiment 2), 2 ml was taken. For the flushed samples, measurements were taken 3 times a week to enable calculation of a production rate of CO2 and CH4. The CO2 and CH4 data extracted from the Ultra-Portable Gas Analyzer was processed by calculating the area of the emission peaks to acquire the total amount CO2 and CH4 [mol] using equations derived from calibration with standard solutions (Appendix B).

3.2.4 Oxygen spots

In one of each replicate in Experiment 1 and all replicates in part B2 and B3 of Experiment 2, optical oxygen sensor spots were placed to able measurement of oxygen levels. The oxygen sensor spot was attached to the inner surface of the glass vials. An optical sensor was then used to measure O2 % from the spot inside the glass vial, reading the oxygen level of the headspace. The oxygen spots in Experiment 1 were used to ensure anoxic environment in the vials. For the treatments in Experiment 2, all open vials were placed with oxygen spots to be able to measure oxygen consumption hence the amounts of CO2 and CH4 would be too low for analysis. To be able to measure decomposition of the oxic incubations, the vials where closed so that oxygen consumption could be measured over time. The closed incubations lasted 3-5 days during three times under the total incubation time of 40 days. Before reading the values, the vials were vigorously shaken to ensure equilibrium.

3.3 STATISTICAL METHODS AND OTHER CALCULATIONS

For the evaluation of the data from the experiments all plots and statistical methods where performed in the statistical computing program R (R Core Team 2015).

3.3.1 Analysis of variance (ANOVA)

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CO2 over time. An example of the parameters from ANOVA is presented in a table with results showing the significance and error values (Table 3).

Table 3. Example of computations and results from an ANOVA. df = degrees of freedom, SS = sum of squares, MS = mean square, F = F-ratio, k = number of values, N = numbers of outliers and p-value (95

% confidence interval) (Helsel & Hirsch 1992).

ANOVA TABLE

Variables df SS MS F-ratio p-value

x k-1 SSx MSx MSx/MSE p

Error (E) N-k SSE MSE

Residuals N-1 Total SS

For Experiment 1, the incubation with increasing concentrations of carbon, ANOVA was used for the creation of two linear models. The models were created to answer to Q1 and Q2 from the introduction, i.e. to compare CH4 production between different autochthonous sources and estimate how much CO2 and CH4 is produced from the sediment.

To compare the CH4 production from the different sources, CH4 production (normalized for TOC content) was used in a linear model (Eq. 4). The categorical variable was “type OC” (phytoplankton or macrophyte (i.e. factor). The continuous variable, “day”, was represented by the time series, day 5–31. If the categorical variable “typeOC” has a significant effect on the CH4 production in the linear model, it will mean that CH4 production differs between the two “typeOC”. Interaction between “typeOC” and day (day:typeOC) was also included. This interaction will be significant if the slope of the increase of CH4 with time will differ between the two types of OC.

CH4 ~ day + typeOC +day:typeOC Eq. 4

To estimate the allochthonous contribution to the CH4 produced, a linear model was performed according to Eq. 5. The categorical variable used was “type OC” (phytoplankton or macrophyte) as for Eq. 4. The continuous variables were day (5-31) and the concentration of TOCauto (1- 1.75). The estimates of the model could give the CH4 production from the sediment when no autochthonous source is added (TOCauto = 0). Three interactions were included in the model and tested for significance: (1) Interaction between type of OC and day (day:typeOC). (2) Interaction of concentration of TOCauto with time (day:TOCauto) (significant if the slope of the increased CH4 with TOCauto concentration would be different with time). (3) Interaction between TOCauto and type of OC (typeOC:TOCauto) (significant if increasing amount of CH4 with concentration TOCauto would differ between the two types of autochthonous source).

CH4 ~ day + typeOC + TOCauto + day:typeOC + day:TOCauto + typeOC:TOCauto Eq. 5

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3.3.2 Carbon loss

When OM is decomposed and production of GHG takes place, there is a loss of carbon mass from the decomposed source. To calculate the carbon loss (C loss) due to emission, the initial TOC added to the vials and the amount of accumulated CO2 µmol and CH4 µmol were used according to Eq. 6. The molar mass of carbon 12 g/mol was used. C loss [g] = (TOCsed+TOCauto) [g] – ((CO2[µmol] + CH4[µmol]) ·10-3_·_{12 [g/mol]) [g]}

Eq. 6

3.3.3 Experiment 2 B - Calculation of CO2-equivalents

The oxygen consumption measured in the vials of Experiment 2 B2 and B3 had do be translated to CO2 production for comparison with B1 (measurement of CO2 and CH4). The respiratory quotient (RQ) was used to calculate CO2 from O2. The RQ is a relation between consumption of O2 and CO2 produced (Eq. 7, expressed in molar units) which depends among other on the composition and quality of the organic matter. Because there was no knowledge about the specific composition of the sources, an assumption that the substrate would be completely mineralized (as for glucose) was made. This is equal to RQ = 1 (Dilly 2001).

𝑅𝑄 = 𝑂_{2 𝑐𝑜𝑛𝑠𝑢𝑚𝑒𝑑}/𝐶𝑂_{2 𝑝𝑟𝑜𝑑𝑢𝑐𝑒𝑑} Eq. 7

Measurements of % O2 for the incubations during 3-5 days gave data points for calculation of rates with linear regression. The rate of O2 consumption was converted to CO2 which gave |O2/day|=|CO2/day|.

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4. RESULTS

4.1 RELATIVE IMPORTANCE OF DIFFERENT AUTOCHTHONOUS SOURCES

4.1.1 Solid phase and carbon content

After measurements of water content and total organic content, the results showed that the sediment had a low carbon content with only 1.2 % TOC (Table 4). The autochthonous OM sources had a range of 15-25 % TOC. The carbon content was similar between the autochthonous sources, though the differences in water content were large. The TOC for the fresh mass was calculated according to Table 5 so that the same TOC content was added to all the vials.

Table 4. Analysis of total organic carbon (TOC) and the water content for the allochthonous sediment (Chapéau d’Uvas) and the autochthonous sources: phytoplankton and the different species of

macrophytes.

% TOC % water content

Sediment (Chapéau d'Uvas) 1.2 3.4

Phytoplankton 25.3 44.7

Eichhornia crassipes 20.7 8.9

Salvinia auriculata (Simplicio) 15.9 11.6

Salvinia auriculata (João Penido) 20.8 12.5

Nymphoides indica 21.8 9.8

Polygonum ferrugineum 22.0 9.6

Pistia stratiotes 16.2 18.6

4.1.2 Variability in CH4 production between different types and amounts of

carbon

The amount of produced methane had variations between the two observed sources, in both trend over time and magnitude (Figure 6). The resulting amount of CH4 (in µmol) produced for phytoplankton had a magnitude of four to five times lower than that for the macrophyte, even though the TOC content was identical between the treatments. The production of methane highly increased the first 30 days for both autochthonous sources.

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Figure 6. Amount of CH4 (µmol) from day 2 to 46 for the macrophyte Pistia stratiotes (M) and

phytoplankton (P). The lines show the mean of the replicates, which values are shown as points. The different colored lines represent treatments with different amounts of autochthonous total carbon

(TOCauto), increasing with 1.25·0.014 g TOC for each of the four levels.

To determine the differences in methane production between type of autochthonous source, an ANOVA was performed. Measurement points from day 5-31 were chosen to only include the part of the production that was linear, and to avoid the decline in CH4 production after day 30 (Figure 6). The effect of type OC and the interaction day:type OC was significant (p < 0.05) (Table 6). This means that the difference in CH4 production between the macrophyte and phytoplankton was significant.

Table 5. ANOVA table with SS = sum of squares, MS = mean square, F = F-ratio and the p-value of the continuous variable day, the factor variable type OC and interaction

Day 1 1370944701 1370944701 820.2 2·10-16

Type of OC 1 1500539813 1500539813 897.8 2·10-16

Day:TypeOC 1 552151336 552151336 330.3 2·10-16

Residuals 76 127029519 1671441

Fitting linear regression to CH4 production rates that were normalized to the amount of OC resulted in the production rate for P. stratiotes at 735.9 CH4 µmol/gC·d (Eq. 8) and for phytoplankton 164.5 CH4 µmol/gC·d (Eq. 9).

CH4 (macro) = -2023.1 +735.9·[CH4/gC·day] Eq. 8

CH4 (phyto) = -514.2 + 164.5·[CH4/gC·day] Eq. 9

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The linear regression performed for the amount CH4 µmol/TOC g in relation to time (days) for the macrophyte and the phytoplankton (r2=0.96, p<2.2·10-16) illustrates the difference (Figure 7).

Figure 7. The difference between macrophyte (blue) and phytoplankton (green) for the estimated rates (dotted lines) obtained with Eq. 8-9 and the measured points from the replicates (dots) of CH4

(µmol/TOC g).

The accumulated amount of CO2 and CH4 produced in the phytoplankton treatment was very low in relation to P. stratiotes (Table 6). The maximum production of CO2 and CH4 for sediment shows that the production is small in comparison to the two autochthonous sources, especially for CH4. Calculation of C loss and measurements of pH were also made at the end of incubation. The C loss was calculated with the emission of CO2 and CH4. P. stratiotes had a total C loss between 40-60 % while phytoplankton had a loss of 7-10 %. The allochthonous sediment had a C loss of 3.3 %. For pH, the treatments with phytoplankton had much lower pH with a mean of pH 5.3 while the mean pH was 6.9 for

P. stratiotes.

Table 6. Resulting percentage of total C loss (calculated for carbon emitted in relation to added carbon), pH and maximum emission of CH4 and CO2 for phytoplankton (P), the macrophyte P. stratiotes (M) and

the allochthonous sediment.

Vial, xTOCauto Max CO2 µmol Max CH4 µmol Ctot loss % pH

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Evaluation of the difference in carbon production, for both CO2 and CH4, could be made with the ratio CH4 (µmol/day) /CO2 (µmol/day) for the different amounts and sources (Figure 8). Considering the production of CO2, the CH4 production is consequently higher than CO2 in all cases with a significant difference between the types of autochthonous sources (t-test, p<0.05). The ratio shows that for phytoplankton, there seems to be a slight decrease with amount added TOCauto, although for most cases the ratio is constant.

Figure 8. Bar plot of the ratio of CH4/ CO2 production with increasing TOCauto, from the 31st day of

incubation.

4.1.3 CH4 production from the degradation of different macrophyte species Experiment 2, part A, included incubation for five different macrophyte species to evaluate the difference in production of CH4 and CO2. A very large variation of CH4 production between the species was seen (Figure 9). Both quantity and shape of the curves differs strongly between species. Pistia stratiotes has a more exponential growth and

Nymphoides indica has a zero-methane production. The other species have all a linear

production. There is a clear difference in curve shape for Pistia stratiotes: when the vials were flushed with N2 gas every week, the CH4 production did not reach a plateau (Figure 9), compared to Figure 6, where vials were N2-flushed only at the beginning.

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4.2 ESTIMATION OF ALLOCTHONOUS CONTRIBUTION

The estimation of the allochthonous OC contribution to CH4 production was made with

ANOVA and linear regression. The linear model consisted of the categorical variables days and concentration, the factor variable typeOC and the interactions day:typeOC, day:TOCauto and typeOC:TOCauto from Eq. 4. For the ANOVA, all variables and interactions were significant (p < 0.05) (Table 7).

Table 7. Variables, degree of freedom (df), sum of squares (SS), mean square (MS), F-ratio and p-value from the ANOVA with Eq. 4 (with interaction typeOC:TOCauto)

day 1 1601301 1601301 747.3 2·10-16 type OC 1 1711708 1711708 798.8 2·10-16 TOCauto 1 99622 99622 46.5 2.26·10-9 Day:type OC 1 642156 642156 299.7 2·10-16 TOCauto:typeOC 1 26014 26014 12.1 8.4·10-4 Day:TOCauto 1 72648 72648 33.9 1.4·10-7 Residuals 73 156427 2143

The hypothesis was that the allochthonous contribution to CH4 is equal to the total CH4 produced when the concentration of autochthonous source is zero for the predicted parameters (TOCauto = 0). After comparison between models with and without interaction of TOCauto:day, the model with the interaction day:TOCauto was chosen because of less

Figure 9. Production of CH4 µmol/TOCfor different species of macrophytes between day 2-39. The lines represent the mean of the three replicates of each species and the dots represent every replicate.

TOC content in all vials was ~ 0.035 g.

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heteroscedastic residuals (Appendix A). The result from the linear model is presented in Table 8 and the parameters had a significant regression for the intercept α for phytoplankton and the parameter β (relation between type OC and time) for both sources (Appendix A). The allochthonous contribution was calculated for when TOCauto= 0 from the equations described (Table 8). The adjusted r2=0.96 and most variables had a significant regression (p < 0.05), except the intercept for macrophyte and TOCauto concentration.

Table 8. Linear model with ANOVA for CH4 (µmol) = α +β·day+γ·TOCauto. The error terms are shown ±

for each predicted variable.

Estimate α β γ

Macrophyte -47.7 ± 63.1 9.0 ± 2.9 -17.9 ± 44.4

Phytoplankton 184.0 ± 118.7 - 8.9 ± 1.1 -146.9 ± 7.4

A prediction for the contribution to CH4 production from the allochthonous OC source (sediment) could be made with the linear model for the different types of autochthonous sources (Figure 10). The model estimates that the contribution to CH4 from the allochthonous sediment OC differs for the two sources, the contribution decreases with time for phytoplankton (184 - 8.9·day) and increases with time for macrophyte (-47.7 + 9·day). The result from the incubation of sediment by itself shows that the values from just the allochthonous source were very low (close to 0) during the entire incubation.

Figure 10. Contribution of phytoplankton, macrophyte and sediment by itself in relation to the estimated allochthonous contribution. The estimates of allochthonous sediment show different estimates for

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4.3 DEGREGATION OF AUTOCHTHONOUS SOURCES UNDER DIFFERENT CONDITIONS

To determine the differences in carbon emissions from macrophytes degrading under different conditions (oxic and anoxic, dry and wet) production rates from Experiment 2, part B (Figure 5), were analyzed. Rates were calculated to compare degradation differences between anoxic and oxic/wet and oxic/dry conditions. To get the difference of the GWP100 in different environments, CO2-equivalents (CO2e) were calculated. The average rate was calculated from three different time periods during the days 5-40. The total amount was calculated from interpolation of the rates obtained for the three time periods. The amount from each time interpolation was used adding up to the accumulative total g CO2e. The results are shown in Figure 11. The anoxic treatments for both species had the highest rate and total CO2e. E. crassipies had consistently the highest rate of CO2e production during the entire incubation for all different conditions. There is also a clear pattern in differences of CO2e production rates between S. auriculata and E. crassipies decomposed in different oxygenized conditions where the wet treatment has the highest CO2e average rate and amount.

Figure 11. The bar plots present the rate (g CO2e/day) and total (g CO2e) accumulated CO2-equivalents

obtained from the incubations for each condition wet anoxic (anox/wet), wet oxic (ox/wet) and dry oxic (oxic/dry) and for each species from S. auriculata (S) and E. crassipies (E). The total (g CO2e) was the

accumulated produced CO2e over 40 days. Both CH4 and CO2 have been used in the calculation with

GWP100 to get CO2e.

The anoxic incubation with E. crassipies had especially high CO2e production rates because of higher CH4 production than S. auriculata (Figure 12). Even though the emission of CO2 was higher than CH4 (Figure 12), the GWP100 of methane is 28 times stronger, which influences the calculated CO2e-equivalents in Figure 11.

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Figure 12. The boxplot for the anoxic/wet incubation of S. auriculata and E. crassipies presents the variability in production of CH4 and CO2 (µmol/C·g) from day 5-40. The boxes represent the 1st quartile

(25 % of the data fall below) and 3rd_{quartile (75 % of the data fall above) of the dataset. The black line in}

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5. DISCUSSION

5.1 RELATIVE IMPORTANCE OF TYPE AND AMOUNT OF

AUTOCHTHONOUS OC SOURCES FOR CH4 PRODUCTION

Different types of decomposing organic carbon will contribute to different amounts of CH4 and CO2 production due to the different characteristics of the sources. The two types of autochthonous OC sources studied, macrophytes and phytoplankton, differ greatly in their biological and chemical characteristics. Phytoplankton are single-cell organisms, while macrophytes contain several specialized cells and thus different tissues, e.g. structural tissues composed of cells with high cellulose and lignin contents, vascular tissues, etc. However, the results from the incubations show that the anoxic decomposition of the macrophyte P. stratiotes emits more CH4 than that of phytoplankton (Figure 6), and with a five times higher production rate (Figure 7). The C loss of the total organic carbon, calculated from the beginning to the end of the incubation, also show the large difference in the amount of TOC decomposed between the sources. The C loss of the macrophyte was about 40% higher (Table 6). These results are unexpected since they contrast the theory that phytoplankton, due to higher lability (Hanamachi et al. 2008), would generate higher levels of carbon emissions. This comparatively high CH4 production from a macrophyte, or the comparatively low CH4 production from phytoplankton, can have many explanations. P. stratiotes is a macrophyte that is considered to have a high detritus quality due to low fiber content and C:N:P ratio (Bottino et al. 2015). As high nutrient content in a substrate has a positive correlation with decomposition rate (Enríquez et al. 1993; Chimney & Pietro 2006), this could explain the higher CH4 production in P. stratiotes (Figure 6, Figure 7). Methane production is also influenced by many processes and factors, for example, low pH inhibits methanogenesis (Liu & Whitman 2008). Therefore, the low pH (pH 4.9-5.8) measured in the phytoplankton treatment (Table 6) can be one viable explanation for the comparatively low CH4 production. Additionally, phytoplankton could have higher contents of electron acceptors (sulfates, nitrates) or other substances, which could inhibit methanogenesis (e.g. sulfate reduction occurs before methanogenesis and some volatile compounds are known to inhibit methanogenesis) or fuel anaerobic methane oxidation when methane reaches high levels. Inhibitory concentrations of ammonia could have also been produced (Zeng et al. 2010). The phytoplankton sample could also have contained more microbial communities that inhibits methane production than the macrophyte. Overall, the microbial community could have changed with time whereas methanogenesis was more favored in the incubations with P. stratiotes.

The strong decrease of GHG emissions after one month of anoxic incubation was observable in the two treatments, both macrophyte and phytoplankton (Figure 6). Explanation for the decrease in production after one month of incubation could be that the vials were not flushed continuously with N2 in the same way as for the vials in Experiment 2 A. The results were different between flushed/not flushed samples of P.

stratiotes (Figure 6, Figure 9). The flushed samples do not have a decline, but rather a

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5.1.1 Influence of increasing concentration of TOCauto

The hypothesis was that a linearly increasing concentration of TOCauto would have a linear relation with increased CH4, i.e. that an increase in substrate concentration results in an equally large increase in CH4 production. In the experiment, larger amounts of TOCauto added produced a higher amount of CH4 and CO2 for both sources. The ANOVA performed with increasing TOCauto concentration showed that there is a significant effect of substrate concentration on CH4 production (Table 7). The results indicated that there is no linear correlation (Figure 6, Table 4). For example, one would have expected a bigger difference in the amount CH4 produced between TOCauto·1.75 and TOCauto·1.5 for the macrophytes. In addition, comparing the production of CH4 and CO2 (µmol·d -1_/µmol_·_d-1_{) shows that there is no evident shift in CO2 ad CH4 production between the} different amounts of TOCauto (Figure 8). Therefore, the conclusion is that increasing amount of substrate did not result in a linear increase in CH4 production. This is of importance as it indicates that the microbial community did not produce CH4 linearly as a function of substrate concentration. This result is important with respect to future assessments and models of CH4 production in lakes and reservoirs.

Possibly, the different amounts of added TOCauto were too close to each other in the experimental setup. To see a more obvious trend, the range of added TOCauto should have probably been larger and with more concentrations. For this experiment, adding more TOCauto was considered to not be viable as the glass vials of 100 ml were too small to fit more mass of macrophyte. To go lower was also difficult, as the lowest amount TOCauto added was the smallest amount to produce emission that probably could be detected at the beginning of the incubation in the CO2 and CH4 analyzer. Therefore, incubations with larger vials and with a wider range of concentrations of TOCauto could help in refining the understanding how increased amounts of autochthonous organic carbon fuels methane production.

5.1.2 Variances in the degradation of different macrophyte species

Incubation with different macrophyte species from Experiment 2 A, show a great variability in methane production between different macrophyte species (Figure 5). All species except N. indica produced CH4, whereas N. indica instead produced a substantial amount of CO2. Overall, the linear trend in production is similar for CO2 and CH4 between the different macrophyte species. The differences in produced amounts of CH4 and CO2 can be appointed to the different nutrient content and plant traits for the species (Enríquez et al. 1993; Song et al. 2013). High contents of lignin, cellulose, high C/P and C/N rations, show negative correlation with decomposition rates (Enríquez et al. 1993; Chimney & Pietro 2006). It is apparent that the potential for methane emission from autochthonous sources is very dependent on the species.

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5.2 LINEAR MODEL FOR THE ESTIMATE OF ALLOCHTHONOUS CONTRIBUTION

To determine the relative allochthonous contribution in Experiment 1, a linear model with ANOVA was used for the estimation. The estimation of allochthonous contribution aimed to test if the decomposition of autochthonous source added to a sediment may lead to a priming effect: i.e. would stimulate the decomposition refractory C contained in the sediment. If there would have been a priming effect, the allochthonous contribution in presence of autochthonous sources (more labile) would be higher than that of the sediment decomposing on its own (the control).

It was assumed that the allochthonous contribution to CH4 production could be calculated with a linear model. The assumption was made that the contribution to CH4 from the allochthonous sediment could be estimated for when the autochthonous concentration TOCauto was zero. The ANOVA presented a significant effect for all variables (p < 0.05) although no significance for the intercept and concentration TOCauto was found with the linear regression model (Appendix A, Table 9). With the linear model, the allochthonous contribution to CH4 production was estimated (Table 7). The model presented a difference between the allochthonous contribution for macrophyte and phytoplankton, both in magnitude and rate. The estimated allochthonous contribution decreased with time for phytoplankton (184 - 8.9·day) and increased with time for macrophyte (-47.7 + 9·day). The contribution to CH4 production by allochthonous OC in relation to the autochthonous OC appears low in both cases. For the control, i.e. the incubation of the allochthonous sediment, the sediment contribution is negligible in comparison to both macrophyte and the phytoplankton, with almost no methane produced. The sediment used in this experiment was assumed to contain predominantly allochthonous OC, and the high C/N ratio supports this assumption and explains the low CH4 production. However, the different allochthonous contributions estimated with the model in comparison to the values from the allochthonous sediment, indicate that the estimate is questionable. Therefore, there is no certainty in the conclusion about priming effect.