MSc - thesis March 2020

Effects of tree species composition and planting methods on survival and growth in a 15-year-old forest in southern Iceland

Jón Hilmar Kristjánsson

Faculty of Environmental and Forest Sciences

MSc - thesis March 2020

Effects of tree species composition and planting methods on survival and growth in a 15-year-old forest in southern Iceland

Jón Hilmar Kristjánsson

60 ECTS thesis submitted in partial fulfilment of a Magister Scientiarum degree in forest science

Academic advisors: Páll Sigurðsson and Bjarni D. Sigurðsson

Agricultural University of Iceland Faculty of Environmental and Forest Sciences

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Clarification of contribution I hereby declare that this project is based on my own observations, has been written by me and that it has not been submitted, in part or in whole, to a higher degree.

______Jón Hilmar Kristjánsson

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Ágrip [Áhrif blöndunar trjátegunda og gróðursetningaraðferða á lifun og vöxt 15 ára skógar á Suðurlandi] Blöndun trjátegunda í nytjaskógrækt getur aukið ræktunaröryggi þegar kemur að loftslagsbreytingum og mögulega aukið efnahagslegt öryggi í timburframleiðslu. Áhrif tegundablöndu á vöxt trjáa í skógi, framleiðni og kolefnisbindingu hafa verið rannsökuð í mun meira mæli á öðrum Norðurlöndum en á Íslandi. Það er þó mikilvægt að skoða áhrif tegundablöndu við íslenskar aðstæður vegna þess að hér eru bæði jarðvegsskilyrði og veðurfar með öðru móti en gengur og gerist annarsstaðar og á Íslandi eru ræktaðar tegundablöndur sem sjaldnast eru ræktaðar í öðrum löndum. Tilraun sú sem mæld var og fjallað er um í þessari ritgerð (LT-verkefnið) er fyrsta tilraun hér á landi með trjátegundablöndu í stórum samfelldum reitum (1/2 ha) í blokkum sem endurteknar voru við sömu jarðvegsskilyrði. Í Gunnarsholti á Rangárvöllum voru borin saman birki (Betula pubescens Ehrh.), sitkagreni (Picea sitchensis (Bong.) Carr.), stafafura (Pinus contorta Douglas) og alaskaösp (Populus trichocarpa Torr. & A. Gray ex. Hook.). Fyrir utan lerki (Larix sp.) eru þetta fjórar mikilvægustu trjátegundirnar í skógrækt á Íslandi. Tegundirnar voru ýmist ræktaðar einar sér, eða í 50 % eða 25 % blöndu með sitkagreni. Fyrsta markmið rannsóknarinnar var að endurmeta eldri tilraun 15 árum eftir gróðursetningu. Í henni voru prófaðar mismunandi aðferðir við gróðursetningu. Annað markmið var að taka út lifun í allri LT-tilrauninni í Gunnarsholti, það þriðja að meta vöxt, framleiðni og bolgæði trjátegundanna og það fjórða að kanna hvort einhver munur væri á lifun, vexti, framleiðni og vaxtarlagi trjáa í tegundablönduðum reitum samanborið við einnar tegundar reiti. Fimmta og síðasta markmiðið var að bera saman allar meðferðir á tveimur mismunandi gróðurlendum, graslendi með þykkum jarðvegi sem var fyrrum tún, og fyrrum örfoka svæði með rýrum og grunnum jarðvegi þar sem sáð var með lúpínu (Lupinus nootkatensis Donn ex. Sims) fyrir 24 árum. Engin marktæk langtímaáhrif fundust í gróðursetningartilrauninni, nema hvað að jarðvinnsla með gróðursetningarplóg hafði marktæk jákvæð áhrif á lifun og hæðarvöxt allra tegunda miðað við handflekkingu, en jarðvinnsluáhrifin voru einnig martækt meiri í graslendinu en gömlu lúpínubreiðunni. Heildarlifun í LT-verkefninu á Suðurlandi var 58 % og standandi viðarrúmmál var alls 254 m3 bolviðar á 30 ha (reitir með blöndu af birki: gulvíði ekki teknir með). Birkið var með besta lifun allra tegunda. Alaskaöspin hafði vaxið mest, meira en birki og sitkagreni við 15 ára aldur. Kolefnisbinding var samt jafn mikil í öspinni og birkinu, sem höfðu safnað upp

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87 % og 85 % meira kolefni (C) ofanjarðar en grenið. Það var vegna hærri lifunar í birkinu, þó hvert birkitré væri að jafnaði minna en öspin. Hins vegar hafði grenið betra vaxtarform en hinar tegundirnar. Jákvæð áhrif voru af því að planta trjám í lúpínubreiðu samanborið við graslendi, trén þar uxu að jafnaði 33 % hraðar, bundu 1,5 sinnum meira kolefni og sýndu 10 % meiri lifun. Hins vegar var munurinn á rúmmálsvexti grenis og birkis ekki marktækur í mismunandi gróðurlendum, aðeins hjá öspinni. Meðal árleg kolefnisbinding í 30 ha skóginum í Gunnarsholti var 7,4 tonn C á ári eða ca. 42 tonn af CO2 á ári. Alls höfðu trén bundið ca. 110 tonn af kolefni eða 404 tonn af CO2 á 13-15 árum frá gróðursetningu. Fósturaðferðin (þegar alaskavíði var blandað saman við grenið) hafði marktækt jákvæð áhrif á yfirhæðarvöxt sitkagrenis. Hins vegar voru engin önnur jákvæð áhrif af fósturtrjánum. Einu marktæku blönduáhrifin í öðrum meðferðum voru neikvæð hæðarvaxtaráhrif blöndu samanborið við einnar tegundar reiti, óháð trjátegund. Það að engin jákvæð áhrif komu fram af blöndun tegunda 15 árum eftir gróðursetningu gæti breyst þegar lengra líður á vaxtarlotuna og vaxtarrýmið fyllist. Frekari rannsókna er þörf á áhrifum tegundablöndunar á vöxt trjáa og framleiðni skóga hérlendis.

Lykilorð: Blandskógur, skógrækt, millibilsjöfnun, kolefnisbinding, einnar tegunda skógur, jarðvinnsla.

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Abstract Mixing tree species can increase the security growing a crop when facing climate change, as well as possibly making timber production economically safer. More research has been done on the effect of mixing tree species on tree growth, production and carbon sequestration in other Nordic countries than in Iceland. However, it is important to study further the effects of species mixtures for Icelandic conditions, because of its unique soil and weather conditions and because we are often growing tree mixtures that are not common in other countries. The assessment that was carried out on the field trials (the LT-Project) and are discussed in this thesis, was the first initiative where the most important tree species for the Icelandic forest industry, apart from larch (Larix sp.), were compared in the same soil conditions and on large continuous (1/2 ha) plots at Gunnarsholt in southern Iceland. Those species included the native downy birch (Betula pubescens Ehrh.) and three introduced tree species: Sitka spruce (Picea sitchensis (Bong.) Carr.), lodgepole pine (Pinus contorta Douglas) and black cottonwood (Populus trichocarpa Torr. & A. Gray ex. Hook.). These species were either planted in monocultures or in 50 % or 25 % mixture with Sitka spruce. The first objective of the study was to re-evaluate an older experiment with different planting methods 15 years later, the second was to monitor survival in the entire LT-project in Gunnarsholt, the third was to evaluate the growth, productivity and stem form of three tree species and the fourth was to examine whether there was any significant difference in survival, growth, productivity and stem form in species mixtures compared to monocultures. The fifth goal was to compare all the treatments in two different habitats; a former hayfield with thick soil that had turned into an unmanaged grassland before planting, and an eroded area with thin soils which had been reclaimed by Nootka lupine (Lupinus nootkatensis Donn ex. Sims). No significant long-term effect was found in the different planting methods, except that soil scarification with a planting machine (harrowing) had a significant positive effect on survival and height growth of all the species compared to manual scarification, but the harrowing effect was also significantly higher in the grassland compared to lupine. Total survival in the LT- project in southern Iceland in 2018 was 58 % and the total standing stem volume was 254 m3 on 30 ha (one downy birch: tea-leaved willow mixture was not included). Downy birch had the highest survival of all species. Black cottonwood had the highest growth increment by the age of 15 years, more than birch and spruce on average per tree. Still, both cottonwood and birch and sequestered similar amounts of carbon (C), or 87 % and 85 % more total aboveground C stock than the spruce. This was because of the higher survival of birch, even though the mean

v tree was smaller. The Sitkaspruce had the best stem form of the species measured in the study. There was a positive effect from growing trees in lupine field compared to grassland, trees grew on average 33 % faster, sequestrated 1.5 times more carbon and showed 10 % higher survival. However, the difference in volume growth between the two habitats was not significant for spruce and birch alone, only for the black cottonwood. Mean annual carbon sequestration

(MAC) in 30 ha forest in Gunnarsholt was 7.4 ton C per year or ca. 42 ton of CO2 during the 13-15 years from planting. The foster-tree method (50/50 mixture of Sitka spruce and Alaskan willow (Salix alaxensis (Andersson) Coville) had a significant positive effect on dominant height growth of Sitka spruce. However, there were no other significant positive effects found from the foster-tree method. The only significant mixture effects in the other treatments was a negative average height growth of mixtures compared to monoculture plots, across all species. Even if no significant positive mixture effects were found 15 years after planting, that could change later in the rotation when the growing space has filled more. Further research is needed on species mixture effects on growth of trees and forest production in Iceland.

Keywords: Mixture effect, forestry, pre-commercial thinning (PCT), carbon sequestration, monoculture, soil scarification.

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Acknowledgements I would like to begin with thanking my academic advisors Páll Sigurðsson and Bjarni D. Sigurðsson for a high-quality guidance and assistance with the project, e.g. with statistics and reading over earlier drafts of the thesis. I would also like to thank them for helping me with field measurements along with a German forestry student, Ben Lukas Wisniewski. This project would not have been possible without their help. I would also like to thank Árni Bragason, the head of the Soil Conservation Service of Iceland, along with his whole staff for providing me accommodation in Gunnarsholt and allowing me to inventory the two forests on their land. I would like to thank Björgvin Eggertsson for allowing me to measure his experiment on planting methods and for giving me information about it. I would like to thank Nordgen for partially financing the drive to and from the forest in Gunnarsholt. I would also want to thank Framleiðnisjóður landbúnaðarins for a scholarship [no: 20-062] that partially funds the costs of the study.

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Table of contents

1.1. Monocultures ...... 2

1.2.1. Mixture benefits ...... 3

1.3.1. Sitka spruce ...... 5 1.3.1.1. Origin ...... 5 1.3.1.2. General information ...... 5 1.3.1.3. Regeneration ...... 6 1.3.1.4. Spruce in Iceland ...... 6 1.3.1.5. Common pests and pathogens on Spruce in Iceland ...... 7 1.3.2. Downy birch ...... 8 1.3.2.1. Origin ...... 8 1.3.2.2. General information ...... 8 1.3.2.3. Regeneration ...... 9 1.3.2.4. Birch in Iceland ...... 10 1.3.2.5. Common pests and pathogens on birch in Iceland ...... 11 1.3.3. Black cottonwood ...... 11 1.3.3.1. Origin ...... 11 1.3.3.2. General information ...... 12 1.3.3.3. Regeneration ...... 12 1.3.3.4. Poplar in Iceland ...... 13 1.3.3.5. Common pests and pathogens on black cottonwood in Iceland ...... 13

1.4.1. Management of spruce and birch mixture ...... 16

1.7.1. Forest management for climate change ...... 21

1.9.1. Initial Spacing ...... 22 1.9.2. Soil scarification ...... 22 1.9.3. Planting in Nootka lupine and grassland areas ...... 24

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2.1. Site description and experimental background ...... 31

2.2. Site characteristics ...... 31

2.3. Site conditions ...... 31 2.3.1. The LT-Project in southern Iceland ...... 32 2.3.2. Eggertsson’s project ...... 35

2.4. Inventory in spring and autumn 2018 ...... 36 2.4.1. Planting methods / Eggertsson’s project ...... 36 2.4.2. Survival ...... 37 2.4.3. Growth, production and stem-form measurements ...... 37

2.5. Calculations of tree growth and stand characteristics ...... 39

2.6. Statistical analysis ...... 41 2.6.1. Eggertsson’s project: Long-term effects of different planting methods...... 42 2.6.2. Survival in the LT-Project in 2018 ...... 42 2.6.3. Effect of species mixtures on forest growth ...... 42

3.1. Eggertsson’s project: Long-term effects of different planting methods ...... 43 3.1.1. Survival ...... 44 3.1.2. Height growth ...... 46 3.1.3. Diameter growth ...... 47 3.1.4. Volume growth ...... 49

3.2. Inventory of survival in the LT-Project in 2018 ...... 50

3.3 Effects of species mixtures on forest growth ...... 54 3.3.1. Forest characteristics ...... 54 3.3.1.1. Realised planting density ...... 54 3.3.1.2. Stand density ...... 54 3.3.1.3. Stand Basal Area (BA) ...... 55 3.3.2. Growth responses per living tree ...... 57 3.3.2.1. Height growth ...... 57 3.3.2.2. Volume growth per tree ...... 61 3.3.3. Stand production (growth reponses per stand) ...... 63 3.3.3.1. Species and habitat differences ...... 63 3.3.3.2. Mixture effects ...... 65 3.3.4. Stem form ...... 66 3.3.4.1. Species differences ...... 66 3.3.5. Effects of the Alaska willow foster trees ...... 67 3.3.6. Carbon sequestration ...... 69

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4.1. Re-evaluation of the Eggertsson’s experiment ...... 70 4.1.1. The planting methods ...... 70 4.1.2. The importance of proper site preparation ...... 70

4.2. Survival of planted seedlings ...... 71 4.2.1. Species differences in survival ...... 72

4.3. Growth and production in the LT-project ...... 72 4.3.1. Black cottonwood ...... 73 4.3.2. Sitka spruce ...... 73 4.3.3. Downy birch ...... 74

4.4. Wood and biomass production of the whole forest ...... 75

4.5. Grassland or old lupine fields – which is better for forestry? ...... 75

4.6. Did the species mixture lead to positive responses? ...... 76

4.7. Foster tree method ...... 77

4.8. Stem form ...... 77

4.9. Unrooted cuttings ...... 78

4.10. Carbon stock and CO2 sequestration ...... 78

4.11. Methodological issues ...... 79

4.12. What then? ...... 81

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List of Figures

Figure 1. Monoculture of Sitka spruce in grassland and lupine at Gunnarsholt in Southern Iceland...... 8 Figure 2. Monoculture of Icelandic native downy birch in grassland and lupine at Gunnarsholt in southern Iceland ...... 11 Figure 3. Monoculture of black cottonwood in grassland and lupine at Gunnarsholt in southern Iceland ...... 14 Figure 4. Two mixtures of Sitka spruce and downy birch from Spámannsstaðaskógur (Spámannsstaðaforest) at Gunnarsholt in Sourthern Iceland...... 16 Figure 5. Two mixtures of Sitka spruce and black cottonwood from Ketluskógur (Ketluforest) at Gunnarsholt in Sourthern Iceland...... 18 Figure 6. Distribution of Nootka lupine in Iceland 2017, total area 299 km2...... 25 Figure 7. Severely frost damaged Sitka spruce planted in 2002 in grassland in Gunnarsholt in Southern Iceland...... 28 Figure 8. The two forest areas Spámannsstaðaforest and Ketluforest at Gunnarsholt in southern Iceland with stand numbers from 1 to 64. P and C are harrowed and untreated unplanted control areas ...... 33 Figure 9. Trees stem form A, B and C...... 38 Figure 10. Average survival by habitat and site preparation (harrowing) treatments for Sitka spruce, black cottonwood and downy birch...... 45 Figure 11. Average height for habitat and site preparation (harrowing) treatments for Sitka spruce, black cottonwood and downy birch...... 46 Figure 12. Average height for Sitka spruce, black cottonwood and downy birch and site preparation (harrowing) treatments...... 47 Figure 13. Average diameter at breast/knee height for habitat and site preparation (harrowing) treatments...... 48 Figure 14. Average diameter for Species and site preparation (harrowing) treatments ...... 49 Figure 15. Volume per tree in cubic decimeters (liters) for Sitka spruce, black cottonwood and downy birch with plough string and without plough string treatments within lupine and grassland habitats ...... 50 Figure 16. Average survival for trees planted in grassland and lupine ...... 51

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Figure 17. Average survival for black cottonwood, downy birch, lodgepole pine and Sitka spruce ...... 52 Figure 18. Average survival for Alaskan willow in a 50/50 mixture with Sitka spruce and tea- leaved willow in a 25 % mixture with 75 % downy birch ...... 53 Figure 19. Stand density calculated from the survival inventory at Gunnarsholt in grassland and lupine...... 53 Figure 20. Stand density calculated from the growth inventory at Gunnarsholt in grassland and lupine...... 55 Figure 21. Basal Area at Gunnarsholt in lupine and grassland...... 56 Figure 22. Dominant height of Sitka spruce, downy birch and black cottonwood ...... 58 Figure 23. Dominant height for tree species planted in lupine and grassland...... 59 Figure 24. Average height of all tree species in monoculture-and mixed stands...... 60 Figure 25. Average volume per tree for Sitka spruce, downy birch and black cottonwood. .. 61 Figure 26. Average volume per tree for Sitka spruce, black cottonwood and downy birch in grassland and lupine ...... 62 Figure 27. Volume per hectare for all monoculture plots in grassland and lupine ...... 64 Figure 28. Stand volume per hectare for monocultures and mixtures in both habitats ...... 66 Figure 29. Number of >3 m trees evaluated for stem form A, B and C for Sitka spruce and black cottonwood ...... 67 Figure 30. Dominant height of Sitka spruce in a monoculture and a 50 % Sitka spruce with 50 % Alaskan willow foster tree mixture in grassland and lupine ...... 68 Figure S1. Pre-commercial thinning plan for Spámannsstaðaforest in Gunnarsholt...... 114 Figure S2. Pre-commercial thinning plan for Ketluforest in Gunnarsholt...... 115

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List of Tables

Table 1. Temperature and windspeed per month at Hella weather station from the years 2006 to 2019 and precipitation from Sámsstaðir weather station from the years 2002 to 2019...... 32 Table 2. All the treatments and different species in each of the stands from nr. 1 to 64 shown on map in Figure 8. The table shows ratios of 50/50, 75/25 mixtures and monocultures...... 34 Table 3. The initial planting treatments in Spámannsstaða- and Ketluforest used for monoculture of Sitka spruce, downy birch and black cottonwood ...... 36 Table 4. ANOVA analysis of planting treatments 1-6 on seedling survival, height, diameter and stem volume for Sitka spruce, black cottonwood and downy birch planted in 2002...... 43 Table 5. ANOVA analysis of the differences due to habitat, tree species and site preparation (harrowing) treatments on survival, height, diameter and stem volume for Sitka spruce, black cottonwood and downy birch planted in 2002...... 44 Table 6. Post-ANOVA Tukey’s HSD comparisons for the interaction between habitat and site preparation (harrowing) on seedling survival, height, diameter and stem volume for Sitka spruce, black cottonwood and downy birch ...... 45 Table 7. Post-ANOVA Tuckey’s HSD comparisons for the interaction between tree species and site preparation (harrowing) on seedling survival, height, diameter and stem volume for Sitka spruce, black cottonwood and downy birch ...... 47 Table 8. ANOVA analysis and post-ANOVA Tukey’s HSD comparisons of survival of species between habitat, tree species and mixture effect for Black cottonwood, Sitka spruce and downy birch...... 51 Table 9. Stand Basal Area (m2/ha) in monoculture and mixed stands...... 56 Table 10. Dominant (Hd, m), average height (H, m) and average bole volume per tree in monoculture and mixed stands ...... 57 Table 11. ANOVA analysis of the differences in stem volume per tree, average and dominant height ...... 58 Table 12. Post-ANOVA Tukey’s HSD comparisons for average height and stem volume for Sitka spruce, black cottonwood and downy birch ...... 59 Table 13. Post-ANOVA Tukey’s HSD comparisons for the interaction between species and habitat (lupine or grassland) on height and stem volume for Sitka spruce, black cottonwood and downy birch ...... 60

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Table 14. Post-ANOVA Tukey’s HSD comparisons for the interaction between tree mixtures on height and stem volume for Sitka spruce, black cottonwood and downy birch...... 61 Table 15. Stand volume, mean annual increment and woody aboveground biomass in monoculture and mixed stands ...... 63 Table 16. ANOVA analysis of the difference due to habitat and species in monoculture stands on stand volume per hectare (m3/ha) and biomass per hectare (ton/ha)...... 64 Table 17. Post-ANOVA Tukey’s HSD comparisons for the average species diffrences on standing volume per hectare (m3/ha) and Biomass per hectare (tonn/ha) ...... 65 Table 18. Post-ANOVA Tukey’s HSD comparisons for the interaction between species and habitat on standing volume per hectare (m3/ha) and Biomass per hectare (tonn/ha) for Sitka spruce, black cottonwood and downy birch ...... 65 Table 19. ANOVA analysis of the difference due to habitat and mixture effects on stand volume per hectare (m3/ha) and biomass per hectare (tonn/ha) ...... 66 Table 20. ANOVA analysis and post-ANOVA Tukey’s HSD comparisons of Stem form of species between habitat, tree species and mixture effect ...... 67 Table 21. ANOVA analysis of the difference due to habitat and mixture effects on dominant height, Average height and volume per tree stem in monoculture and foster tree stands ...... 68 Table S1. Pre-commercial thinning plan for Ketluforest and Spámannsstaðaforest in Gunnarsholt...... 113

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Introduction The present research was done within a long-term forest experiment, called the „LT-project”. The goal of the project was to create a future experimental site that could be used for various forestry experiments, as well as to study the effects of species composition, fertilization and initial spacing on wood growth, stem quality and biodiversity (Sigurðsson et al., 2006). All the major tree species used in Icelandic forestry have been planted in 5000 m2 plots in Gunnarsholt on Rangárvellir (southern Iceland) and in Fljótsdalshérað (eastern Iceland). The plots are set according to a specific experimental plan to facilitate future comparisons between treatments. They were also made large enough to perform new experiments within them in the future. In total, these two experiments cover 64 hectares of land. In the southern part of the country, Sitka spruce (Picea sitchensis (Bong.) Carr.), downy birch (Betula pubescens Ehrh.), black cottonwood (Populus trichocarpa Torr. & A. Gray ex. Hook.) and lodgepole pine (Pinus contorta Douglas) were planted in monocultures as well as mixtures of Sitka spruce with the other three species – cottonwood, pine and birch. In eastern Iceland, Siberian larch (Larix sibirica Ledeb. / L. sukaczewii Dyl.) is the main species and black cottonwood was not included there. There the downy birch, Sitka spruce and lodgepole pine were planted in monocultures and in mixtures with the Siberian larch. In the East, Siberian larch initial stand density experiments were also made, with an initial density of 1000, 2000, 3500 and 5000 trees per hectare. The LT-project in eastern Iceland has received more attention and there are number of publications that have appeared; including an early study of early survival and growth (Sigurðsson et al., 2011), and initial stand density effects (Jóhannsdóttir 2012; Jóhannsdóttir et al., 2013). Two more publications are now underway from eastern Iceland; Heiðarsson et al. (in prep.) gives the second assessment of the initial stand density experiments and Rúnar Ingi Hjartarson (unpublished) is working on a thesis about species mixture effects between Siberian larch and lodgepole pine. The present work is, however, the first publication on the LT-project in southern Iceland, since the initial project description was published by Óskarsson (2003) and Sigurðsson et al. (2006) and survival of the initial planting was evaluated (Eggertsson, 2004). In the following sections I will review the state of knowledge for the research questions being asked by the present project in southern Iceland.

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1.1. Monocultures A significant part of planted forests in the world are single species plantations, comprising of a few taxonomic genera, for example, Pinus, Picea, Pseudotsuga and more (Kelty, 2006; Piotto, 2008; Richards et al., 2010). Monocultures are often even-aged stands, and planted in accessible areas at high planting density, allowing easy management and high durability of the plantations; better yields per hectare and more productive crops can therefore be achieved, resulting in consistent products (Baltodano, 2000; Kelty, 2006; Nichols et al., 2006; Piotto, 2008). Rapidly- growing, alien and low-density wood species are widely used for timber, paper, pulpwood, coal and energy since they have a brief rotation periods and therefore advantages over native trees and shrubs in the efficiency of using light, nutrients and water (Li et al., 2014; Nguyen et al., 2014; Chaudhary et al., 2016). Usually the focus of all site resources in monocultures is on the productivity of one species with the most desirable traits, like rate of growth and quality of wood (Kelty, 2006; Piotto, 2008; Moghaddam, 2014). In the present project I will address those effects (see later). Single species plantations can, however, have some environmental impacts, including loss of soil quality and fertility, disruption of water processes, risks associated with introduction of exotic species, risks of pest and disease promotion, higher risks of windthrow, risk of fire increases and negative impacts on biodiversity (Baltodano, 2000; Evans, 2001; Bowyer, 2006). Pests and diseases can be more severe in monocultures. Because of the uniform genetic composition and closeness of tree species in monocultures, they can provide an immense source of food and optimal habitat for insects and pests, leading to rapid colonization and infection spread (Hartley, 2002; Bowyer, 2006; Sta et al., 2006; Moghaddam, 2014). Some studies have shown that monoculture plantations have lower biodiversity levels than native forests around them (Bowyer, 2006; Bremer & Farley, 2010; Pawson et al., 2013), even if that was not found in Iceland (Elmarsdóttir et al., 2011). Felton et al. (2010) analyzed the detrimental ecological and environmental consequences of spruce monoculture crops and found that such plantations had weak biotic and abiotic tolerance. However, with correct planning and good management of monocultures, potential hazards can be reduced (Bowyer, 2006; Kelty, 2006). In the present project I will, however, not evaluate effects on biodiversity between monocultures and mixed stands, but focus on survival, growth and stem form (see later).

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1.2. Mixtures First, there is a need to ask what is the definition of a mixed forest stand? One definition of mixed stand is: “… stands composed of different tree species, mixed on a small scale leading to competition between trees of different species, as a main factor influencing growth and management” (Olsthoorn, 1999). There are also more specific ways to describe mixed stands by the number of species and their proportions in stem density, basal area or volume. The mixture can also be described by the temporal factor. The vertical structure i.e. the number of canopy layers, age or height differences, also gives important descriptions of the mixed stand (Prevost & Dumais, 2014; Man et al., 2010). For example, in Sweden, the basal area of the dominant species in a mixed forest cannot exceed more than 65 % of the total basal area, to be called a mixed stand (Skogsdata, 2014). In Finland the number is 75 % and in Norway 80 % (Johansson, 2003; Peltola, 2014). In Iceland the following definition is used; “no species with more than 75 % crown coverage” (Árnason & Matthíasson, 2009; Snorrason, 2013).

1.2.1. Mixture benefits Stands with mixed tree species are thought to have a lot of positive effects compared to monocultures. They can enhance the ecosystem values, give increased biodiversity, increase biomass production and improve soil quality (Roscher et al., 2008; Bravo-Oviedo et al., 2014). Stands with mixed species also have a general risk reduction, which includes both abiotic- and biotic risks (Felton, 2010b). None of these effects are, however, evaluated in the present work. Theoretically, since different species may obtain resources from different strata, have different root growth rythm, occupy different soil depths and differ in shade-tolerance, the exploitation in mixed stands can be complementary and in fact increase the total production. The complementary effect is reached when interspecific competition (between species) is lower than intraspecific competition (within a species). By facilitation one species may even help and improve the conditions for other species, for example by increasing resources in the soil by fixating nitrogen (Rothe & Binkley, 2001). However, the long-term objective for mixed production forests is primarily to produce a final pure crop of a desired target species such as Sitka spruce with the help of another species (Taylor, 1985). In the present project I wanted to evaluate if any such early facilitation effects could be detected in the LT-project in southern Iceland during early stand development.

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One known way to compare mixtures with monocultures is by comparing yield. By comparing yield of a species in a mixture to its yield in monoculture it is possible to see if there are any positive or negative effects from either monoculture or mixture (Harper 1977, Vandermeer 1989). In Boreal and temperate forests, mixtures can sometimes lead to a decrease in stand yield, compared to the most productive (and shade-adapted) species in a monoculture (Dirnberger & Sterba, 2014; Hynynen et al., 2011; Smith et al., 1997). This is probably due to a low differentiation between the functional groups because of reduction of species since the Ice Age. However, some complementary effects for species with similar growth patterns and ecol ogical traits have also been found (Collet et al., 2014; Lindén & Agestam, 2003). It is important to choose tree species that complement each other, for example; one that is shade- tolerant and grows slow in a mix with a fast-growing light demanding pioneer species (Man & Greenway, 2013; Smith et al., 1997). In the current project the effect on Sitka spruce (shade- tolerant and slower growing in early stand development) from the light demanding pioneer species black cottonwood, downy birch and Alaskan willow (Salix alaxensis (Andersson) Coville) will be evaluated. A mixed stand reduces the abiotic and biotic risks compared to a monoculture (see earlier). High proportions of spruce in a stand can for instance increase the risk for windthrow (Griess et al., 2012). A mixture with birch, which is considered to have higher mechanical stability than Norway spruce (Picea abies (L.) H. Karst.), could therefore be one way to decrease the risk for windthrow in a stand (Peltola et al., 2000). One study after the big storm Gudrun in southern Sweden in 2005, indicates that a Norway spruce mixture with 30 percent birch can decrease the risk of storm felling by 50 percent (Valinger & Fridman, 2011). The risk of windthrow concludes many factors, as stand exposure, tree height, stem density, time since thinning and the season. That is why no firm conclusion should be drawn from one study of one disturbance (Gudrun) (Griess et al., 2012; Felton et al., 2016). Windthrow is an aspect that normally only appears in the latter half of the rotation (Smith et al., 1997), hence, is not an aspect that is possible to evaluate after 15 years‘experiment, as the LT-Project in Iceland is, but is an example of a factor that will be interesting to monitor in the future. Mixed forests may have an increased adaptive capacity for future threats. The climate change may lead to amplified risks of windthrow, spring frosts and summer droughts for spruce. Broadleaved tree species are on the other hand expected to benefit from some of the scenarios due to climate change (Felton et al., 2016). I will go into more details about how different countries are managing the problems that come up with changing climate later in the introduction.

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1.3. Species 1.3.1. Sitka spruce 1.3.1.1.Origin Sitka spruce (Figure 1) is a conifer species from the northwest coast of North America. Within its native range, it is often found in places with heavy precipitation and cool climate, well drained acidic soils, in monoculture stands or in a mixture (Earle, 2019a). The salt tolerance of Sitka spruce is well known. Growing on poor rocky soil near the sea, however, often contributes to twisted stem form in its native range (Löve et al., 1970). Sitka spruce usually grows in mixtures rather than monocultures in its natural range, pure stands happen more often in early successional situations or as tidewater stands influenced by saltwater from the ocean (Burns, 1990).

1.3.1.2.General information Sitka spruce is an economically valuable tree in some countries outside its native range, for example Great Britain, Norway and Denmark (Thompson & Harrington, 2005). Since it can withstand extreme exposure, develops well in a large variety of sites and at the same time is very productive and produces high-quality wood (Cameron, 2015; Øyen & Nygård, 2007; Brien, 1986). In northern latitudes, conifers are often preferred over broadleaves due to their high production of stem wood and high valued timber, as well as for their suitability for pulpwood industry (Hallsby, 2013). Sitka spruce has a mean annual increment (MAI) of 7.2 m3/ha per year and a dominant height of 8.6 m in Britain at the age of 19 (Matthews, 2016). Conifers in the Boreal forest in Sweden generaly have a MAI of 2- 5 m3/ha/year at similar latitude as Iceland (63-66°N) (Bergh et. al., 2005). Windthrow is one of the biggest threats to Sitka spruce (Franklin, 1988; Harris, 1990). However, it depends on the type of soil and in some places, it has been shown to be more wind- resistant on deep soils than other conifers except for firs (Abies sp.; Dixon et al., 2013; Nicoll et al., 2006). Many provenances of Sitka spruce from more southern latitudes are susceptible to damage from late spring frosts when young in UK (Cannell & Smith, 1984). In most cases Sitka spruce is growing fast enough to get through the frost threshold, so this is normally not a major restriction on planting in the UK. Nonetheless, in the UK it has been found that damage when cold air accumulates in depressions on flat lands (i.e. “frost holes”) are likely to be more serious if Sitka spruce is planted in them, compared to e.g. pines or Norway spruce, and it will most likely not survive in such habitats (Cannell et al., 1985).

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Views differ about the shade tolerance of Sitka spruce. In its native range it is regarded as tolerant (Harris, 1990), but in Britain it is concidered light demanding (compared to e.g. Norway spruce) and cannot, for example, be used for underplanting (Harris, 1990). Sitka spruce is one of the conifer species that can produce epicormic branches. If a stand is opened to light, for instance by an adjacent clear-cut, new branches may originate along the exposed tree trunks (Harris, 1990). Thinning can stimulate such epicormic branching and could decrease the quality of the wood (Harris, 1990).

1.3.1.3.Regeneration Natural regeneration is a reliable means of obtaining a successor crop on many Sitka spruce sites in Great Britain (Malcolm et al., 2001; Mason et al., 2004). It works best in areas with good crop stability and rotations that are long enough (50 years or more) to produce many seeds. Re-establishment at such sites is often almost entirely by natural regeneration. Regeneration is very much dependant on density of the canopy. Mason et al. (2004) showed that the critical level of below-canopy light for survival and growth of young Sitka spruce is at basal areas of 25-30 m2 ha−1. They suggested that an irregular shelterwood system with frequent interventions would be a suitable silvicultural system for Sitka spruce. Planting is another common way to establish Sitka spruce forests.

1.3.1.4.Spruce in Iceland In Iceland, Sitka spruce was first introduced in the beginning of the early 20th century, and after a pause between the years 1913 and 1933, experiments with various spruce species were initiated (Blöndal & Gunnarsson, 1999b). Initially, a lot of Norway spruce was imported from Norway (Blöndal & Gunnarsson, 1999a). The Norway spruce did not thrive well in Iceland if it was not planted into downy birch woodlands, therefore since the 1970s Sitka spruce from Alaska has become more commonly planted (Blöndal & Gunnarsson, 1999a). However, after the harsh spring of April 1963, when almost all Sitka spruces together with most other imported tree species from Alaska, died or had severe frost damage in S-Iceland, foresters became skeptical and Sitka spruce was not planted in any large amounts again until the 1980s (Blöndal & Gunnarsson, 1999a). Sitka spruce has since 1990 been among the top four tree species planted in Iceland, the other three being downy birch, Siberian larch and lodgepole pine (Eysteinsson, 2009; Eysteinsson, 2017). It has been one of the most planted species in forests in southern Iceland, or 32 % of all planted trees from 2002 to 2015 by the southern Iceland’s

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Regional Afforestation Programme (Suðurlandsskógar) (Jónsson, 2002b, 2003, 2004, 2005, 2006, 2007, 2008, 2009, 2010, 2011, 2012, 2013, 2014, 2015). Sitka spruce is now the highest measured tree in Iceland, reaching a height of 28.4 meters in 2018 in Kirkjubæjarklaustur in southern Iceland (Halldórsson, 2018). It has been noted, that Sitka spruce in Iceland has a relatively good stem form for timber production and might make some saw timber, though not avaiable in any big quantities for the next years due to the young age of most plantations (Snorrason & Kjartansson, 2017). Reynisson (2011) showed that Sitka spruce has higher production than Norway spruce in Iceland, that. The Sitka spruce had 87 % more standing volume and with a MAI of 3.7 m3/ha/year in the western part of Iceland. He also concluded that Sitka spruce was the right spruce species for the Icelandic conditions. However, better Norway spruce provenances could maybe also be found for Iceland. In 2009, Þorvaldsson (2010) studied the growth and survival of 26 different Alaskan provenances in the western part of Iceland of 14-year-old Sitka spruces. The average survival of all the provenances was 36 % with a maximum of 64.3 % and a low of 10 %. There was one provenance ‘Nash Road’ that is close to ‘Seward’ in Alaska, which is used in the current study. The survival for Sitka spruce from Nash Road was 43 %. He also had one Icelandic first generation provenance ‘Ártúnsbrekka’ with a survival of 33 %. The average height for all the provenanaces was 99 cm after 14 years. He also found that the best provenances had some percentage of the genes from white spruce (Picea glauca (Moench) Voss). Sigurgeirsson (1992) mentioned that 10 % of the genome in the Sitka spruce provenance ‚Seward’ in Iceland comes from white spruce.

1.3.1.5.Common pests and pathogens on Spruce in Iceland Sitka aphid (Elatobium abietinum Walker) was first found in Iceland in 1959 and can now be found almost everywhere where spruce is grown in Iceland (Ragnarsson, 1962, Halldórsson & Kjartansson, 2005). It affects both height- and diameter growth of Sitka spruce in Iceland (Halldórsson et al. 2003). Halldórsson et al. (2006) studied the affect of Sitka aphid on tree growth. They found that at the end of the observation period, the average timber volume of trees that had not been damaged by the aphid was 112 liters, while the most damaged trees were only 83 liters.

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Figure 1. Monoculture of Sitka spruce in grassland (Stand nr. 12) on the left and lupine (Stand nr. 38) on the right at Gunnarsholt in Southern Iceland. (See figure 8 and table 2. for stand description). Picture taken 26.12.2019 by Jón Hilmar Kristjánsson. 1.3.2. Downy birch 1.3.2.1.Origin In Scandinavia there are two species of birch (Betula sp.) trees; silver birch (Betula pendula Roth), which is diploid, and downy birch (Figure 2), which is tetraploid (Tuley, 1973). Silver birch is a taller tree, more dominant in more fertile lowlands and typically forms stands within the Boreal forest after forest fires or clear cutting, which later become replaced by the taller, but more slow-growing conifers, by secondary succession or forest management (Atkinson, 1992; Fahlvik et al., 2011; Johansson, 2014). Downy birch is more prominent on marginal sites in Scandinavia and above or north of the Boreal tree line (Atkinson, 1992). These two species have similar native range, which extends from the Atlantic to eastern Siberia, growing in almost all of Europe (Hultén & Fries, 1986; Atkinson, 1992). Downy birch is one of three native tree species in Iceland, and the only one which forms continuous forests in Iceland (Eysteinsson, 2017).

1.3.2.2.General information In the Nordic countries silver birch favors dry soils with a low concentration of solutes, whereas downy birch occupies wet, cool, finely textured and poorly aerated soils (Sutinen et al., 2002). A mature silver birch in Finland often reaches a height of about 25 meters at the age of 30 years in the best sites, 6 m in poor sites (Eriksson et al., 1997). Raulo (1977) showed that downy birch grows way slower than silver birch in an experiment in Finland. Downy birch grew between 17.0 and 15.4 m in average height. On the other hand, silver birch showed an average height of 21.0 and 18.8 m in agriculture land and Oxalis-Myrtillus type of forest (OMT), respectively, at the age of 30 years.

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To grow to their full potential, birches need lot of space for the canopy, because they are very shade intolerant (Kinnaird, 1974). The mean annual growth for a silver birch is about 10 m3/ha and the rotation period is about 30-60 years in northern Europe (Vihera-Aarnio, 1994; Niemisto, 1996). Research has shown that silver birch in Scandinavia produces 15-20 % more volume than downy birch (Frivold & Mielikaninen, 1991). Birch is known for increasing the pH (making the soil less acidic) and increasing? the fertility of the soil (Atkinson 1992). In a recent study in Finland, silver birch had a higher MAI (5.8 m3/ha/year) than downy birch (3.9 m3/ha/year) on mineral soils. However, on organic soil the MAI of both birch species was no different (3.3–3.4 m3/ha/year). In the same study, planting a 50 % silver birch and 50 % downy birch mixture did not affect the growth of the trees on organic soils. However, on mineral soils the mean diameter and mean volume of silver birch trees were higher in mixed than in pure birch plantations (Hytönen et al., 2014). Some silviculture methods aim for high quality timber production in birch stands by thinning early and heavily in a combination with high stem pruning early in the rotation, and pruning is only done for selected future timber trees. This is done to improve the quality in a faster way than it would happen naturally with natural pruning and at the same time increasing the diameter growth to minimize production risks by reducing the rotation age (Hynynen et al. 2010). Nieuwenhuis & Barrett (2001) felled and analyzed tree ring data from 100 downy birch trees at six sites in Ireland. They found that the fastest diameter growth in unthinned even-aged downy birch was between 5 and 20 years of age. Over 32 years the fastest growing tree achieved a diameter of 25 cm. Maximum height growth took place before the trees became twenty years old. Throughout this period rapidly growing trees accomplished a height growth of over 1 m/year. The study showed that within 42 years a well stocked unthinned downy birch stand could produce a standing volume of 203 m3/ha.

1.3.2.3.Regeneration Birch seeds are wind dispearsed and they are often among the first species to grow in open areas (Matlack, 1989). In Sweden mixtures of planted Norway spruce seedlings and natural regenerated birch is the most common composition in plantations (Holmström, 2015) (See more about this topic later). Natural regeneration is a common way to regenerate birch and can lead to high densities, with over 10.000 seedlings/ha (Rytter et al., 2014). The seed production of birch varies a lot for different years, but in a good year one birch tree can produce about 5-10 million seeds. Even if the seeds can spread long distance, most seeds do not spread more than 100 meters from the

9 mother tree. Since the seeds are very small and therefore can´t contain much energy, their ability to grow depends on where they end up. Open mineral soils or soils with both mineral and organic matter are good growing substrate for birch seeds (Rytter et al., 2014).

1.3.2.4.Birch in Iceland Forestry in Iceland started around 1900 and since then until the 1960s exotic tree species were planted in natural Icelandic birch forests in some ways similar to the „Kronobergs method“ that was introduced in the 1980s in Norway, Sweden and Finnland (Braathe, 1988; Mielikäinen, 1985; Johansson, 1983). Except for that all species were planted in old birchforest (not only spruce) to shelter them from the wind and frost (Skógrækt ríkisins, 2008; Johansson, 2003). It is estimated that 25-40 % of Iceland was covered with birch forests before the settlement and that forest cover in present time is estimated to be almost 2 %, consisting mostly of birch among with some imported tree species (Bjarnason, 1942, 1974; Bergþórsson, 1996; Þórarinsson, 1961; Sigurðsson, 1990; Eysteinsson, 2017). Most of this woodland cover has been lost due to clearing of the woods for pasture and hay fields, overgrazing and over-exploitation for firewood and charcoal (Bjarnason, H., 1971, 1974; Thorarinsson, 1974; Guðbergsson 1975, 1996; Bjarnason, A., 1980; Levanic & Eggertson, 2008). The birch is now mostly found in shelters in lowland valleys and areas protected from sheep grazing (Levanic & Eggertson, 2008). Downy birch can grow to 12-15 meters in height in Iceland (Eysteinsson, 2015; Jónsson, 2004). However, most of the birch that grows in Iceland is less than 2 m in height. Environmental factors such as snow heaviness, soil conditions and wind affect the appearance of the trees. They often have a crooked stem form which means that the height of the tree is often much lower than the length of the log (Jónsson, 2004; Thórsson et al., 2007). The growing season of birch in Iceland is from June to August (Thórsson et al., 2007). Average summer heat does not have a significant effect on the height of birch trees, although it does have a positive effect on the overall birch growth along with wet winters (Jónsson, 2004; Levanic & Eggertson, 2008). Downy birch has many qualities that are interesting to foresters, it is easy to regenerate, grows in various types of soil, has a short rotation period and well pronounced self-pruning. However, it is known to have bad stem form (Þorsteinsson et al., 1996; Blöndal, 2002a; Snorrason & Kjartansson, 2017) and therefore it is not grown as a timber crop in Iceland (Snorrason & Kjartansson, 2017)

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1.3.2.5.Common pests and pathogens on birch in Iceland In Iceland there are 31 arthropod herbivore species that live on birch (Halldórsson et al., 2013). Among those are the nut-leaf weevil (Strophosoma melanogrammum Forster), some fly larvae (Pegomya fulgens Meigen, Semudobia betulae Winnertz), various small downy birch aphids (Betulaphis brevipilosa Börner, Betulaphis pelei Hille Ris Lambers, Betulaphis quadrituberculata Kaltenbach, Euceraphis punctipennis Zetterstedt), some moths, like rusty birch button (Acleris notana Donovan), narrow-winged marble (Apotomis sororculana Zetterstedt), marbled carpet (Dysstroma citrate Linnaeus), mottled umber (Erannis defoliaria Clerck) and the argent and sable moth (Rheumaptera hastata Linnaeus) (Ottósson, 1982; Halldórsson et al., 2013). Rust pathogen (Melampsoridium botulinum (Pers.) Kleb.) is also considered important on birch in Iceland and some other European countries, associated with less height growth and increased mortality (Silva, 2008; Sverrisson, 2013).

Figure 2. Monoculture of Icelandic native downy birch in grassland on the left (Stand nr.4) and lupine on the right (Stand nr.40) at Gunnarsholt in southern Iceland. (See figure 8 and table 2. for stand description). Picture taken 26.12.2019 by Jón Hilmar Kristjánsson. 1.3.3. Black cottonwood 1.3.3.1.Origin Black cottonwood (Figure 3) has a similar native range as Sitka spruce, both species originate from North America in a narrow strip along the north Pacific coast from south central Alaska to northern California (Burns, 1990). They are often associating in the beginning of succession, either pioneering recently exposed areas or joining red alder (Alnus rubra Bong.) in a seral field. This association is usually found around the West Olympic Peninsula river terraces (Fralish & Franklin, 2002). Habitat requirements in its native range are plenty of soil moisture and quite good soil and it becomes unsuccesful in plantations with dry soil. It does not like wet soils, the soil must be well drained and porous, and it can survive on nearly pure sand if it has enough water (Roe, 1958).

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In British Columbia the optimal production of black cottonwood can be succeeded with adequate rainfall, minerals, oxygen, and near-neutral soil (pH 6.0 to 7.0) (Smith, 1957).

1.3.3.2.General information Black cottonwood, along with several other related Populus sp. are commonly named „poplars”. Other two species of the same genera are, however, commonly named „aspen”; i.e. European aspen (Populus tremula L.) in Eurasia and trembling aspen (Populus tremoloides Michx.) in N-America (Brown, 1997; Little, 1979). European aspen is the only native Populus species in Iceland, but only found naturally in few locations in N and E Iceland and generally not being taller than 9 m (Eysteinsson, 2015; Eysteinsson, 2017; Heiðarsson & Blöndal, 2002b). On the other hand, black cottonwood has already reached 26 m in Iceland (Halldórsson, 2016). In Europe, most poplars have been found to be hardy to winter cold, but some clones in the northern part of Europe have suffered some severe frost damage (Ferm et al., 1989; Telenius, 1999; Karačić et al., 2003; Christersson, 2006). In Swanburn in England, cultivars of poplar trees are more sensitive to water deficiency than many other broad-leaved species and require high soil moisture to maintain fast rates of growth. (Allen et al., 1999). Both poplars and aspen can easily coppice and is therefore often used for coppicing for biomass or as a coppice with standards (Allen et al., 1999). Poplars can, however, also grow into large trees. The largest decidious tree in N-America is a black cottonwood, reaching 47.26 m in height in Willamette Mission State Park in Oregon (Monumental trees, 2015). Growth form of poplars is also usually considered to consist of erect stems with compact crowns. They are normally planted in pure stands at spacings of about 8 × 8 m in the UK (Beaton, 1987). This produces trees of 45 cm dbh, with no thinning, on rotations as little as 22 years (Beaton, 1987). The black cottonwood is also often used in mixtures with white spruce in Canada (See more later).

1.3.3.3.Regeneration Seed dispersal of the native European aspen in Iceland does not happen, it only regenerates with root suckers. Also, planting winter cuttings does not work for the native aspen (Sverrisson, 2011). Black cottonwood on the other hand can be planted with winter cuttings and it naturally regenerates with both seeds and root suckers in Iceland (Sigurgeirsson, 2000; Sverrisson et al., 2006; Sverrisson et al., 2011).

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1.3.3.4.Poplar in Iceland Use of black cottonwood in Icelandic forestry did not start until after 1990 even though it had been introduced to the country in 1944 by Hákon Bjarnason (Sverrisson, 2011). In forestry it is used mainly for timber production and as a windbreaker in shelterbelts. The Icelandic Forest Service has made some efforts in developing better material of clones that are more resilient and economically beneficial (Sverrisson, et al., 2006; Sverrisson, 2011; Sverrisson, et al., 2011; Sverrisson, 2019). In 1989, the Government of Iceland approved the so-called industrial project (IS: iðnviðar- verkefnið), which was a research and developmental project under the subervision of the Mógilsá State Forestry Research Centre. The purpose of the project was to study black cottonwood forestry regarding the industrial needs of the silicon factory at Grundartangi (now Elkem Iceland) by producing wooden pellets for burning in the factory (Jónsson, 2011). However, if the cottonwood forestry is managed with a traditional forest management with a focus on the final production as saw logs with long rotations and thinnings in between, it is likely to have about a 60-year rotation with two thinnings (then it would be thinned at 20 years old and then 40 years old) (Snorrason, 2009). Black cottonwood is said to have relatively good stem form in Iceland for timber production and might make saw timber in some quantities. (Snorrason & Kjartansson, 2017). In Iceland black cottonwood is very commonly planted in monocultures or in a mixture with spruce (Eggertsson, 2004). Usually it is planted in very fertile and wet areas with the spruce and in a single species plantation (Snorrason, 2013; Eggertsson, 2004). It has been proven to be successful in a reasonably humid, fertile and sloping land, such as drained swamps, the lower part of mountain slopes and around rivers (Sverrisson, 2011).

1.3.3.5.Common pests and pathogens on black cottonwood in Iceland Black cottonwood has so far been mostly free of pests and pathogens in Iceland, but two recent vagrants have hit the black cottonwood. The rust fungi Melampsora laricis-populina Kleb., 1902 and the brassy willow beetle (Phratora vitellinae L.) (Sverrisson et al., 2001; Halldórsson et al., 2013). The rust fungi came to Iceland around 1999 (Sverrisson et al., 2001). The rust is a basidus fungi that uses larch (Larix spp.) as a medium host, where the fungi can multiply through reproduction. During the summer the fungi lives on the black cottonwood leaves, forming yellow rust spots underneath the leafs. A layer of rust spores can form and spread with the wind to other black cottonwood leaves and the spores germinate and grow into the leaf, forming a

13 new generation of rust that spreads the disease further and thus infection can continue (Halldórsson & Sverrisson, 2006). Therefore, black cottonwood is not planted in mixtures with larch in Iceland (Snorrason, 2013). It is important to choose the right black cottonwood clones and finding the ones that are not succeptible to the rust fungi (Sverrisson et al., 2001; Sverrisson et al., 2006; Sverrisson et al., 2011). The brassy willow beetle came to Iceland in 2005 (Halldórsson et al., 2013). The adult beetles begin to wake up from winter hibernation in mid-April and accumulate on the stems and branches of poplar and willow trees (Icelandic Institute of Natural History, 2007). In Europe, three generations can develop over the summer (Urban, 2006). The number of generations in Iceland is unknown, but adult beetles are found throughout the summer and into mid-October (Icelandic Institute of Natural History, 2007). They feed on the leaves and can therefor decrease the photosynthetic rate of trees; hence the trees grow slower (Icelandic Institute of Natural History, 2007; Sverrisson & Oddsdóttir, 2008).

Figure 3. Monoculture of black cottonwood in grassland on the left (Stand nr.1) and lupine on the right (Stand nr.47) at Gunnarsholt in southern Iceland. (see figure 8 and table 2. for stand description). Picture taken 26.12.2019 by Jón Hilmar Kristjánsson. 1.4. Existing mixtures in Scandinavia Some of the most common mixtures in Scandinavia consist of European beech (Fagus sylvatica L.), English oak (Quercus robur L.), European aspen, alder (Alnus sp.) or birch in a mixture with the coniferous Norway spruce. Scots pine (Pinus sylvestris L.) and birch are also a common mixture. Some common deciduous mixtures are birch/alder or birch/aspen. A conifer mixture that is common in Nordic regions consists of Scots pine and Norway spruce. In my thesis I will most of all focus on black cottonwood and downy birch in a mixture with Sitka spruce. Norway spruce and birch (Betula sp.) are two different species that complement each other in the Boreal forests in Scandinavia (see earlier). In more recent times there are also some Norway

14 spruce and European aspen mixtures being cultivated in Scandinavia (Johansson, 2003) (see later). Regeneration of planted Norway spruce and natural regeneration of birch is the most common broadleaf/conifer mixture in plantations in Sweden and birch is the most important broadleaved tree species in Northern Europe. Since many broadleaves have a lower biomass production than conifer species and the economic value of many broadleaves are lower, broadleaves are often removed to the advantage of the crop trees during thinnings. Since the 1980s herbicide treatments to remove broadleaves have been prohibited (Ekelund & Hamilton, 2001; Ligné, 2004). In precent time the most common way to remove competition to the crop trees is with pre-commercial thinning (Holmström, 2015). An increase of broadleaf tree species in the landscape is favoured by a policy initiative by the Forest Stewardship Council (FSC). A minimum of 10 percent broadleaved tree species by volume, must be retained until the final felling at the end of the rotation period in a monoculture, according to FSC Sweden and 5 % in the northern part of Sweden (FSC, 2010). An increased proportion of broadleaves in the landscape can reduce edge effects at the boundaries of natural vegetation patches (Fischer et al., 2006). It also provides a base for future conservation actions (Felton et al., 2011). In general, broadleaved trees are less flammable than conifers, due to higher levels of resins and oils in the conifers (Bond & van Wilgen, 1996). A mixture with birch and spruce can therefore decrease the risk of fires compared to a monoculture of spruce (Felton et al., 2016). The risk for pest and pathogens outbreaks also decreases in a mixed stand (Pautasso, 2005). This could be explained by greater diversity of predators and parasitoids of pest species and a decrease in the transmission potential (Tahvanainen & Root, 1972; Keesing & Ostfeld, 2006). A disadvantage of mixed stands is that larger herbivores prefer birch to Norway spruce. Norway spruce stands containing birch have therefore been observed to have more impacts from browsing, than stands without birch (Månsson et al., 2007). Even if Sitka spruce is not native to Iceland, some of the above findings for Scandinavia can be assumed to be valid for Icelandic forestry where the native downy birch is used in mixed stands. This particularly concerns the mixture effects from the birch on the volume growth and sheltering for Sitka spruce. Sitka spruce is found in the Boreal zone just like the Norway spruce and there are various studies that classify Iceland as being part of the Boreal zone or at least the lowelands of Iceland (Steindórsson, 1964; Tuhkanen, 1993; Rees et al., 2002). This is relevant because this experiment in Gunnarsholt is situated in the lowlands of Iceland and therefore in the Boreal zone.

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1.4.1. Management of spruce and birch mixture Even if the present study has Sitka spruce and downy birch mixtures (Figure 4), it is interesting to review Scandinavian literature on Norway spruce and birch mixtures. In the present project I only focus on the first 15 years of the experiment rotation. It is important to keep in mind that the economics of a mixed stand depend on many factors, which many are not observed until later in the stand rotation; e.g. quality of logs, prices for different species at the time of harvest, yield, rotation period, investments and labour intensity. The cost for regeneration depends on the method, seedling-material and species composition. One way to decrease the cost of regeneration can for example be to use natural regenerated birch with planted Norway spruce seedlings; something that is not an alernative when a new forest is established in a treeless landscape as at the site in Iceland. Saving retention birches at clear-cuts and in neighbourly stands can have positive effects on the natural regeneration of birches (Agestam et al., 2006). Birch is not very sensitive to frost damages and can therefore be used as a shelter tree to protect more sensitive tree species, for example Norway spruce from frost (Rytter et al., 2014). The next management to be done in the LT-project is a pre-commerical thinning. It is often more expensive in mixtures, because they are more complicated to thin and have often higher stem densities (Agestam, 2015; Pettersson et al., 2012), albeit not in this project where the stand density was the same in mixtures and monocultures.

Figure 4. Two mixtures of Sitka spruce and downy birch from Spámannsstaðaskógur (Spámannsstaðaforest) at Gunnarsholt in Sourthern Iceland. Stand nr. 7 on the left and nr. 9 on the right (see figure 8 and table 2. for stand description). Picture taken 26.12.2019 by Jón Hilmar Kristjánsson. Pre-commercial thinning often must be performed at least two times, compared to a monoculture of Norway spruce were once often is enough (Agestam, 2015; Pettersson et al., 2012). The economics of first thinning are very dependent on the removed volume of the stand.

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As mentioned before, volume production in mixed stand can be higher, than in a monoculture and could therefore lead to an increased income in the first thinning. But the economics in the first thinning are also dependent on how large the stems are. Small stems lead to higher costs (Agestam et al., 2006). The economic outcome for the last thinning and final felling are more dependent on the timber quality and since competition in the young stand is important for the quality, this can be an advantage for mixed stands with high density of natural regenerated birch (Johansson, 1996). A shelter with birch has also been proven to give Norway spruce higher timber quality with smaller branch diameter (Klang & Ekö, 1999). Pre-commercial thinning is a good way to change the composition and density of tree species and the structure in a stand. It is important that the pre-commercial thinning isn´t too late, since it is hard to transform a suppressed tree to a crop tree and the light demanding birches need large canopies to be able to grow as good as possible within the mixed stand (Pretzsch, 2009; Rytter et al., 2014). To maximize the result from pre-commercial thinning, it is important to perform the thinning with different characteristics of the species in mind. For instance, so can the shade-tolerant Norway spruce grow well under birches, but the light demanding birch has very little chance to develop to a crop tree under Norway spruce (Tham, 1994; Agestam et al., 2006). It can also be a good idea to wait with the commercial thinning to be able to have a larger selection of crop trees for better quality. If, however, pre-commercial thinning is done too late, it is possible that one species has outcompeted the other species and the goal composition of species in the stand cannot longer be reached (Rytter et al., 2014). In a pre-commercial thinning experiment at the Asa Experimental Forest in Sweden, different mixtures of Norway spruce and birch were tested. Pure Norway spruce plots were compared to mixtures with 20 % and 50 % birch. Four years after establishment, the mixture with 20 % birch had the largest basal area, but the differences between the treatments were small (Lindén, 2003). The present experiment has 25 % and 50 % downy birch mixtures with Sitka spruce.

1.5. Mixtures between spruce and aspen The natural mixture of trembling aspen and white spruce is among the most common forest type in Canada (Rowe, 1972). Even if these species are not the same as used in the present study, it is interesting to look at other mixtures of aspen or poplar with spruce, as there are not many studies on the mixture of Sitka spruce and black cottonwood to be found. Trembling aspen / white spruce mixtures have been predicted to produce larger amounts of timber than stands of monoculture (Man & Lieffers, 1999). Kabzems et al. (2007) studied trembling aspen density effect on white spruce in a controlled mixture experiment from 1989 in British

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Columbia. Early results from the 13 to 17-year-old forest showed that there was no significant difference between spruce growing in a mixture with 5000 or 10000 aspen trees per hectare. The aspen on the other hand showed increased diameter growth with less density. Prediction model showed that the total productivity of the spruce over the rotation period may be 21 % higher in mixed stands, compared to a monoculture of spruce.

Figure 5. Two mixtures of Sitka spruce and black cottonwood from Ketluskógur (Ketluforest) at Gunnarsholt in Sourthern Iceland. Stand nr. 39 on the left and nr. 58 on the right. (See figure 8 and table 2. for stand description). Picture taken 26.12.2019 by Jón Hilmar Kristjánsson. 1.6. Mixtures in Iceland Birch is the only native tree species that forms forests or woodlands in Iceland. Native mixed forests are therefore rare. The most common mixture in natural forests is birch and tea-leaved willow (Salix phylicifolia L.) where the birch has low stature, but otherwise the willow generally forms a shrublayer below the birch canopy (Hallgrímsson, 1995; Blöndal, 2002a). A much less common blend is birch and mountain ash (Sorbus aucuparia L.; also named rowan), where the rowan usually consists of a few trees or patches in the rowan/birch forest mixture (Snorrason, 2013; Blöndal, 2000a; Bjarnason, 1987). In a unique location in eastern Iceland (Egilsstaðaskógur), birch and European aspen are found in a mixture where the European aspen has only regenerated from root suckers under existing canopy gaps in the birch forest (Snorrason, 2013). Common juniper (Juniperus communis L.) is the only native conifer species in Iceland. It is found almost everywhere in Iceland, but less in the southern part and it grows both on its own and in a mixture with the native birch. Juniper does seldom reach heights of more than two meters (Icelandic Institute of Natural History, (e.d.a). The common juniper can be found in the Þórsmerkur area (southern Iceland), Fnjóskadal (northern Iceland) and in old birch forests around Búrfell and Hekla (both in southern Iceland). The juniper in Iceland has

18 recently begun to grow higher and even reaching the heights of small willows (Salix sp.) in some areas (Óskarsson, personal communication). After foreign trees had been planted into the native birch, the birch was removed in later pre- commerical thinning or was shaded out when more shade tolerant conifers outgrew the birch (Pétursson, 1993; Snorrason, 2013). Such mixtures can be found in Þjórsárdalur where spruce, pine and larch have been planted into a natural birch forest between the years 1939 and 1990 (Skógrækt ríkisins, e.d.). Since ca. 1990 there has been a systematic move to more mixed planted forests (Snorrason, 2013). Both native and foreign tree species are planted in mixture and in the last inventory ca. third of planted forests in Iceland are mixed stands (Snorrason, 2013). The so-called Corine land classification has been used in Icelandic land use classification, where mixed forests are defined as forest grown areas where neither conifers nor deciduous trees dominate, where the average height of trees is at least 2 meters, the total forest coverage is greater than 30 % or the number of trees is greater than 500 per hectare. The proportion of coniferous or deciduous trees should not exceed 75 % of the coverage of the tree crown (Árnason & Matthíasson, 2009). The most likely trees to be used as main species in planted mixtures in Iceland will be those that have shown high survival rate and good growth with decades of experience. The most common species are Siberian larch, native birch, Sitka spruce, black cottonwood and lodgepole pine (Pétursson, 2000; Snorrason, 2013). In Iceland there has little research been done on the effects of species composition on growth and forest production, outside the relatively recent LT-project (Eggertsson, 2004; Sigurðsson et al., 2006; Sigurðsson, 2011; Jóhannsdóttir, 2012; Jóhannsdóttir et al., 2013). Therefore, the present project is of high importance for the Icelandic forest sector on the initial effects of species mixtures on survival, growth and production.

1.7. Effect of Climate Change in the Nordic countries The global mean surface temperature (GMST) is expected to increase in the next decades by between 1.4 and 4.48°C because of increased atmospheric concentration of carbon dioxide

(CO2) (IPCC, 1995; IPCC, 2007). The GMST has already reached an increase of 0.87°C when temperatures between 2006–2015 are compared with 1850–1900 (Hoegh-Guldberg et al., 2018) and in Iceland the rise in air temperature has been similar when the trend during the last two centuries is plotted (Björnsson et al., 2018). Until the middle of the century, it is likely that the land and sea area around Iceland will be warmer and that the years 2046–2055 will be on

19 average 1.3-2.3°C warmer than the years 1986–2005. It is further expected that winters will warm more than the summers in the coming years (Björnsson et al., 2018). Precipitation has also increased from being on average 1500 mm / year to 1600-1700 mm / year in recent years (Björnsson et al., 2018). Temperature- and rain increase might have big impact on trees that are less water tolerant and trees that are sensitive to temperature changes for example if winters become warmer, some trees might start growing in the winter time and then suddenly it gets colder again leading to frost damage. Not only will increased temperature make the growing season longer for trees (Linderholm,

2002; Perez-Garcia et al., 2002) also, the increase of CO2 will affect the function of photosynthetic and growth response (Curtis, 1996; Ainsworth & Long, 2005; Wang et al.,

2012). One such study on the effects of rising CO2 concentrations was done in the Gunnarsholt Experimental (black cottonwood) Forest in the 1990s (Sigurðsson, 2001, 2003). Even though photosynthesis will increase with higher atmospheric CO2 concentrations, it is uncertain how much it will affect the growth rate of trees (Sigurðsson, 2001, 2003; Körner, 2006; Hyvönen et al., 2007). Some studies have been conducted on impacts of climate change on Boreal forests (Lapenis et al., 2005; Schlyter et al., 2006), and even including the Gunnarsholt Experimental Forest (Bergh et al., 2003). Sigurðsson et al. (2013) concluded that the poor supply of nutrients, or mostly nitrogen, in

Boreal forests is likely to restrict their reaction to the continuous rise in CO2. This might be usefull for trees planted with lupine that releases nutrient from the soil, otherwise it is hard for trees to get nutrients from the Icelandic soil (see later). Scientists also agree that environmental disasters in response to climate change are certainly going to increase in frequency and severity during the 21st century (IPCC, 2007). Extreme events can have a tremendous impact on Boreal forests and natural resources. It is likely that unusual weather conditions such as variations in spring weather, and summer drought will increase in number and duration, and combined with an increased mean temperature, severe climatic conditions can impact trees adversely and increase their vulnerability to secondary damage from pests and pathogens (Schlyter et al., 2006). In northern Boreal forests, the limits and capacity for timber production are restricted by low temperature and often by nutrient accessibility. Precipitation is not usually restricted. The higher atmospheric temperature expected by future scenarios could extend the growing season and thus increase production. For the southern region of the Boreal forest, production is limited by water supply and less by temperature and nutrients (Kellomäki & Leinonen, 2005). Climate change in the Boreal zone can in some parts be applied to the Icelandic lowlands because they

20 are a part of the Boreal zone (Bergþórsson, 1985). Establishing more mixed forests, and thereby likely increasing the resilience towards climatic change and climate extremes, is one of the proposed methods for climate change adaptation of the forest sector (e.g. Boshier, 2007) (see below).

1.7.1. Forest management for climate change Forest management will need to be adapted to needs and opportunities at local, regional and national scales (Perez-Garcia et al. 2002). Scotch pine in Finnland is expected to grow faster with increasing temperature and CO2 levels (Kellomäki & Kolström, 1993). With faster growth the rotation will be shorter if regeneration rate doesn´t change. There will be a need for earlier and more intensive thinnings which will result in more pulp wood before final felling (Kellomäki & Kolström, 1993; Kellomäki et al., 1997). If the rotation length becomes longer, there might be a possibility of increasing the proportion of saw log timber by thinning away small dimension trees and increasing the space between the future crop trees (Kellomäki et al., 1997). Briceno-Elizondo et al. (2006) used a simulation that represent the Boreal forests in Southern and Northern Finland. They stress that the current management rules might need to be changed in order to exploit the benefits that climate change seems to provide in the form of increased growth and timber yield in the Boreal conditions. Boshier (2007) argues that the focus on local seed supplies may pose a problem as the habitat of a site may no longer encounter the conditions in which the trees developed, due to the long lifespan of the trees and projected global warming. The selection of species might also have to be widened. The idea and terminology of 'species nativity' may need to be questioned, as the development and maintenance of reliable, long term-proof forests may involve the use of a multitude of native species sources in a mixture with exotic species where appropriate. Because Iceland has so few native species it is important to use exotic species, e.g. spruce, black cottonwood and pine, of provenances from different latitudes than Iceland.

1.8. General climate in Iceland Iceland has a cool temperate maritime climate created by the Gulf Stream bringing up warm air from the equator to the southern and the western coast which makes the climate more moderate (Einarsson, 1984). On the other hand, when the mild Atlantic air meets the colder arctic air it can result in a climate with frequent changes in the weather. This also leads to more

21 precipitation in the southern and western part of Iceland than in the northern part (Einarsson, 1984).

1.9. Planting Methods Apart from studying the effects of species mixtures on survival and growth, this project re- evaluates an experiment studying the effects of different planting methods, which was established in the monoculture plots at the time of planting (Eggertsson, 2004). Here I give some background for the state of knowlege on those issues.

1.9.1. Initial Spacing Initial spacing in plantations affects the competition between trees for sunlight, moisture and nutrients and therefore influences tree growth patterns and wood formation. Differences in stand density can also affect other aspects of the trees’ physical environment such as soil temperature (Zobel & van Buijtenen, 1989) and wind flow (Green et al., 1995; Gardiner et al., 1997). There is a general agreement that trees planted at wider initial spacing tend to have bigger knots, increased ring widths during the period of juvenile wood formation resulting in a larger juvenile core, and reduced average wood density (Brazier, 1970, 1977; Gardiner & O’Sullivan,1978; Humphreys, 1991; Brazier & Mobbs,1993). Michie (1926) advocated a maximum plantation spacing of 2.1 m in Scotland, which he considered adequately close to prevent the formation of large knots. In Britain, planting Sitka spruce in a 1.7 m spacing or 3460 trees/ha is a common practice (Matthews, 2016). The realized stand density in a 15-year-old planted stand is a funciton of two things; the intitial planting density and the survival (see later) of the initially planted seedlings. However, this might also be affected by natural regeneration and rootshots. The average planting density in Iceland before and after 1990 was estimated as 4000 and 3000 seedlings per ha, respectively (Snorrason & Kjartansson, 2017). The initial planting density in the current experiment (3200 Trees per ha) can be considered common for Icelandic conditions (Sigurðsson, personal communication).

1.9.2. Soil scarification In 1960, the first soil scarification for forestry in Iceland was carried out in a swamp in Haukadal in Biskupstungur and in mooreland in Heiðmörk in Reykjavík with a so-called sharpening plow (Bjarnason & Benedikz, 1980). Harrowing in swamps became a bigger success than in mooreland, so more swamps were site prepared for planting the next years (Sigurgeirsson &

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Ásgeirsson, 1998; Blöndal, 1998). However, this practice has been rejected since 1990 in Iceland (Jónsson, 2002a). There are a few different types of scarification methods commonly used in Iceland. Some of the most common ones are; manual scarification, machine screefing, trenching with a TTS- mechanical disc trencher, screefer, and machine harrowing with agricultural ploughs. Manual scarification is done with either a notch or with a trimmer which gives the same effect (the surface is scraped off) but might be easier on the worker (Baldvinsdóttir & Sigfússon, 2002). The TTS-disc trencher is most commonly used in meadows, with thick vegetation and moss, but mainly in areas with dwarf birch (Betula nana L.). The disc trench tears up the vegetation (two channels at once) and sets it aside to the wound it forms (Baldvinsdóttir & Sigfússon, 2002). A screefer is a trench that tears up turf at certain intervals and puts them upside down. The device is lightweight and causes less ground damage than e.g. the TTS disc trenchers and does not form channels that create a risk of water erosion. However, in shallow soils on gravel or clay, there may be a risk of frost lifting if the seedlings are planted into the open soil (Baldvinsdóttir & Sigfússon, 2002). Machine harrowing (trenching) is preferably done by a modified agricultural plough that cuts the plough string loose and places it next to the resulting open soil. The plough string should be laid so that surface water flows out of it into a nearby ditch and the plough string shelters the plants in the worst wind direction. Harrowing can be suitable in thick vegetation with a lot of moisture and grass, e.g. in old agriculture land. Harrowing has the disadvantage that the land will be difficult to cross both on foot and on machines (Baldvinsdóttir & Sigfússon, 2002). In the present study a special planting machine harrowed and planted at the same time and was used in the whole experiment. However, manual scarification was used partially in the Eggertsson’s project (see later in methods). The goal of soil scarification is to improve soil conditions for planting by loosening and pushing aside vegetation (Baldvinsdóttir & Sigfússon, 2002). This increases the soil moisture, soil temperature and decreases the risk of frost damage (Örlander et al.,1990; Oleskog, 1999). The reduced competition from field vegetation for water, nutrition and light is another positive effect of soil scarification (Hagner, 1962; Jónsson, 2002a). In addition, the tree plant receives nutrients from the decaying vegetation that has been peeled off and, in some cases, sheltering increase with such action (Baldvinsdóttir & Sigfússon, 2002). The disadvantages are an increased risk of frost-lifting, but this can be prevented by planting in the spring and applying fertilizer to the

23 plants shortly after planting (Oddsdóttir et al., 1998). Seedlings show more growth and higher rate of survival in soil that has been scarified (Óskarsson et al., 2011; Jónsson, 2002a). Soil scarification is most commonly used in grassland, semi-wetland and drained wetlands in Iceland (Skúlason et al., 2003). It is less common in dryer areas with little vegetation (Skúlason et al., 2003). Vegetation vigor of the future forestland also has a great influence on the choice of type and size of plants that should be used, as well as the selection of soil scarification methods (Jónsson, 2002a). The more vegetation the land has, the more soil processing is normally required to reduce competition (Jónsson, 2002a). Eggertsson (2004) studied the effects of harrowing among other methods on seedling growth and survival in the year after planting. Björgvin found that trees had more volume growth in harrowed treatments than in unharrowed treatments. Plants that got intitial small-dose fertilization increased their diameter growth more than those without fertilizer. There was also less frost damage in harrowed areas than in unharrowed. The survival for Sitka spruce, downy birch and black cottonwood was on average very high, or 95 %, 94 % and 97 %; which made no treatment significant, except for the non-harrowed treatments, where the survival was significantly lower for all species (Eggertsson, 2004). The long-term effects of harrowing have only been slightly observed in Iceland (Karlsson, 2009; Óskarsson et al., 2011) and more research is needed in this area to further enhance understanding of the subject. The results of the current study will hopefully give some further insight into the topic.

1.9.3. Planting in Nootka lupine and grassland areas In general, Icelandic soils are poor in nitrogen (N) and phosphorus (P) in accessible form (Pálmason et al., 1996; Arnalds & Óskarsson, 2009). The lack of these nutrients in the soil prevents the formation of strong and continuous vegetation that can withstand erosion (Arnalds et al., 1997). It may well be, that one of the main reasons why Icelandic soils became so easily eroded is that the flora lacked key species that make ecosystems stronger, for example more plants that fix N (legumes). Iceland's geographical isolation might be the reason why the country has so few species of legumes and other plants. Only eight species of legumes are recognized in the native Icelandic flora, but in comparison, around 100 species of legumes grow natively in Norway (Orradóttir & Helgadóttir, 1997; Lid & Lid, 1994). Around the middle of the last century, Hákon Bjarnarson, then a Forest Commissioner of the Forest Service of Iceland, brought few seeds and roots of Nootka lupine from Alaska to use

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for land reclamation. For a long time, the distribution of the species was limited, but after 1990 the distribution increased and the Nootka lupine is now widespread throughout the country; or on ca. 30.000 ha in 2017 (Guðjohnsen & Magnússon, 2019) (Figure 6). These changes can be attributed to various factors, such as reduced sheep grazing Figure 6. Distribution of Nootka lupine in Iceland 2017, total area 299 km2. Map from the Icelandic after 1980 and increased use of the institution of natural history. Source: Guðjohnsen Nootka lupine for land reclamation and & Magnússon (2019). forestry purposes (Icelandic Institute of Natural History, n.d.b). With the advent of lupins, N flow multiplies into the ecosystem and the productivity of vegetation increases greatly. Soil is enriched and the entire ecosystem transforms all the way from micro-organism to small-scale wildlife, vegetation and up to larger animals (Davíðsdóttir, 2013; Davíðsdóttir et al., 2016). Species that cause such changes in evolution, species composition, activity and ecosystem processes have been referred to as ‚ecosystem engineers’ (Crooks 2002; Hastings et al., 2007, Liao et al., 2008). The effects of such species can be felt long after they disappear from communities. There are indications that ecosystem engineers that increase habitat diversity are accompanied by a rise in the number of species in communities, but those that increase area homogeneity are accompanied by a decrease in species richness (Crooks, 2002). Nootka lupine can be regarded as an ecosystem engineer in Iceland. When planting in grasslands the focus should be on planting the most nutrient-demanding tree species, such as black cottonwood and spruce according to Icelandic recommendations (Baldvinsdóttir & Sigfússon, 2002). However, species such as downy birch, silver birch, mountain ash and pine (Pinus sp.) can also do well, but larch, however, does not withstand competition with grass and therefore should not be planted in the most fertile sites in Iceland (Baldvinsdóttir & Sigfússon, 2002). Many studies have shown that grass is a serious competitor to trees and that their survival can often depend on removing grass or limiting the competition effect from grass. (Þórsson, 2008, Jónsson, 2002a, Kimmins, 2004; Fensham & Kirkpatrick, 1992; Holl et al., 2000). On the other hand, Magnússon et al. (2001) found that downy birch and small willows (Salix lanata L. & Salix phylicifolia L.) do not thrive in very dense lupine but can survive better in less density. Lupine is usually densest the first 10-15 years after

25 establishing and is denser in the southern part of Iceland compared to the northern part. Eysteinsson (1988) found that Sitka spruce grows usually better if planted in lupine compared to without lupine. Sigurðsson (2005) found that planting cuttings of black cottonwood, Alaskan willow and Tea-leaved willow in lupine had a positive effect on growth compared to sandy areas without lupine. However, there was no difference in survival between the two habitats if longer cuttings were used in the lupine than outside. Also, longer cuttings showed more growth and less frost damage in lupine compared to without lupine. Aradóttir (2000) studied the effect of different lupine density and the effect of mowing the lupine on growth and survival for planted downy birch. The results showed that birch had less survival in lupine and competition between birch and lupine was more in denser lupine. However, the growth of birch could be significantly increased when the birch was planted into lupine that had been mowed when it was starting to flower and hence was killed off (Aradóttir, 2000; Sigurðsson et al., 1995). Also, Jóhanna Ólafsdóttir (2015) found that Downy birch showed higher survival and increased height growth in lupine plantation compared to sandy area without vegetation.

1.10. Survival of tree seedlings in Iceland There are many things that can impact mortality rate (survival) for plants in a sparsely vegetated land, like frost heaving, frostbite, limited or no nutrition and pests (Aradóttir & Magnússon, 1992; Aradóttir & Grétarsdóttir, 1995). When planting trees in such areas it is possible to increase the survival for example by giving fertilizer and animal manure to the plant (Óskarsson et al., 1997; Aradóttir & Grétarsdóttir, 1995, Óskarsson et al., 2006). Sirka 10-15 g of chemical NPK fertiliser around planted seedlings has been found to improve initial survival and enhance establishment growth and is after since 2000 a standard planting method in Iceland (Óskarsson et al., 1997; Óskarsson & Brynleifsdóttir, 2009; Óskarsson, 2013). It is also possible to increase seedling survival by choosing more sheltered planting-spots (Aradóttir & Magnússon, 1992; Aradóttir & Grétarsdóttir, 1995) or by planting into spots with some type of short living plant species has been sown (Oddsdóttir et al., 1998). One way to create vegetation in a short time in such areas is to plant Nootka lupine, which gives shelter, minimizes frost heaving and increases the fertility of the soil. However, lupine can make dense vegetation and even so dense that lupine kills off other smaller vegetation, including tree seedlings (Magnússon, 1995). In Iceland, survival of planted seedlings may also differ between planting seasons. Pétursson & Sigurgeirsson (2004) found that planting Sitka spruce seedlings in Iceland in the spring, rather than late autumn improved the survival. Direct seeding under a plastic cone gave similar results of establishment after 4 years, as planted seedlings (Pétursson & Sigurgeirsson, 2004).

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Aradóttir & Magnússon (1992) studied land reclamation areas planted by tree seedlings in a forestry campaign called the Land Reclamation Forests Project (LRF; IS: Landgræðsluskógar). A total of 76 areas were established across the country and 1.1 million tree plants were planted in the summer of 1990. Their evaluation of the effectiveness of the land reclamation forest from 1990 was conducted in the spring of 1991. The results of the study revealed that mortality rate for downy birch was 0-19 %, for Siberian larch the mortality was 1-6 % and for lodgepole pine it was 24 %. The pine was only measured in one location while the birch was measured in 10 different areas and the larch in 3. The best survival was in patchy land and heather (Calluna vulgaris L.), but worst in areas covered by moss and gravel. The general conclusion was that mortality in land reclamation forestry were rather low in the first year after planting (Aradóttir & Magnússon 1992). Aradóttir & Grétarsdóttir (1995) continued the research in the LRF Areas. In spring and autumn 1992 and autumn 1993 they looked at the most LRF same areas as they examined in 1991. They looked at the planting of 1991 and 1992. The birch was usually the best of the three species that were planted in 1991 and measured in autumn 1993. For birch, the mortality was about 15 % and just over 30 % for the larch and pine. For plants planted in 1992, the mortality was 15 % for the birch in the fall of 1993, 15 % for the pine and 30 % for the larch. Usually the mortality was higher for the birch and pine that had been planted in grassland in 1992. In 1996, Aradottir & Arnalds (2001) found that the mortality continued to increase and that the average survival rate for birch was then down to 70 %, for the pine it was on average 63 %, and 44 % for the larch, four and five years after planting. Also, the variability was high in the data and birch survival ranged e.g. between 32 % and 94 % at individual sites. Sigurjónsdóttir (1993) studied Siberian larch plantings in Fljótsdalshérað from 1991 and 1992, one and two years after planting. Mortality varied somewhat between years and regions and were at least about 15 % and as high as 35 % in some cases. Very little difference was between the survival in plantings planted in the spring and autumn in this study. Eggertsson (2005) studied the survival of forest seedlings in the southern part of Iceland the summer 2004. He surveyed 24 forest estates and almost 530 hectares. The method of evaluation was based on counting alive plants in 50 m2 circular plots and comparing how many plants were supposed to be planted in that area according to a cultivation plan (actual survival compared to planned). Survival in different vegetation communities was; moss 67 %, heather 74 %, grassland 59 %, moist land 45 %, wetland 44 %, unvegetated 88 % and level fens 80 %. On average, mortality rate was about 40 %.

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Þórsson (2008) carried out a survey in the summer of 2007 and surveyed plantings from the years 2000 - 2006 in northern Iceland. Living plants were assessed and spots with missing plants identified in 100 m2 random pots. The results of the assessment gave a range of mean survival from 65 % to 75 %. There was neither significant difference in survival of different tree species, nor did survival depend on whether the planting was done in spring or autumn. There was a significant difference in survival by vegetation classes and there was a significantly better survival in heathlands than in grasslands and moss heath. Since 2005, data have been collected in the Icelandic Forest Inventory (IS: ÍSÚ) (Snorrason & Kjartansson 2004a, 2004b, 2005). Mortality from the ÍSÚ was evaluated in such a way that the number of dead plants in each metric area was evaluated based on the location of live plants. National average survival from the Icelandic Forest Inventory was 60 %, with the 95 % confidence intervals of 43-51 % (Snorrason & Kjartansson 2004a, 2004b, 2005). Average survival in southern Iceland was 67 % (Snorrason & Kjartansson, 2004b).

Figure 7. Severely frost damaged Sitka spruce planted in 2002 in grassland in stand nr. 8 in Gunnarsholt in Southern Iceland. (See figure 8 and table 2. for stand description). Picture taken 26.12.2019 by Jón Hilmar Kristjánsson.

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1.11. Aims As mentioned earlier, the present study is a part of an existing long-term research project (IS: LT-verkefnið) in southern and eastern Iceland. The main aim of the LT-project is to compare mixtures of the most used conifers and broad-leaf trees in Iceland with monocultures of the same species. This project will in the long-run show if or what the benefits of the mixtures will be on potential wood production, biomass and carbon sequestration, soil quality and biodiversity. The LT-Project is the first initiative where the species of downy birch, Sitka spruce, lodgepole pine and black cottonwood are compared with each other on large continous plots in the same soil conditions in Iceland. It has been customary in Iceland to plant birch and pine in degraded soil, but Sitka spruce and black cottonwood are usually planted in more fertile soils; i.e. the species are chosen in each site according to their demands on soil fertility (Baldvinsdóttir & Sigfússon, 2002). The first main goal of the present research was to remeasure the planting experiment done by Eggertsson (2004) at the Gunnarsholt site, to see if any long-term effects would be visible in survival and the growth potential of downy birch, Sitka spruce, and black cottonwood 15 years after planting. The second goal of this project was to investigate if there existed any difference between mixed and monoculture plots in survival, tree growth, stand productivity and stem quality. This is the first big inventory in the LT-Project in southern Iceland, and by establishing fixed plots in this project, the measurements will also form the basis of further research in the future. The third goal was to compare the two different habitats used in the LT-Project in southern Iceland; a former hayfield with thick soil that had turned into an unmanaged grassland and an eroded area with thin soil which had been reclaimed by Nootka lupin. Research questions: Survival: • What is the total survival rate in the experiment? • Which tree species has the highest rate of survival in the experiment? • Did different planting methods have any long-term effects on survival? • Has survival been affected at all by species mixtures? • Was the habitat (land type) important for the survival? Growth and production: • What is the total volume and biomass production in the forest? • What species grows and produces the most timber in the experiment? • How was the native downy birch doing compared to the exotic species?

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• Do different planting methods have any long-term effect on tree growth? • Does a mixed forest grow and produce more than a monoculture? • Do the proportions 50/50 or 75/25 have different effects on growth and production? • Was the habitat (land type) important for the growth?

• How much CO2 did Sitka spruce, black cottonwood and downy birch sequestrate/year? • What was the carbon and carbon dioxide total sequestration in the forest? Stem form: • Does mixing species have any effect on the stem form of 15-year-old Sitka spruce and black cottonwood? Foster trees • Does 50 % mixture of the fast-growing Alaska willow increase Sitka spruce performance?

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2. Materials and methods 2.1. Site description and experimental background This study was conducted within a larger long-term experiment (IS: LT-verkefnið) and was partly a re-evaluation of an earlier study on planting methods (the Eggertsson’s experiment; Eggertsson, 2004). Here I will give more background information about those experiments as well as a general site information.

2.2. Site characteristics The study area is located in the southern part of Iceland at Gunnarsholt where the Soil Conservation Service of Iceland (SCSI) office is situated (Figure 8). This is a part of the Rangárvallasýsla district, about 105 km from Reykjavík. The soil around this area is very basaltic, originating from the volcanoes around the area. As mentioned previously, the experiment is divided between two areas; Spámannsstaðaskógur (Spámannsstaðaforest (63°51'38.1"N 20°11'18.9"W)) and Ketluskógur (Ketluforest (63°51'13.2"N 20°14'47.7"W)), with about 2.7 km distance between them. i) Ketluforest lost its vegetation due to wind erosion long time ago, this made the area sandy and sparse before vegetation was established. The sandy soil is thin (ca. 20-30 cm) on top of a petrified Ice-Age sediment (IS: móhella). Lupine was introduced to the area in 1996 to improve the soil (Eggertsson, 2004). The site was then used for lupine seed harvesting by SCSI, which had led to a partial dieback of the lupine at the time of planting. ii) Spámannsstaðaforest is a hayfield that was originally harrowed into natural grassland and sown with fescue (Festuca rubra Höf.) and Kentucky bluegrass (Poa pratensis Höf.) in 1965. The area was fertilized and used for feeding livestock until 30 years prior to 2019 and for a decade or more before the start of the experiment it had been left as unmanaged horse pasture (Eggertsson, 2004). It also has a thicker soil than the Ketluforest.

2.3. Site conditions The study site has a mean annual temperature of +5.0°C, with average annual minimum temperatures going down to -6.9 °C and maximum being on annual average +14.1°C. The average wind speed is 5.9 m/s, even though the average annual highest wind speed is 19.2 m/s with average highest annual wind gusts reaching 26.1 m/s. The mean annual precipitation is 1264 mm, with most of it falling between January and July and less in August to December (Table 1).

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Table 1. Temperature and windspeed per month at Hella weather station from the years 2006 to 2019 and precipitation from Sámsstaðir weather station from the years 2002 to 2019. Hella weather station is situated 6.5 km south of Ketluforest and 8.7 km south of Spámannsstaðaforest. Sámsstaðir is situated 15 km east of Ketluforest and 13 km east of Spámannsstaðaforest. The data is from the Icelandic Meteorological office (Veðurstofa Íslands). Temperature Windspeed Precipitation

Average Average Average Average Average Average Min Max Month (°C) high (°C) Low (°C) (m/s) high (m/s) (mm) (mm) (mm) 1 -0.5 8.7 -13.6 6.8 22.4 144.3 69.6 239.9 2 0.1 8.6 -12.3 7.3 23.0 101.7 39.9 290.1 3 0.9 10.1 -11.6 6.7 21.6 104.6 23.6 171.1 4 3.7 12.6 -8.4 6.3 19.6 121.7 25.7 200.6 5 6.9 17.1 -4.9 5.7 17.3 126.5 58.9 220.8 6 10.2 19.1 0.7 4.6 15.2 104.7 24.7 277.3 7 12.0 21.9 1.9 4.3 15.1 100.6 25.4 270.7 8 11.0 19.7 -0.3 4.5 15.8 89.7 15.9 180.8 9 8.4 16.5 -2.5 5.4 18.2 59.3 16.9 141.8 10 4.3 13.2 -6.8 6.0 19.7 55.6 23.4 113.8 11 1.2 10.2 -11.3 6.7 21.1 79.0 19.1 201.7 12 -0.8 9.1 -14.7 6.8 22.6 85.0 32.2 174.5

2.3.1. The LT-Project in southern Iceland This is a long-term research project. It was founded in 2002 by the Icelandic Forest Service (Skógrækt ríkisins), the Ministry of Agriculture, as well as the Soil Conservation Service of Iceland (SCSI, Landgræðsla ríkisins), which lended land and equipment for the experiment (Sigurðsson et al., 2006). The aim of the project is to provide a future facility for various forestry research, as well as to study the effects of species composition, future fertilizer applications and other forest management on wood growth, stem quality and biology of the forest. In southern Iceland, all the main tree species used there were planted in ½ ha stands with four replications at Gunnarsholt, as monocultures or in different mixtures with the Sitka spruce (Picea sitchensis (Bong.) Carr.), all with the same total planting density of ca. 3200 trees/ha (Figure 8) (Sigurðsson, 2011). The replicated plots are randomly assigned within four blocks, with 16 plots in each block (each block is 8 ha) and a total of 72 plots in the four blocks. Two blocks are in Spámannsstaðaforest and two blocks are in Ketluforest. In total these experimental areas cover about 32 hectares of land (Sigurðsson et al., 2006). Between these the two main areas of the LT-project in Gunnarsholt is the Gunnarsholt (black cottonwood) Experimental Forest, seen as a dark square on Figure 8.

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The following genetic material was used for the experiment: i) Sitka spruce of the provenances ‚Taraldsöy’, ‚Tumastaðir’ and ‚Seward’. ii) Lodgepole pine (Pinus contorta Douglas) of the provenance ‚Tutsi Lake’. The pine was planted one year later than the other species (2003) and replanted in 2004 due to high initial mortality. iii) native downy birch (Betula pubescens Ehrh.) of the provenance ‚Bæjarstaðarúrval’, iv) black cottonwood (Populus trichocarpa Torr. & A. Gray ex. Hook.) of the clones ‚Brekkan’, ‚Jóra’‚ ‚Súla’, ‚Haukur’, ‚Tumi’ and ‚Pinni’. The provenances / clones of each species were randomly mixed before planting. These four tree species are the most used tree species for afforestation in southern Iceland. According to Gunnarsson (2009) 67 % of the planting by all the Regional Afforestation Programmes in Iceland in 2008 was by these four species. In 2015, 91 % of planted trees by the Regional Afforestation Program in southern Iceland (IS: Suðurlandsskógar) included these four tree species (Jónsson, 2015). Two treatments also had some native tea-leaved willow (Salix phylicifolia L.) of local origin (Tumastaðir) and Alaskan willow (Salix alaxensis (Andersson) Coville) of ‚Gústa’, ‚Máni’, ‚Töggur’ and ‚Mjölnir’ clones (see later).

Figure 8. The two forest areas Spámannsstaðaforest and Ketluforest at Gunnarsholt in southern Iceland with stand numbers from 1 to 64. P and C are harrowed and untreated unplanted control areas. The green stands were chosen for the growth and production measurements. Treatments and species are shown in Table 2. 33

Table 2. All the treatments and different species in each of the stands from nr. 1 to 64 shown on map in Figure 8. The table shows ratios of 50/50, 75/25 mixtures and monocultures. Ratio Spámannstaðaforest Ketluforest Treatment Common name Latin name % Stand nr. 38, 43, 51, 100 8, 12, 29, 30 Monoculture Sitka spruce Picea sitchensis 64 Black Populus 44, 47, 49, 100 1, 5, 17, 20 Monoculture cottonwood trichocarpa 55 36, 40, 41, 100 4, 6, 21, 26 Monoculture Downy birch Betula pubescens 54 33, 35, 53, 100 13, 14, 28, 31 Monoculture Lodgepole pine Pinus contorta 63 Sitka spruce Picea sitchensis 50 Mixture Black Populus 15, 19 39, 50 50 cottonwood trichocarpa Sitka spruce Picea sitchensis 50 Mixture 7, 27 52, 62 Downy birch Betula pubescens 50 Sitka spruce Picea sitchensis 50 Mixture 16, 24 45, 42 Lodgepole pine Pinus contorta 50 Sitka spruce Picea sitchensis 50 Mixture 11, 32 46, 59 Alaska Willow Salix alaxensis 50

Sitka spruce Picea sitchensis 75 Mixture Black Populus 3, 22 48, 58 25 cottonwood trichocarpa Sitka spruce Picea sitchensis 75 Mixture 9, 25 56, 57 Downy birch Betula pubescens 25 Sitka spruce Picea sitchensis 75 Mixture 10, 18 37, 60 Lodgepole pine Pinus contorta 25 Downy birch Betula pubescens 75 Mixture Tea-leaved 2, 23 34, 61 25 willow Salix phylicifolia

A ½ ha experimental plot would consist of either monoculture of Sitka spruce, downy birch, black cottonwood or lodgepole pine (two replicated plots in each block) or it would be a mixture of downy birch, black cottonwood or lodgepole pine with Sitka spruce in two different proportion: either 50 % Sitka spruce and 50 % of the other three species or 75 % of Sitka spruce and 25 % of the other three trees (Figure 8; Table 2). There is also a treatment with a mixture of birch 75 % and 25 % tea-leaved willow (planted as unrooted cuttings), which is a common native forest type in Iceland (Eysteinsson, 2017) and therefore represents a restoration of a native ecosystem. Furthermore, there is also one treatment with Sitka spruce 50 % and 50 % Alaskan willow. The much more rapidly growing willows were planted as a foster tree for the Sitka spruce.

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The Sitka spruce, birch, black cottonwood and the Alaskan willow were all planted with a planting machine in 2002. The tea-leaved willow unrooted cuttings were planted manually in 2002 as the maching planting advanced. Its manual planting started in early spring in Spámannsstaðaforest and continued until late June in Ketluforest, as the planting machine continued its mechanical planting. The lodgepole pine was handplanted in spring 2003. In the spring 2004 there was an inventory done on mortality and planting mistakes (the plants that never got into the soil or went under the soil when the planting machine got stuck) in the experiment. The results were that 8 % for Alaskan willow, 9 % of black cottonwood, 9 % of downy birch and 26 % of Sitka spruce (most of all in Spámannsstaðaforest), 39 % of tea-leaved willow and 60 % for lodgepole pine which had been hand planted the spring before, were dead (Sigurðsson et al., 2006). It was concluded that the lodgepole pine had had severe root frost damage before planting, a problem well known from nurseries in S-Iceland (Jónsdóttir, 2007). This led to the replanting of lodgepole pine in the spring 2004 and 2005; which makes a direct comparison with the other treatments difficult. If the mortality of the lodgepole pine is not included, then the total mortality rate was only 18 % in spring 2004 (Sigurðsson et al., 2006).

2.3.2. Eggertsson’s project Björgvin Eggertsson studied forest engineering at the forestry department in Yrkeshögskolan at Ekenäs in Finland at the time of the experiment. Björgvin managed the planting of the LT- project and worked on his final project (4th year’s project). His final project was set up inside the LT-project and the main goal was to evaluate the impact of different initial planting methods on the survival and growth of Sitka spruce, black cottonwood and downy birch in Gunnarsholt (Table 2). His treatments included machine harrowed furrows in the monoculture plots of the three tree species, where the plants were planted in the middle of the furrow, without applying any fertilizer or annual ryegrass (Lolium multiflorumi Lam.) seeding to help with the initial survival. This was the basic method used when the whole experiment was planted. Björgvin then had seven other treatments that varied by planting methods (Table 3): with the harrowing excluded but harrowed and planted by a planting machine (treatments 7 and 8); planted the seedlings at the edge of the plough string for shelter from the prevailing wind direction (treatment 6); included seeding of annual ryegrass (treatments 3 and 4); and applying ca. 10- 15 g of chemical NPK fertiliser around the planted seedlings (treatments 1, 3 and 5-7). Within each plot, the treatments started in row number 20 to 22 and continued to row 28 or 31 (counted from the east edge). The treatments where market with a stick at the beginning of the treatment

35 row, the stick was market with a plastic ribbon with the method number and which treatments where used in that row (Table 3.). Table 3. The initial planting treatments in Spámannsstaða- and Ketluforest used for monoculture of Sitka spruce, downy birch and black cottonwood in the summer of 2002 (from Eggertsson, 2004). Method nr. Soil preparation Planting position in plough string Fertilization Ryegrass 1 Machine harrowed Centre With Without 2 Machine harrowed Centre Without Without 3 Machine harrowed Centre With With 4 Machine harrowed Centre Without With 5 Machine harrowed Centre With Without 6 Machine harrowed East edge With Without 7 Manually scarified No plough string With Without 8 Manually scarified No plough string Without Without

Eggertsson (2004) measured the treatments shortly after planting in the summer 2002, and again in the summer of 2003, one year after planting. This was done to see the difference in frost damage, growth and survival for the first year after planting.

2.4. Inventory in spring and autumn 2018 Data was collected in three parts; i. Planting methods ii. Survival iii. Growth measurements

2.4.1. Planting methods / Eggertsson’s project The same rows that Eggertsson (2004) planted and measured had been located and measured again in January 2018. I measured the height and diameter at the same time valuating survival. Three tree species were measured in the Eggertsson’s project - Sitka spruce, black cottonwood and downy birch and all of them where planted into the monoculture stands within the LT- project, except for treatments nr. 8 and 7, they were planted in the C and P stands which are harrowed and untreated unplanted control areas (Figure 8). On the map of the experiment from Eggertsson (2004) methods where marked 1-8 and the numbers were marked on the map in the same order as they were planted. This made it quite easy to find the same rows as Eggertsson had measured and planted the rows. However, some of the markers (pins) had been buried in grass or lupine which made it harder to spot the markers right away.

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Diameter for Sitka spruce and black cottonwood was measured at breast height (1.3 m) with a caliper if the trees reached that height. Otherwise, they were measured at knee height (0.5 m) along with the birch which was only measured at that height. Height was then measured from the lowest part of the tree trunk to the top with either a height measuring pole or for trees under breast height with a folding ruler. Survival was counted and the distance was expected to be two meters between trees. Every time there was a cap two meters from the last counted tree, the cap would be counted as a dead tree.

2.4.2. Survival Survival was counted for 62 out of the 74 plots. The plots that were excluded consisted of soil and comparison plots without forests or trees that were a part of other experiments that were not testing the species mixture effect. The P and C harrowed and untreated unplanted control areas where excluded from the survival inventory (Figure 8). Survival was evaluated by randomly selecting 8 rows in each plot and walking them and marking living trees and dead ones and identifying to species. The „extra” rows from Eggertsson’s project within the monoculture plots were also included in this inventory. The trees were planted at regular 2 m interrow spacing and species mixtures were regular, i.e. every second tree (50 %) or every fourth tree (25 %), so it was assumed to be a tree within every two meters and if no tree was seen then it was considered dead. By counting number of rows in each plot and survival in a sub-set of those rows, it was possible to calculate the stand density in the experiment. The density was then later compared with the initial density of 3500 trees per hectare, that made it possible to evaluate if there were any extra trees in the stand that might have been added when the experiment was replanted or by natural regeneration with seeds or root suckers.

2.4.3. Growth, production and stem-form measurements Altogether 40 half hectare plots were selected out of the 72 to measure growth, production and stem form (Figure 8). All the 16 plots with lodgepole pine (13, 14, 28, 31, 33, 35, 53 and 63) were excluded, as shown in Figure 8 and Table 2, since it was planted 1-2 years later than the other species, as well as the 50:50 % birch : tea-leaved willow plots (2, 23, 34 and 61). Further, some plots that had been found to have less than 50 % survival (5, 8, 10, 16, 17, 18, 24, 37, 42, 45, 60 and 64) were excluded. The measured plots included monocultures of Sitka spruce, black cottonwood, downy birch and 50/50 and 75/25 mixtures of Sitka spruce with either of the two broadleaved trees. Also, the 50/50 mixture of Sitka spruce with Alaskan willow as a shelter tree

37 was measured (Figure 8; Table 2). Where there was a need for more replications (i.e. mininum three), plots with less survival than 50 % where taken into the growth inventory; which was the case for five plots (1, 11, 19, 22 and 39) and in total 40 plots were measured (plots number 1, 3, 4, 6, 7, 9, 11, 12, 15, 19, 20, 21, 22, 25, 26, 27, 29, 30, 32, 36, 38, 39, 40, 41, 43, 44, 46, 47, 48, 49, 50, 51, 52, 54, 55, 56, 57, 58, 59 and 62). Two fixed circular 100, 150 and 200 square meter (m2) measurement plots where randomly placed inside each of the 40 chosen stands, but in the way that each was inside different 50x50 m part of the plot (future sub-plots for forest management treatments). The size of the measurement plot depended on whether they described the stand well enough. If the survival was low and the trees were scattered all over the stand then a bigger circle was used (200 or 150 m2), but if it was dense then the measurement plot was smaller (100 m2). The plots were all marked with a GPS device and a 1 m long permanent wooden heel (with a wood protecting cover) was placed in the centre of each plot. The diameter was measured in the same way as in the Eggertsson’s project (see 2.4.1.). Tree height was measured by a measurement pole or with a carpenter folding ruler if the trees were under 1.3 m height on 9 trees in each measurement plot in the way that two of the smallest, two of the largest and five of medium sized trees were measured for height in monocultures. In mixed stands all the trees were measured, because in mixtures there were sometimes fewer trees of one species than the other. Dominant height was taken as the highest tree in a 100 or 150 m2 plot and the average of the two highest trees in a 200 m2 plot.

Figure 9. Trees with stem form A, B and C. The figure on the left shows an A-tree with straight stem up to 3 m height, the top has cracked just over 3 m height. The figure in the middle shows a B-tree with straight stem up to 2 m in height, where also the top has cracked but grown up again from 2 m height. The figure on the right shows a tree with crooket form on the whole stem up to 3 meters. Pictures from Birgisdóttir (2005).

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The stem form of the trees was evaluated at the same time as the growth measurements were carried out. The stem form evaluation was modified and based on a scale, used and described by Birgisdóttir (2005), for larch. Only trees that reached 3 m in height were assessed. Only the form of Sitka spruce and black cottonwood was evaluated. Form for downy birch was not evaluated. Trees were classified in categories as A, B or C, where A has a straight stem from root collar and upto 3 m height, B has a straigh stem upto 2 m height and C has a crooked stem (Figure 9). This is to distinguish between the trees that are expected to be used as future crop trees and those with large deformations or classified as wreckage trees. Figure 8, 19, 20 and 21 were created using both the tools in Microsoft Powerpoint and satellite pictures from the website: www.ja.is/kort/.

2.5. Calculations of tree growth and stand characteristics Data for trees with both diameter and height measurements were used to develop height- diameter models so that the heights of individual trees without height measurements could be predicted. This was done by making a linear regression in excel from all the diameters in the plot that was measured for each species in different stands. A regression formula was made from the 9 measured heights and their diameters. The height was then calculated by using the diameter of each tree with the formula: Y= a + b*X, (0)

Where: Y is the height in meters, X is the diameter at 1.3 m height or 0.5 m height in centimeters, b is the slope of the line and a is the y-intercept. All measurements were written into an excel spreadsheet where derived variables were calculated from them. The following variables were calculated for each plot: i. Dominant tree height (m), ii. Average height (m), iii. Average diameter (cm), iv. Stand basal area (m2/ha), v. Stand volume (m3/ha), vi. Average volume per tree (dm3/tree), vii. Mean annual volume increment (m3/ha/year), viii. Aboveground woody biomass (ton DM/ha), ix. Carbon stocks (C ton/ha),

39 x. Mean annual carbon sequestration (C ton/ha/year), xi. Mean annual carbon dioxide increment (CO2 ton/ha/year). Basal area of a tree (BA; cm2 /tree) describes area occupied by a tree stem. It is the cross- sectional area of tree stems and it was calculated with the equation: BA = (d/2)2 * π, (1) Where: d = diameter measured in cm at breast height (1.3 m) or at knee height (0.5 m) for downy birch (Philip, 1994). The sum of basal areas for all the trees in a measurement plot was then converted into square meter per hectare (m2/ha) by dividing the total basal area with the size of the plot. Stem volume (V; dm3/tree) for stem with bark was calculated with a formula from Snorrason, and Einarsson (2006) for Sitka spruce (Eq. 2), Black cottonwood (Eq. 3), feltleaf willow (Eq. 4) and downy birch (Eq. 5): V = 0.0739 * d1.7508 * h1.0228 (2) V = 0.0732 * d1.6933 * h1.0562 (3) V = 0.0687 * d1.8074 * h0.7659 (4) V = 0.0452 * d1.8091 * h1.0487 (5) Where: d = diameter measured in cm at breast height (1.3 m). h = height of tree measured in meters. Because of a shortage of formulas for small Sitka spruce and black cottonwood trees in Iceland the formulas for small Siberian larch (Larix sibirica Led. / L. sukaczewii Dylis) from Bjarnadóttir et al. (2007) was used to calculate volume for trees under 1.3 m in height: V = 0.1022 * d1.7718 * h0.4829 (6) Where: d = diameter at knee height (0.5 m). h = height of tree measured in meters. The total stand volume was then calculated into square meters per hectare (m3/ha). To calculate mean annual increment (MAI), the volume in m3/ha was divided with the age of the trees. Total aboveground woody biomass (B; Kg DM/tree) was also calculated for each tree with a formula from Snorrason and Einarsson (2006) for Sitka spruce (Eq. 7), black cottonwood (Eq. 8), feltleaf willow (Eq. 9) and downy birch (Eq. 10) they were calculated with the equations:

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B = 0.1334 * d1.8716 * h0.4386 (7) B = 0.0717 * d1.8322 * h0.6397 (8) B = 0.0348 * d1.9123 * h0.8904 (9) B = 0.0634 * d2.1552 * h0.2877 (10) Where: d = diameter measured in cm at breast height (1.3 m). h = height of tree measured in meters. The total biomass (ton DM/plot) was then calculated into ton per hectare (ton DM/ha). To calculate mean annual biomass increment (MAI), the volume in m3/ha was divided with the age of the trees. I used a 50 % carbon content in woody biomass (Snorrason et al., 2017) to derive the woody aboveground carbon stock for each tree and to get mean annual aboveground carbon sequestration rate (MAC), where the carbon stock is divided with the tree age. To convert carbon sequestration to mean annual carbon dioxide (CO2) sequestration, the MAC was multiplied with the multitudial difference in molar mass between carbon (C) and carbon dioxide

(CO2), which is 3.67. The total carbon sequestration was then calculated for all the plots with mixture and monocultures except for the 75 % downy birch and 25 % tea-leaved willow mixture (Plots number: 2, 23, 34 and 61). By assuming that the average lodgepole pine was 2.7 m tall and 3.8 cm in stem diameter (Benedikz & Freysteinsson, 1997), it was possible to calculate its stem volume (eq. 11) and biomass (eq. 12) with the equations and multiply it with the measured stand density (survival) data in each pine plot: V = 0.1491 * d1.6466*h0.8325 (11) B = 0.1429 * d1.8887 * h0.4332 (12) Where: d = diameter measured in cm at breast height (1.3 m). h = height of tree measured in meters.

2.6. Statistical analysis All data was entered in the Microsoft Excel for Office 365 MSO 2017 spreadsheet and statistical analysis was done in the JMP version 14. Microsoft® Windows® for x64. First, I looked at normal distribution with Shapiro-Wilk on the residuals and the result showed that all of the data used for ANOVA analysis was normal distributed. The difference in treatment was assessed as significant if P <0.05.

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2.6.1. Eggertsson’s project: Long-term effects of different planting methods The two-way analysis of variance (ANOVA) followed by Tukey's honest significant difference test (Tukey HSD test) were used for statistical data processing for data from survival, height, diameter and volume in the Eggertsson’s project. When the variance analysis showed a significant difference between treatments (P <0.05), Tukey's HSD test was used for further analysis of species, treatments or habitats. This was done to see if there were significant differences between different planting methods in different habitats and between different species.

2.6.2. Survival in the LT-Project in 2018 The Mixed-design analysis of variance (ANOVA) and Tukey's HSD test were used for statistical data processing for data from the survival inventory. In the mixed design block is a fixed effect. The habitat is a random effect nested with the block. When the variance analysis showed a significant difference between treatments, species or habitat (P <0.05), Tukey's HSD test was used for further analysis. This was done to see if there were significant differences between survival of species in different mixtures, habitats and between different species. The willow species tea-leaved willow and Alaskan willow did not have enaugh repetitions for a Tukey's HSD test and for a full factorial ANOVA. They were analysed seperately with a simple two-way ANOVA on the willow species with the interaction of habitat.

2.6.3. Effect of species mixtures on forest growth The mixed design analysis of variance (ANOVA) and Tukey's HSD test were used for statistical data processing for data from the growth inventory. In the mixed design block is a fixed effect. The habitat is a random effect nested with the block. When the variance analysis showed a significant difference between treatments, species or habitat (P <0.05), Tukey's HSD test was used for further analysis. This was done to see if there were significant differences between growth of species in different mixtures, habitats and between different species. The same statistical analysis was done for stem form. Trees had a grade A, B and C (see chapter 2.4.3). the different letters would get different numberical values depending on the stem quality. The highest stem quality A would get the highest number, 8, B would get the next highest number, 5, and C would get the lowest number, 1. The average grade of each tree in each plot was then statistically analysed with a mixed design analysis of variance (ANOVA) and Tuckeys HSD test was used if there was any significance. The grading could also have been analysed with non-parametric tests, such as Kruskal-Wallis; but this was done as a first approximation.

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The Sitka spruce/Alaskan willow mixture did not have enough repetitions for a Tukey's HSD test and for a full factorial anova. They were analysed seperately with a simple two-way anova with the interaction of habitat.

3. Results 3.1. Eggertsson’s project: Long-term effects of different planting methods As can be seen in Table 4, there were no long-term overall effects from any of the planting treatments that included harrowing (Treatments 1-6, site preparation by harrowing by planting machine, see chapter 2.1.2 for more detailed description of the treatments). In other words, the difference in planting methods, which included a single small application of fertiliser, seeding of annual ryegrass around the seedlings, or different placement of plants within or at the harrowed furrow, did not have any siginificant effect on tree survival or growth 15 years later. This effect was general across all the tree species, indicated with non-significant treatment*species interaction (Table 4). Still there were some significant differences found on survival, height growth, diameter growth and volume growth within Eggertsson’s experiment (ANOVA effects in Table 4), but it was mainly because of differences between the three tree species (see Species in Table 4, highest F- values), followed by a significant block (within habitat) effect for survival and height growth, but not for diameter or volume growth (Table 4). Since more extensive inventories on both species and habitats were done (see later), they are not going to be addressed in detail here.

Table 4. ANOVA analysis of planting treatments 1-6 in the so called „Eggertsson’s experiment” within the LT-Project in Gunnarsholt in southern Iceland in 2018 on seedling survival, height, diameter and stem volume for Sitka spruce, black cottonwood and downy birch planted in 2002. Survival Height Diameter Volume F- Variable P-val. F-val. P-val. F-value P-val. F-value P-val. val. ANOVA 6.1 <0.0001 78.4 <0.0001 16.2 <0.0001 13 <0.0001 Block [Habitat] 13.1 <0.0001 6.4 0.0009 1.5 0.238 1.1 0.3595 Species 8 0.0009 200.1 <0.0001 45.2 <0.0001 25.5 <0.0001 Ryegrass 1.9 0.1771 1.3 0.258 0.4 0.5316 0.3 0.5727 Species*Ryegrass 0.02 0.9847 0.2 0.8494 0.6 0.5423 1.5 0.2299 Fertilizer 0.1 0.7436 0.2 0.6503 1.5 0.2307 0.5 0.5037 Species*Fertilizer 0.6 0.5506 1 0.3792 0.2 0.7867 0.4 0.6734 Edge 0.4 0.5161 0 0.9968 0.02 0.881 0.1 0.7393 Species*Edge 0.1 0.8818 0.3 0.7615 0.4 0.6691 1.2 0.3018

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Table 5 shows a second statistical analysis that also included data from Treatments 7 and 8, where plants were planted after only manual scarification, but no site preparation by harrowing was done. There, all the different treatments in Eggertsson’s experiment which were not significant were merged.

3.1.1. Survival The significant differences in survival between habitats (lupine vs. unmanaged grassland) were explained by 59 % less average survival in the Eggertsson’s treatments in the unmanaged grassland than the lupine (Fig. 10; 22 % and 80 % for grassland and lupine, respectively).

Table 5. ANOVA analysis of the differences due to habitat, tree species and site preparation (harrowing) treatments in the so called „Eggertsson’s experiment“ within the LT-Project in Gunnarsholt in southern Iceland in the spring 2018 on survival, height, diameter and stem volume for Sitka spruce, black cottonwood and downy birch planted in 2002.

Survival Height Diameter Volume Variable F-val. P-val. F-val. P-val. F-val. P-val. F-value P-val. ANOVA 11.7 <0.0001 96.4 <0.0001 47.1 <0.0001 20.2 <0.0001 Block [Habitat] 18.6 <0.0001 0.5 0.5905 2.4 0.0976 0.9 0.4096 Habitat 34.3 <0.0001 89.2 <0.0001 27.7 <0.0001 11.3 0.0013 Species 16.5 <0.0001 151.4 <0.0001 124.1 <0.0001 42.9 <0.0001 Harrowing 11.4 0.0012 24.2 <0.0001 3.8 0.0568 0.9 0.3361 Harrow*Habitat 31.3 <0.0001 48.6 <0.0001 20.4 <0.0001 15 0.0003 Harrow*Species 0.9 0.4228 61.2 <0.0001 13.9 <0.0001 10.1 0.0002

Survival was also found to be significantly affected by the type of site preparation (harrowing vs. manual scarification) across all species and both habitats (p = 0.0012; Table 5, Fig. 10), but the average survival of harrowed treatments was 57 %, compared to 51 % where no mechanical site preparation was done (Fig. 10). There was, however, no significant interaction between species and harrowing for survival (Table 5; Harrow* Species p = 0.4228), indicating that the response to the type of site preparation was the same for all the three species. There was also a signifcant interaction for all four measured variables between habitat and harrowing, indicating that the site preparation effect was not the same in the unmanaged grassland and in the lupine field (Table 5). This effect is reported more thouroghly in the following paragraphs, where the results are shown separately for the grassland and the lupine field. As is seen in Figure 10 and Table 6, the harrowing significantly increased survival in the grassland site. In the grassland manual scarification was not enough to allow the plants to

44 establish, seen as very low survival of only 22 %, but no significant difference was in the survival between the harrowed grassland plots and all the treatments in the old lupine field, irrespective if they were harrowed or not (Table 6). Further data on survival by species and habitats are shown later (chapter 3.1).

Figure 10. Average survival with standard error, by habitat and site preparation (harrowing) treatments in the so called „Eggertsson’s experiment” within the LT-Project in Gunnarsholt in southern Iceland in the spring 2018 on tree survival for Sitka spruce, black cottonwood and downy birch planted in 2002. This is the Harrow*Habitat interaction shown in Table 5 and statistical differences between columns are found in Table 6. Table 6. Post-ANOVA Tukey’s HSD comparisons for the interaction between habitat and site preparation (harrowing) in the so called „Eggertsson’s experiment“ within the LT- Project in Gunnarsholt in southern Iceland in the spring 2018 on seedling survival, height, diameter and stem volume for Sitka spruce, black cottonwood and downy birch planted in 2002. Different letters (vertically) indicate significant differences. See Table 5 for main effects and Figures 10, 11, 13 and 15 for data. Survival Height Diameter Volume Harrow*Habitat Lupine Harrowed a a a a Not Harrowed a a a a Grassland Harrowed a b a a Not harrowed b c b b

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3.1.2. Height growth Height growth was also significantly increased by harrowing (Table 5; p <0.0001) in the Eggertsson’s treatments, across all the three species and both habitats, giving average height 221 and 193 cm in the harrowed and the manually scarified treatments, respectively (data not shown). Both the interactions were also significant for the harrowing treatment (Table 5); indicating that the site-preparation response on height growth also differed across habitats and among species. When the habitat*harrowed interaction was tested (Table 6; Figure 11), results show that the positive harrowing effect on height growth was only significant in the grassland habitat, but not in the lupine fields.

Figure 11. Average height with standard error for habitat and site preparation (harrowing) treatments in the so called „Eggertsson’s experiment” within the LT-Project in Gunnarsholt in southern Iceland in the spring 2018, planted 2002. Trees of Sitka spruce, black cottonwood and downy birch pooled. This is the harrow*Habitat interaction shown in Table 5 and statistical differences between columns are found in Table 6. Figure 12 and Table 7 show the interaction between harrowing and different tree species; as can be seen, the significant harrow*Species interaction in Table 5 was caused by the significant possitive height growth response of black cottonwood, while the two other species did not show a significant response.

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Figure 12. Average height with standard error for species (Sitka spruce, black cottonwood and downy birch) and site preparation (harrowing) treatments in the so called „Eggertsson’s experiment“ within the LT-Project in Gunnarsholt in southern Iceland in the spring 2018 on seedling height for Sitka spruce, black cottonwood and downy birch planted in 2002. Table 7. Post-ANOVA Tuckey’s HSD comparisons for the interaction between tree species and site preparation (harrowing) in the so called „Eggertsson’s experiment“ within the LT- Project in Gunnarsholt in southern Iceland in 2018 on seedling survival, height, diameter and stem volume for Sitka spruce, black cottonwood and downy birch planted in 2002. Different letters (vertically) indicate significant differences. See Table 4 for main effects. Letter marked with a star (*) had diameter measured at knee height. Insignificance is marked with (ns). See Table 5 for main effects and Figures 12, 14 and 15 for data. Survival Height Diameter Volume Harrow*Species Harrowed downy birch ns b a* b black cottonwood ns a b a Sitka spruce ns d c c Not harrowed downy birch ns b a* ab black cottonwood ns c c b Sitka spruce ns d c c

3.1.3. Diameter growth Diameter growth did not respond significantly to the type of site preparation (harrowing) across habitats and tree species (Table 5; p = 0.06) as the height growth did, but similar to the height growth there were signifcant interactions between harrowing and species or habitats (Table 5; p < 0.0001). Figure 13 shows the Harrow*Habitat interaction for diameter growth. Again, the interaction was because the harrowing had no signifcant effect in lupine areas, while there was a strong

47 positive effect of harrowing, as compared to manual scarification, in trees planted in grassland (Figure 13, Table 6). Figure 14 shows the Harrow*Species interaction for diameter growth. The reason for this interaction being significant was both because only black cottonwood had a significant positive site preparation reponse (Table 7), but also because the non-significant trends for downy birch were negative and not a lack of response in the Sitka spruce.

Figure 13. Average diameter at breast/knee height with standard error for habitat and site preparation (harrowing) treatments in the so called „Eggertsson’s experiment“ within the LT- Project in Gunnarsholt in southern Iceland in the spring 2018 on seedling diameter at breast height for Sitka spruce and black cottonwood and diameter at knee height for downy birch planted in 2002. This is the Harrow*Habitat interaction shown in Table 5 and statistical differences between columns are found in Table 6.

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Figure 14. Average diameter with standard error for Species and site preparation (harrowing) treatments in the so called „Eggertsson’s experiment“ within the LT-Project in Gunnarsholt in southern Iceland in the spring 2018 on seedling diameter at breast height for Sitka spruce and black cottonwood and diameter at knee height for downy birch planted in 2002. This is the Harrow*Species interaction shown in Table 5 and statistical differences between columns are found in Table 7.

3.1.4. Volume growth Stem volume sums up both height and diameter changes and therefore it would be expected that those results would be similar as for each parameter separately. As expected, volume growth responded to harrowing in a similar way as diameter growth in the Eggertsson’s treatments, both in the main effect and with interactions, but with somewhat lower F-values, indicating not as strong response (Table 5). Figure 15 shows all treatments in one graph and is therefore not directly showing the interactions in Table 5 as was done for height and diameter growth previously. Still, Table 6 reports the findings behind the Harrow*Habitat interaction on volume growth. There no significant harrowing effect was found for the lupine field, while it was highly significant in the grassland. As Figure 15, however, shows, is that this may also be caused by the lack of black cottonwood trees in the non harrowed grassland site (100 % mortality), rather than a true effect of the harrowing in the grassland on volume growth, since both for the Sitka spruce and downy birch the differences in volume growth were minimal between the harrowed and non- harrowed grassland treatments (Figure 15). Similarly, the significant Harrow*Species interaction on volume growth was mainly explained by a significant difference for the black cottonwood, while the other two species are not signifcantly different across both habitats

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(Table 7, Figure 15). Also, this effect may therefore be caused by the 100 % mortality of black cottonwood in the manually scarified grassland and those interactions should therefore be interpreted by great care.

Figure 15. Volume per tree in cubic decimeters (liters) with standard error bars for Sitka spruce, black cottonwood and downy birch with plough string and without plough string treatments within lupine and grassland habitats in Gunnarsholt in spring 2018 in the so called „Eggertsson’s experiment” within the LT-Project.

3.1. Inventory of survival in the LT-Project in 2018 The average survival in 2018 in the whole LT-Project in Gunnarsholt was 58 %, across all species (including the willows). This translates into ca. 1.850 tree/ha on average across all species, assuming the initial planting density of 3.200 trees/ha. Survival in the harrowed old lupine field was 62 % and it was significantly higher than in the harrowed grassland habitats, where it was 52 % (Figure 16; Table 8, p = 0.02). Again, this translates into ca. 1.985 vs. 1.665 trees/ha, respectively. No significant differences were found in survival between species mixture plots vs. monoculture plots in 2018 (Table 8, p = 0.81). Table 8 shows that there was a highly significant difference between the average survival for different tree species (p<0.0001), but there was no significant Habitat*Species interaction (p = 0.07).

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Figure 16. Average survival with standard error for trees planted in the two habitats grassland and lupine in 2003 and 2004 with replantings in 2005 in the LT-project in Gunnarsholt in southern Iceland. Survival inventory was carried out in the spring and autumn 2018. This is the Habitat effect shown in Table 8. The average survival for the four species was 58 %, 75 %, 39 % and 55 % for the black cottonwood, downy birch, lodgepole pine and Sitka spruce, respectively (Figure 17). Post hoc comparisons using the Tukey’s HSD test indicated that the mean score of survival for downy birch was significantly higher than for the other tree species, Sitka spruce was not significantly different in survival from black cottonwood, but lodgepole pine had significantly lowest survival rate, compared to all the other species (Figure 17; Table 8).

Table 8. ANOVA analysis and post-ANOVA Tukey’s HSD comparisons of survival of species between habitat, tree species and mixture effect in the „LT-project” in southern Iceland in spring and autumn 2018. Black cottonwood, Sitka spruce and downy birch planted in 2002. Lodgepole pine planted in 2003 and replanted in 2005. Survival Variable F-value P-val. ANOVA 2.7 0.0011 Block [Habitat] 2.1 0.1325 Habitat 5.9 0.0188 Species 13.4 <0.0001 Mixture effect 0.2 0.8083 Habitat x Mixture effect 1.3 0.2873 Habitat x Species 2.5 0.0675 Mixture effect x Species 0.5 0.8347

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Habitat x Mixture effect x Species 1.3 0.2645 Species HSD comparison Downy birch a Sitka spruce b Black cottonwood b Lodgepole pine c

Figure 17. Average survival with standard error for species (black cottonwood, downy birch, lodgepole pine and Sitka spruce) planted in Gunnarsholt in southern Iceland in 2003 except for the pine which was planted 2004. The survival inventory was carried out the spring and autumn 2018. This is the Species effect shown in Table 8. Tea-leaved- and Alaskan willows did not have enough repetitions to compare with the other four tree species, therefore differences between the two willow species and the two habitats were tested separately by using a two-way ANOVA on just those two species (Figure 18). The main effect of species was not significant (p = 0.553), and neither was the main effect of habitat (p = 0.286; not shown). There was, however, a significant species*habitat interaction when [F (1, 4) = 26.7, p = 0.007], indicating that the two species and habitats should be looked at separately (Figure 18). Alaska willow showed much higher, and significant (p<0.05) survival in the old lupine field than in the grassland, or 76 % ±17 %, compared to 43 % ±8 % (Figure 18). This means that potential stand density of the Alaska willow foster trees was ca. 1.330 trees/ha in the old lupine field and only 753 trees/ha in the grassland in 2018. Interestingly, the tea-leaved willow showed the reversed response to all other tree species, its survival was significantly (p<0.05) better in the grassland compared to the old lupine field; or 81 % ± 8 %, compared to 28 % ±2 %, respectively (Figure 18).

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Figure 18. Average survival rate with standard error for Alaskan willow in a 50/50 mixture with Sitka spruce and tea-leaved willow in a 25 % mixture with 75 % downy birch planted in 2003 in Lupine and grassland in Gunnarsholt in southern Iceland. Inventory in the spring and autumn 2018.

Finally, Figure 19, shows the spatial distibution of plots with 1.800-3.000 trees/ha (green plots) and plots with <1.800 trees/ha (orange plots), for a quick overview.

Figure 19. Stand density calculated from the survival inventory at Gunnarsholt in the grassland on the right and the old lupine field on the left. Green stands have between 1800 and 3000 trees/ha, but orange stands have less than 1800 trees/ha. See information about plots in Table 2.

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3.3 Effects of species mixtures on forest growth 3.3.1. Forest characteristics 3.3.1.1.Realised planting density The planned stand density was ca. 3.200 trees per hectare in the experiment, something that can be diffucult to achieve, since small differences in distance between planted rows can lead to that the realized stand density can be higher or lower. Total density found in the growth measurement plots for the three tree species (excluding lodgepole pine plots) was 1.941 trees per hectare. This means that the realized intitial stand density was on average 45 % of the planned stand density. It was, however, not a fixed difference across the whole experiment. Average density for trees planted in the old lupine field was 2.028 trees/ha (ca. 42 % below the goal), while it was 1.846 trees/ha in grassland (47 % below the set goal) (data not shown).

3.3.1.2.Stand density For Sitka spruce, black cottonwood and downy birch in monocultures density was 1.611, 1.994 and 2.300 live trees/ha, respectively, for lupine. Stand density for the same species respectively in grassland was 1.922, 1.588 and 1.706 live trees/ha (data not shown). For the 50/50 mixtures of Sitka spruce and black cottonwood the realized average stand density of living trees was 1.653 trees/ha (713 and 940 trees/ha, respectively, or 43/57 mixture). For the 75/25 spruce/cottonwood mixture plots the realized stand density was 2.163 trees/ha (1.475 and 688 trees/ha, respectively, or 68/32 mixture) (data not shown). For the 50/50 mixtures of Sitka spruce and downy birch the realized average stand density of living trees was 1.950 trees/ha (783 and 1.167 trees/ha, respectively, or 40/60 mixture). For the 75/25 mixture it was 2075 trees/ha (1.400 and 675 trees/ha, respectively, or 67/33 mixture) (data not shown). Figure 20 shows the spatial distribution of stand density where forest growth and production were measured by two 100, 150 or 200 m2 inventory plots per stand. Eighteen stands were used where stand density was less than 1.800 living tree/ha; plot nr. 6, 4 (birch monoculture), 47, 44, 20, 1 (cottonwood monoculture), 51, 43, 38, 12 (spruce monoculture), 62, 7 (50/50 spruce/birch mixture), 39, 19, 15 (50/50 spruce/cottonwood), 59 (50/50 Spruce/willow), 56 (75/25 spruce/birch mixture), 22 (75/25 spruce/cottonwood). Most of the plots were monoculture plots with Sitka spruce and black cottonwood along with the 50/50 plots of spruce and broad-leaf trees.

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Figure 20. Stand density calculated from the growth inventory at Gunnarsholt in grassland on the right and lupine on the left. Green stands have between 3000 and 1800 living trees/ha. Red marked stands have less than 1800 living trees/ha. Uncolored stands were not measured (mainly lodgepole pine stands). See information about stands in Table 2. 3.3.1.3.Stand Basal Area (BA) Average BA for all monoculture and mixed stands was 3.41 m2/ha. BA for all monoculture stands of Sitka spruce, black cottonwood and downy birch was 0.32, 6.34 and 6.63 m2/ha, respectively. It should be noted here that BA was calculated at knee height (0.5 m) for downy birch, but at breast height (1.3 m) for Sitka spruce and black cottonwood and are therefore not fully comparable. This also applies to the mixed stands containing downy birch, there the stand BA. There was, however, also some difference between habitats. Average BA for the monoculture stands of the three species was 0.4, 8.0 and 4.8 m2/ha for the old lupine field, but 0.2, 3.0 and 8.4 m2/ha in grassland areas, respectively (Table 9). That is, Sitka spruce and black cottonwood had more BA growth in the old lupine field, but the downy birch in the grassland habitat. Both less growth and lower survival of birch in the lupine explained the lower BA there (see later).

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Table 9. Stand Basal Area (m2/ha) in monoculture and mixed stands of Sitka spruce (SS), black cottonwood (BC) and downy birch (DB) or in 50/50 or 75/25 SS/BC or SS/DB mixtures in two different habitats in Gunnarsholt in southern Iceland in the autumn 2018. Treatments Grassland Old lupine field Monocultures SS 0.24 ±0.003 0.40 ±0.01 BC 2.99 ±0.03 8.01 ±0.03 DB 8.44 ±0.03 4.81 ±0.03 Mixtures SS75/BC25 1.25 ±0.02 4.33 ±0.04 SS50/BC50 2.71 ±0.02 3.52 ±0.05 SS75/DB25 4.32 ±0.05 1.88 ±0.03 SS50/DB50 4.80 ±0.04 3.82 ±0.03

For mixtures 50/50 mixtures of Sitka spruce and black cottonwood the average BA was 3.1 m2/ha across both habitats, where Sitka spruce only had 0.1 and black cottonwood 3.0 m2/ha. For the 75/25 mixture the average BA was 2.8 m2/ha, where Sitka spruce had 0.7 and black cottonwood 2.1 m2/ha for (Table 9). In the 50/50 mixtures of Sitka spruce and downy birch the BA was 4.3 m2/ha across both habitats, where Sitka spruce had 0.3 and downy birch 4.0 m2/ha. In the 75/25 mixture the BA was 3.1 m2/ha, where Sitka spruce had 0.4 and downy birch 2.7 m2/ha (Table 9). Figure 21 shows the spatial distribution of BA in stands where forest growth and production were measured by two 100, 150 or 200 m2 inventory plots per stand. Most of the stands had BA lower than 5 m2/ha.

Figure 21. Basal Area at Gunnarsholt on the left is lupine area and grassland on the right. Green stands have Basal Area above 10 m2/ha, yellow stands have Basal Area between 5 and 10 m2/ha. Red stands have basal area below 5 m2/ha. See information about stands in Table 2.

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3.3.2. Growth responses per living tree 3.3.2.1.Height growth Table 10 shows the dominant height (Hd) and average height (H) per tree in different treatments, i.e. averages for all trees in mixed plots. As can be seen in Table 11 there were significant differences in Hd and H between the species, habitats and in species*habitat interaction. The strongest explaining factor for differences in these variables was the species used (F-values 78 % and 90 % of the explaining power of ANOVA model for Hd and H, respectively), followed by the habitat differences and the Species*Habitat interaction (F-values of which gave together 20 % and 8 % of the explaining power of the ANOVA model for Hd and H, respectively), which only left ca. 2 % explained by other factors. What the statistical results are showing is that black cottonwood had significantly most height growth (Hd and H) of all the three species (Table 12; Figure 22) and dominant height across all stands was 5.9 m, which was 48 % and 37 % more than was found in downy birch (4.0 m) and Sitka spruce (4.3 m; Figure 22). Downy birch was also, on average, significantly higher than the Sitka spruce (Table 12). The same values for average height, across all stands, were 3.6, 2.5 and 2.2 m, respectively (data not shown, but statistical analysis in Table 12). Table 10. Dominant (Hd, m), average height (H, m) and average bole volume per tree (V, dm3) in monoculture and mixed stands of Sitka spruce (SS), black cottonwood (BC) and downy birch (DB) or in 50/50 or 75/25 SS/BC or SS/DB mixtures in two different habitats in Gunnarsholt in southern Iceland in the autumn 2018. Statistical analysis of this data is shown in Table 11. Grassland Lupine field Treatments Hd H V/tree Hd H V/tree Monocultures SS 2.6 ±0.2 1.0 ±0.1 0.4 ±0.1 3.0 ±0.2 1.2 ±0.1 0.7 ±0.1 BC 4.7 ±0.2 3.6 ±0.2 3.8 ±0.5 6.7 ±0.3 5.1 ±0.2 9.8 ±1.5 DB 3.8 ±0.1 2.7 ±0.7 3.4 ±0.2 4.0 ±0.1 2.8 ±0.2 2.9 ±0.2 Mixtures SS75/BC25 4.7 ±0.2 2.1 ±0.3 1.9 ±0.8 6.2 ±0.6 3.1 ±0.3 4.1 ±1.7 SS50/BC50 5.4 ±0.2 3.1 ±0.4 4.1 ±1.2 6.5 ±0.2 3.2 ±0.4 4.7 ±2.1 SS75/DB25 4.0 ±0.3 2.1 ±0.3 2.7 ±1.4 3.9 ±0.2 1.9 ±0.3 1.6 ±0.9 SS50/DB50 3.9 ±0.1 2.4 ±0.3 3.5 ±0.5 4.2 ±0.1 2.6 ±0.2 2.9 ±0.8

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Table 11. ANOVA analysis of the differences in stem volume per tree, average and dominant height, shown in Table 10, due to habitat, tree species and mixture effects in the LT-Project in Gunnarsholt in southern Iceland in the autumn 2018. Volume/tree Average height Dominant height Variable F-value P-value F-value P-value F-value P-value ANOVA 15.9 <0.001 56.4 <0.0001 20.2 <0.0001 Block [Habitat] 0.1 0.88 0.4 0.6536 1.8 0.166 Habitat 9.8 0.0024 29.9 <0.0001 25.7 <0.0001 Species 102.7 <0.001 429.4 <0.0001 134.6 <0.0001 Habitat*Species 18.7 <0.001 10.5 <0.0001 8.3 0.0005 Mixture 1.6 0.2153 4.9 0.0094 0.1 0.8769 Mixture*Habitat 1.3 0.2795 0.7 0.5091 0.4 0.7041 Mixture*Species 0.9 0.4761 0.5 0.7507 2 0.1096

The highly significant Habitat factor in Table 11 for Hd and H was caused by an overall difference between the grassland and the old lupine field. Trees planted in lupine had an average height of 3.0 m and dominant tree height was 4.9 m across all stands (data not shown). Average height of trees in grassland was 2.4 m and dominant height was 4.0 m (data not shown); i.e. the Hd and H were 23 % and 24 % higher in the old lupine field. However, since the Habitat*Species was also significant, it was clear that not all the tree species were responding the same way to the two habitats. This can be seen in Figure 23 and Table 13. Both Sitka spruce and the black cottonwood had significantly higher heigth growth in the lupine field (18 % and 25 % for Hd, respectively), but the downy birch did not significantly differ in Hd nor in H between the two habitats.

Figure 22. Dominant height of Sitka spruce, downy birch and black cottonwood, with standard error, across all monoculture and mixture plots, in the LT-project in Gunnarsholt in the autumn 2018.

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Table 12. Post-ANOVA Tukey’s HSD comparisons for average height and stem volume for Sitka spruce, black cottonwood and downy birch planted in 2003 in the LT-Project in Gunnarsholt in southern Iceland in the autumn 2018 on. Different letters (vertically) indicate significant differences (p<0.05). See Table 11 for main effects and Figure 22 for data). Volume/tree Average height Dominant height Species black cottonwood a a a downy birch b b b Sitka spruce c c c

Figure 23. Dominant height (m) with standard error in autumn 2018 for tree species planted in different habitats (lupine and grassland) in the LT-project in Gunnarsholt in 2003. Statistical analysis is shown in Table 13.

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Table 13. Post-ANOVA Tukey’s HSD comparisons for the interaction between species and habitat (lupine or grassland) within the LT-Project in Gunnarsholt in southern Iceland in the autumn 2018 on height and stem volume for Sitka spruce, black cottonwood and downy birch planted in 2003. Differnt letters (vertically) indicated significant differences of p<0.05). See Table 11 for main effects. Variable Volume/tree Average height Dominant height Species*Habitat Lupine black cottonwood a a a downy birch b c c Sitka spruce c d d Grassland black cottonwood b b b downy birch b c c Sitka spruce c d d

In Table 11 only one growth variable showed significant mixture effect, i.e. the average height. Surprisingly, this was not a positive effect, since H was on average 7 % higher for the monoculture stands compared to both two mixtures (Figure 24; Table 14). The difference in H between 50/50 and 75/25 mixture stand was not significant (Table 14).

Figure 24. Average height of all tree species in meters in monoculture stands and mixed stands in the LT-Project in southern Iceland in autumn 2018.

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Table 14. Post-ANOVA Tukey’s HSD comparisons for the interaction between tree mixtures within the LT-Project in Gunnarsholt in southern Iceland in the autumn 2018 on height and stem volume for Sitka spruce, black cottonwood and downy birch planted in 2003. Different letters (vertically) indicated significant (p<0.05) differences. See Table 11 for main effects. Average Dominant Variable Volume/tree height height Mixture effect: Mixture 75/25 ns b ns Mixture 50/50 ns b ns Monoculture ns a ns

3.3.2.2.Volume growth per tree Table 10 shows the average stem volume per tree (V) in different treatmetns, i.e. averages for all trees in mixed plots. As can be seen in Table 11, tree volume responded in the similar way to treatments as height growth did; i.e. 76 % of the variabilty explained by the ANOVA model was due to species differences and other 21 % by habitat differences and the Species*Habitat interaction. There was, however, no significant tree mixture effect found for volume (Table 11). Black cottonwood had the highest volume per tree, and it had produced ca. 11 times more volume per tree than Sitka spruce and 1.8 times more than downy birch and both differences were highly significant (Figure 25; Table 12). Downy birch, on the other hand, had produced six times more volume than Sitka spruce (Figure 25, Table 12).

Figure 25. Average volume in cubic decimeters (liters) per tree with standard error for Sitka spruce, downy birch and black cottonwood planted in 2003 in the LT-Project in Gunnarsholt in southern Iceland. Inventoried in autumn 2018.

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The highly significant Habitat factor in Table 11 for volume was caused by an overall +33 % V in the old lupine field across all species and mixtures. However, since the Habitat*Species was also significant (p = 0.002), it was clear that not all the tree species were responding the same way. This can be seen in Figure 26 and Table 13. For V the black cottonwood had significantly higher volume growth in the lupine field (+27 %), but the downy birch and Sitka spruce did not significantly differ in V between the two habitats. Looking at the volume growth of the three species in the two different habitats also revealed that downy birch had had the same volume growth per tree as black cottonwood in the grassland, while it grew significantly more slowly than the black cottonwood in the old lupine field (Figure 26, Table 13). This was because volume growth did not significantly change for the birch between the grassland and the lupine field (Table 13).

Figure 26. Average volume in cubic decimeters (liter) per tree with standard error for Sitka spruce, black cottonwood and downy birch in grassland and lupine within the LT-Project in Gunnarsholt in 2018.

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3.3.3. Stand production (growth reponses per stand) Total accumulated stand volume in the experiment the first 15 years was 254 m3 for 30 ha with an experiment-level average stemwood production of 17.7 m3/ year and MAI of 0.6 m3/ha/year for all the mixtures and monocultures, except for the downy birch/tea-leaved willow mixture and not taking into account the age-difference for pine (data not shown). For only the Sitka spruce, black cottonwood and downy birch the accumulated stand volume was 152.1 m3 in the first 15 years (data not shown). Table 15 shows the stand volume (SV), mean annual increment of stemwood (MAI) and total woody biomass (B) accross all treatments. The SV, MAI and B were lowest in the monoculture Sitka spruce stands in the grassland (0.9 m3/ha, 0.1 m3/ha/year and 0.7 ton/ha, respectively), but highest in the black cottonwood monoculture stands in the old lupine field (22.1 m3/ha, 1.5 m3/ha/year and 13.8 ton/ha, respectively). Table 15. Stand volume (SV, m3/ha), mean annual increment (MAI, m3/ha/year) and woody aboveground biomass (B, ton/ha) in monoculture and mixed stands of Sitka spruce (SS), black cottonwood (BC) and downy birch (DB) or in 50/50 or 75/25 SS/BC or SS/DB mixtures in two different habitats in Gunnarsholt in southern Iceland in the autumn 2018. Statistical analysis of this data is shown in Table 16, 17 and 18. Grassland Lupine field Treatments SV MAI B SV MAI B Monocultures SS 0.9 ±0.2 0.1 ±0.01 0.7 ±0.2 1.7 ±0.2 0.1 ±0.01 1.6±0.2 BC 11.7 ±0.9 0.8 ±0.06 9.7 ±0.7 22.1 ±2.4 1.5 ±0.16 13.8±1.2 DB 7.9 ±0.7 0.5 ±0.05 10.0 ±1.1 6.7 ±0.7 0.4 ±0.05 6.5±1.1 Mixtures SS75/BC25 2.9 ±0.3 0.2 ±0.02 2.4±0.3 10 ±1.8 0.7 ±0.12 8.4±1.4 SS50/BC50 6.2 ±2.1 0.4 ±0.14 5.4±1.6 8.6 ±1.1 0.6 ±0.08 6.8 ±1.2 SS75/DB25 6.4 ±1.4 0.4 ±0.09 6.7±1.4 3.3 ±1.1 0.2 ±0.07 3.3 ±1.0 SS50/DB50 6.7 ±1.3 0.4 ±0.09 7.5±1.4 6.2 ±1.3 0.4 ±0.09 6.1 ±1.3

3.3.3.1.Species and habitat differences Table 16 shows the outcome of statistical analysis among monoculture plots for species and habitat differences. Since all the treatments included in this analysis were planted the same year, all statistical differences found for SV in Table 16 are also valid for MAI. MAI is the average growth of each year since the trees were planted, in cubic meters per hectare per year (m3/ha/year). Black cottonwood had the significantly highest MAI of the three species in monoculture plots, or 1.5 m3/ha/year. Sitka spruce grew the slowest or 0.1 m3/ha/year and MAI for downy birch was 0.4 m3/ha/year (Table 15, 16 & 17). The highly significant species effect for SV was due to black cottonwood and downy birch had on average ca. 16.7 and 7.3 times higher standing volume in monoculture than (and MAI) Sitka spruce, respectively, and the black cottonwood had on average 94 % more SV (and MAI) than

63 the Sitka spruce (Tables 15, 16 and 17). The total woody aboveground biomass of the three species did not differ in the same way as SV. No significant difference was in B for downy birch and black cottonwood in monoculture stands, but the Sitka spruce had significantly less total biomass (Table 17).

Figure 27. Volume per hectare with standard error bars for all monoculture plots in grassland and old lupine field in Gunnarsholt. All tree species pooled. Planted in 2002 and measured in the autumn 2018. The significant habitat effect in stand volume (SV) was caused by an average 33 % higher SV in the monoculture plots in the old lupine field than in the grassland (from 6.8 to 10.2 m3/ha; Figure 27, Tables 15 and 16). Similar to SV, there was a significant (p = 0.02) average 33 % increase in biomass (B) in the old lupine field compared to the grassland monoculture plots (Table 15 and 16). Table 16. ANOVA analysis of the difference due to habitat and species in monoculture stands in the LT-Project in Gunnarsholt in southern Iceland in the autumn 2018 on stand volume per hectare (m3/ha) and biomass per hectare (ton/ha). Standing volume Biomass/ha

Variable F-value P-value F-value P-value ANOVA 28 <0.0001 22 <0.0001 Block [Habitat] 1.6 0.2194 2.1 0.1422 Habitat 20.1 <0.0001 5.7 0.0235 Species 43.5 <0.0001 44.2 <0.0001 Species*Habitat 23.5 <0.0001 20 <0.0001

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There was also a significant Species*Habitat interaction in SV and B (Table 16). A further statistical analysis (Table 18) showed that this was due to that while black cottonwood had significantly enhanced SV in the lupine field, neither the downy birch nor the Sitka spruce had significantly altered SV between the two habitats. The Species*Habitat interaction in B was also due to the enhancement of black cottonwood, while the other two species showed similar B in both habitats (Table 18). Table 17. Post-ANOVA Tukey’s HSD comparisons for the average species diffrences on standing volume per hectare (m3/ha) and Biomass per hectare (tonn/ha) within the LT- Project in Gunnarsholt in southern Iceland in the autumn 2018 Different letters (vertically) indicate significant differences (p < 0.05). See Table 16 for main effects. Standing volume Biomass/ha Species black cottonwood a a downy birch b a Sitka spruce c b

Table 18. Post-ANOVA Tukey’s HSD comparisons for the interaction between species and habitat within the LT-Project in Gunnarsholt in southern Iceland in the autumn 2018 on standing volume per hectare (m3/ha) and Biomass per hectare (tonn/ha) for Sitka spruce, black cottonwood and downy birch planted in 2003. Different letters (vertically) indicate significant differences). See Table 16 for main effects. Standing volume Biomass/ha Species*Habitat Lupine black cottonwood a a downy birch b bc Sitka spruce c d Grassland black cottonwood b b downy birch b c Sitka spruce c d

3.3.3.2.Mixture effects When the monoculture stands were compared to the mixed stands across the three species, no significant mixture effects or Mixture*Habitat interactions were found on SV, MAI or B (Table 19). Figure 28 shows the observed average differences in SV between monoculture and mixed stands in the two habitats. Even if there were no significant differences (Table 19), there was a strong trend for less SV with increasing Sitka spruce ratio in mixtures, as expected due its slower intial growth rate. This trend was less apparent in the grassland than the lupine field (Figure 28).

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Table 19. ANOVA analysis of the difference due to habitat and mixture effects in the LT- Project in Gunnarsholt in southern Iceland in the autumn 2018 on stand volume per hectare (m3/ha) and biomass per hectare (tonn/ha) in different stands planted in 2003. Stand volume Biomass/ha Variable F-value P-value F-value P-value ANOVA 0.7 0.6507 0.7 0.6507 Block [Habitat] 0.1 0.8953 0.1 0.8953 Habitat 1.4 0.2470 1.4 0.2470 Mixture effect 0.4 0.6965 0.4 0.6965 Mixture effect*Habitat 0.4 0.6481 0.4 0.6481

Figure 28. Stand volume per hectare with standard error for monocultures and mixtures in grassland and lupine. Monocultures are either Sitka spruce, black cottonwood or downy birch. The mixtures are 75 % or 50 % Sitka spruce in a mix with 25 % or 50 % downy birch or black cottonwood. 3.3.4. Stem form 3.3.4.1.Species differences Of the 479 trees evaluated in Gunnarsholt in 2018, 421 were black cottonwood and the rest was Sitka spruce, as there were more cottonwood trees than spruce trees that had reached 3 meters. Most of the trees evaluated for stem form had the form C (85 % of all trees) and some of the trees had form B (13 %) but only the Sitka spruce had form A (2 %) (see classification of stem form in chapter 2.4.3.). Most of the black cottonwood (91 %) had form C and a few form B (9 %). The Sitka spruce had significantly more quality trees than the black cottonwood; or 16 % A and 42 % had form B (Figure 29; Table 20). The species difference was found to be the only

66 effect that was significant (p = 0.03). This would mean that Sitka spruce in monoculture plots would have 1021 good quality trees/ha (A and B trees) and black cottonwood only have 161 good quality trees/ha in monoculture if all the trees where >3 m heigh.

Table 20. ANOVA analysis and post-ANOVA Tukey’s HSD comparisons of Stem form of species between habitat, tree species and mixture effect in the „LT-project” in Southern Iceland in the autumn 2018 and spring 2019. Black cottonwood and Sitka spruce planted in 2002 and replanted in 2004. Stem form Variable F-value P-val. ANOVA 2.2 0.0531 Block [Habitat] 2.4 0.1094 Habitat 1.8 0.1890 Species 5.1 0.0321 Mixture effect 1.0 0.3932 Habitat x Species 1.5 0.2323

Figure 29. Number of >3 m trees evaluated for stem form A, B and C for Sitka spruce and black cottonwood in Gunnarsholt in 2018. 3.3.5. Effects of the Alaska willow foster trees The Alaskan willows were significantly taller than the Sitka spruce trees in 2018 in the 50/50 foster-tree mixture. The dominant height (Hd) for the willow and the spruce in the 50/50 stands was 4.7 m and 2.8 m, respectively, and average height (H) was 4.0 and 1.3 m for the two species, respectively (data not showed). The dominant height of Sitka spruce with a foster tree in

67 grassland and lupine was 40 % and 45 % higher than spruce that grew in a monoculture in the same habitat (Figure 30). The goal to create taller foster trees by the willow was therefore reached. However, foster tree effect was not significant for the average height and V. It should, however, be noted that there were clear differences in the average height of the Alaskan willow and the Sitka spruce between the grasslands and the old lupine field, or 5.1 m and 2.8 m, respectively (data not shown). On the other hand, the spruce had significantly higher dominant height (4.8 m) with a foster tree compared to monoculture (2.8) (Table 21) (data not shown). The Mixture effect*Habitat was also significant for dominant height (Table 21). The spruce had 48 % and 30 % higher dominant height in mixture with the Alaskan willow in lupine and grassland compared to monoculture (Figure 30) (data not shown).

Figure 30. Dominant height of Sitka spruce in a monoculture and a 50 % Sitka spruce with 50 % Alaskan willow foster tree mixture in grassland and lupine habitat in the LT-project in Gunnarsholt in southern Icelad measured in the autumn 2018 and planted in 2003. Table 21. ANOVA analysis of the difference due to habitat and mixture effects in the LT- Project in Gunnarsholt in southern Iceland in the autumn 2018 on dominant height (Hd), Average height (H) and volume per tree stem (dm3) in monoculture and foster tree stands planted in 2003. Hd H V Variable F-value P-value F-value P-value F-value P-value ANOVA 4.0 0.0468 4.8 0.0091 2.3 0.1038 Block [Habitat] 1.8 0.2039 0.6 0.5793 1.2 0.3194 Habitat 86.1 0.0001 15.8 0.0014 7.2 0.0178 Mixture effect 17.5 0.0009 4.1 0.0631 0.02 0.9009 Mixture effect*Habitat 28.6 <0.0001 4.1 0.0617 0.1 0.7290

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3.3.6. Carbon sequestration In the 15-year-old LT-Project plantation, black cottonwood and downy birch had accumulated 87 % and 85 % more aboveground C-stock than Sitka spruce, respectively (data not shown). The trees that had been planted in the old lupine field also had accumulated significantly (p = 0.02) more C-stock aboveground than those planted in grassland, or 3.4 ton C/ha in the lupine field and 2.7 ton/ha in the grassland (data not shown). The mixture effect was not significant for C-stock (p = 0.7) (data not shown). By using C-stock values from each stand it was possible to calculate the amount of C sequestered aboveground in wood biomass of Alaskan willow, black cottonwood, downy birch and Sitka spruce in the whole LT-Project in southern Iceland and the C-stock of the pine was estimated in each plot, it was found that the whole experiment had sequestered ca. 25.7 t C/ha at the age of 13-15 years since plantation at Gunnarsholt (tea-leaved willow method not included). Mean annual C-sequestration (MAC) for the whole 32 ha of the forests was 7.4-ton C per year or ca. 42 ton of CO2 per year. In total during the 13-15 years since the 32 ha of the forest was planted, the trees have sequestrated ca. 110.3 tons of C or 404.3 tons of CO2 (data not shown). Trees in the lupine areas have sequestrated the most, or 1.5 times more than in the grassland.

Average annual CO2 sequestration for black cottonwood, Sitka spruce and downy birch during the first 15 years of the stand development in monoculture plots was 5.8, 0.6- and 4.1-ton

CO2/ha (data not shown).

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4. Discussion 4.1. Re-evaluation of the Eggertsson’s experiment 4.1.1. The planting methods I did not find any significant long-term effects of the different planting methods (initial fertilization, use of annual ryegrass, different placements of the planted seedlings) on survival or growth that were compared within the ploughed plots of Eggertsson (2004). I am not aware of any other study which has made such a comparison 15 years after the planting Sitka spruce, black cottonwood and downy birch, but all existing papers I know about have evaluated the effects during the first 1-2 years (Oddsdóttir, 1998; Jónsson, 2002a; Eggertsson, 2004). I am however aware of that Karlsson (2009) found that soil scarification had a positive effect on growth but not survival of lodgepole pine 19 years after planting. It should, however, be kept in mind that already in the first year following the planting there were almost no significant effects, except for significant difference in frost damage and survival between the unmanaged and the harrowed treatments (Eggertsson, 2004). Since it is to be expected that such treatment effects would emerge in the first years, it may not be surprising that no legacy effects could either be found now. Annual variability in initial conditions may therefore also have strong effect on such results from a single study, and multiple studies are needed to evaluate such treatment effects.

4.1.2. The importance of proper site preparation The optained results on the difference between mechanical trenching (harrowing) compared to manual scarification were more interesting. It turned out that black cottonwood grew slower in the unharrowed grassland area and that was a clear indicator of the significance in the harrowing effect. Harrowing did however not affect the growth of Sitka spruce, downy birch or black cottonwood in lupine. It turned out that the tops of the black cottonwood had been cut before planting in the grassland area, so that they would fit the planting machine (Sigurðsson, personal communication). This of course would make the plants weaker when competing with grass and increases the danger of getting diseases through the wound. Already in the first year Eggertsson (2004) found an almost significant effect of the site preparation on volume and diameter, but a significant effect on survival. Surprisingly few data seem to exist in Iceland on the effect of different site preparation methods. However, there are a few studies that show that soil scarification has positive effect on survival and growth of trees in grassland (Þórsson, 2008; Jónsson, 2002a; Møller, 2010). This is also true for a few Nordic countries (Lundqvist, 1997; Haugberg, 1971). Óskarsson & Sigurgeirsson

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(2004) showed that survival could be good in dense lupine patches if plug-plants were planted into trenched furrows in the lupine. Similarly, Aradóttir (2000) showed a high mortality when plug-plants were planted directly into lupine patches without any site preparation in southern Iceland. One reason for why that was not observed as strongly in the present project may be due to the age and history of the lupine. It had been used for seed harvesting and maybe therefore the lupine had started to retreat before the tree seedlings were planted. If the lupine had been denser, the effect of the mechanical site preparation could have been larger.

4.2. Survival of planted seedlings The second main objective of the present research was to compare the survival of the four tree species and the growth potential of downy birch, Sitka spruce, and black cottonwood 15 years after planting and how it had changed since the first inventory was done one year after planting (Eggertsson, 2004) and 2 years after planting (Sigurðsson et al., 2006). By counting live trees and evaluating how many trees had died since initial planting. I found that more than half (58 %) of the trees were still alive 15 years after planting. Still, 58 % survival was much lower than the averages reported by Eggertsson in the first year (95 %) and by Sigurðsson et al. (2006) after 2 years (76 %). Total mortality in the experiment in Gunnarsholt has increased by 24 % since Sigurðsson et al. (2006) evaluated mortality in 2004. Therefore, it seems that ca. half of the mortality must have occurred after 3 years (after replanting 2004 - 2005). Aradottir & Arnalds (2001) found that mortality continued after the first three years in their studies on survival of downy birch, lodgepole pine and Siberian larch in a land recovery forest project and my results are indicating the same. Óskarsson et al., (2006) studied Sitka spruce, downy birch and Siberian larch seedling survival and growth in Mosfell and Haukadalur in southern Iceland. They found that most of the mortality in Haukadalur happened in the first year after planting but continued steadily the first 5 years after planting in Mosfell. However, because no inventory was done between my inventory at 15 years and the inventory of Sigurðsson et al. (2006) at year 2, I don’t know if and when the mortality stabilized in the Gunnarsholt experiment. However, Was the observed survival of 58 %, or 61 % when the lodgepole pine and the willows were excluded, unnormal? This survival was consistent with other studies in Iceland, showing between 40 % and 75 % survival (Þórsson, 2008; Snorrason & Kjartansson, 2005; Eggertsson, 2004). The result was, similar to what Eggertsson (2004) found for survival in the southern part of Iceland in the summer of 2004 (60 %). On the other hand, it was lower than Þórsson (2008) got from his study in northern Iceland, but this might be affected by the survival of different combination of tree species, for example Siberian larch.

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4.2.1. Species differences in survival It is maybe not surprising that the native species, the downy birch, had the highest survival in the present experiment. Aradóttir & Grétarsdóttir (1995), Aradóttir & Magnússon (1992), Þórsson (2008) have also shown that downy birch usually shows high survival compared to exotic species, and probably this is because it has evolved in Icelandic conditions since after the last Ice-age (Eysteinsson, 2017). In the current study the species with highest survival after downy birch were black cottonwood and Sitka spruce with similar survival, but lodgepole pine had far the worst survival, even if it was manually replanted in 2004-2005. Sitka spruce in Gunnarsholt had similar survival (55 %) as found here, and it was higher than Þorvaldsson (2010) found (36 %) in his study of spruce in the western part of Iceland. Why such a low survival in lodgepole pine? Sigurðsson et al. (2006) hypothized that the low survival rates for the lodgepole pine in 2004 were because of root damage before planting (frost damage in the nursery). However, why did the pine not survive after the replanting then? Lodgepole pine has showed a survival rate between 60 – 85 % in other studies (Aradóttir & Grétarsdóttir, 1995; Aradóttir & Magnússon, 1992; Þórsson, 2008). A possible explaination may be the provenance that was used ‘Tutshi lake’. Maybe instead ‘Skagway’, ‘Bennet lake’, ‘Carcross’ should have been used, these are the best lodgepole pine provenances used in Iceland (Eysteinsson, 2013). It might be that ‘Tutshi lake’ was not well adapted to the local conditions in Gunnarsholt. Also, Sigurgeirsson (1988) recommends using ‘Skagway’ in southern Iceland, so maybe the wrong provenance was used. Then again, the risk of failure could have been decreased by using more different provenances than just one provenance and mixing them before planting.

4.3. Growth and production in the LT-project The species investigated here are the most important species for forestry in Iceland except for larch, so it is important to understand how they perform comparing to each other in homogenous sites, and which species should be used in what habitat for the best possible growth, stem form and survival. This is the first initiative where the species downy birch, Sitka spruce, lodgepole pine and black cottonwood are compared with each other in the same soil conditions in Iceland on continous plots.

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4.3.1. Black cottonwood Black cottonwood was the most fast-growing species in the experiment both in height and volume. The black cottonwood had 10.6 times more volume per tree than Sitka spruce and 1.8 times more than downy birch (Figure 25). Average height was 3.6 m and dominant height was 5.9 m after 15 years. This is very high growth rate, when compared to other Icelandic studies on different species, excluding Siberian larch, that also has rapid intial growth (Sigurgeirsson, 1988; Benedikz & Heiðarsson, 2006; Eggertsson & Þórarinsson, 2011; Ólafsdóttir, 2015). The cottonwood usually grows fast in the start of the rotation (pioneer) and then slows down later (Man & Greenway, 2013; Smith et al., 1997). The black cottonwood had a volume of 22.5 m3/ha on average and a mean annual increment (MAI) of 1.5 m3/ha per year. This was, however, very little compared to what black cottonwood has produced in the nearby Gunnarsholt Experimental Forest during the first 25 years (Bogason, 2015), where stands with 2000 trees/ha had produced 106 m3/ha with MAI of 9 m3/ha/year and when growing at 10.000 trees/ha the production was 236 m3/ha with MAI of 18 m3/ha/year. The production of the black cottonwood will therefore continue to increase in the LT-project. The relatively good growth of black cottonwood might be because it gets plenty of rain (Table 1), even if the soil is sandy. It is crusial for black cottonwood to get adequate water to grow well (Smith, 1957; Roe, 1958).

4.3.2. Sitka spruce Sitka spruce does the opposite to black cottonwood (late successional species) and that is why black cottonwood grows faster than Sitka spruce in the beginning (Man & Greenway, 2013; Smith et al., 1997). Sitka spruce is a late successional species that grows faster in later years so with time it will likely catch up with the cottonwood (Harris, 1990). Sitka spruce showed the least growth of all the species with average volume of 1.5 m3/ha and MAI of 0.1 m3/ha/year. This is 9 m3/ha/year lower MAI than a 19-year-old Sitka spruce in Britain (Matthews, 2016) and 4-8 m3/ha/year slower than the average for conifer growth in Sweden at the same latitude (Bergh et al., 2005). This is also very low for older Sitka spruce stands in Iceland (Snorrason & Einarsson, 2002). However, a slow start is expected for this species and the average height of the Sitka spruce in Gunnarsholt is 1.0 m which was similar as Þorvaldsson (2010) got (99 cm) from his study on 14-year-old Sitka spruce in West Iceland. Snorrason and Einarsson (2002) measured Sitka spruce at different ages in southern Iceland and made growth curves. These curves showed that Sitka spruce grows slow for the first 15-20 years and then it starts growing faster, even faster than black cottonwood when both species are

73 between the age of 30-40. Freysteinsson (1995) found that sitka spruce has similar growth curves in Iceland compared to other countries except for a 20 year stagnation phase for Sitka spruce in southwest Iceland. This might explain the slow initial rate of growth from the Sitka spruce in Gunnarsholt. Some spruces in the experiment were growing much faster than those around them and those individuals look like the hybrid between Sitka spruce and white spruce (Picea × lutzii Little) (Sigurðsson, personal communication). The ‚Seward’ provenance could be the reason for this difference (Sigurgeirsson, 1992). However, this can not be confirmed unless someone would study the genetic composition of these individuals (the largest spruces) in the future.

4.3.3. Downy birch As far as I know this is is the first experiment in Iceland where growth rate and production of native downy birch can be compared to other exotic tree species in an experiment where all species are grown on the same soil and with comparable conditions. It has often been stated that the native birch has very low growth rate compared to the exotic species used in forestry (Snorrason & Kjartansson, 2017), but is it so? Downy birch came second, after black cottonwood, in this survey after 15 year’s growth, or with an average standing volume of 6.0 m3/ha and MAI of 0.4 m3/ha/year. This MAI was way lower than a study in Finland with the same species with MAI of between 3.3 and 3.9 in a 42- year-old forest (Hytönen et al., 2014). But relative to the other species in the Gunnarsholt experiment the downy birch producton is surprisingly high! It will be very interesting to follow its production into the future and compare it to the other species. The stem form of Icelandic birch is as a rule not good enough for high quality timber production (Snorrason & Kjartansson, 2017). On the other hand, if there is a need for Icelandic natural birch timber then maybe the timber quality could be improved with the right silvicultural method, for example intence early thinning and pruning of chosen future timber trees (Hynynen et al. 2010). Even if it is at present not a timber-tree, downy birch had the largest proportion in wood products in Iceland until 2008 (Sigurðsson, personal comm.), but its main product is firewood.

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4.4. Wood and biomass production of the whole forest The MAI in the 28ha forest was 17.7 m3 per year and the mean annual biomass increment (MABI) was 15.4 ton in 28ha per year. The total standing volume in 28 ha of the forest after 15 years was 253.7 m3 and 220.5 tons of biomass. It will be expected that this growth will increase in the coming years and that volume growth and CO2 sequestration will rise. This is because forest growth is exponential (Smith et al., 1997).

4.5. Grassland or old lupine fields – which is better for forestry? One goal was to compare the two different habitats used in the LT-Project in southern Iceland; a former hayfield with thick soil that had turned into an unmanaged grassland and an eroded area with thin soil, which had been reclaimed by Nootka lupine ca. 10-12 years earlier. Trees planted in the old lupine field showed better survival than those planted in grassland. This can be explained by higher flow of nitrogen into the ecosystem and increased productivity that follows the planting of lupine (Crooks, 2002; Hastings et al., 2007; Davíðsdóttir et al., 2016; Davíðsdóttir, 2013). Also, grass is a tough competitor to planted seedlings and can significantly affect the rate of survival in a negative way (Þórsson, 2008, Jónsson, 2002a, Kimmins, 2004; Fensham & Kirkpatrick, 1992; Holl et al., 2000). This information and the results tell us that planting trees in older lupine fields might increase the chances of survival compared to planting in grassland; even when the grassland has been site prepared by harrowing. However, the successional stage of the lupine may also be important in this respect (see earlier). Trees planted in lupine showed more height growth than trees planted in grassland (Figures 26 & 27). On the other hand, the difference was only significant for Sitka spruce and black cottonwood, but not for the downy birch. This lack of response in the native birch is interesting and comes as a surprice. However, downy birch has been found to grow especially well in grassland areas (Baldvinsdóttir & Sigfússon, 2002). This might explain why there was no significant difference between height growth of downy birch in Nootka lupine compared to grassland. Trees also showed increased volume production in lupine with 10.2 m3/ha compared to 6.8 m3/ha in grassland (Figure 27). The increased growth of Sitka spruce and black cottonwood matches what other studies have found in Iceland in lupine (Eysteinsson, 1988; Sigurðsson, 2005). Many other studies have also shown that grass is a major competitor to trees (Þórsson, 2008, Jónsson, 2002a, Kimmins, 2004; Fensham & Kirkpatrick, 1992; Holl et al., 2000).

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4.6. Did the species mixture lead to positive responses? One of the main goals of this project was to investigate if there existed any differences between mixed and monoculture plots in survival, tree growth, stand productivity. This is the first big inventory in the LT-Project in southern Iceland, and by establishing fixed plots in this project, the measurements will also form the basis of further research on this topic in the future. This is one of the first studies in Iceland done on the effect of species mixtures on growth. It is important to study the effects of different species mixtures for multitude of reasons that have been mentioned before in the introduction and in literature (Felton, 2010b; Sigurðsson, 2011; Taylor 1985; Rothe & Binkley, 2001). The positive effects from mixtures on biodiversity, growth, timber production and climate change are a big factor that is important to study in more detail and especially for Icelandic conditions. There was no significant effect from any of the mixtures regarding growth and production (Table 19 & 14), except for that there was a negative effect on height growth of Sitka spruce from mixing when compared with monoculture (Figure 24). However, it did not matter which mixture was used, both 50/50 and 75/25 mixtures did not have any significant negative or positive effect on stem volume growth or biomass production (Table 19 & 14), so there should not too much weight be put on the observed negative mixture effect on height of Sitka spruce. Was this lack of mixing effect after 15 years of growth surpricing? Not really, the main effects of species interaction would be expected when the species have filled the growing space and start to actively interact and compete. This has been shown by e.g. Radtke & Burkhart, 1999; Thorpe et al., 2010. However, in an 2019 inventory of the LT-project at Hjartarstaðir in eastern Iceland, a strong effect was already found on the growth of Sitka spruce if it was mixed with Siberian larch, and the effect was additive; i.e. it increased with increasing mixing ratio of larch (Sigurðsson, 2019). Still, this mixing response of the Sitka spruce was not as pronounced at Litla-Steinsvað, where the two species had been planted in separated rows, instead of mixed within rows as at Hjartarstaðir and in Gunnarsholt (Sigurðsson, pers. comm.). It will therefore be very interesting to follow the Gunnarsholt experiment into the future.

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4.7. Foster tree method The Sitka spruce/Alaskan willow mixture is the only positive mixture effect that was significant. It increased the dominant height of Sitka spruce (Figure 30). The spruce with foster tree had a higher dominant height in both habitats compared to the monoculture spruce. Since the Alaskan willow had such high numbers in mortality, the density was only between 753 and 1330 willow trees/ha in grassland and lupine, respectively. The low density of Alaskan willow might have resulted in lower mixture effect on the Sitka spruce than would otherwise have been found. It would have been better to plant 3500 Sitka spruce trees/ha and the same number of foster trees to give the spruce more shelter. However, these are just speculations and this needs to be testet in a separate study. 4.8. Stem form The stem form evaluation was modified and based on a scale, used and described by Birgisdóttir (2005), for Siberian larch. Trees were classified in categories as A, B or C (Figure 9). This was to distinguish between the trees that are expected to be used as future crop trees and those with large deformations or classified as wreckage trees. I did the same for black cottonwood and Sitka spruce, but not the other species. Only 2 % of the evaluated >3 m stems had stem form A across both species, i.e. >3 m straight stem, which gives good timber trees (Kerr & Morgan, 2006; Hynynen et al., 2010). Most of the trees evaluated for stem form had the form C (85 % of all trees) and only 13 % of the trees had form B. This finding is worrysome for the future of the plantation. These data are only preliminary, because the experiment is really too young and the trees mostly too small to give final stem form values; especially for the Sitka spruce. Birgisdóttir (2005) found that in Siberian larch in Fljótsdalshérað, only 0.9 % of the planted trees had A-grade stem form. She pointed out that such low values may not be surpricing when planting tree seedlings on exposed sites in Iceland and that much higher ratio of A-trees might be expected in the following rotations. Jóhannsdóttir (2012) evaluated stem form of larch trees in the east part of the LT-project 9 years after planting. She categorized trees into two vizual categories; A trees (with straight stem and no visual deformation or damage) and C trees (deforemed and damaged in any way). She found that only 5 % of the trees where A trees. This is not so far from the 2 % in the present project.

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4.9. Unrooted cuttings The tea-leaved willow had a higher rate of survival in grassland (81 %) compared to lupine (28 %). The p-value for species with the interaction of habitat (Habitat x Species) for Sitka spruce, black cottonwood and downy birch was only slightly insignificant (p = 0,0675), but since it was insignificant no further conclusions can be drawn from that. However, Magnússon et al. (2001) found that downy birch and tea-leaved willow have higher mortality in dense lupine than on more open lupine areas. This might mean that downy birch in the lupine habitat could have higher mortality in the denser parts of the lupine habitat that might have affected the p-value. This might also, have affected the tea-leaved willow’s mortality. On the other hand, this can be explained in the way that the tea-leaved willow cuttings in the lupine were put in the ground at the wrong time compared to the ones in the grassland (Sigurðsson, personal communication). Cuttings were planted in the spring in the grassland when usually there is a lot of rain in Gunnarsholt (Table 1). However, the cuttings planted in lupine were planted later after the 10th of July, this is when it starts getting dryer in the area (Table 1). Most of the cuttings in the lupine simply dried up and that is why there were more casualties in the lupine compared to the grassland.

4.10. Carbon stock and CO2 sequestration In the 15-year-old LT-project plantation, black cottonwood and downy birch had accumulated 87 % and 85 % more aboveground C-stock than Sitka spruce, respectively. It was found that lodgepole pine had sequested ca. 25.7 t C/ha for the 13-year-old pine monoculture stands at

Gunnarsholt. Average CO2 sequestration for black cottonwood, Sitka spruce and downy birch during the first 15 years of the stand development in monoculture plots was 5.8, 0.6- and 4.1- ton CO2/ha or 21.3, 2.2 and 15.0 t CO2/ha/year. Is that little or much?

When estimated for 50 years, 4.4 t CO2/ha/year (but then including the stump and the coarse roots) has commonly been used as an average CO2-sequestration rate of coniferous or black cottonwood plantations in Iceland (Sigurðsson, personal comm), so it is clear that those CO2 sequestration values are low in comparison. However, my values of course do not represent 50 year’s averages, but only the first 15 years. Sigurðsson et al. (2008) found that 18-year-old downy birch was sequestrating 0.6 t CO2/ha/year in eastern Iceland and a nine-year-old Sitka spruce in western Iceland was sequestering 0,2 t CO2/ha/year. Mean annual C-sequestration (MAC) for the whole 32 ha of the forests was 7.4 tonn C per year or ca. 42 ton of CO2 per year. In total during the 13-15 years since the 32 ha of the forest was planted, the trees have sequestrated ca. 110.3 tons of C or 404.3 tons of CO2 (data not shown).

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That is enough to offset the annual driving (20.000 km) of ca. 55 Toyota Yaris cars (Europe’s energy portal, e.d).

4.11. Methodological issues How can lodgepole pine be better compared to the other species in the future, since it was not planted at the same time? This makes direct comparisons in tree size or in standing stem volume, biomas or C-stock tricky, especially during the first half of the rotation. However, meaningful comparisons using mean growth rates could still be done; such as MAI or mean carbon sequestration rate. The lodgepole pine could also be measured two years later than the other species, but that would mean that it would take longer time to get results in the study. Maybe more realistically, if its current annual increment (CAI) would be measured, it could be used to calculate two-year growth and add that to the total volume, biomass or C-stock to correct for the age differences. I got into some trouble because of the 50 vs 130 cm diameter measurements for different species. I did so because e.g. for downy birch the Snorrason et al. (2006) volume and biomass equations use diameter at 50 cm, not breast heigh, but then comparisons in e.g. DBH and BA were difficult across species. So, what to remember next time such an inventory is made? Try to have at least some trees measured at both 50 and 130 cm height, so a conversion function for D50 and DBH can be made. Another methodological issue to point out was the total lack of black cottonwood trees in the non-harrowed grassland treatment (100 % mortality) in Eggertsson’s planting-method experiment. This made it a little tricky when the ANOVA model was used to look at average effects of other treatments across all species, as was pointed out in the results chapter. This can have caused an over-interpetration on the average positive effects of mechanical soil scarification in the experiment and partly the more positive effect for the lupine habitat (Figure 15), but only when the results of the Eggertsson’s experiment were compared with the extra manually-scarified treatments. Yet another methodological issue was that I analysed stem form with ANOVA, after giving each grade a numerical value. It can be questioned if that was the best way to analyse stem- form grades? The simple answer is probably “no” because the stem form was evaluated visually and therefore it is non-parametric and probably not linear. It would have been better to use Kruskal-Wallis test, followed by Mann-Withney U-tests to evaluate the ranking of different grades, instead of analysing their averages like the ANOVA test does. However, because of

79 lack of time the simpler method was used for this instance, but when the data in this thesis will be published, I will use the better method for this analysis. It can also be questioned if stem form should be evaluated after only 15 years, i.e. was the Sitka spruce and black cottonwood too young for stem form evaluation? The answer is not straightforward. There were many trees of black cottonwood that had grown well above 3 m in height making the cottonwood quite ready to be evaluated for stem form. The most valuable part of the stem is its lowest 3-5 m, even if the tree is harvested at the end of its rotation (Smith et al., 1997). Most of the Sitka spruce had, however, not yet grown to 3 m, or even 2 m, making the present stem-form evaluation too early for this species to draw any firm conclusions on. For Sitka spurce such evaluation should take place after at least 5 or 10 years. Why did I skip the downy birch:tea-levaed willow (SG:TLW) treatment in the standing volume and C-stock estimates? Calculating volume for the 75/25 SG:TLW mixture became to problematic because I found no research that showed standing stock or the volume or biomass functions for tea-leaved willow. Due to the generally low stature of the TLW in birch woodlands (Sigurðsson, unpubl. data), there is probably not much interest in calculating volume or biomass growth of the tea-leaved willow. Still it would be interesting to do so, e.g. if one would want to use tea-leaved willow for short rotation coppicing, biomass production or for some ecological purposes. A small note of caution for future inventories. When I did the inventory for both survival and growth measurements in monoculture stands in the lupine area (Ketluforest), sometimes I had to start again or move the plot. This was because of a black cottonwood shelterbelt that had been recently planted at the time the plots were laid out and runs diagonically through the experiment. The belt should of course be taken down, because it might interact with the other trees in the experiment. The poplar could take nutrients, sunlight and water from other species nearby which would be negative for survival and growth. However, it could also give trees extra shelter and increase the survival and growth of trees nearby. Anyway, this will affect the trees in the future and would be an extra, unwanted, variable in the experiment.

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4.12. What then? Future inventories should preferably take place every 5-10 years on the same measurement plots I established. This way it is possible to monitor the survival and growth of trees over the whole rotation and create e.g. yield tables for each tree species. Such information could be used in a variety of ways, e.g. where the volume of all felled trees is measured in a standard way, a site- specific and more accurate volume functions could be created from known tree height and diameters, which can be used to make volume tables for logs and thus further improve the calculation of timber production in the forest (cf. Bjarnadóttir et al., 2007; Jónsson & Sigurðsson, 2010). What about further management? The next step should be to start the fertilizing treatments. One of the ideas of the LT-Project was to do so, and therefore four extra (½ ha) plots of each monoculture stand for each species was established. I would have recommend using these four “extra” plots of each species in the monoculture for fertilizaiton if the stand density was more homogenous across all plots of the same species, but since that is not the case (see Fig. 19) I do not think it is meaningful. Instead, I recommend only using only few monoculture plots for the fertilization experiment of each species, to find what the maximum growth potential is for downy birch, Sitka spruce and black cottonwood. However, the decision of choosing plots for this treatment would also be influenced by the future thinning treatments (see later). The next management to start across most treatments is the pre-commercial thinning (PCT). The original experimental plan stipulated that half of each ½ ha plot should receive the optimum stand management, while the other half should be left unmanaged. This has already been implemented in some of the Siberian larch treatments in eastern Iceland in the same experiment (Heiðarsson, et al., 2020). Do we need to start PCT in the southern Iceland now or later? PCT would only be relevant for the black cottonwood and downy birch, because they have grown the most so far. PCT is done to even the growing space or to change tree species composition (Aspelund, 2014; Héraðs- & Austurlandsskógar & Skógrækt ríkisins, 2011). Héraðs- & austurlandsskógar & Skógrækt ríkisins (2011) in eastern Iceland recommend that PCT is done 15-20 years after planting or when trees have dominant height of 4-5 m. Stands (of larch) are then thinned down to 1500 trees/ha. There are currently no models available for PCT in the southern part of Iceland, that I know of, and it is likely that the numbers developed for larch do not apply. For example, in Finland it is recommended that PCT for downy birch is done at the dominant height of 4-7 m and spacing reduced down to 1600 trees/ha (Tapio, 2006). According to these reccomendations, PCT should soon take place in the downy birch treatments. The same authors recommend that hybrid poplar gets PCT at dominant height of 6-8 m and spacing is

81 reduced to 1600-2000 trees/ha. This probably means that it is getting very important to start with PCT in the black cottonwood. Some of the poplar stands (44, 47, 49 and 55) have even more than 6 m dominant height and are ready for PCT. Tapio (2006) do not have recommendations for Sitka spruce, but they recommend that Norway spruce gets PCT at 2-4 m and and its spacing is reduced to 1800-2000 trees/ha. The recommendations could also be relevant about the Norway spruce for the Sitka spruce. If PCT would be done in all stands with trees that have more than 1600 trees/ha and dominant height of more than 4 m, then stands nr. 20, 44, 47, 49 and 55 would get PCT now in monoculture of black cottonwood and stands nr. 4, 26, 36, 41 and 54 for monoculture downy birch. None of the Sitka spruce stands are ready for PCT and only 27 and 58 would be ready for PCT in the mixed forest stands. Then the issue with the fertilization treatments becomes more complex. Should we do PCT on the fertilized plots as well? If the half hectare plots have been devided into ¼ ha area for the fertilizer treatments and then the 2500 m2 area would have to be divided again into 1250 m2 area to add the PCT treatment. If for example the number of trees would be taken down to 1500 trees/ha with PCT, that would only leave around 375 trees in each treatment. This is very low if the idea is to thin the stand maybe two or three times until the final felling. After a longer period, there would not be many trees left in each treatment for making the PCT fertilizer treatment quite complicated. I would therefore recommend PCT half of each plot (1/4 ha) in every monoculture plot and leaving the other half without PCT for a comparison. Then fertilize only two plots (2*1/2 ha) in each habitat and not fertilize the other two plots in each habitat as a comparison. By that way I would still use all the eight plots for each species in monoculture and randomly choose plots for each treatment in each habitat.

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5. Conclusions No long-term effects were found from different planting methods where mechanical site- preparation was included. However, harrowing may have some long-term effect over manual scarification, but multiple studies are needed to evaluate the generality of such treatment effects. Total mortality has increased in the past 13 years by 24 % since the last inventory, and the survival is now 58 %. It is not known if the mortality has stabilized in the Gunnarsholt experiment. It is therefore important to repeat such an inventory relatively soon. The native downy birch had the advantage over the introduced species in survival, probably because it has evolved with Icelandic conditions for a longer time and that the provenance of the other species might not be the most suitable ones. Trees grew faster and showed on average higher survival in the old Nootka lupine field compared to the grassland habitat. Likely because grass competition was too high, and the lupine gave both nutrients and shelter to the tree seedlings. The standing volumes in the experiment will increase much in the next 15 years, due to the the exponential growth that is normal for the establishment phase of planted forsests. Black cottonwood grew, so far, the fastest of all the species, while sitka spruce grew slowest. However, Sitka spruce had more trees with better stem form than the black cottonwood and downy birch. Sitka spruce could therefore possibly be the most valuable future timber tree. There was a significant positive effect of the foster-tree method on dominant height of the Sitka spruce, but no other positive effects were detected on its growth or production. It is therefore premature to give a firm conclusion if this method is to be recommended. The only other significant mixture effect on growth was the average negative height growth effect, across all species, which was unexpected, and further inventories are needed to see if this effect is a real treatment effect or not. Even if the positive trends observed from mixing species for various parameters were not significant after only 15 years, this might change later when the growing space fills up (BA>20), and further research is therefore needed on tree species mixture effects. Future inventories should preferably take place every 5 years, and it is already urgent to decide and start the planned fertilizer and pre-commercial thinning treatments within the next 5 years.

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Apendix Table S1. Treatments and different species from growth measurement stands shown on map in Figure S1 & S2. The table shows ratios of 50/50, 75/25 mixtures and monocultures and permanent plots nr. 1 and 2 with GPS coordinates for future pre-commercial thinning treatments. Area Treatment Common name Latin name Ratio % Stand nr. GPS coordinate: Plot 1. GPS coordinate: Plot2 PCT Spámanns. Mono. Sitka spruce Picea sitchensis 100 12 63° 50.830'N, 20° 11.026'W 63° 50.812'N, 20° 11.053'W No Spámanns. Mono. Sitka spruce Picea sitchensis 100 29 63° 50.524'N, 20° 11.191'W 63° 50.490'N, 20° 11.227'W No Spámanns. Mono. Sitka spruce Picea sitchensis 100 30 63° 50.510'N, 20° 11.145'W 63° 50.490'N, 20° 11.155'W No Ketilhúshagi Mono. Sitka spruce Picea sitchensis 100 38 63° 51.222'N, 20° 14.616'W 63° 51.200'N, 20° 14.622'W No Ketilhúshagi Mono. Sitka spruce Picea sitchensis 100 43 63° 51.184'N, 20° 14.708'W 63° 51.165'N, 20° 14.737'W No Ketilhúshagi Mono. Sitka spruce Picea sitchensis 100 51 63° 51.210'N, 20° 14.840'W 63° 51.188'N, 20° 14.849'W No Spámanns. Mono. Black cottonwood Populus trichocarpa 100 1 63° 50.897'N, 20° 11.187'W 63° 50.875'N, 20° 11.207'W No Spámanns. Mono. Black cottonwood Populus trichocarpa 100 20 63° 50.575'N, 20° 11.248'W 63° 50.546'N, 20° 11.255'W Yes Ketilhúshagi Mono. Black cottonwood Populus trichocarpa 100 44 63° 51.185'N, 20° 14.769'W 63° 51.171'N, 20° 14.792'W Yes Ketilhúshagi Mono. Black cottonwood Populus trichocarpa 100 47 63° 51.296'N, 20° 14.633'W 63° 51.273'N, 20° 14.632'W Yes Ketilhúshagi Mono. Black cottonwood Populus trichocarpa 100 49 63° 51.161'N, 20° 14.868'W 63° 51.142'N, 20° 14.898'W Yes Ketilhúshagi Mono. Black cottonwood Populus trichocarpa 100 55 63° 51.304'N, 20° 14.734'W 63° 51.287'N, 20° 14.751'W Yes Spámanns. Mono. Downy birch Betula pubescens 100 4 63° 50.844'N, 20° 11.143'W 63° 50.817'N, 20° 11.177'W Yes Spámanns. Mono. Downy birch Betula pubescens 100 6 63° 50.788'N, 20° 11.170'W 63° 50.767'N, 20° 11.187'W No Spámanns. Mono. Downy birch Betula pubescens 100 21 63° 50.535'N, 20° 11.310'W 63° 50.499'N, 20° 11.351'W No Spámanns. Mono. Downy birch Betula pubescens 100 26 63° 50.625'N, 20° 11.101'W 63° 50.602'N, 20° 11.126'W Yes Ketilhúshagi Mono. Downy birch Betula pubescens 100 36 63° 51.176'N, 20° 14.659'W 63° 51.153'N, 20° 14.678'W Yes Ketilhúshagi Mono. Downy birch Betula pubescens 100 40 63° 51.279'N, 20° 14.567'W 63° 51.251'N, 20° 14.587'W No Ketilhúshagi Mono. Downy birch Betula pubescens 100 41 63° 51.137'N, 20° 14.752'W 63° 51.113'N, 20° 14.788'W Yes Ketilhúshagi Mono. Downy birch Betula pubescens 100 54 63° 51.273'N, 20° 14.832'W 63° 51.252'N, 20° 14.861'W Yes Spámanns. Sitka spruce Picea sitchensis 50 Mixture 15 63° 50.734'N, 20° 11.109'W 63° 50.721'N, 20° 11.131'W No Spámanns. Black cottonwood Populus trichocarpa 50 Spámanns. Sitka spruce Picea sitchensis 50 Mixture 19 63° 50.576'N, 20° 11.313'W 63° 50.561'N, 20° 11.314'W No Spámanns. Black cottonwood Populus trichocarpa 50 Ketilhúshagi Sitka spruce Picea sitchensis 50 Mixture 39 63° 51.259'N, 20° 14.508'W 63° 51.241'N, 20° 14.530'W No Ketilhúshagi Black cottonwood Populus trichocarpa 50 Ketilhúshagi Sitka spruce Picea sitchensis 50 Mixture 50 63° 51.166'N, 20° 14.936'W 63° 51.142'N, 20° 14.945'W No Ketilhúshagi Black cottonwood Populus trichocarpa 50 Spámanns. Sitka spruce Picea sitchensis 50 Mixture 7 63° 50.746'N, 20° 11.255'W 63° 50.710'N, 20° 11.255'W No Spámanns. Downy birch Betula pubescens 50 Spámanns. Sitka spruce Picea sitchensis 50 Mixture 27 63° 50.576'N, 20° 11.197'W 63° 50.550'N, 20° 11.198'W Yes Spámanns. Downy birch Betula pubescens 50 Ketilhúshagi Sitka spruce Picea sitchensis 50 Mixture 52 63° 51.219'N, 20° 14.897'W 63° 51.195'N, 20° 14.933'W No Ketilhúshagi Downy birch Betula pubescens 50 Ketilhúshagi Sitka spruce Picea sitchensis 50 Mixture 62 63° 51.291'N, 20° 14.949'W 63° 51.268'N, 20° 14.972'W No Ketilhúshagi Downy birch Betula pubescens 50 Spámanns. Sitka spruce Picea sitchensis 50 Mixture 11 63° 50.843'N, 20° 11.093'W 63° 50.821'N, 20° 11.081'W No Spámanns. Alaska Willow Salix alaxensis 50 Spámanns. Sitka spruce Picea sitchensis 50 Mixture 32 63° 50.461'N, 20° 11.149'W 63° 50.440'N, 20° 11.172'W No Spámanns. Alaska Willow Salix alaxensis 50 Ketilhúshagi Sitka spruce Picea sitchensis 50 Mixture 46 63° 51.240'N, 20° 14.737'W 63° 51.221'N, 20° 14.751'W No Ketilhúshagi Alaska Willow Salix alaxensis 50 Ketilhúshagi Sitka spruce Picea sitchensis 50 Mixture 59 63° 51.237'N, 20° 14.933'W 63° 51.209'N, 20° 14.973'W No Ketilhúshagi Alaska Willow Salix alaxensis 50 Spámanns. Sitka spruce Picea sitchensis 75 Mixture 3 63° 50.846'N, 20° 11.218'W 63° 50.820'N, 20° 11.218'W No Spámanns. Black cottonwood Populus trichocarpa 25 Spámanns. Sitka spruce Picea sitchensis 75 Mixture 22 63° 50.518'N, 20° 11.270'W 63° 50.495'N, 20° 11.278'W No Spámanns. Black cottonwood Populus trichocarpa 25 Ketilhúshagi Sitka spruce Picea sitchensis 75 Mixture 48 63° 51.285'N, 20° 14.673'W 63° 51.267'N, 20° 14.705'W No Ketilhúshagi Black cottonwood Populus trichocarpa 25 Ketilhúshagi Sitka spruce Picea sitchensis 75 Mixture 58 63° 51.190'N, 20° 15.052'W 63° 51.174'N, 20° 15.082'W Yes Ketilhúshagi Black cottonwood Populus trichocarpa 25 Spámanns. Sitka spruce Picea sitchensis 75 Mixture 9 63° 50.888'N, 20° 11.085'W 63° 50.863'N, 20° 11.084'W No Spámanns. Downy birch Betula pubescens 25 Spámanns. Sitka spruce Picea sitchensis 75 Mixture 25 63° 50.627'N, 20° 11.159'W 63° 50.597'N, 20° 11.181'W No Spámanns. Downy birch Betula pubescens 25 Ketilhúshagi Sitka spruce Picea sitchensis 75 Mixture 56 63° 51.320'N, 20° 14.795'W 63° 51.297'N, 20° 14.829'W No Ketilhúshagi Downy birch Betula pubescens 25 Ketilhúshagi Sitka spruce Picea sitchensis 75 Mixture 57 63° 51.179'N, 20° 15.002'W 63° 51.155'N, 20° 15.041'W No Ketilhúshagi Downy birch Betula pubescens 25

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Figure 31. Spámannsstaðaforest at Gunnarsholt in southern Iceland with stand numbers from 1 to 32. P and C are harrowed and untreated unplanted control areas. The green and red stands were chosen for the growth and production measurements. The yellow numbers are permanent plots nr. 1 and 2. Treatments species and GPS coordinates for each plot is shown in Table S1.

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Figure 32. Ketluforest at Gunnarsholt in southern Iceland with stand numbers from 33 to 64. P and C are harrowed and untreated unplanted control areas. The green and red stands were chosen for the growth and production measurements. The yellow numbers are permanent plots nr. 1 and 2. Treatments species and GPS coordinates for each plot is shown in Table S1.

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