Assessment and Use of Sea Buckthorn and Apple Diversity in Northern Pakistan

Home , Malus orientalis, Spantik, Stak Valley, Thowar

Assessment and use of sea buckthorn and apple diversity in northern Pakistan

Muhammad Arslan Nawaz

Dissertation submitted for the academic degree Doktor der Agrarwissenschaften (Dr. agr.)

Dissertation presented to the

Faculty of Organic Agricultural Sciences Organic Plant Production and Agroecosystems Research in the Tropics and Subtropics (OPATS) University of Kassel

1st supervisor: Prof. Dr. Andreas Bürkert, University of Kassel 2nd supervisor: Prof. Dr. Asif Ali Khan, Muhammad Nawaz Shareef University of Agriculture, Multan Co-supervisor: Dr. Martin Wiehle, University of Kassel

Date of submission: 03.12.2020 Date of defence: 15.04.2021

Witzenhausen, Germany

Table of Content Acknowledgments ...... I Summary ...... III Zusammenfassung ...... VI Chapter 1 - General introduction and research objectives ...... 1 1.1 Perennial plant genetic resources – their importance and management ...... 2 1.2 PGR in Pakistan and its mountainous regions ...... 4 1.3 PGR in Gilgit and Baltistan ...... 5 1.3.1 Topography, climate, and vegetation ...... 5 1.3.2 Neglected research region and threats to local PGR ...... 7 1.4 State of the art of assessing agrobiodiversity ...... 9 1.5 Investigated local plant species ...... 11 1.5.1 Sea buckthorn (Hippophae rhamnoides L.) ...... 11 1.5.2 Apple (Malus × domestica Borkh.) ...... 12 1.6 Research hypotheses and objectives ...... 14 1.7 Outline of the thesis ...... 15 1.8 References ...... 17 Chapter 2 – Morphological and genetic diversity of sea buckthorn in the Karakoram Mountains of northern Pakistan ...... 23 2.1 Abstract ...... 24 2.2 Introduction ...... 25 2.3 Materials and Methods ...... 28 2.3.1 Plant Material and Sampling Area ...... 28 2.3.2 Dendrometric Traits ...... 30 2.3.3 Leaf and Fruit Morphometry Traits ...... 30 2.3.4 Leaf and Fruit Colours ...... 30 2.3.5 DNA Isolation and EST-SSR Analysis ...... 32 2.3.6 Data Analysis ...... 33 2.4 Results ...... 35 2.4.1 Dendrometric Traits ...... 35 2.4.2 Leaf and Fruit Morphometry Traits ...... 38 2.4.3 Leaf and Fruit Colour ...... 38 2.4.4 Genetic Diversity and Differentiation of Markers ...... 39 2.4.5 Genetic Diversity and Differentiation of Populations ...... 42 2.5 Discussion ...... 46 2.5.1 Morphological Variation ...... 46 2.5.2 Genetic Diversity and Differentiation ...... 48 2.6 Conclusions ...... 50 2.7 Appendix ...... 52 2.8 References ...... 53 Chapter 3 – Superfruit in the niche — Underutilized sea buckthorn in Gilgit-Baltistan, Pakistan ...... 60 3.1 Abstract ...... 61 3.2 Introduction ...... 62 3.3 Materials and Methods ...... 66 3.3.1 Study Area ...... 66 3.3.2 Survey on Sea Buckthorn Management, Harvest, and Post-Harvest Handling Practices ...... 67 3.3.3 On-Farm Drying and Laboratory Experiment ...... 69 3.3.4 Statistical Analysis ...... 71 3.4 Results ...... 72 3.4.1 Survey on Sea Buckthorn Management, Harvest, and Post-Harvest Handling Practices ...... 72 3.4.1.1 Status and Subsistence through Collection ...... 72

3.4.1.2 Conditions and Methods of Harvest to Post-Harvest Handling ...... 73 3.4.1.3 Collectors´ Problems ...... 74 3.4.1.4 Collectors’ Perception about Trainings...... 76 3.4.1.5 Preferred Plant and Fruit Traits by Collectors ...... 76 3.4.1.6 Sustainable Supply Chain Constructs ...... 77 3.4.2 On-Farm Drying and Laboratory Experiment ...... 78 3.4.2.1 Days Required for Drying and Moisture Content ...... 78 3.4.2.2 Concentration of Ascorbic Acid ...... 79 3.5 Discussion ...... 80 3.5.1 Status of Collection, Post-Harvest Handling, and Management ...... 80 3.5.2 Quality Loss Due to Sun Drying of Sea Buckthorn Berries ...... 82 3.5.3 Sea Buckthorn Supply Chain...... 83 3.6 Conclusions ...... 85 3.7 Appendix ...... 87 3.8 References ...... 89 Chapter 4 - Pheno-genetic studies of apple varieties in northern Pakistan: A hidden pool of diversity? ...... 97 4.1 Abstract ...... 98 4.2 Introduction ...... 99 4.3 Materials and Methods ...... 102 4.3.1 Study site, plant material, and owner interview ...... 102 4.3.2 Dendrometry, management, and use ...... 104 4.3.3 Fruit phenotypic description and phenotype ...... 104 4.3.4 DNA isolation and SSR analysis ...... 104 4.3.5 Data analysis ...... 106 4.4 Results ...... 108 4.4.1 Varietal diversity ...... 108 4.4.2 Dendrometry, management, and use ...... 112 4.4.3 Fruit phenotype ...... 115 4.4.4 Genetic diversity and differentiation of markers ...... 119 4.4.5 Genetic diversity and differentiation of valleys and villages ...... 119 4.4.6 Synonyms and homonyms ...... 124 4.5 Discussion ...... 128 4.5.1 Varietal diversity and management ...... 128 4.5.2 Fruit phenotype ...... 131 4.5.3 Genetic diversity and differentiation...... 132 4.5.4 Synonyms and homonyms ...... 134 4.6 Conclusions ...... 135 4.7 Appendix ...... 138 4.8 References ...... 151 Chapter 5 – General discussion ...... 158 5.1 Relevance of current research ...... 159 5.2 Testing the first hypothesis ...... 159 5.3 Testing the second hypothesis ...... 163 5.4 Testing the third hypothesis ...... 166 5.4.1 Sea buckthorn ...... 166 5.4.2 Apple ...... 168 5.4.3 Common problems and constraints ...... 170 5.4.4 Solutions ...... 171 5.4.4.1 Training for management practices ...... 172 5.4.4.2 Improving marketing/commercialization skills ...... 173 5.5 Concluding recommendations ...... 174 5.6 References ...... 176

Acknowledgments My doctoral journey has been an exciting rollercoaster ride with plenty of experiences and exposures. There are many persons I owe my thanks. First of all, I would like to express my gratitude to Prof. Dr. Andreas Bürkert (University of Kassel, Germany) for accepting me as a doctoral student and providing me the opportunity to work in a multi-national academic environment. I am equally grateful for his professional guidance, scientific inputs, support, and encouragements not only in the office but also during field expeditions. I am equally indebted to Prof. Dr. Asif Ali Khan (Muhammad Nawaz Shareef University of Agriculture, Multan, Pakistan) for his co- supervision. His support in arranging the scientific discussions, seminars regarding sea buckthorn as well as networking with other scientists is highly appreciated. I am also grateful to Dr. Martin Wiehle for co-supervision, friendship and for giving significant inputs during the whole course of this PhD. He was available for every discussion related to research, organizational issues and for keeping me motivated throughout. The research expeditions in Gilgit-Baltistan were also very memorable as well as source of learning with healthy academic discussions. I also thank Prof. Dr. Eva Schlecht (University of Kassel and Georg-August- Universität Göttingen) for her support during field expeditions and contribution to the success of the field research. I acknowledge Prof. Dr. Konstantin V. Krutovsky and Prof. Dr. Oliver Gailing (Department of Forest Genetics and Forest Tree Breeding, Georg-August-Universität Göttingen) for welcoming me in their working group for genetic studies. Dr. Markus Müller for discussing genetic findings and for answering my queries whenever I knocked at his office door. Additionally, I am grateful to Alexandra Dolynska and Christine Radler for their technical assistance during the laboratory analysis. Also, I owe thanks to Christina Mengel from Conservation Biology, University of Marburg, for her technical support and sharing of marker-related data and reference samples for apple project. My special thanks go to Mr. Richard Dahlem (Pomologenverein, Landesgruppe Rheinland-Pfalz/Saarland/Luxemburg) for sharing pomological knowledge in many field training sessions to characterize apple cultigens. I also acknowledge Prof. Dr. Stefan Seuring (University of Kassel) for his scientific support in supply chain related research. Mr. Mahmood Salam for his

assistance in data collection and partly analysing the data. Dr. Usman Khalid for helping in the interpretation of the results of the sustainable supply chain constructs. Funding from the German Federal Ministry for Economic Cooperation and Development (BMZ) through a scholarship of the German Academic Exchange Service (DAAD) to the International Center for Development and Decent Work (ICDD) as part of the EXCEED initiative is thankfully acknowledged. The yearly PhD workshops in different ICDD partner universities facilitated new insights and networking. I am grateful to respondents in Gilgit-Baltistan, Pakistan for their willingness to take time and participate in questionnaires and field work. Furthermore, I extend my great respect to village hosts especially, Haji Gulzar from Skardu, Pakistan for providing accommodation and rides as well as delicious local food. I am also indebted to the Department of Agriculture, Government of Gilgit-Baltistan for sharing the nursery-maintained varieties and NGO initiatives such as the Agar Khan Rural Support Programme (AKRSP), which greatly facilitated my study. I would also like to thank Mr. Inayat Amir for organizing the very first trip to Gilgit-Baltistan with a very low budget and warm welcome by his family at their place. I thank Mr. Iftikhar Alam, for often driving the vehicle during our field trips and his scientific collaboration in apple and apricot based research, Mr. Shakeel Ahmad for discussing the data analyses, and Dr. Loius Amprako and Mrs. Khadija Sabir for proof- reading my thesis. I am grateful to my colleagues: Mr. Budiman, Mr. Deogratias Agbotui, Dr. Marion Reichenbach, Dr. Gayyor Fatima, Mr. Asif Hameed, Dr. Mariko Ingold, Dr. Tobias Feldt, Dr. Jessica Andriamparany, Dr. Juliane Dao, Dr. Tsevegmed Munkhnasan, Dr. Alim Sabir, Dr. Gunadhish Khanal, Dr. Sven Gönster-Jordan, for informal meal invitations, jokes, emotional, and their professional support. Finally, I express my sincere gratitude to my family and friends, especially to my father, Mr. Muhammad Nawaz and mother, Mrs. Shehnaz Begam for their enduring support and encouragement that made me who I am today. I am also greatly indebted to my wife Khadija Sabir for her unconditional love and constant support. She never asked me to stop working and simply did the dishes, folded the laundry, and cooked food without question. Thank you for being my wife, sounding board, and above all my friend.

Summary Many local perennial plant genetic resources (P/PGR) are under threat due to over-exploitation, depletion, degradation, farmers’ favoring few cash crops, poor marketing conditions leading to low product prices along with the lack of knowledge about alternative uses and management strategies. Such processes often cause the underutilization and replacement of local P/PGR causing them to become neglected and underutilized species (NUS). The decline of species abundance may cause genetic erosion of these NUS crops and prevents the adaptation or improvement of valuable traits. Many of these traditional NUS crops can be conserved on human- managed farmlands (in-situ conservation). The study area in Gilgit-Baltistan (GB), Pakistan harbors important local P/PGR hotspots with a still largely unknown species diversity reflecting a millennia old trading history along the historic Silk Route. The ongoing depletion and irreversible loss of indigenous plant genetic resources calls for an assessment of status quo of agrobiodiversity and the conservation of plant genetic resources. Sea buckthorn (Hippophae rhamnoides L.) and local apple (Malus × domestica) varieties are typical representatives of such local P/PGR, contribute substantially to farmers’ household incomes, and provide essential ecosystem services. Both species were intensively studied to assess their use, to unravel potential effects of past and present anthropogenic activities on varietal richness and diversity, and to derive location- specific management, conservation, and promotion strategies. As sea buckthorn berries are considered a “superfood” due to their nutritional properties, fruits of the species have a large international market potential, especially in China and Europe. Contrary to the situation in other countries, in Pakistan this species is heavily underutilized and neglected. During 2016-2017, the first study on natural sea buckthorn populations was conducted to assess the effects of putative ongoing domestication. Both, morphological and genetic diversity were characterized and evaluated based on the present variability. For this purpose, 300 individuals from eight different villages were selected where farmers were directly involved in sea buckthorn collection. Within each village the samples were classified as wild and supposedly domesticated stands. Dendrometric, fruit, and leaf morphometric traits were recorded. For genotyping, twelve EST-SSR (expressed sequence tags-simple sequence repeats) markers were used. The results showed significant differences in

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morphological traits across stands (village and wild) and there was a significant positive correlation among leaf area and altitude. Berries exhibited 22 colour shades and 20 dorsal and 15 ventral leaves colour shades. Mean genetic diversity was high

(He = 0.699) and comparable to other studies. Three distinct genetic clusters were found corresponding to the geographical location of the populations with mountains acting as a physical barrier against gene flow. Likely gene flows within and among village of the same valley/region and lacking trends in morphological traits among stands yielded little evidence of domestication. Considering high allelic richness and genetic diversity, the population of GB is likely natural and seems to be a promising source for selection of improved germplasm. The reason for low market performance of sea buckthorn in Gilgit-Baltistan was assessed during a second study (2017–2018) conducted to assess the factors influencing local trade. A total of 111 fruit collectors and 17 commission agents were interviewed using semi-structured questionnaires. This study provided comprehensive data regarding the value chain from collection to post-harvest management practices of sea buckthorn berries including effects of sun and shade drying of fruits on vitamin C. The findings were complemented by an analysis of the underlying supply chain (collectors ~ supplier and commission agents ~ buyer). The results showed that berry marketing is severely hampered by low raw product quality, varying prices, and low local demand. Fruit sale prices were low and not satisfactory for the collectors (1.82 US$ kg−1) although mostly poor households were/are involved in the harvest and sale for their subsistence. Post-harvest conditions such as traditional sun drying, and storage were inappropriate leading to a decline of fruit physical appearance and chemical quality, thereby negatively influencing the sales price of produce. Supply chain analyses indicated lack of coordination among actors and infrastructure which prevent sea buckthorn production at a larger scale. The study provides evidence for an urgent need to define appropriate food quality standards, to increase communication among different stakeholders, and to intensify training of collectors. Malus × domestica is one of the main fruit crops of temperate regions, traded globally, and a comparatively well documented species, whereas diversity of germplasm in remote areas is yet to be explored. In GB, germplasm diversity of apple is threatened by gradual loss due a recent increase in market demand and farmers’ preference for modern, high yielding cultivars. Therefore in 2018–2019, a third study was conducted on local apple cultigens to assess their diversity, varietal richness,

arboricultural activities as well as phenotypic and genotypic parameters. To this end, two dead-end valleys (Ishkoman and Baltistan) were selected by assuming that plant genetic materials was introduced from its lower end via roads and trading markets rather than tedious mountain pathways. A total of 106 individual apple trees were sampled, and 35 tree owners were interviewed from seven villages of these two valleys. For the first time in this area dendrometric parameters, fruit traits (qualitative and quantitative), and varietal diversity (based on alpha- and beta-diversity) were measured in each village. Eleven SSR markers were used for genotyping and synonyms and homonyms were distinguished based on cluster analysis. Alpha varietal diversity was highest in Baltistan, where even a wild apple relative (Malus baccata) was found. Beta-diversity revealed three compositionally distinct clusters among villages. Fruit weight, calyx depth, and axis pit width represented highest variability as compared to other assessed characters and seem thus useful traits to distinguish the studied accessions. Arboricultural activities were rarely observed and only a few local varieties were marketed, while most of them were used for home consumption only. Genetic data revealed sixty-one multi-locus genotypes (MLG; mean genotype diversity: 58%) and 18 putative clones (comprising 2 to 9 ramets) while mean genetic diversity was moderate (He = 0.677). Observed negative inbreeding coefficients indicated excess of heterozygotes in three genetic clusters with high gene flow among villages and valleys. Against our expectations there was no apparent effect of accessibility (lower to upper part of the valley) on varietal diversity exhibited by morphological or genetic traits. Moderate correlation (r = 0.627, p = 0.001) between phenotypic and genotypic and dendrogram analysis indicated genetically linked fruit traits, which merit further investigation. The moderate to high varietal, phenotypic, and genetic diversity revealed the need and potential of in situ conservation for the apple germplasm of GB and as a basis for future breeding programs. Our studies show that sea buckthorn and apple can act as model species for P/PGR in GB emphasizing the need for the development of locally suitable conservation and management strategies. The marketing promotion of indigenous P/PGRs may open new income sources for local communities. This will also help to maintain the historical biological heritage of the region. Studies combining results of P/PGR agrobiodiversity with socio-economic data will provide guidance to identify P/PGR that merit conservation and further promotion.

Zusammenfassung Weltweit ist eine Vielzahl lokaler mehrjähriger pflanzengenetischer Ressourcen (P/PGR) durch Übernutzung, Degradation, Simplifizierung, schlechte und unattraktive Vermarktungsbedingungen, sowie mangelndes Wissen über alternative Nutzungformen und Managementstrategien bedroht. Diese Faktoren führen oft zur Abnahme lokaler P/PGR, wodurch sie zu vernachlässigten und nicht genutzten Arten (NUS) werden. Der Rückgang des Artenreichtums kann die genetische Erosion dieser NUS-Kulturen beschleunigen und die Anpassung oder Verbesserung wertvoller Merkmale verhindern. Viele dieser traditionellen NUS-Kulturen können jedoch auf vom Menschen bewirtschafteten Ackerflächen erhalten werden (in-situ-Erhaltung). Das Untersuchungsgebiet dieser Studie in Gilgit-Baltistan (GB), Pakistan, ist ein bedeutender wenn auch weitgehend unbekannter Biodiversitäts-Hotspot für lokale P/PGR, der eine jahrtausendealte Handelsgeschichte entlang der historischen Seidenstraße widerspiegelt. Die fortschreitende Übernutzung und der irreversible Verlust der einheimischen pflanzengenetischen Ressourcen erfordern deren momentane Zustandsaufnahme und -bewertung sowie der Beurteilung von Erhaltungsmaßnahmen. Sanddorn (Hippophae rhamnoides L.) und lokale Apfelsorten (Malus × domestica) sind typische Vertreter solcher lokaler P/PGR, tragen wesentlich zum Haushaltseinkommen der Bauern bei und erbringen wichtige Ökosystemdienstleistungen. Beide Arten wurden intensiv untersucht, um ihre Nutzung zu beurteilen und mögliche Auswirkungen vergangener und gegenwärtiger anthropogener Aktivitäten auf die Sortenvielfalt zu analysieren. Daraus können dann, standortspezifische Management-, Erhaltungs- und Förderungsstrategien abgeleitet werden. Da Sanddornbeeren aufgrund ihrer ernährungsphysiologischen Eigenschaften als "Supernahrungsmittel" gelten, haben die Früchte ein bedeutendes internationales Marktpotenzial, insbesondere in China und Europa. Im Gegensatz zu diesen Regionen, ist Sanddorn wird Pakistan kaum genutzt und nachezu vernachlässigt. In den Jahren 2016-2017 wurde deshalb die erste Studie über natürliche Sanddornpopulationen durchgeführt, um die Auswirkungen von möglichen Domestikationprozessen zu beurteilen. Sowohl die morphologische als auch die genetische Vielfalt wurden charakterisiert und auf der Grundlage der gegenwärtigen Variabilität bewertet. Zu diesem Zweck wurden 300 Individuen aus acht

verschiedenen Dörfern ausgewählt, in denen die Bauern direkt an der Sanddornsammlung beteiligt waren. Innerhalb jedes Dorfes wurden die Proben als wilde und vermeintlich domestizierte Bestände klassifiziert. Dendrometrische, frucht- und blattmorphometrische Merkmale wurden erfasst. Für die Genotypisierung wurden zwölf EST-SSR-Marker (expressed sequence tags - einfache Sequenzwiederholungen) verwendet. Die Ergebnisse zeigten signifikante Unterschiede in den morphologischen Merkmalen der verschiedenen Bestände (domestiziert und wild), und es bestand eine signifikante positive Korrelation zwischen Blattfläche und Höhenlage. Die Beeren wiesen 22 und die Blattflächen 20 dorsale und 15 ventrale Farbschattierungen auf. Die mittlere genetische Vielfalt war hoch

(He = 0.699) und ist mit anderen Studien vergleichbar. Es wurden drei verschiedene genetische Cluster gefunden, die der geographischen Lage der Populationen entsprachen, wobei Berge als physische Barriere gegen den Genfluss wirkten. Wahrscheinliche Genflüsse innerhalb und zwischen den Dörfern desselben Tales/derselben Region und fehlende Trends bei den morphologischen Merkmalen zwischen den Beständen wiesen auf einen nur geringen Domestizierungsgrad hin. In Anbetracht des hohen Allelreichtums und der genetischen Vielfalt ist die Population von GB als natürlich einzustufen und scheint eine vielversprechende Quelle für die Selektion von verbesserten Sorten zu sein. Der Grund für die geringe Marktleistung des Sanddorns in Gilgit-Baltistan wurde in einer zweiten Studie (2017-2018) untersucht, um die Faktoren zu bewerten, die den lokalen Handel beeinflussen. Insgesamt wurden 111 Obstsammler und 17 Zwischenhändler mittels halbstrukturierter Fragebögen befragt. Diese Studie lieferte umfassende Daten zu Managementpraktiken entlang der Wertschöpfungskette von der Sammlung bis zur Lagerung der Früchte. Dies schloss auch die Auswirkungen der Sonnen- und Schattentrocknung der Früchte auf den Vitamin C Gehalt ein. Die Ergebnisse wurden durch eine Analyse der zugrunde liegenden Lieferkette (Sammler ~ Lieferant und Kommissionäre ~ Käufer) ergänzt. Die Ergebnisse zeigten, dass die Vermarktung der Beeren durch niedrige Rohproduktqualität, schwankende Preise und geringe lokale Nachfrage stark behindert wird. Die Verkaufspreise der Früchte waren niedrig und für die Sammler nicht zufriedenstellend (1,82 US$ kg-1), obwohl zumeist arme Haushalte für ihren Lebensunterhalt an der Ernte und dem Verkauf beteiligt waren/sind. Die Aufarbeitungsbedingungen nach der Ernte, wie z.B. das traditionelle Trocknen in der

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Sonne und die Lagerung, waren unangemessen, was zu einer Verschlechterung der physischen und chemischen Qualität der Früchte führte und sich somit negativ auf den Verkaufspreis der Produkte auswirkte. Lieferkettenanalysen wiesen auf einen Mangel an Koordination zwischen den Akteuren und Problemen mit der Infrastruktur hin, die eine Sanddornproduktion in größerem Maßstab verhindern. Die Studie liefert Belege für die dringende Notwendigkeit, angemessene Lebensmittelqualitätsstandards zu definieren, die Kommunikation zwischen den verschiedenen Akteuren zu verbessern und die Ausbildung von Sammlern zu intensivieren. Malus × domestica ist eine der wichtigsten Obstkulturen der Gemäßigten Breiten, wird weltweit gehandelt und ist ein vergleichsweise gut dokumentiertes Kultigen, während die Sortenvielfalt in abgelegenen Gebieten noch weitgehend unerforscht ist. In GB ist die pflanzengenetische Vielfalt bei Äpfeln aufgrund der in jüngster Zeit gestiegenen Marktnachfrage und Bevorzugung moderner, ertragreicher Sorten durch die Landwirte von einem allmählichen Verlust bedroht. Daher wurde zwischen 2018 und 2019 eine dritte Studie zu den lokalen Apfelsorten durchgeführt, um deren Vielfalt, Sortenreichtum, baumpflegerische Aktivitäten sowie phänotypische und genotypische Parameter zu bewerten. Zu diesem Zweck wurden zwei Sackgassentäler (Ishkoman und Baltistan) ausgewählt, wobei zugrundegelegt wurde, dass pflanzengenetisches Material nur vom unteren Talende aus über Straßen und Handelsmärkte und nicht über wenig erschlossene Bergpässe eingeführt wurde. Insgesamt wurden 106 einzelne Apfelbäume beprobt, und 35 Baumbesitzer aus sieben Dörfern befragt. Pro Dorf wurde die Sortenvielfalt (basierend auf Alpha- und Beta-Diversität), dendrometrische Parameter und Fruchtmerkmale qualitativ und quantitativ gemessen. Für die Genotypisierung wurden elf SSR-Marker verwendet und Synonyme und Homonyme wurden auf der Grundlage einer Clusteranalyse unterschieden. Die Alpha-Sortenvielfalt war in Baltistan am höchsten, wo sogar ein Verwandter des Wildapfels (Malus baccata) gefunden wurde. Die Beta-Diversität zeigte drei kompositorisch unterschiedliche Cluster unter den Dörfern. Fruchtgewicht, Kelchtiefe und Achskernbreite zeigten die höchste Variabilität unter allen untersuchten Merkmalen und scheinen somit nützlich zur Unterscheidung der untersuchten Akzessionen zu sein. Baumpflegerische Maßnahmen wurden nur selten beobachtet und nur wenige lokale Sorten wurden vermarktet sondern die meisten wurden nur für den Eigenverbrauch verwendet. Die genetischen Daten zeigten 61 Multi-Locus-

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Genotypen (mittlere Genotypvielfalt: 58%) und 18 mutmaßliche Klone (bestehend aus

2 bis 9 Rameten), während die mittlere genetische Vielfalt mäßig war (He = 0.677). Die beobachteten negativen Inzuchtkoeffizienten deuteten auf einen Überschuss an Heterozygotie in drei genetischen Clustern mit hohem Genfluss zwischen Dörfern und Tälern hin. Entgegen unseren Erwartungen gab es keinen offensichtlichen Effekt der Zugänglichkeit (unterer bis oberer Teil des Tals) auf die Sortenvielfalt basierend auf den morphologischen oder genetischen Merkmalen. Eine moderate Korrelation (r = 0.627, p = 0.001) zwischen phänotypischen und genotypischen Merkmalen visualisiert durch eine Dendrogrammanalyse deutete auf genetisch verknüpfte Fruchtmerkmale hin, die eine weitere Untersuchung verdient. Sowohl der mäßige bis hohe Sortenreichtum als auch die, phänotypische und genetische Diversität unterstreicht die Bedeutung einer in-situ-Erhaltung des pflanzengentischen Materials von GB, das als Grundlage für zukünftige Züchtungsprogramme dienen kann. Unsere Studien zeigen überdies, dass Sanddorn und Apfel als Modellarten für P/PGR in GB dienen können, was die Notwendigkeit der Entwicklung von lokal geeigneten Erhaltungs- und Managementstrategien unterstreicht. Die Förderung von Vermarktungsstrukturen für einheimische P/PGRs kann zudem neue Einkommensquellen für lokale Gemeinschaften eröffnen. Dies kann dazu beitragen, das historisch biologische Erbe der Region zu erhalten. Studien, die Ergebnisse der Agrobiodiversität von P/PGR mit sozio-ökonomischen Daten kombinieren, bieten eine Orientierungshilfe bei der Identifizierung von P/PGR bieten, die es verdienen, erhalten und weiter gefördert zu werden.

Chapter 1 - General introduction and research objectives

1.1 Perennial plant genetic resources – their importance and management Plant genetic resources (PGR) comprise all cultivated plants such as cultivars, breeding lines, genetic stocks, landraces, and their wild progenitors and relatives (Delêtre et al., 2012). PGR which live more than two years are referred to as perennial plant genetic resources (P/PGR). About two-third of the 1.4 billion world’s poorest people inhabit rural areas. Their livelihoods mainly depend on agricultural production, and to a large proportion on P/PGR resources (Chandra et al., 2020). Tree integration into crop cultivation as an agroforestry practice is adopted widely throughout the world. Approximately 560 million farmland people manage their lands with a tree cover > 10% (Zomer et al., 2009). Trees in agricultural environments provide a number of services such as soil erosion control, soil improvement, fibre provision, fodder, food, fuel, medicine, shade, shelter, and timber (Dawson et al., 2014). The use of trees in the subsistence of local peoples’ livelihoods and their management in forests and farms have often been ignored or poorly targeted by policy makers due to complexities in quantification and negligible appreciation of agroforestry systems (Belcher and Schreckenberg, 2007; World Bank, 2008). Also, the present intra-specific variation of tree species and their management in rural communities is of less importance for policy makers in contrast to plant researchers (Dawson et al., 2009). This realm, however, is essential to understand the mechanism of rural communities benefiting from trees and to improve management of these resources for optimised future use. Moreover, many PGR are under threat and reasons are manifold. First, local communities manage PGR either through resource use or by managing influx (Chandra et al., 2020) resulting often in over-exploitation, depletion, and degradation. Second, increasing agricultural intensification tends to rely only on a few food (mainly cash) crops, whereby local PGR have often no or a very little market value (Pichop et al., 2016). This leads in turn into the underutilization of traditional and local food crops (Adhikari et al., 2017). Third, the lack of knowledge about alternative uses and management strategies (Jama et al., 2008; Okafor, 1976) such as storage, preservation, and value addition is an important parameter causing the underutilization and replacement of PGR. This is often connected with a reduced knowledge transfer between generations causing disuse of PGR (Carvalho and Frazão-Moreira, 2011). Fourth, low and unreliable market prices may prevent preservation although some

products may have the potential to gain significant national and international value (Alves and Ramos, 2018). The above discussed facts often result in PGR and P/PGR becoming neglected and underutilized species (NUS) which were differently categorized, though Eyzaguirre et al. (1999) who attempted to define “neglected” and “underutilized” species in a more contextualized manner. Crop species primarily grown by local farmers in their centre(s) of origin or diversity and acting as an important source of subsistence, are considered neglected. Some of these crop species may be distributed globally, and often occupy special niches in local ecology, production, and consumption systems related to socio-cultural preferences. The crops in these niches often are inadequately characterized, thus neglected by conservation and research. On the other hand, crop species that farmers are not commonly growing or using and whose full potential has not been recognized are considered underutilized. Production of these plant species has no competition with other cash crops in the same agricultural system. Delêtre et al. (2012) proposed to characterise NUS by combining the concepts of neglected and underutilized species. They refer to crops that are (i) harvested from wild plants or grown with less or no external inputs in local farming system with a long history of cultivation; (ii) adapted to particular agro-ecological and marginal niches; (iii) maintaining substantial intra-specific diversity; (iv) mainly playing a subsistence role, therefore, being insignificant for the formal economy or supply systems; (v) possess an underexploited potential either as income source, food, fibres, fodder, medicine, or cosmetics; (iv) associated with a local cultural heritage; and (vii) not tackled by mainstream agricultural research and development efforts. The ecogeographic decline which may cause genetic erosion of these NUS crops prevents the improvement of distinctive valuable traits. Many of these traditional NUS crops can be conserved on human-managed farmlands and some native and wild fruits are vital for conserving faunal diversity, thus increasing agrobiodiversity by in situ conservation on farmlands (Baul et al., 2015). Although the indigenous varieties may be low yielding, they have usually well adapted to environmental variability over the course of evolution and become resistant to different biotic and abiotic stresses. Many of these local resources therefore are of great value for different ecosystem services and stability. Hence, awareness of concerned people at farm, region, and nation level about P/PGR’s sustainable use, management, harvesting, and

conservation is crucial. In many developing countries including Pakistan, there are also institutional threats to the successful conservation and promotion of P/PGR as the relationship between local communities and their associated agricultural/forestry/horticultural departments is hostile. Evidence shows that state-owned and communal management by public organizations have been unsuccessful in controlling the loss of local P/PGR by deforestation and degradation (FAO, 2009). Thus, on-farm community-based management of such resources by local people committed to conserve P/PGR through use could be an effective alternative approach. This, however, requires indigenous community rights to access and control local P/PGR to adopt sustainable use and management strategies.

1.2 PGR in Pakistan and its mountainous regions Approximately two-third of Pakistan’s total area is mountainous which spreads along the western and northern boundaries, namely Balochistan, Federally Administered Tribal Areas (FATA), Khyber Pakhtunkhwa (KPK), Azad Jammu and Kashmir (AJK), and Gilgit-Baltistan (GB). Given Pakistan’s altitudinal range of 0 to 8611 m, a vast range of climatic and ecological zones exists offering suitable habitats for many species. Pakistan harbours a flora comprising almost 6000 species of higher plants (Haq et al., 2010), whereby 6.7% is harboured in alpine and mountainous regions with marked forest resources. Moreover, cultivation of horticultural tree crops such as fruits and nuts are increasing in mountainous regions. Balochistan has the country’s highest production of almond (Prunus dulcis), grapes (Vitis vinifera), apple (Malus domestica), pomegranate (Punica granatum), apricot (Prunus armeniaca), cherry (Prunus avium), peach (Prunus persica), and walnut (Juglans nigra) (Rasul and Hussain, 2015). Due to a rapid population increase, poor socio-economic conditions, unavailability of alternate fuel, and reliance on domestic energy sources, almost 3.9% (170,684 ha out of 4.34 million ha) of forest land had been deforested in Pakistan (Qamer et al., 2016) between 1990 and 2010. This has fastened the process of land use change, enhancing the increase in floods due to glacier melting, soil erosion, loss of habitat. To mitigate these land use change effects Pakistan has planned to plant over 100 million trees in five years (GOP, 2019). Populus spp., Eucalyptus spp., Acacia nilotica, Zizyphus mauritania, Dalbergia sissoo and others have been used for

this purpose (Baig et al., 2020). Aside these large-scale planting activities, many local farmers grow or/and maintain trees by default (intentionally or unintentionally) on their farm and in homesteads to reduce soil erosion, increase soil water retention, provide shade, and generate income (Essa et al., 2011). This farmer-driven process, however, is far less documented and measurable and might even fail to successfully establish tree banks on farms due to inadequate extension services (Baig et al., 2020). Furthermore, encouragement campaigns with help of Government Organizations (GOs) such as GIZ (German Agency for International Cooperation) (Bari, 2019) and non-Government Organizations (NGOs) such as AKRSP (Aga Khan Rural Support Program; Baig et al., 2020) are considered beneficial by providing financial incentives, education, and training programs. Main constraints to the establishment of sustainable agroforestry systems are insufficient marketing of produce, problems with land titles, lack of technical support, and in some areas water shortage (Baig et al., 2020).

1.3 PGR in Gilgit and Baltistan 1.3.1 Topography, climate, and vegetation Gilgit-Baltistan (GB) is situated in northern Pakistan (35.35 °N and 75.90 °E) at the periphery of Central Asia bordering with India (south-east), Afghanistan (northwest), and China (north-east). Historically, it was part of the ancient Silk Route – today partly transformed into the Karakoram Highway (KKH) and the recently completed China-Pakistan Economic Corridor (CPEC). GB is a highly mountainous region comprising the Himalaya, the Karakorum, the Pamir, and the Hindu Kush ranges with an elevation from 1400 to 8611 m prone to frequent landslides (Khan et al., 2019). The area covers about 73,000 km2 of which about 1500 km2 (2%) is covered by natural forest (Figure 1.1; Qamer et al., 2016). The altitudinal range offers a large number of ecosystems covering alpine scrub (3600-4900 m), sub-alpine forests (3000-3800 m), dry temperate forests (1550-3000 m), and moist temperate forests (1500–3000 m; Figure 1.1; Qamer et al., 2016). The climate varies widely from moist temperate monsoon (western Himalayas) to cold arid and semi-arid (northern Hindu Kush and Karakoram) conditions. The precipitation is low and ranges annually from 200 mm (rainfall < 3,000 m) to around 2,000 mm (mainly snow ≥ 6000 m). The temperature may peak above 40 °C in summer and the mean monthly temperature in winter is below 0 °C in valleys above 2000 m (Ismail et al., 2018). In general, the region has an arid climate with many sunshine hours (Whiteman, 1985) and low humidity.

GB is divided into ten districts (Gilgit, Ghizer, Diamer, Nagar, Hunza, Astora, Skardu, Kharmang, Shigar, and Ghanche). It harbours a population of about 1.8 million inhabitants (Burki, 2015) with annual population growth rate of 4.9% from 1998 to 2011 (Government of Gilgit-Baltistan, 2013) and is outstandingly rich in ethnic and linguistic diversity (Kreutzmann, 2014). The fragile mountains of the region have only 2% (90.000 ha) arable land of which approximately 1% (58.000 ha) is cultivated (mainly subsistence farming) with small landholdings averaging 0.05 ha (Usman, 2018). GB has four cropping systems: (i) double cropping (< 1900 m) suitable for cultivating wheat, maize, fruits, and vegetables, (ii) marginal double cropping (1900 – 2300 m) for barley, wheat, buckwheat, fruit trees, nuts, and vegetables, (iii) single cropping (2300 – 3000 m) for potato, peas, wheat, barley, faba bean, and fruit trees, and (iv) alpine pastures (> 4000 m) with limited cultivation possibilities of fruit trees as mostly covered with snow and very low temperature including frost throughout the year (Anwar et al., 2019). GB also has ample glacier water channelled by traditional karez irrigation systems. Although, farming possibilities are topographically limited, some production factors such as high sunlight, low air humidity, ample water for irrigation are favourable for horticultural activities. Hence, cropping system with tree integration play vital roles in these areas often along with livestock by offering a range of ecosystem services such as provisioning of fuel wood, timber, food, and traditional medicine as a component of health care and hence income generation (Rasul and Hussain, 2015). Gilgit-Baltistan is an important PGR hotspot for many tree, shrub, herb, and forb species and their diversity is important for local communities. (Fahad and Bano, 2012; Khan et al., 2015; Salim et al., 2019). Some PGR species play an important role against the effect of natural crises such as droughts, floods, death of a livestock, personal illness, and during lean seasons by providing food and additional income. Local PGR related products may also act as a safety net when landslides cut off infrastructure between different valleys leaving people with no money and food for several weeks. For example, the Attabad landslide on 4th January 2010 formed a natural lake of about 14 km and blocked the road access between areas of both sides for five months.

Figure 1.1 Map of Pakistan showing the study region Gilgit-Baltistan, and its major vegetation cover, districts and ethno-linguistic groups as in (Salim et al., 2019)

1.3.2 Neglected research region and threats to local PGR GB has a long history of trade and migration from various Asian regions and is an important trade junction as it connects the Indian subcontinent with Central and West Asia. Until today the ancient exchange of plant material into this region remains important (Salim et al., 2019) making the area a significant hub for dispersal of germplasm whose many pathways are still not fully understood. Despite of historical significance, PGR research in GB is only marginal and conducted with a strong emphasis on medicinal species. Particularly, perennial plant species such as Elaeagnus angustifolia, Berberis brandisiana, Capparis spinosa, Datura stramonium,

Hippophae rhamnoides, Salix acmophylla, Thymus serphyllum were not studied in detail (Salim et al., 2019; Aziz et al., 2020). Moreover, GB being a politically disputed region with comparatively poor infrastructure, is considered rather remote. Thus, many even well-studied species are still unexplored in this region. GB experienced strong population growth and land-use transformation which affected a wide range of ecosystems and wild as well as cultivated species (Fahad and Bano, 2012; Khan et al., 2016). During the last decades with the opening of the KKH and agricultural intensification, pressures on local PGR increased (Khan, 2014). Due to the region’s limited amount of arable land, intensification effects on PGR such as logging, mono-cropping activities, and replacement of traditional cultivars are more prevalent than in other parts of the country (Khan, 2014; Adhikari et al., 2017). Traditional farming in GB is considered chemical-free (no application of any pesticides and fertilizer) which makes it an organic farming system by default. Farmers’ communities of the region favour this type of cropping because it allows their products to be valued on regional and national, but also international markets. The Hunza Fruit Processing enterprise in Karimabad is a pioneer in marketing of organic products since 1986 (Usman, 2018). Some of the producers of GB are formally organically certified providing further trainings to the farmers with the help of the country’s agricultural department and local NGOs (Poerting, 2015). However, chemical fertilizer and pesticide companies also get established in the region and are lobbying against organic farming strategies on a larger scale. Similarly, some seed companies introduce new seeds to the farmers, while international NGOs promote high-yielding modern fruit tree cultivars. Therefore, local NGOs such as AKRSP are facing challenges to promote traditional farming and to maintain local and partly yet unexplored agrobiodiversity. In addition, the tourism sector is likely to affect the local PGR in GB in several ways. While the growing number of national and international visitors offers better income opportunities for local people, the increase of touristic infrastructure such as the construction of resorts, hotels, and connecting roads may negatively affect GB’s biodiversity (Saqib et al., 2019). Another threat to local PGR is the premature harvesting and over-exploitation of wild plants (including illegal harvesting of medicinal and aromatic plants) to maximize the profit per harvest (Bano et al., 2014; Aziz et al., 2020). In the future also increases in livestock population may exert pressure on PGR even if in 2008, the stocking rate was with 2.7 ha of rangeland per animal (0.86 million

animals for 2.34 million ha) only about 85% of the threshold level established by FAO (ICIMOD, 2013). The above discussed factors all affect agrobiodiversity and may lead to an irreversible loss of indigenous PGR. Hence, there is an urgent need to assess the status quo of the current agrobiodiversity as an initial step to conserve unique plant resources in the region.

1.4 State of the art of assessing agrobiodiversity Agrobiodiversity has been defined as the genetic and phenotypic variability present in cultivated plants and livestock including their wild relatives and cultivars evolving under natural and anthropogenic conditions (Thrupp, 1997). There are two main scales of assessing biodiversity that is within- and between-species diversity. The present work focuses only on within P/PGR genetic diversity, which can be measured at different scales: inter-varietal, morphological, and genetic. Although there is a vast range of approaches and methodologies, one must restrict to those that are applicable under field conditions, financially suitable, and timely feasible. Inter-varietal diversity among crops can be estimated using demographic information such as number and percentage of crop accessions that occur at different temporal or spatial scales (Meng et al., 1998). This approach presumes the existence of variation in the accession names and that these are related to genetic differences. This approach can be used either for accessions that are conserved in vitro / ex situ or managed in vivo / in situ (Le Clerc et al., 2006; Jarvis et al., 2008). On-farm assessments are conducted by doing interviews using questionnaires about a crop (Teklu and Hammer, 2006; Jarvis et al., 2008). However, this approach does not address the diversity at the gene or intra-varietal level, whereas trends such as losses of genetic diversity can be observed, and germplasm collection data bases can be established through this approach (Hammer et al., 1996; Cebolla-Cornejo et al., 2012). Moreover, using this approach allows to collect information about farmers’ knowledge and perceptions about the crop and its on-farm management practices (Jarvis et al., 2011). Morphological diversity can also be estimated using physical traits which are visible and measurable under field conditions such as fruit colour, height or growth habit (Kongkiatngam et al., 1995). This approach helps to identify important features and statuses of crops which could be further used as a reference to improve PGR an

related breeding programs (Fjellheim et al., 2007). For the morphological assessment of the tree crops, dendrometric characters (height, girth, and canopy area) are the most important traits as they may be reflect prevailing natural conditions and applied arboricultural practices such as pruning, watering, nutrient supply, and age of cultivation (Wiehle, 2014; Laakili et al., 2016). For fruits, qualitative (such as colour, shape, and taste) and quantitative (such as length, width, and diameter) traits are commonly used in agrobiodiversity studies. However, these traits are environmentally influenced and genetically controlled, thus require repeated sampling and characterization at certain seasons and space throughout the sampling area (Beer et al., 1993; Boller and Greene, 2010). However, they allow for comparative studies, are important to identify the superior PGR germplasm, and provide a basis for PGR conservation. Biochemical and molecular approaches are used to identify and quantify less obvious parameters such as valuable secondary plant metabolites such as ascorbic acid, phenols, and carotenoids and related specific alleles. Biochemical analyses are technically demanding and less applicable under field conditions. Also, secondary plant metabolites are strongly governed by environmental factors, while allele-based genetic variation through molecular markers can be estimated by excluding the direct effects of environmental variables. The use of molecular markers has hence important advantages over the characterisation of biochemical and morphological parameters. There are several marker systems available to investigate a wide range of crops species such as allozymes, RFLPs, AFLPs, RAPDs, SSRs, EST-SSR, and SNPs (Freeland et al., 2011). The applications of these marker systems include the quantification of genetic diversity within and among populations, partitioning of genetic structure, genome mapping, relatedness based on genetic distance between individuals and populations, and identification of alleles, genes or genotypes important for specific breeding purposes (Lowe et al., 2004; Agarwal et al., 2008; Freeland et al., 2011). While the use of molecular markers is helpful in identifying intra-specific and intra-varietal variability and useful to compare among studies using the same set of markers, they are still costly and time intensive. The attempt to combine results about PGR agrobiodiversity with socio- economic data – as performed in the present work – may help to identify the weaknesses and strengths in our current understanding of biodiversity and local

knowledge in the target region. This may further help to study, develop, and maintain site-specific conservation strategies for P/PGR.

1.5 Investigated local plant species We suspect that many P/PGR in GB are unrecognized, and their survival is threatened because of the reasons discussed above. We anticipated that species- based approaches should be adopted in which multidisciplinary data about a single crop are collected and combined with data about other species of similar ecologies and use. This approach will focus on the people involved in harvesting of the target species and their post-harvest handling practices. The social-ecological approach will allow to prioritize NUS species taking into account the views of the local population, research institutes, and government institutions, which would help to improve their status. Following the classification criteria of NUS, we choose to study two species of which one is underutilized and the other one is neglected. We then focussed on a detailed morphological and genetic characterization of the available germplasm to assess the current diversity status, the on-going process of domestication, potential threats to the diversity, use and marketing of the crops, as well as current and potential uses in the region.

1.5.1 Sea buckthorn (Hippophae rhamnoides L.) Hippophae rhamnoides L. is a diploid species (2n = 24) belonging to the Elaeagnaceae family. Most species belonging to this family inhabit dry habitats of the northern hemisphere, express xerophytic characters, and are tolerant to high soil salinity (Bartish and Swenson, 2010). The center of origin of Hippophae rhamnoides is supposedly the Qinghai–Tibet Plateau (as for many other temperate plants) from where it spread to other Eurasian and Nearctic regions (Figure 1.2; Jia et al., 2012). Sea buckthorn is dioecious in nature and wind pollinated. It can proliferate clonally through suckers and grows as a shrub or tree of 1 – 9 m height. The species requires 3 - 4 years to start fruiting at an annual rainfall of 250 to 800 mm (Bernáth and Földesi, 1992). The sea buckthorn berry is known as a “superfood” mainly because of secondary metabolites such as the vitamin C, B and K complexes (Bernáth and Földesi, 1992). These constituents have ailment properties against scurvy diseases, help in child development, protect the skin, relieve pain, synthesize and epithelize

collagen, and possess anti-ulcer, anti-cancer, and anti-atherogenic properties. As such they are also used in traditional Chinese medicine (Wani et al., 2016). The area under sea buckthorn worldwide (wild and natural stands) is about 3 million ha out of which 90% are found in China, Mongolia, Russia, Europe, and Canada (Stobdan and Phunchok, 2017). Sea buckthorn is considered a NUS species although comparatively many studies are available. GB belongs to the central area of sea buckthorn distribution, but in-depth research is limited, and indigenous people are only poorly aware of this crop. In 2008, the total estimated berry harvest in GB amounted to 3600 tons (Khan, F. et al., 2019) equalling only and estimated 5% of its potential. It is presently sold on local markets, but dried berries are also exported to Europe. Until recently, the management practices of sea buckthorn stands, and processing of its products were largely unknown and exploitation and marketing were considered to be largely unsustainable (Table 1.1).

Figure 1.2 a) Dispersal of sea buckthorn (Hippophae rhamnoides) from Qinghai‐Tibetan Plateau (QTP) based on the cpDNA data (b) ITS data (c) Colour coding follows Figs 1 and 2. Five major distributions were defined as Qinghai-Tibet Plateau (Q), northern China (N), Mongolian Plateau (M), central Asia (C) and Europe⁄Asia Minor (E). Sequences of the same subspecies or distribution were compressed. Ancestral areas with probability < 0.05 were represented by asterisks. Source: Jia et al., 2012. Reprinted with the permission of John Wiley and Sons under License No. 4823241408000 accessed on 6 May 2020 1.5.2 Apple (Malus × domestica Borkh.) Malus × domestica Borkh. is mostly diploid, occasionally triploid and tetraploid species (n = 17) and belongs to the Rosaceae family, subfamily Maloideae. The Malus

genus comprises approx. 40 widely occurring, but less cultivated species occurring across the world’s temperate regions (Folta and Gardiner, 2009). The origin of apples is believed to be in the Tian Shan Mountains from where it dispersed to Eurasia via the Silk Route followed by several hybridization events (Figure 1.3; Cornille et al., 2014). Its seeds are dispersed through birds and mammals (especially bears and humans). Apple is a self-incompatible plant which favours outcrossing and pollination through insects. It is a woody long-lived tree and mostly clonally propagated through grafting.

Figure 1.3 Evolutionary history of the cultivated apple. (A) This history was revealed by recent population studies using different types of molecular markers for evolutionary inferences. (1) Origin in the Tian Shan Mountains from Malus sieversii, followed by (2) dispersal from Asia to Europe along the Silk Route, facilitating hybridization and introgression from the Caucasian and European crabapples. Arrow thickness is proportional to the genetic contribution of various wild species to the genetic makeup of Malus domestica. (B) Genealogical relationships between wild and cultivated apples. Approximate dates of the domestication and hybridization events between wild and cultivated species are detailed in the legend. Abbreviations: BACC, Malus baccata; DOM, M. domestica; OR, Malus orientalis; SIEV, M. sieversii; SYL, Malus sylvestris; ya, years ago. Source: Cornille et al., 2014 Reprinted with permission from Elsevier under License No. 4823541004240 accessed on 7 May 2020 Apple extracts are also used for the treatment of several diseases such as cancer (colon, prostate, and lung cancer), arthritis, inflammation, and dementia (Biedrzycka and Amarowicz, 2008). In 2018, world production of apple fruits was about 86,142,197 t, whereby that of Pakistan was only 545,875 t (FAOSTAT, 2018). Although apple in GB is intensively studied and among the main fruit crops (370,117 t; Anonymous, 2014), the locally available varieties are underused and not further

improved. Moreover, local apple germplasm lacks scientific characterisation and potential marketable traits such as sweetness, low bitterness and sourness, large size, and homogenous colour. Therefore, the status of available local germplasm in GB merits exploration as orchards are increasingly replaced by modern cultivars due to several factors (Table 1.1.).

Table 1.1. Summary of botany, ecology, status and problems of sea buckthorn (Hippophae rhamnoides L.) and apple (Malus × domestica Borkh.) under study. Attributes Sea buckthorn Apple Botany and ecology Family Elaeagnaceae Rosaceae Genus Hippophae Malus Species rhamnoides domestica Min. and Max. temperature −43 to +40 °C -44 to 32 °C Pollen dispersal Wind Insects Sex compatibility Dioecious Self-incompatible Fruit type Single seeded berries Pipifruit Seed dispersal Birds, mammals (incl. humans) Birds, mammals (incl. humans) Importance World production Unknown 86,142,197 t Pakistan production 3600 t (2008) 545,875 t Status in Gilgit-Baltistan Production 3600 t (2008) 370,117 t (2014) Cultivation status Wild Semi- to fully domesticated Selling of dried berries, animal Selling, eating, animal feed, Uses forage, fuel wood, small scaled value addition (jam, juice, chip) value addition (jam, juice, oil) Per kg price (US$) Dried 1.8 1.0 (2018) Fresh 1.0 0.5 Very limited to local market for Substantial local market value added products while Market value dried berries are exported to Europe No known varieties, only Known by name but not/poorly Local varieties/Landraces naturally grown mainly for fuel studied wood • Unmanaged stands/farms, • Abandonment of farms, • Underutilized, • Traditional varieties are • Extensively used as fuel Threats undervalued or neglected, wood • Replacing of local with • Infrastructure (roads, commercial varieties resorts, hotels) development

1.6 Research hypotheses and objectives The characterization of both species requires data on the available germplasm in GB. To this end, the following hypotheses and objectives were developed to

describe the status quo of the germplasm and to propose potential conservation and management strategies: 1. Human induced domestication in natural sea buckthorn populations is higher in stands near to settlements. → This requires an analysis of the effects of domestication on morphological and genetic traits of sea buckthorn (by comparing wild and supposedly domesticated stands). 2. Varietal richness and diversity in apple accessions decline from remote to main road areas. → This calls for an assessment of dendrometry, fruit morphometry, richness and genetic variation among accessions found in different villages of dead-end valleys. 3. Underutilization of apple and sea buckthorn resources results from local peoples’ unawareness regarding their management and potential uses. → This necessitates an appraisal of the current situation and management related to both sea buckthorn and apple in order to adopt site- and species-specific conservation strategies.

1.7 Outline of the thesis The present study is divided into five chapters (Figure 1.4). Chapter 1 (the current chapter) introduces the concept of plant genetic resources including neglected and underutilized species. Furthermore, insights about the status, management, and potential threats of these resources globally and of the two studied species in Gilgit- Baltistan, Pakistan are given. Chapter 2 elaborates on the morphological and genetic diversity of sea buckthorn (Hippophae rhamnoides L.) among eight different locations from Gilgit-Baltistan, Pakistan. Chapter 3 identifies the reasons of sea buckthorn underutilization in the region by discussing its management, collection, drying, marketing, and supply chain. Chapter 4 describes the varietal richness and diversity of local apples (Malus × domestica Borkh.) in GB in combination with phenotypic and genotypic variation among varieties. Chapter 5 gives a general overview of the study, critically evaluates the collected methods and data, and provides conclusions and recommendations based on the described results.

Figure 1.4. Overview of the thesis research on biodiversity of sea buckthorn and apple in Gilgit-Baltistan, Pakistan.

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Chapter 2 – Morphological and genetic diversity of sea buckthorn in

the Karakoram Mountains of northern Pakistan

The contents of this chapter have been published in Diversity 2018,10(3), 76: https://doi.org/10.3390/d10030076

Morphological and Genetic Diversity of Sea Buckthorn (Hippophae rhamnoides L.) in the Karakoram Mountains of Northern Pakistan Muhammad Arslan Nawaz 1, Konstantin V. Krutovsky 2,3,4,5, Markus Mueller 2, Oliver Gailing 2, Asif Ali Khan 6, Andreas Buerkert 1 and Martin Wiehle 1,7,

1 Organic Plant Production and Agroecosystems Research in the Tropics and Subtropics, University of Kassel, Steinstrasse 19, D-37213 Witzenhausen, Germany; [email protected]; [email protected] 2 Department of Forest Genetics and Forest Tree Breeding, University of Göttingen, Büsgenweg 2, D-37077 Göttingen, Germany; [email protected] goettingen.de; [email protected] 3 Laboratory of Population Genetics, Vavilov Institute of General Genetics, Russian Academy of Sciences, Moscow 119991, Russian Federation; [email protected] 4 Laboratory of Forest Genomics, Genome Research and Education Center, Siberian Federal University, Krasnoyarsk 660036, Russian Federation 5 Department of Ecosystem Science and Management, Texas A&M University, College Station, TX 77843-2138, USA 6 Department of Plant Breeding and Genetics, Muhammad Nawaz Shareef University of Agriculture, 66000 Multan, Pakistan; [email protected] 7 Tropenzentrum and International Center for Development and Decent Work (ICDD), University of Kassel, Steinstrasse 19, D-37213 Witzenhausen, Germany

2.1 Abstract Sea buckthorn (Hippophae rhamnoides L.) is a dioecious, wind-pollinated shrub growing in Eurasia including the Karakoram Mountains of Pakistan (Gilgit-Baltistan territory). Contrary to the situation in other countries, in Pakistan this species is heavily underutilized. Moreover, a striking diversity of berry colours and shapes in Pakistan raises the question: which varieties might be more suitable for different national and international markets? Therefore, both morphological and genetic diversity of sea buckthorn were studied to characterize and evaluate the present variability, including hypothetically ongoing domestication processes. Overall, 300 sea buckthorn individuals were sampled from eight different populations and classified as wild and supposedly domesticated stands. Dendrometric, fruit and leaf morphometric traits

were recorded. Twelve EST-SSR (expressed sequence tags-simple sequence repeats) markers were used for genotyping. Significant differences in morphological traits were found across populations and between wild and village stands. A significant correlation was found between leaf area and altitude. Twenty-two colour shades of berries and 20 dorsal and 15 ventral colour shades of leaves were distinguished. Mean genetic diversity was comparatively high (He = 0.699). In total, three distinct genetic clusters were observed that corresponded to the populations´ geographic locations. Considering high allelic richness and genetic diversity, the Gilgit-Baltistan territory seems to be a promising source for selection of improved germplasm in sea buckthorn.

Keywords: biodiversity; domestication; EST-SSR markers; gene flow; Gilgit- Baltistan; RHS colour charts

2.2 Introduction Sea buckthorn (Hippophae rhamnoides L.; 2n = 24; family Elaeagnaceae) is a shrubby species of native Eurasian plant communities ranging within 27°– 69° N latitude (from Russia to Pakistan) and 7° W–122° E longitude (from Spain to Mongolia) with a center of origin on the Qinghai–Tibet Plateau. It is a dioecious, wind-pollinated, 1–9 m tall shrub or tree capable of propagating clonally. As a pioneer species it spreads on marginal soils across a vast range of dry temperate and cold desert soils (Rousi, 1971; Zeb, 2004) and requires minimum annual rainfall of 250 mm for proper growth. Sea buckthorn possesses a specialized root system that can fix N2 through forming Frankia-actinorhizal root nodules (Kato et al., 2007) and is known to improve the soil structure, which makes it an ideal species for land reclamation and wildlife habitat improvement (Enescu, 2014). The flowering of male and female plants takes place between mid of April and May before the leaves appear. It requires 2–3 days for dehiscence of pollen grains, which are viable up to 10 days after anthesis, and formation of pollen tubes happens about 72 h after pollination (Ali et al., 2015; Mangla et al., 2015). The stigma remains most receptive for three days post-anthesis. The number of fruits produced during the season depends on the growing conditions of the previous year when flower buds are formed (Mangla and Tandon, 2014). Sea buckthorn requires 3–4 years to start fruiting depending upon the propagation method (seed or cuttings) and produces yellow, orange or red berries (6–9 mm in diameter, Figure 2.1) containing a single seed (Shah

et al., 2007). Berry colour seems to be correlated with the amount of tannins (proanthocyanins; Yang et al., 2016). The global sea buckthorn production area is unknown and country-wise data lack a standardized assessment: China´s natural production range covers more than 10,000 km2 (Durst et al., 1994), Mongolia´s natural range is 29,000 km² (data only available for Uvs province; Lecoent et al., 2010), former USSR covers 472 km2 (Rongsen, 1992), while in India the production areas of naturally grown sea buckthorn are available Leh (115 km2; Stobdan et al., 2008) and Uttarakhand (38 km2; Yadav et al., 2016). There is a high potential of different kinds of products from sea buckthorn berries including cosmetics (mainly in Russia and China) and food (mainly in Europe). According to an assessment of the sea buckthorn business in Europe, Russia, New Independent States countries and China in the year 2005, the value of by-products from berries and leaves accounts approximately for 42 million Euros (Waehling, 2007). Pakistan includes many thousands of hectares of sea buckthorn growing naturally in the Gilgit and Baltistan regions, of which only about 20% are utilized (Shah et al., 2007) to produce a variety of products. Hence, the species has a great untapped economic and social potential with important plant genetic resources whose use may add to rural livelihoods. The species has several unique medicinal properties, such as high concentrations of vitamins, tannins, triterpenoids, phospholipids, caumarin, catechins, leucoenthocyans, flavanols, alkaloids, serotonin, and unsaturated fatty acids (Fan et al., 2007; Hussain et al., 2007; Li et al., 2007) providing supplements for a healthy food and a variety of ingredients for medical use (Ansari, 2003) against obesity, diabetes, cardiovascular disease, cancer, ulcer, inflammation, immune system disease, burn wounds, and radiation damage (Saggu et al., 2007; Upadhyay et al., 2009). Wild sea buckthorn germplasm, however, varies widely with respect to morphometrical, visual, nutritional, and genetic properties (Shah et al., 2007; Yadav et al., 2006; Yang et al., 2008), which has implications for the quality of products. This variation, especially for leaf and fruit morphometry and colour is likely controlled by a combination of factors rather than by a single factor. First, the wide distribution of sea buckthorn throughout Asia, including the Gilgit and Baltistan regions (Figure 2.2) implies the species’ occurrence in many climatic zones (Rongsen, 1992; Yang and Kallio, 2001). Second, altitudinal (Chen et al., 2008) and environmental stresses such

as water availability (Yang et al., 2005; Guo et al., 2007) and soil nutrient status (Sharma et al., 2014) affect sea buckthorn traits and sexual propagation (Li et al., 2007). Third, geographical physical barriers (mountain ranges, glaciers, rivers, etc.) may cause genetic differentiation by preventing gene flow potentially resulting in allopatric divergence as it was observed for sea buckthorn in the Himalayan Mountains (Jia et al., 2012; Qiong et al., 2017) and for other species (Bauert et al., 1998; Su et al., 2003). Fourth, the genetic setup itself may play a role in phenotypic variation, although to our knowledge no study has so far analyzed this association in sea buckthorn. Fifth, human-induced plant material exchange, overexploitation, and domestication could have negative consequences on population structures leading to genetic bottleneck effects (Miller and Schaal, 2006; Dawson et al., 2008; Ekué et al., 2011). For northern Pakistan, the identification and characterization of superior ecotypes and populations with respect to yield, nutritional characteristics, time of ripening, and genetic constitution are important to allow for the collection of berries of higher nutritional quality and other market demanded properties, such as fruit size and colour. There are several genetic studies of sea buckthorn based on RAPD (random- amplified polymorphic DNA; Bartish et al., 1999; Bartish et al., 2000; Ruan et al., 2004; Sheng et al., 2006; Singh et al., 2006; Ercişli et al., 2008), AFLP (amplified fragment length polymorphism; Ruan, 2006; Shah et al., 2009), SSRs (simple sequence repeats, microsatellite; Wang et al., 2008), ISSRs (inter simple sequence repeats; Chen et al., 2008; Li et al., 2009) and gene-based EST-SSR (expressed sequence tags-simple sequence repeats; Jain et al., 2010; Jain et al., 2014) markers. The EST- SSR markers are more likely to reflect adaptive genetic variation than other markers since they are linked with expressed (functional) genes and usually found in 3' untranslated regions (3'-UTRs) of expressed sequence tag (EST) sequences. Therefore, this study aims at estimating the morphological and genetic variability by measuring morphological traits and genotyping EST-SSR markers, respectively. The specific objectives of the study were to (1) compare the dendrometry, fruit traits and genetic diversity patterns of sea buckthorn among different populations, (2) analyze the influence of domestication processes on genetic and morphological traits by comparing wild and supposedly domesticated village stands, and (3) evaluate the genetic variation and differentiation found in the study area.

Figure 2.1 A sample of fruits from different sea buckthorn individuals collected in the Gilgit and Baltistan regions, Pakistan in 2016 representing diversity in size, shape and colour.

2.3 Materials and Methods 2.3.1 Plant Material and Sampling Area The field study was carried out in September–November 2016 in the Karakoram Mountains of northern Pakistan. To quantify the morphological and molecular diversity, eight populations at different altitudes in two regions, Gilgit (Shimshal, Passu, Gulmit) and Baltistan (Thesal, Chandopi, Chutran, Bisil and Arando) (Figure 2.2), were selected, and 300 individual plants were sampled in total (Table 2.1). To test for the effects of human selection on sea buckthorn, populations were subdivided into “village” (within the residential area) and “wild” stands (a minimum distance of 1 km from the nearest house), forming corresponding stand pairs. Per stand, ten individuals were randomly sampled based on a nearest neighbor criterion with a minimum distance of 100 m between individuals to avoid sampling of clonal plants (Muchugi et al., 2008). Depending on the size of villages, occasionally more than one stand pair was sampled, resulting in more than 20 individuals per population. The exact location and altitude (meter above sea level, m.a.s.l.) of all individuals were determined with a hand-held GPS device (Garmin-eTrex 30, horizontal accuracy ± 2 m, GARMIN® Ltd., Southampton, U.K.).

Figure 2.2 Map of the studied populations in the Gilgit and Baltistan regions, Pakistan used for sea buckthorn collection in 2016 (source: Landsat picture (2015), modified, Image courtesy of the U.S. Geological Survey (above); Pakistan and administrative areas, modified, diva-gis.org, accessed 30 July 2018 (below)).

Table 2.1 Average geographic coordinates of the eight sea buckthorn populations studied in the Gilgit and Baltistan regions, Pakistan. Elevation, Region Population No. of individuals Longitude E Latitude N m.a.s.l. Gulmit 60 36.4049805 74.8734 2525 Gilgit Passu 40 36.4558832 74.8997 2516 Shimshal 60 36.4412537 75.3008 3112 Thesal 20 35.4697578 75.6654 2275 Chandopi 40 35.5428859 75.5711 2330 Baltistan Chutran 40 35.7268528 75.4046 2435 Bisil 20 35.8568179 75.4156 2655 Arando 20 35.8695884 75.3677 2700

Total 300 2.3.2 Dendrometric Traits Height (cm) of shrubs was measured with the help of a measuring pole, whereby the height of the tree was determined by intercept theorems (Arzai and Aliyu, 2010). The stem girth (cm) at the shrub or tree base was determined twice (perpendicular axes) with a digital Vernier caliper. Subsequently, the geometric mean was transformed to the diameter. Plant canopy area (m2) was calculated from the canopy diameters measured in the N-S and W-E directions.

2.3.3 Leaf and Fruit Morphometry Traits Ten leaves per individual were randomly collected for length measurements including the petiole and width (both in mm) at the widest point with the help of a digital Vernier caliper. Leaf area (mm2) was calculated by assuming an oval-oblong shape of a leaf. To assess differences in leaf shape, the length to width ratio was calculated. Afterward, leaves were stored, and air dried in filter bags for further genetic analysis (see below). For each individual, around 20 grams of berries were collected randomly. A digital balance (accuracy: ±0.01 g, Tomopol p250) was used to measure the bulked weight (g) of 20 berries. Out of this, 10 randomly chosen berries were measured with the Vernier caliper to determine length and width (both in mm) at the widest point of each fruit. Fruit volume (mm3) was calculated by assuming an ellipsoid shape of the berry. As for the leaves, fruit length to width ratio was calculated. Afterwards, fruits were air dried in the shade until a constant weight was obtained. Based on weight differences moisture contents were calculated. Means and coefficient of variation (CV) were calculated for all morphometric traits to identify highly variable and therefore promising parameters for breeding and ecology of sea buckthorn.

2.3.4 Leaf and Fruit Colours The colour of leaves (dorsal and ventral part) and berries was determined using the Royal Horticultural Society (RHS) colour charts (sixth edition, 2015, RHS media, 80 Vincent-Square, London). The 920 RHS coded reference colours are a standard to identify plant tissue colours used by horticulturalists worldwide. The RHS colour code was decoded into the Red-Green-Blue (RGB) colours available at the RHS webpage

(http://rhscf.orgfree.com, accessed on 2nd February 2017) and used for visual presentation (Figures 2.3 and 2.4).

Figure 2.3 Fruit colour shades (Royal Horticultural Society (RHS) colours) observed in eight sea buckthorn populations and their percentage per population studied in the Gilgit and Baltistan regions, Pakistan. Different letters (a–d) above bars indicate significant differences among populations; * indicates unique colours.

Figure 2.4 Ventral (A) and dorsal (B) leaf colour shades (RHS colours) observed in eight sea buckthorn populations and their percentage per population studied in the Gilgit and Baltistan regions, Pakistan. Different letters (a–d) above bars indicate significant differences among populations; * indicates unique colours.

2.3.5 DNA Isolation and EST-SSR Analysis Total genomic DNA was extracted from each of the 300 leaf samples using the DNeasy™ 96 Plant Kit (Qiagen GmbH, Hilden, Germany). Twelve already established

and highly polymorphic EST-based SSR markers–six USMM (1, 3, 7, 16, 24, and 25, respectively; Jain et al., 2010) and six HrMS (003, 004, 010, 012, 014, and 018; respectively, Jain et al., 2014) markers were screened and used in this study. Forward primers of these markers were labeled with fluorescent dyes to design four different multiplexes depending upon the PCR (polymerase chain reaction) product sizes. The PCR amplifications were performed in a total volume of 15 μL containing 2 μL of genomic DNA (about 10 ng), 1X reaction buffer (0.8 M Tris-HCl pH 9.0, 0.2 M

(NH4)2SO4, 0.2% w/v Tween-20; Solis BioDyne, Tartu, Estonia), 2.5 mM MgCl2, 0.2 mM of each dNTP, 0.3 μM of each forward and reverse primer and 1 unit of Taq DNA polymerase (HOT FIREPol® DNA Polymerase, Solis BioDyne, Tartu, Estonia). The amplification protocol was as follows: an initial denaturation step at 95 °C for 15 min, followed by 30 cycles consisting of a denaturing step at 94 °C for 1 min, an annealing step at 55 °C for 30 s and an extension step at 72 °C for 1 min. After 30 cycles, a final extension step at 72 °C for 20 min was included. Reproducibility was checked by repeating positive and negative controls in all reaction plates. The PCR fragments were separated and sized on an ABI 3130xl Genetic Analyzer (Applied Biosystems Inc., Foster City, CA, USA). The GS 500 ROX (Applied Biosystems Inc., Foster City, USA) was used as an internal size standard. The genotyping was done using the GeneMapper 4.1® software (Applied Biosystems Inc., Foster City, CA, USA).

2.3.6 Data Analysis All metric morphological data were analyzed with the R-software (version 3.3.3, R core team, 2017, Vienna, Austria) using the multcomp package (Hothorn et al., 2008). Data were checked for normal distribution of residuals and homogeneity of variances followed by t-tests or analyses of variance (ANOVA). The Tukey-Kramer post hoc test was used to identify significant differences among subgroups, which is considered to be the most suitable test for unbalanced designs according to Herberich et al., (2010). The total mean of populations and stands (village and wild) was calculated to indicate local variation. For colour variation (nominal data) of leaves and fruits, Fisher’s exact Chi (χ2)-square test and post hoc tests (pairwise nominal independence) were performed using the “rcompanion” package in R (Mangiafico, 2017). Additionally, Pearson correlations were performed to estimate the significance of the correlation between altitude and leaf area, and between altitude and fruit colour shade.

MICRO-CHECKER (Van Oosterhout et al., 2004) was used to test and correct for potential genotyping errors due to stuttering, large-allele dropout, and null-alleles.

Genetic variation parameters such as the number of alleles per locus (Na), the number of private alleles, allelic richness, percentage of polymorphic loci, expected (He) and observed (Ho) heterozygosities were determined for each population. In addition, deviations from Hardy-Weinberg equilibrium (HWE) were checked by χ2-tests for each locus per population. All parameters were calculated using the GenAlEx 6.5 software (Peakall and Smouse, 2012) except for allelic richness which was calculated to account for differences in sample size with the HP-Rare program 1.0 (Kalinowski, 2005) considering a sample size of 40 individuals in each sample. Isolation-by-distance (IBD) was tested with a Mantel test using pairwise geographic distance and standardized genetic differentiation G’ST (Hedrick, 2005) with 1000 random permutations in GenAlEx 6.5. To analyze differentiation between populations and characterize population genetic structure, an analysis of molecular variance (AMOVA) was applied with 999 permutations. F-statistics (FST, FIS, and FIT; range: 0–1; null hypothesis: indices equal to zero) were calculated using the same software. FST indicates the extent of population differentiation. FIS and FIT are indices of fixation of an individual relative to its population and the total sample, respectively. Their positive values are indication of deficiency of the observed heterozygosity relative to the expected one, which could be a signature of inbreeding, population subdivision (Wahlund effect) or mis-genotyping heterozygotes as homozygotes due to null-alleles or large-allele dropout. In addition, Genepop 4.7 software was employed to calculate population-wise fixation indices (FIS) and their significance with 10,000 dememorizations, 100 batches and 5000 iterations per batch for the Markov chain parameters. The genetic clusters (K) were inferred using EST-SSRs and the Bayesian approach implemented in the STRUCTURE 2.3.4 software (Pritchard et al., 2000). The admixture model with correlated allele frequencies and a burn-in period of 100,000 Markov Chain Monte Carlo (MCMC) replicates were used. We tested from 1 to 12 possible clusters (K), using 10 iterations per each of them. The most likely number of K was determined according to the ΔK method implemented in the open- access software STRUCTURE-HARVESTER (Earl and Holdt, 2012) and considering K with the highest value of ΔK and the lowest value of mean posterior probability of

the data (LnP(D); Evanno et al., 2005). Microsoft excel was used for summation and graphical representation of the results obtained by STRUCTURE 2.3.4.

2.4 Results 2.4.1 Dendrometric Traits Average plant height ranged from 138 to 198 cm with individual minimum and maximum of 10 and 450 cm, respectively (Table 2.2). Average stem diameter ranged from 3.7 to 6.0 cm with individual minimum and maximum of 0.8 and 82.0 cm, respectively (Table 2.2). Canopy area averaged 2.5 m2 ranging from 0.1 to 15.0 m2 and had the highest CV (70%, Table 2.2). As a general tendency, plants in village stands were higher than plants in wild stands. This difference was the most pronounced and statistically significant in Thesal followed by Shimshal, Bisil, Arando, and Passu.

Table 2.2 Average morphological traits of sea buckthorn at the eight populations and their corresponding stands studied in the Gilgit and Baltistan regions, Pakistan.

Dendrometry Leaf Fruit Grouping Population/Stand Height, cm Stem Diameter, cm Canopy, m2 Area, mm2 Length to Width Ratio Volume, mm3 Length to Width Ratio 20-berry wt., g Moisture, % Gulmit 146 b 5.1 ab 2.4 ab 85 a 7.5 b 75 a 1.1 b 1.6 a 66 a Passu 138 ab 4.4 a 1.5 a 93 a 7.2 ab 85 a 1.1 b 1.8 a 66 ab Shimshal 174 c 4.9 b 2.1 ab 192 e 6.5 a 150 c 1.1 a 3.1 b 77 c Thesal 193 ac 4.5 ab 3.1 bc 98 ab 7.9 bc 123 bc 1.2 b 2.5 b 67 ab Populations Chandopi 198 bc 6.0 ab 3.5 c 131 bc 7.8 bc 135 bc 1.2 b 2.9 b 67 ab Chutran 156 b 4.6 ab 2.6 bc 129 bc 7.9 bc 120 b 1.2 b 2.6 b 69 ab Bisil 189 bc 4.1 ab 2.5 ac 186 de 8.8 c 129 bc 1.1 ab 2.9 b 70 ab Arando 151 bc 3.7 ab 2.6 ac 155 cd 8.6 c 141 bc 1.2 b 2.9 b 71 b p-value < 0.001 < 0.001 < 0.001 < 0.001 < 0.001 < 0.001 < 0.001 < 0.001 < 0.001 Wild 160 4.8 2.5 126 a 7.7 117 1.1 2.5 70 Stands Village 177 5.7 2.5 141 b 7.8 122 1.1 2.6 69 p-value 0.050 0.140 0.950 0.009 0.527 0.257 0.817 0.780 0.130 Wild 162 ab 6.2 ab 2.5 ac 84 a 7.3 ace 75 a 1.1 ac 1.7 a 68 ac Gulmit Village 131 a 3.9 a 2.3 ac 85 a 7.6 bcd 74 a 1.1 ac 1.5 a 64 a Wild 125 a 3.6 a 1.3 a 80 a 6.8 ac 91 ab 1.1 ac 1.9 ac 67 ac Passu Village 151 ad 5.2 ab 1.6 ab 106 ab 7.6 ad 80 a 1.2 ac 1.7 ab 66 ab Wild 128 a 3.6 a 1.6 ab 171 ef 6.4 a 153 e 1.2 ab 3.2 e 82 d Shimshal Village 221 b 6.2 b 2.5 ac 213 g 6.6 ab 148 ce 1.1 a 2.9 de 72 c Wild 155 ab 4.3 a 2.5 ac 92 ab 7.7 ad 104 acd 1.2 ac 2.3 ade 66 ac Thesal Village 231 bd 4.7 a 3.5 bc 105 ac 8.1 ad 141 de 1.2 ac 2.7 bce 68 ac Populations*stands Wild 210 bcd 7.5 ab 4.2 c 143 bcdf 8.3 cd 147 de 1.1 ac 3.2 e 70 bc Chandopi Village 185 ab 4.5 a 2.9 ac 120 abd 7.3 ad 124 bde 1.2 c 2.6 ce 64 ab Wild 174 ab 6.1 ab 2.9 ac 124 abd 7.6 ad 109 ad 1.1 ac 2.3 acd 65 ab Chutran Village 138 ac 3.1 a 2.3 ab 134 bce 8.1 cd 131 de 1.1 ac 2.8 de 73 c Wild 187 ab 4.1 a 2.5 ac 173 deg 8.6 cd 117 ade 1.1 ac 2.7 bce 69 ac Bisil Village 192 ab 4.0 a 2.5 ac 199 fg 9.1 d 141 de 1.1 ac 3.1 de 71 ac Wild 137 ab 3.4 a 2.5 ac 145 bcdf 8.9 de 142 de 1.2 bc 3.1 ce 71 ac Arando Village 165 ab 3.9 a 2.6 ac 166 cdeg 8.2 bcd 139 de 1.1 ac 2.8 bce 71 ac 36

p-value < 0.001 < 0.001 0.030 0.028 0.095 0.021 0.173 0.042 < 0.001 Grand mean 165 5.3 2.5 132 7.5 117 1.1 2.5 69 CV, % 45 62 70 46 20 39 12 41 11 Letters indicate the significance of similarities among sites (populations sharing the same letters are similar and vice versa). CV—coefficient of variation.

2.4.2 Leaf and Fruit Morphometry Traits Significant variation was found in the leaf traits between village and wild stands, for population*stand interactions and among populations (Table 2.2). Leaf area (mm2) was higher in village stands than in wild stands except for Chandopi, whereas mean values of populations (village and wild stands together) were the highest in Shimshal followed by Bisil, Arando, Chandopi, Chutran, Thesal, Passu and Gulmit (Table 2.2). A significant positive correlation (r = 0.493, p = < 0.001) was found between leaf area and altitude. The leaf length to width ratio indicates the narrowness or wideness of the leaf; the widest leaves were found in Bisil (8.8 cm) and the narrowest in Shimshal (6.5 cm; Table 2.2). Significant variation was also found in all fruit traits within population*stands and among populations, but not between wild and village stands (Table 2.2). Fruit volume was highest in Shimshal (150 mm3) and lowest in Gulmit (75 mm3; Table 2.2). The maximum and minimum weight of 20 berries was 6.28 and 1.08 g, respectively. Means of 20-berry-weight were lower in Passu and Gulmit, whereas they were higher in Shimshal. This trend was also reflected in moisture content, which was the highest in Shimshal (77%) and lowest in Passu and Gulmit (66% each). All leaf and fruit morphometric parameters showed the same trend of having significantly lower values in Passu and Gulmit as compared to the other populations. The CV was the highest for leaf area followed by weight of 20 berries, fruit volume, leaf length to width ratio, fruit length to width ratio and moisture percentage (Table 2.2).

2.4.3 Leaf and Fruit Colour Significant differences were observed for ventral and dorsal leaf colour and for fruit colour among populations (Table 2.3). The most common shades of fruit colours across all samples were strong orange (N25A, N25B, and N25C) and strong orange yellow (N25D and 17A), which were in 55% of the samples. Rare colours such as 17B, 23B, 28B, 30C, 33B, N34A, N34B, 44A, and 44B accounted for 4% and were more common in the Gilgit region (Figure 2.3). Fifteen RHS ventral leaf colour shades with seven rare colours and twenty RHS dorsal leaf colour shades with five rare colours were observed in all populations (Figure 2.4). There were more dark colour shades observed in the ventral than dorsal leaf part (Figure 2.4). Across-region colour richness was significantly higher in Gilgit than in Baltistan, while within populations differences were less significant. A higher frequency of dark shades was observed 38

with increasing altitude (r = 0.388 and p = < 0.001; correlation analysis was based on field observations, data not shown).

Table 2.3 Fischer´s exact χ2-square test results of leaf and fruit colours of sea buckthorn across all populations in the Gilgit and Baltistan regions, Pakistan. Parameter Dorsal Leaf Colour Ventral Leaf Colour Fruit Colour No. of shades 20 15 22 Degree of freedom 7 7 7 χ2-value 236 142 241 p-value <0.001 0.002 <0.001

2.4.4 Genetic Diversity and Differentiation of Markers A total of 76 alleles were found in the eight populations for the 12 microsatellite loci (EST-SSRs) used in our study. The number of alleles per locus (Na) was 8 on average and ranged from 2 to 16 alleles per locus. Observed and expected heterozygosity, Ho and He, ranged from 0.340 to 0.867 and 0.334 to 0.843, respectively

(Table 2.4). The mean FIS was 0.038. A few loci had pronounced positive and significant values, such as HrMS004 and HrMS018 (Table 2.4). In general, loci across all populations did not deviate from HWE, except for HrMS004 (strong) and HrMS018 (slightly) (Table 2.5).

Table 2.4 Characteristics of 12 EST-SSR markers genotyped in sea buckthorn accessions of the Gilgit and Baltistan regions, northern Pakistan.

EST-SSR Primer Sequence (5'-3') Repeat Motif Size Range, bp Na He Ho FIs USMM1 GGCGAAACTTGACTTGTTGC (TAC)16 184–237 14 0.843 0.853 0.001 ACCGATCAATACCGTTCTGC USMM3 AAGGATGTGGTCGATCCAAG (TTC)10 155–169 7 0.704 0.729 −0.036 GTTTGCAGGCATTCCTTTGT USMM7 TCGCCGTCTGTTTCAGATAA (AG)18 170–191 9 0.786 0.867 −0.068 GCTGATCCAACGGTCTCATT USMM16 CCAACCAACCTCATCGTTTC (TC)14 157–169 7 0.744 0.769 −0.004 ATCGGAGGGATCGTTGAAAG USMM24 TAGCATTGCAGGCTCAGAGA (AG)11 229–240 7 0.740 0.809 −0.071 ATCCGTGGTTAAGGTTGCAC USMM25 CGAGGTCCGAGTAGGAAGA (AAG)10 214–237 9 0.676 0.653 0.036* CATTGGCCTTCAATCTCCTC HrMS003 GCTCTCATCCGATTTGATCC (TCA)6 335–470 16 0.828 0.784 0.056* GTCGCAGTCTTCTTGGGTTC HrMS004 GTTTGAGGTCGGTGCTGAGT (TC)8 260–304 9 0.739 0.492 0.331*** GGGTAACCCAACTCCTCCTT HrMS010 GGAAGCGTGAGGAAATGTC (TGG)5 213–216 2 0.334 0.340 −0.015 GAACAGACAGACCATTAGAGAAC HrMS012 CTCCATCTCAATCATCACTGC (CTT)11 133–169 7 0.722 0.721 0.034 * TTAGGGATCCGGATGAAG HrMS014 ATACCTAGCTCGGCAACAAG (TG)6(TA)8 227–239 4 0.444 0.454 −0.011 ACGACCCATGGCATAATAGTAC HrMS018 CAACATTGTTTCGTGCAG (ATG)5 189–225 13 0.823 0.678 0.207 *** ACTCACATAATCGATCTCAGC Mean 8 0.699 0.681 0.038

Na—number of alleles; He—expected heterozygosity; Ho—observed heterozygosity; FIS—fixation index; * p < 0.05, *** p < 0.001.

Table 2.5 Summary of χ2 tests for Hardy-Weinberg equilibrium per population and microsatellite locus in sea buckthorn accessions of the Gilgit and Baltistan regions, northern, Pakistan.

USMM1 USMM3 USMM7 USMM16 USMM24 USMM25 HrMS003 HrMS004 HrMS010 HrMS012 HrMS014 HrMS018 Population Df χ2 Df χ2 Df χ2 Df χ2 Df χ2 Df χ2 Df χ2 Df χ2 Df χ2 Df χ2 Df χ2 Df χ2 Gulmit 78 88 15 13 55 63 36 56 * 15 14 45 48 136 280 *** 45 174 *** 1 1 36 30 15 12 55 203 *** Passu 55 68 15 17 55 43 28 19 15 7 36 25 66 46 45 142 *** 1 0 15 14 6 1 45 60 Shimshal 91 82 21 26 45 51 15 14 21 24 36 37 15 10 36 96 *** 1 0 28 34 10 16 45 44 Thesal 78 82 28 10 28 15 10 6 21 23 21 26 105 121 15 14 1 1 28 18 3 1 66 85 Chandopi 91 66 28 27 36 19 15 8 21 14 55 178 *** 253 286 36 127 *** 1 0 21 14 6 8 120 143 Chutran 171 156 21 18 66 47 21 11 21 29 55 59 325 295 36 77 *** 1 1 36 54 * 6 22 ** 136 173 * Bisil 78 94 21 27 21 20 15 13 21 13 15 10 78 82 36 86 *** 1 0 21 23 3 6 66 73 Arando 55 52 10 11 6 1 15 19 21 13 15 8 66 74 45 148 *** 1 1 10 10 3 2 66 98 ** Df—degrees of freedom; χ2—Chi-square; Sig.—significance level; * p < 0.05, ** p < 0.01, *** p < 0.001.

2.4.5 Genetic Diversity and Differentiation of Populations All loci were polymorphic in each population. The mean number of private alleles found in each population was ranging from 2 to 11 with an average of 7 (Table 2.6). The highest level of genetic diversity was found in the Shimshal population

(He = 0.713) (Table 2.6), while the lowest genetic diversity (He = 0.684) was observed in the Chandopi population. The mean value of observed heterozygosity (Ho) was

0.683, whereas the mean expected heterozygosity (He) was 0.699. The comparison of genetic richness and diversity measures between stands did not reveal a clear difference between wild and village stands (Table 2.6 and A2.1); nevertheless, more than 50% private alleles were found in village stands. All obtained F values, except for Thesal, were significantly different from zero (Table 2.6). When exemplarily excluding

HrMS004 from the analysis, FIS values were considerably reduced and became non- significant.

Table 2.6 Genetic diversity and differentiation parameters of eight sea buckthorn populations studied in the Gilgit and Baltistan regions, Pakistan.

FIS without Region Population n Na PNa A He Ho FIS HrMS004 marker Gulmit 60 9.3 8 7.5 0.708 0.668 0.063 *** 0.038 Gilgit Passu 40 7.9 3 7.0 0.688 0.670 0.038 *** 0.006 Shimshal 60 7.8 10 6.3 0.713 0.731 −0.016 *** −0.044 ** Thesal 20 7.8 10 7.8 0.690 0.717 −0.013 −0.032 Chandopi 40 9.7 8 7.7 0.684 0.663 0.062 *** 0.034 Baltistan Chutran 40 10.8 11 8.6 0.711 0.653 0.097 *** 0.083 *** Bisil 20 7.7 4 7.7 0.707 0.675 0.071 *** 0.028 Arando 20 6.9 2 6.9 0.689 0.688 0.058 *** 0.009 Mean 8.5 7 7.4 0.699 0.683 0.045 0.016 Wild 150 11.3 27 14.7 0.739 0.695 0.063 ** 0.035 *** Stands Village 150 14.8 69 11.2 0.724 0.665 0.085 *** 0.060 n—number of individuals analyzed; Na—mean number of alleles; PNa—number of private alleles; A—allelic richness (corrected Na for sample size); He—expected heterozygosity; Ho—observed heterozygosity; FIS—fixation indices; ** p < 0.01, *** p < 0.001.

AMOVA results showed the highest genetic variation (89%) within individuals across populations, 4% of the total genetic variation was among individuals within populations, and only 7% was among populations, resulting in a low FST of 0.067 (Table 2.7). Similar estimates were found for other groupings ranging from 0.052 to

0.075. The FIS values were also low and ranged from 0.041 to 0.075, while FIT values were higher but still low ranging between 0.102 and 0.125 (Table 2.7). The Mantel test showed a significant positive correlation (r = 0.643, p = 0.001) between genetic and 42

geographical distances (Figure 2.5). It was also significant and strong for the Gilgit populations (r = 0.921, p < 0.001), but moderate for the Baltistan populations (r = 0.477, p < 0.001). Interestingly, a significant negative correlation was found between stands of Gilgit and Baltistan (r = −0.492, p < 0.001); the distance between these populations ranged from 60 to 135 km (Figure 2.5). Based on STRUCTURE, the total sample indicated a sub-structure with the most likely number of sub-populations (clusters, K) equaling three (Figure 2.6) (highest ΔK at K = 3) and log-likelihood probabilities are plateauing at K > 3.

Table 2.7 Analysis of molecular variance (AMOVA) based on microsatellite loci genotyped in eight populations of sea buckthorn in the Gilgit and Baltistan regions, Pakistan.

Grouping Source Df Sum of Estimated % FST FIS FIT squares variation Population Among populations 7 187 0.30 0.07 Among individuals within populations 292 1301 0.19 0.04 Within individuals 300 1223 4.07 0.89 Total 599 2711 4.57 1.00 0.067 *** 0.045 *** 0.108 *** Stands Among stands 1 76 0.24 0.05 Among individuals within stands 298 1413 0.33 0.07 Within individuals 300 1223 4.07 0.88 Total 599 2712 4.64 1.00 0.052 *** 0.075 *** 0.123 *** Populations*stands Among populations*stands 29 294 0.28 0.06 Among individuals within populations*stands 270 1195 0.17 0.04 Within individuals 300 1223 4.07 0.90 Total 599 2712 4.53 1.00 0.063 *** 0.041 *** 0.102 *** Cluster # Among clusters 2 141 0.34 0.08 Among individuals within clusters 297 1347 0.23 0.05 Within individuals 300 1222 4.07 0.88 Total 599 2711 4.65 1.00 0.075 *** 0.054 *** 0.125 ***

Df—degrees of freedom; FST, FIS and FIT—individual, inter-population and total fixation indexes, respectively; *** p < 0.001; # considering three genetic clusters revealed by the STRUCTURE analysis.

Gilgit: r = 0.921, p < 0.001 0.60 Baltistan: r = 0.477, p < 0.001

Gilgit vs. Baltistan1: r = −0.492, p < 0.001

0.50 Overall: r = 0.643, p = 0.001

st ´ 0.40

0.30 Genetic distance G distance Genetic 0.20

0.10

0.00 0 20 40 60 80 100 120 140 Geographic distance (km)

Figure 2.5 Correlations (r) between genetic and geographical distances in sea buckthorn based on the Mantel test for eight populations studied in Gilgit-Baltistan, Pakistan. 1Pairwise comparisons between Gilgit and Baltistan populations.

Figure 2.6 Bayesian inference of the most likely number of clusters (K = 3) of sea buckthorn sampled in the Gilgit and Baltistan regions, Pakistan. Three colours in vertical individual bars reflect the likelihood of individual genotypes to belong to one of the three clusters, respectively.

2.5 Discussion 2.5.1 Morphological Variation Variation of dendrometric traits across populations and between wild and village stands (Table 2.2) likely reflected the regional and management-dependent practices of sea buckthorn cultivation in the area. In Shimshal and Passu, for instance, sea buckthorn is widely used as firewood complementing the use of dung and gas during the cold winter months. Moreover, freshly cut branches are used as animal feed and fencing material. In these villages, stone-fenced sea buckthorn woodlands of about 1 ha are used as pasture areas for livestock. Pruning plants together with browsing by livestock creates a silvo-pastoral agroforestry system, where plants rather appear as trees including higher DBHs (diameter at breast height) and canopy area typical for most populations. Their corresponding wild stands, in contrast, showed typically shrub-like appearance and dimensions due to higher plant density and, consequently, stronger competition with other plants as they are unmanaged and not pruned. As evidenced by the CV values, dendrometric traits were the most variable among the assessed parameters (Table 2.2). Leaf area was higher in village stands than in wild ones, which might be due to unintentional management of trees or shrubs via irrigation and better nutrition near the farming field, as leaf size responds strongly to such treatments. Similar responses were observed in Eucalyptus grandis plantations in South Africa and for Ziziphus jujube Mill. in China (Du Toit and Dovey, 2005; Li et al., 2015). Interestingly, leaf area tended to increase with altitude, which confirms recent studies on other vascular plant species in China and on Malosma laurinais in California, USA (Pan et al., 2013; Shelley and Gehring, 2014). To our knowledge, this is the first time that RHS charts were used for sea buckthorn colour assessment. We decided to use this tool as it allows an easy and quick determination of fruit and leave colour shades. It is especially suitable for all kinds of surfaces and curvatures compared to a colorimeter that requires a plain surface. The assessment of fruit colour shades, in general, is challenging as fruit colours highly depend on maturity stage, exposure to sun, decay, infestations and soil nutrient status (Telias et al., 2008; McCallum et al., 2010; Paul and Pandey, 2014). In sea buckthorn, fruits start to bleach (dorsal side first) and desiccate on the tree and/or fall off completely. Hence, in-time and in-field colour determination on a set of fruits (10 in our case) was considered the most reliable, easiest and fastest procedure to

assess colours in a remote area, such as the present one. This fact is important to know before sampling areas are visited or resampling of trees is conducted. The variability of colour, size, and shape has been explained in model plants, such as tomato (Tanksley, 2004) and pepper (Naegele et al., 2016). Genes of several pathways are responsible for variation in fruit morphology via mutations in single genes or interactions of genes controlling these traits. As differences of fruit traits were small between village and wild stands, we concluded that there are currently no strong indications for human-induced selection (the first step of domestication) in these traits. However, there was a significant variability observed among populations showing inter-varietal differences. Interestingly, two populations (Passu and Gulmit) with a very low fruit weight and other similar fruit and leaf morphometric parameters also comprised a separate genetic cluster (see below). The CVs of the length to width ratio of both leaf and fruit as well as moisture content did not seem to be effective measures to differentiate between stands and among populations, unlike leaf area, 20-berry weight, and fruit volume. Variations in sea buckthorn populations among different locations have been previously reported in Asia (Sabir et al., 2003; Yadav et al., 2016). Both research groups explained the variation by differences in physical factors across otherwise similar environments. Other scientists found topography, altitude and pollen availability (that reflects the sex ratio) to cause morphological variation (Yao and Tigerstedt, 1995; Li et al., 2007; Mangla and Tandon, 2014). Bearing in mind that sea buckthorn covers a vast area with a diverse set of abiotic and biotic factors in Eurasia (high mountains, rivers, and climatic conditions, among others), processes of adaptation, isolation and natural selection can be manifold (Rongsen, 1992; Ahmad and Kamal, 2002; Ahmad et al., 2003). Lacking trends in dendrometric traits and lack of significant variability in fruit parameters between village and wild stands as compared to those among populations indicate that regional characteristics have stronger influence on traits than different management in wild versus village populations. This furthermore supports the non- specific role of human interference on these traits. Thus, the selection of superior individuals for future domestication based only on the morphological parameters may lead to erroneous results.

2.5.2 Genetic Diversity and Differentiation Each locus showed at least one private allele per population, which is in line with EST-SSR-based studies of Petunia species in Brazil (Turchetto et al., 2015) and Mangifera species in Australia (Dillon et al., 2014). In our study, sea buckthorn showed high numbers of private alleles, especially in village stands, which is an interesting feature for future breeding. Moreover, a relatively high mean genetic diversity within populations (He = 0.699; Table 2.4) was found, as it could be expected for outcrossing, wind-pollinated woody species (Hamrick et al., 1992; Bartish et al., 1999; Breton et al., 2008). Wang et al., 2008 found low to moderate genetic diversity (He) ranging from 0.299 to 0.476 in H. rhamnoides ssp. sinesis based on nine nuclear SSR markers. A study of Wang et al., 2011 revealed low genetic diversity measures (He = 0.144) for the same species, but based on dominant ISSR markers (for which a maximum He of 0.5 is expected).

Tian et al., 2004 also reported relatively low He values in three H. rhamnoides subspecies ranging from 0.137 to 0.216-based also on ISSR markers. Qiong et al.,

2017 found a slightly higher value in H. tibetana (He = 0.288) based on nuclear SSR markers. Higher values in our study can be explained by the employed sampling design that reduced the probability of collecting clones. Indeed, no identical multi-locus genotypes were found, even though clones were obviously present in the field, as evidenced by patches of several m² that included dozens of individuals with identical leave and fruit shapes and colours. To our knowledge, the above-mentioned studies did not explain properly their sampling procedures, which likely led to partly high estimates of identical multi-locus genotypes, hence lower diversity measures. Qiong et al., 2017 did extra sampling to check the spatial autocorrelation of H. tibetana; they found that at distances larger than 60 m the genetic similarities between individuals decreased, which supports our decision to choose a 100-m minimum distance between individuals collected in our study. Interestingly, the Shimshal population growing very remote and at the highest elevation of 3112 m.a.s.l. had also the highest genetic diversity (He = 0.713), while the population of Chandopi growing at the lowest elevation of 2330 m.a.s.l. had the second lowest genetic diversity (He = 0.684; Tables 1 and 5). Although the highest diversity was found at the highest elevation, our data may corroborate a general pattern of plant populations that a greater genetic diversity exists at intermediate elevations (Ohsawa and Ide, 2008).

Although F values were partly highly significant, they do not allow strong conclusions on underlying population sub-structure (hence no Wahlund effect) based on the following observations: First, the values themselves were numerically low to very low and can therefore be considered under HWE. Second, the obviously strong outlier behavior of locus HrMS004 (demonstrated deviation from HWE) might have caused certain shifts in the overall HWE (as supported by the exemplarily exclusion of this loci) implying that significant values do not per se indicate inbreeding that should equally affect all loci in a population. Third, it is known that statistical power is high when the number of polymorphic markers and samples increase (Ryman et al., 2006), which proofs that our sample size seems sufficient. Fourth, also mis-genotyping due to null-alleles or large-allele dropouts could be potential sources of significantly different values across loci (Morin et al., 2009).

Ranges of FST values based on SSR markers were for instance comparable to

Mediterranean hazelnuts (Corylus avellana L.; FST = 0.015–0.194; Boccacci et al., 2013), underlying a similar sampling design including the separation into wild and domesticated accessions.

The absence of signatures for inbreeding (low FIS values for most markers) suggested low probability for inbreeding depression, which is in line with outcrossing behavior (wind pollination) and likely supports sufficient seed exchange within populations of sea buckthorn. Long distance dispersal of pollen by wind (Zeb, 2004; Fan et al., 2007; Mangla et al., 2015;) and seeds by birds (Rousi, 1971) contributes hence obviously to inter-regional gene flow. The clear and unambiguous structure found in the entire sample using the Bayesian approach in STRUCTURE analysis indicated that there could be some local adaptation associated with genes linked to the EST-SSR used in the study or restrictions to gene flow between the clusters inferred (or both). This is supported by the observed FST values for three clusters that were relatively low, but significant

(Table 2.7). The relatively low FST values support the conclusion of sufficient historic gene flow despite high altitude physical barriers in the area—mountain ridges such as Disteghil Sar, Yukshin Gardan Sar, and Momhil Sar and glaciers such as Chogolungma and Hispar glacier (Figure 2.2). The main wind direction in the Gilgit and Baltistan regions during a year is unidirectional from south and south-southwest for all populations (www.meteoblue.com, accessed on 20 April 2018). The above- mentioned physical barriers are almost orthogonal to the main wind direction and could

potentially slow down gene flow as previously concluded by several authors for similar mountain ranges (Su et al., 2003; Gao et al., 2007; Jia et al., 2012; Qiong et al., 2017). The moderate to strong IBD for Gilgit and Baltistan populations and across all populations emphasized a certain local geographic resistance that could be expected (mountain ranges) and is a typical feature found for natural populations. However, the negative IBD found for between Gilgit and Baltistan populations indicated an enhanced gene flow between both regions (see modes of dispersal, above). This, however, could be also a random effect and merits further sampling from more distant northwestern and southeastern regions of Gilgit-Baltistan to enhance the view on possibly underlying patterns. The EST-SSR markers used in our study were developed by Jian et.al. 2010 and 2014 through searching for microsatellite loci in a de novo transcriptome assembly of over 80 million high-quality short EST reads. The transcripts were randomly selected for the development of microsatellites, and, therefore, the EST-SSRs used in our study also represent a random sample of expressed genes. It is unlikely that their variation would be directly associated with the fruit and leaf morphometric traits studied or with local adaptation of different genetic clusters. This aspect merits, however, further investigation.

2.6 Conclusions Currently, there is no evidence of domestication of sea buckthorn in the study area, as no pronounced loss of genetic diversity was observed. The region harbors very vital and diverse populations. The two villages Gulmit and Passu, which showed a very low berry weight and represented a different genetic cluster, may be less suitable for berry collection, while larger fruit sizes at Shimshal make its stands particularly suitable for collection. However, fruit chemical quality parameters may be different between populations, which merits biochemical and organoleptic evaluation. As local fruit collection is still limited, there is little risk of over-exploiting native plant stands, but efforts should be made to propagate non-destructive harvesting techniques to protect this valuable wild crop resource.

Acknowledgments: We gratefully acknowledge funding from the German Academic Exchange Service (DAAD) through the International Centre for Development and Decent Work (ICDD) at University of Kassel, Germany. We thank Alexandra Dolynska and Christine Radler, Department of Forest Genetics and Forest Tree Breeding, Georg-August-Universität Göttingen, for technical assistance during the laboratory analysis and we are also grateful to our village hosts, especially, Mr. Haji Gulzar from Skardu.

2.7 Appendix

Table A2.1 Genetic diversity parameters of sea buckthorn populations among stands (wild and village) studied in the Gilgit and Baltistan regions, Pakistan.

FIS without Region Population Stand N Na PNa He Ho FIS HrMS004 marker wild 30 8.2 3 0.704 0.683 0.047 0.035 Gulmit village 30 8.2 4 0.699 0.653 0.083 * 0.043 wild 20 6.5 2 0.674 0.667 0.037 0.010 Gilgit Passu village 20 6.9 1 0.685 0.674 0.041 * 0.002 wild 30 6.8 2 0.729 0.758 −0.020 *** −0.058 ** Shimshal village 30 6.3 2 0.686 0.703 −0.01 −0.026 wild 10 5.7 3 0.643 0.675 0.002 −0.025 Thesal village 10 6.2 5 0.693 0.758 −0.04 −0.056 wild 20 7.6 2 0.667 0.629 0.082 * 0.064 Chandopi village 20 7.9 6 0.687 0.671 0.050 * 0.008 wild 20 8.5 2 0.699 0.652 0.092 ** 0.061 * Baltistan Chutran village 20 8.4 7 0.698 0.650 0.094 *** 0.096 ** wild 10 6.3 2 0.696 0.667 0.094 * 0.034 Bisil village 10 6.2 1 0.682 0.683 0.05 0.027 wild 10 5.8 1 0.647 0.650 0.048 0.003 Arando village 10 4.9 0 0.672 0.683 0.035 −0.018 Mean 8.5 3 0.699 0.683 0.043 0.012 n—number of individuals analyzed; Na —mean number of alleles; PNa—mean number of private alleles; He— expected heterozygosity; Ho—observed heterozygosity; FIS—fixation index; * p < 0.05, ** p < 0.01, *** p < 0.001

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Chapter 3 – Superfruit in the niche — Underutilized sea buckthorn in Gilgit-Baltistan, Pakistan

The contents of this chapter have been published in Sustainability 2019, 11(20), 5840; https://doi.org/10.3390/su11205840

Superfruit in the Niche—Underutilized Sea Buckthorn in Gilgit-Baltistan, Pakistan

Muhammad Arslan Nawaz 1, Asif Ali Khan 2, Usman Khalid 3, Andreas Buerkert 1 and Martin Wiehle 1,4

1 Organic Plant Production and Agroecosystems Research in the Tropics and Subtropics, University of Kassel, Steinstrasse 19, D-37213 Witzenhausen, Germany; [email protected] (M.A.N.); [email protected] (A.B.) 2 Department of Plant Breeding and Genetics, Muhammad Nawaz Shareef University of Agriculture, 66000 Multan, Pakistan; [email protected] 3 School of Business and Management Sciences, Information Technology University, 54600 Lahore, Pakistan; [email protected] 4 Tropenzentrum and International Center for Development and Decent Work (ICDD), University of Kassel, Steinstrasse 19, D-37213 Witzenhausen, Germany

3.1 Abstract Sea buckthorn is a medicinal plant occurring throughout the temperate regions of the northern hemisphere. Considered as a “superfood” given the nutritional properties of its berries, the latter have a large international market potential, particularly in China and Europe. Although sea buckthorn grows widespread in northern Pakistan, it is a neglected species there. Fruit marketing is severely hampered by low raw product quality, varying prices, and low local demand. During 2017–2018 a total of 111 collectors and 17 commission agents were interviewed from Gilgit-Baltistan, Pakistan using semi-structured questionnaires. The results provide comprehensive information about the current situation from collection to post-harvest management of sea buckthorn fruits including the analysis of vitamin C under different sun and shade drying conditions. The findings are complemented by an analysis of the underlying supply chain. Fruit sale prices were low for the collectors (1.82 US$ kg−1) since mostly poor households are involved in the harvest and sale. Traditional sun drying and storage conditions were inappropriate resulting in a decrease of chemical fruit quality and thus negatively affecting the sales price of produce. Supply chain analyses showed that the non-coordination among actors and lack of infrastructure affect the efficiency of the targeted sea buckthorn production at large. The study also shows the urgent need to set appropriate food quality standards,

to increase communication among stakeholders, and to intensify training offers especially for collectors of sea buckthorn fruits.

Keywords: fruit collection and drying; Hippophae rhamnoides; non-regulated price; post-harvest handling; vitamin C

3.2 Introduction Sea buckthorn (Hippophae rhamnoides L., Elagnaceae) is a shrub whose fruits are rich in vitamins and several other bioactive substances (Rongsen, 1992; Tang and Tigerstedt, 2001). The species is a well-known medicinal plant containing carotenoids (Andersson et al., 2008), tocopherols, ascorbic acid or vitamin C (Kallio et al., 2002), vitamin K, the vitamin B complex (Jamyansan and Badgaa, 2005), phytosterols (Baoru et al., 2001), polyphenolic compounds (Upadhyay et al., 2010), polyunsaturated fatty acids (PUFA), organic acids (Yang and Kallio, 2001), coumarins, triterpenes (Grey et al., 2010), and zinc (Gupta and Singh, 2005). Yet the world market of sea buckthorn as a nutraceutical and medicinal plant is still largely unexplored. To our understanding, in Pakistan, it is traditionally known as a medicinal plant, although as field observations and deskwork suggest, knowledge on its use as a food crop is restrained due to limited awareness of producers and consumers. In the local harvest calendars of farmers in the Karakoram Mountains, sea buckthorn is the last fruit crop ripening between September and November, whereby collection is still possible until January (Ahmed and Joyia, 2003; ICIMOD, 2017). Despite its abundance and timely ripening during the slack season in farm labor demand, the species is hardly exploited and only marginally processed for value addition as juice, jam, squash, and oil (Zeb, 2004; Sabir et al., 2005). Traditionally, some berries are harvested and dried for sale, while branches and bark are used as fuel (source of cooking and heating during the winters), and leaves are browsed by livestock as observed during our field survey. The vitamin C concentration of sea buckthorn is 10 times higher than that of kiwi fruit (Actinidia deliciosa P.) which is commonly known as a rich source of ascorbic acid (Lebeda, 2003). Vitamin C acts as a biological antioxidant for the formation and maintenance of connective tissue, it stimulates the immune system, increases iron uptake, and can help prevent scurvy disease and cancer. As humans are not able to synthesize ascorbic acid, the main source of ascorbic acid in the human diet is supplied by fruits and vegetables (Byers and Perry, 1992; Linster and van Schaftingen,

2007; Marks, 1993; Shrimpton, 1993). Ascorbic acid in Hippophae fresh berries ranges from 200 to 4000 mg 100 g-1 depending upon the species and variety (Rousi and Aulin, 1977; Yang et al., 1988; Yao et al., 1992). It is well known that vitamin C is highly sensitive to post-harvest conservation processes such as drying and storage, thus it is also a freshness indicator (Moser et al., 1991). At harvest, sea buckthorn berries have 70%–80% moisture (Perino-Issartier et al., 2011), which strongly limits their shelf-life. Preservation through drying is an effective solution to minimize quality losses by preventing biochemical and microbiological deterioration (Doymaz and Pala, 2003; Santos and Silva, 2008). Drying of fruits and vegetables, however, causes changes in their physical (such as browning), chemical, and nutritional properties. There are several methods of berry drying depending upon the type of fruit: from cheap and simple processes such as sun drying, to expensive non-conventional methods such as microwave and freeze-drying. Also, non-conventional drying methods with a modified atmosphere have been used to obtain dried products with high nutritional and sensory attributes (Santos and Silva, 2008; Marques et al., 2006). Processing of sea buckthorn fruits varies according to the intended value addition; often the preliminary step is to extract juice or pulp, with a reasonable fraction of floating oil. The remaining press cake contains uncracked seeds that may be separated to extract other oil fractions (Cenkowski et al., 2006; Bal et al., 2011). End products of sea buckthorn are extracts used in herbal medicines for a variety of medicinal and therapeutic (Suryakumar and Gupta, 2011) as well as cosmetic purposes (creams, lotion, body and hair oil, shampoos, soaps), which have a growing market in Europe, Asia, and North America (Beveridge et al., 1999; Li, 2002; Kumar, 2003; Li and Beveridge, 2003). Edible products include juices, jams, jellies, and alcoholic drinks such as wine and beer. In Asia, with 740,000 ha (wild collection) and 300,000 ha (cultivated), China is the leading producer and exporter; a total annual yield of about 8.5 million t has been reported to lead to revenues of 1.43 billion US$ (Jianzhong et al., 2008). Mongolia is the second leading producer with 13,500 ha (wild collection) and 6000 ha (cultivated) leading to an annual yield of between 1200–1600 t earning 5 million US$ (Oyungerel et al., 2014; Gonchigsumlaa, 2016). In India, the species is only marginally utilized with 13,000 ha (wild collection) and a total annual yield of 600 t (Stobdan and Phunchok, 2017). Pakistan in contrast harvests a comparatively low share on

approximately 5700 ha harboring an estimated 12 million individuals. These populations are mainly concentrated in the northern region of Gilgit-Baltistan where most of this area consists of patches of sea buckthorn thickets away from residential areas, used and harvested to only a limited extent (about 285 ha; ~5%; ICIMOD, 2017). The reasons for this low use are manifold: First, the utilization as a food crop seems to be rather recent as it is unknown to the traditional local cuisine. Second, the thorny nature of the plants makes easy harvest within the stand thickets difficult. Third, alternating bearing behavior prevents a reliable annual yield, this may be partly related to the effects of harsh environmental conditions. Fourth, there are areas with a high share of male plants that do not bear fruits at all, though they are important reservoirs of genetic diversity. Fifth, fruit sale revenues are generally low due to the oligopoly of a few middlemen and for value added products due to low customer demand. Sixth, knowledge on suitable stand management as well as harvesting and post-harvesting practices are lacking on a broad scale, though some training units are offered by non- government organizations (NGOs) and extension services. Apart from the limited use of berries in Gilgit-Baltistan, harvesting and handling techniques also differ significantly among villages. Sophisticated harvesting and handling techniques have been rather recently introduced and promoted by local NGOs, foremost the Aga Khan Rural Support Program (AKRSP; ICIMOD, 2017). Collectors of sea buckthorn in Gilgit-Baltistan perform open-air sun drying rather than solar drying which involves protection by nets or transparent materials before selling to commission agents. Drying conditions are inappropriate due to lack of protection and grading facilities to keep fruits clean from dust, stones, leaves, and wood particles (Figure 3.1e–f). Fruit collectors are furthermore largely unaware about the decrease of physical quality of the sea buckthorn fruit under poorly defined drying conditions, such as browning, rancidness, and moisture content. These circumstances also affect the selling price of the final raw product.

Figure 3.1 Different harvesting and drying methods and their effects on sea buckthorn berry quality during 2017−2018 in Gilgit-Baltistan, Pakistan. (a) Simple, non-standardized harvesting tools including a wooden stick and a plastic bag; (b) threshing of sea buckthorn berries from semi-dried branches cut prior and transported home; (c) spread of berries on the roof of a house; cloth between clay surface and berries reduces contamination by foreign particles; (d) spread of berries on concrete floor in an experimental green house; (e) physical quality reduction through browning and dust particles; (f) rancidness of sea buckthorn berries (black spots) due to improper storage.

Fair distribution of value generated by the sea buckthorn supply chain among the various actors also remains a challenge. Small-scale collectors responsible for the collection and processing of sea buckthorn fruits remain on the losing edge. Managing the sea buckthorn supply chain on more sustainable lines can potentially impart a positive impact on the livelihoods of local communities. Our study intended to analyze

various socio-economic and ecological constraints responsible for apparent inefficiencies in the sea buckthorn value chain. Taken together (socio-economic and ecological constraints in the sea buckthorn business), the present study aimed at following an approach known from large agricultural commodities (Pretty et al., 2008), the sustainable supply chain management (SSCM). SSCM intends to analyze the main drawbacks in supply chains and identify measures to upgrade conditions in social, economic, and ecological terms. In view of the above, this study aimed to: 1. Assess the current situation and problems during collection, drying, and marketing of sea buckthorn fruits in the Gilgit-Baltistan area of Pakistan as an example of a highland plant value chain; 2. Recognize the preferences of collectors regarding fruit traits for the sake of future cultivation and introduction; and 3. Examine fruit vitamin C losses under traditional drying (sun drying) versus shade drying conditions. The results will hopefully contribute to rising awareness among stakeholders and provide policy recommendations to tackle recurrent problems related to sea buckthorn harvesting, trade, and marketing to improve revenues for villagers in Gilgit- Baltistan.

3.3 Materials and Methods 3.3.1 Study Area The study was conducted in the Gilgit-Baltistan region of northern Pakistan (Figure 3.2). It stretches over an area of 72,496 km² with almost 1.8 million inhabitants and a multi-dimensional poverty of 35% (Kazim Niaz and Aman, 2017). More than 90% of Gilgit-Baltistan is covered by mountain ranges and glaciers, while the remaining area is arable land used by small-scale, subsistence-oriented farmers, which partly rely on local forest resources (World Bank, 2011; Ali et al., 2014). Among these, sea buckthorn is an underutilized plant resource which grows well under adverse agroecological conditions leading to highly scattered stands (Nawaz et al., 2018). The climate of Gilgit-Baltistan varies widely from arid to semi-arid conditions along the elevation gradient with an annual precipitation of 200 mm (below 3000 meters above sea level (m a.s.l.)) up to 2000 mm (above 6000 m a.s.l.). The temperature ranges from 40 °C during the summer to −10 °C during the winter (Ismail et al., 2018).

Figure 3.2 Map of Pakistan showing the study area in Gilgit-Baltistan.

3.3.2 Survey on Sea Buckthorn Management, Harvest, and Post-Harvest Handling Practices A survey on current management practices of sea buckthorn was conducted between August 2017 and January 2018 to assess its uses and harvesting techniques and to understand the collectors’ and commissioners’ perceptions, problems, and processing steps from collection of the plant parts until marketing. To this end a snowball sampling approach was used to select 111 sea buckthorn collectors and 17 commission agents (four out of which were also involved in collection) from eight different villages (Table 3.1). Per village, 15–20 collectors (currently collecting during the survey year) were interviewed considering the fact that mostly poor people were involved in the collection. In-person interviews with semi-structured questionnaires focused on the following aspects: • status of collection and subsistence through sea buckthorn; • current conditions and methods of harvest and post-harvest handling (collection of berries, storing, drying, value addition through product development);

• description of particular problems during collection, drying (number of days required for drying, price affected due to quality of drying), and marketing of sea buckthorn berries; • perception of collectors about required/needed trainings and impact of already acquired trainings from government, NGOs, and private companies; • identification of collectors’ perception about preferred dendrological and fruit traits.

Table 3.1 Number of total and interviewed households involved in collection and commission during 2017−2018 in Gilgit-Baltistan, Pakistan. Regions District Villages No. of Household Total Interviewed Collector Commissioner Gilgit Hunza Shimshal 240 20 4 Passu 300 4 1 Gulmit 220 15 2 Baltistan Shigar Arando 90 15 1 Bisil 78 12 1 Chutron 120 15 3 Chandopi 140 15 3 Thesil 160 15 2 Total 1348 111 17

A sustainable supply chain management (SSCM) analysis was conducted at a dyadic level with 45 collectors (~suppliers, out of the 111 collectors) and 17 commission agents (~buyers). Respective data were collected using a structured five-point Likert scale questionnaire for seven supply chain constructs (Table 3.2) and their corresponding factors (Table A3.1; Beske and Seuring, 2014; Khalid and Seuring, 2019).

Table 3.2 Description of the sustainable supply chain constructs (based on Khalid and Seuring, 2019) used in the study. Constructs Description References Stakeholder To avoid any gray areas in the sustainable business operations, (Vachani and Smith, engagement "transparency includes not only reporting to stakeholders, but 2008; McMullen, 2011) actively engaging stakeholders and using their feedback and input to both secure buy-in and improve supply chain processes."

Long-term relationships Strategically managed trustworthy long-term relationships with (Hill, 2010; Galariotis et key suppliers in particular and other supply chain actors in al., 2011) general, impacting positively on firm performance.

Technology integration Presence and mode of electronic transactions and communication (Gino and Staats, 2012; for the efficient flow of information among supply chain actors. Berger and Nakata, 2013)

Logistics integration The backbone of the modern supply chain, providing the (Chen and Paulraj, necessary infrastructure to successfully meet market demands 2004; Vachon and through seamless logistics integration based on regular lines of Klassen, 2006; communication for exchanging information about the three Viswanathan et al., cornerstones of logistics: warehouses, inventory, and 2009) transportation between buyer and seller.

Strategic purchasing Proactive and long-term focus in making purchasing decisions (Arnould and Mohr, that will drive the firm’s success. 2005; Kistruck et al., 2013) Supplier integration Communication and coordination with suppliers to seamlessly (Halme et al., 2012; integrate them into focal firm activities for more efficient Ramachandran et al., achievement of sustainability objectives. 2012)

Communication and Enhanced communication and active coordination with suppliers (Berger et al., 2011; coordination with as a prerequisite for supplier integration and sustainable supply Ramani et al., 2012) suppliers chain management.

3.3.3 On-Farm Drying and Laboratory Experiment A sub-selection of 30 out of the 111 collectors were randomly selected for close assessment of the traditional sun drying procedure of sea buckthorn fruits. For this purpose, five sea buckthorn shrubs were randomly selected from those villages that were inhabited by the identified collectors. The exact location of the sample trees and drying households was determined with a hand-held GPS (Garmin-eTrex 30, horizontal accuracy ±2 m, GARMIN® Ltd., Southampton, UK). Per tree, two portions of fresh berries (10−15 g each) were collected and stored in plastic gauze bags. Afterwards, the collectors were requested to traditionally sun-dry one portion while the other portion was kept for open shade drying (Figure 3.3). Collectors were asked to proceed with drying until weight constancy and to note the date when this was

achieved; afterwards samples were taken again. To determine moisture content, final weight after drying was subtracted from the initial fresh weight.

Figure 3.3 Experimental setup of sea buckthorn fruit drying modes: sun drying (farmers´ practice, left) and shade drying (right), Gilgit-Baltistan, Pakistan.

Subsequently, all samples were analyzed in the laboratory to quantify the concentration of ascorbic acid (vitamin C). To this end seeds were separated from the dried pericarp (Figure 3.4) and each weighed separately (±0.5 g). The pericarp samples were homogenized and ground in 5% metaphosphoric acid dissolved in 5 ml of distilled water followed by extraction at room temperature for 15 min using a shaker at 40 rpm. Afterwards, samples were centrifuged at 4000 rpm for 10 min, supernatant was collected, and kept at –18 °C prior to analysis. After dilution, samples were analyzed using an HPLC (PerkinElmer, Series 200, Shelton, CT, USA) equipped with

Shim-Pack CLC-ODS (C18), 25 cm × 4.6 mm, 5 μm. For detection of ascorbic acid, an isocratic mobile phase of double distilled water or 70% methanol was used with a flow rate of 1 ml min-1. The elution was analyzed with a UV–Vis detector set at 280 nm and the results were compared with that of an ascorbic acid standard solution.

Figure 3.4 Sample preparation for ascorbic acid (vitamin C) quantification by HPLC. (a) Seed separation from pericarp; (b) weight measurement; (c) grinding of pericarp; (d) grinded pericarp; (e) supernatant collected in an Eppendorf tube.

3.3.4 Statistical Analysis The obtained data were analyzed with the help of R-software (version 3.3.3, R core team, 2017, Vienna, Austria). Differences in mean annual income between interviewed household groups (collectors, commission agents, and collectors involved in value addition) were explored employing Kruskal–Wallis tests at p < 0.05. The value of the sea buckthorn firewood was estimated according to the household’s monthly consumption and approximate market price. The numbers of days required for drying (DRD) was analyzed with an analysis of variance (ANOVA) using a generalized linear model followed by a Chi-squared test following a Poisson distribution. An ANOVA using a simple linear model was performed for vitamin C concentrations and moisture contents as residuals of the data were normally distributed. Afterwards, if applicable, a Tukey test (p < 0.05) was performed for both data sets to separate means using the MULTCOMP package (Bretz et al., 2002). Data were graphically displayed as alluvial diagrams using RAWGraphs (Licensed under CC BY-NC-SA 4.0.; How to Make an Alluvial Diagram. Available online: https://rawgraphs.io/learning/how-to-make- analluvial-diagram/ accessed on 11 March 2019). Partial least square structural equation modeling (PLS-SEM) was used for model prediction of the SSCM constructs by employing smart-PLS version 3.2.8 (Ringle et al., 2015). Simulation was performed with 300 iterations and a 10−7 stop criterion; furthermore, the model was evaluated using a bootstrapping method with 5000 subsamples at a 0.05 significance level. Normed fit index (NFI) and standardized root mean square residual (SRMR) including confidence intervals (d_UL: unweighted least square discrepancy; d_G: geodesic discrepancy; Ringle et al., 2015), Cronbach alpha (Santos, 1999), and composite reliability (CR; Churchill and Iacobucci, 2006) were used to evaluate model fit. The

acceptable α and CR value for the factors used in the study was ≥ 0.7; factors lower than this value were excluded (Tavakol and Dennick, 2011). In addition, average variance extracted (AVE) was used including the acceptable threshold value of 0.4 (Fraering and Minor, 2006).

3.4 Results 3.4.1 Survey on Sea Buckthorn Management, Harvest, and Post-Harvest Handling Practices 3.4.1.1 Status and Subsistence through Collection Collectors and commission agents had on average four to six years of experience with sea buckthorn management and trade. Collectors’ average income from fruits in the study area was 1.8 US$ kg−1. For commission agents, mean annual income from sea buckthorn berry sale was about 4.5 times higher than for collectors. The income of collectors from the sale of sea buckthorn byproducts was almost twice as high as for berry sales alone (Table 3.3).

Table 3.3 Mean and median (values in brackets) ± SD annual income (US$) of sea buckthorn berry and byproduct sale of interviewed households during 2017−2018 in Gilgit-Baltistan, Pakistan. Groups Berry Sale (US$) Byproduct Sale (US$)

Berries only (n = 93) 181 (125)a ± 196 - Collector Berries and byproducts (n = 18) 213 (101)a ± 247 378 (75)a ± 831

Commission Berries and byproduct (n=17) 838 (385)b ± 924 307 (0)b ± 878 agent ab Medians with different superscripts differ significantly at p ≤ 0.05 (Kruskal–Wallis test).

Men, women, and children (under 15 years) in a family (22:53:25) were involved in collection of sea buckthorn berries, whereas only a few women directly earned cash, as men dominated sea buckthorn sales (Table 3.4). The collection of berries took place mostly on a family’s own land, whereas about half of the landowners allowed other collectors to harvest free of charge (Table 3.4).

Table 3.4 Descriptive statistics of interviewed households (collectors, n = 111; commission agents, n = 17) and status of collection of sea buckthorn berries during 2017−2018 in Gilgit-Baltistan, Pakistan.

Variable Unit Group Mean Min. Max. Year Collector 4 ± 3 1 19 Experience Year Commission agent 6 ± 4 1 18 Amount Kg Collector 110 ± 136 15 1250 collected/purchased Kg Commission agent 3356 ± 3201 500 10,000 US$ kg−1 Current 1.82 ± 0.38 0.96 2.4 Selling price for collectors US$ kg−1 Demand increase 2.84 ± 0.73 1.44 4.81 Firewood for household US$ Estimated price 511 ± 142 240 923 use year−1 Total % Men 22 Family labor involved in % Women 53 collection of berries % Children under 15 years 25 % Owned 62 Picking area % Community land 10 % Both 28 Picking from other land % Allowed 46 than picking area % Not allowed 54

3.4.1.2 Conditions and Methods of Harvest to Post-Harvest Handling Harvesting and drying of sea buckthorn fruits varied depending upon the region/village studied. Nineteen collectors (17%) harvested the fresh berries from October until November and dried them afterwards. This was mainly practiced in the Passu and Gulmit region near the Karakorum Highway and called “in vivo fresh berry threshing” (Figure 3.5a). Twenty collectors (18%) harvested the already dried up berries at the end of December until February and post-dried them afterwards. This was mainly practised in the Shimshal Valley and called “in vivo dry berry threshing” (Figure 3.5a). Seventy-two collectors (65%) chopped the fruit bearing branches from August until November, transported them home, semi-dried these branches, and threshed them afterwards. This practice took place only in Baltistan and was referred to as “ex situ berry branch harvesting” (Figure 3.5a).

Figure 3.5 Alluvial graph showing the collection, processing, and days required for drying of sea buckthorn berries according to collectors (n = 111) in the study area of Gilgit-Baltistan, Pakistan (during 2017–2018). Share of (a) harvesting/drying methods practiced per region; (b) post-harvest processing conducted; (c) number of days required to dry berries; (d) price affected due to deteriorated physical quality (Figure 3.1e); and (e) knowledge of price difference when quality is reduced.

There were different homemade harvesting tools used such as fertilizer bags folded around a mulberry wood stick, beating sticks, and on-spot collection storage bins. For drying, mostly sun drying on clay roofs or concrete floors was performed at collectors’ as well as agents’ homesteads, whereas 11% of agents tried to apply solar drying when fresh bulks were purchased (Figure 3.1a−d). Most of the sea buckthorn collectors (76.5%) were involved in drying, while only a few (4.5%) added value by processing the fruits into jams, juices, and pulp concentrates. Both activities (drying and processing) were conducted by 11.7%, whereas 7.2% of collectors were neither involved in drying nor value addition (Figure 3.5b). The sales price of berries was strongly affected by drying conditions (Figure 3.1c−e), whereby 80% claimed that quality affected price (Figure 3.5d,e). Storage containers used for dried sea buckthorn fruits were either plastic fertilizer or rice bags (90.1%); the remainder was stored in jute fiber bags.

3.4.1.3 Collectors´ Problems Collectors reported major problems during fruit collection and marketing (Table 3.5). The most common problems were lack of collection material, unmanaged and dense thickets of sea buckthorn, as well as lack of direct market access. Though

ranked lower, further constraints were lack of storage facilities, lack of harvesting knowledge, poor road infrastructure, and variable price margins of sea buckthorn berry sale.

Table 3.5 Identified problems during collection, drying, and marketing of sea buckthorn berries and their proposed solutions by collectors (n = 111) interviewed during 2017−2018 in Gilgit-Baltistan, Pakistan. Problems During Collection Response Frequency (%) Lack of collection equipment 74 Unmanaged/dense stands 71 Lack of storage facility 41 Difficult collection due to lack of harvesting 37 knowledge Problems During Drying Harsh weather (strong winds and rainfall) 95 Dust 93 Grading issues 48 Drying equipment unavailability 34 More days needed for drying 15 Bird damage 14 Quality deterioration 12 Problems During Marketing Lack of market access 57 Transportation due to poor road infrastructure 34 No regulated fix price 33 Potential Solutions Availability of drying units 76 Availability of grading units 43 Provisions of latest harvesting tools 55

The major problem of sun drying was reportedly harsh weather conditions (strong winds, precipitation), including depositions of dust particles. Other respondents noticed grading issues, unavailability of drying equipment, a higher number of days required for sun drying due to changing weather conditions, bird damage, and quality deterioration (Table 3.5). Most of the collectors (97%) mentioned that it took more than 10 days for proper sun drying of sea buckthorn berries, whereas only 3% of the collectors needed <10 days for drying (Figure 3.5c). The potential solutions proposed by the collectors to solve these problems were provision of drying and grading units nearby and supply of better harvesting tools (Table 3.5).

3.4.1.4 Collectors’ Perception about Trainings Collectors mentioned the need of trainings about improved practices of sea buckthorn management. The most important trainings concerned collection, value addition, and drying practices (Table 3.6). About one-quarter of collectors already received trainings from government, NGOs, and private enterprises. During these trainings, they learned about safety measures during collection, product development strategies, maintenance of sea buckthorn plants, and marketing strategies (in decedent order; Table 3.6).

Table 3.6 Required trainings for collectors (n = 111) of sea buckthorn interviewed during 2017−2018 in Gilgit-Baltistan, Pakistan. Training Demand Response Frequency (%) Latest collection methods 76 Value addition 60 Latest drying methods 38 Grading techniques 17 Marketing techniques 16 Cultivation practices 6 Yes No Have you taken any type of training? 28 72 Theme of received training Safety measures during collection 81 Product development 74 Maintenance of plants 35 Marketing 23

3.4.1.5 Preferred Plant and Fruit Traits by Collectors Preferred plant traits were increased numbers of fruits per plant (81%), less or no thorns (65%), easy shattering (51%), and large fruits (32%). Collectors from the Gilgit region preferred large and greater number of fruits per plant as well as a large crown area, whereas respondents from Baltistan favored a combination of less or no thorns and easy shattering (Figure 3.6).

Figure 3.6 Radar plots showing plant trait preferences (%) of sea buckthorn collectors (n = 111) interviewed during 2017−2018 in Gilgit-Baltistan, Pakistan; (a) dendrological and (b) fruit traits.

3.4.1.6 Sustainable Supply Chain Constructs One out of seven SSCM constructs showed a Cronbach alpha less than 0.7, namely “Long-Term Relationship”, and was therefore excluded for further analysis, whereas other constructs including their item loadings indicated a reliable and valid outer model (Table A3.1). SRMR did not fit the actual threshold but was close to the actual value (Table 3.7). In addition, the path coefficients (β) showed the significance of the relationships (paths) of the predicted model (Table A3.2). There was a strong correlation between the latent endogenous construct and latent exogenous construct (Table A3.3). The model with communication and coordination with suppliers as antecedents and stakeholder engagement as an outcome is displayed in Figure 3.7 and further discussed in Section 4.

Table 3.7 Model fit summary of the predicted model.

Estimated Model SRMR 0.092 d_ULS 2.734 d_G 1.716 Chi-square 452.915 NFI 0.735 SRMR: standardized root mean square residual, d_ULS: unweighted least square discrepancy, d_G: geodesic discrepancy, NFI: normed fit index.

Figure 3.7 Model of communication and coordination with suppliers for sea buckthorn fruits as predicted by partial least square structural equation modeling (increasing thickness of arrows marks increasing correlation coefficients, cf. Table A3.3).

3.4.2 On-Farm Drying and Laboratory Experiment 3.4.2.1 Days Required for Drying and Moisture Content The moisture content of sun- and shade-dried samples ranged from 26% to 35% with no significant treatment effects (Table 3.8). Days required to dry (DRD) for sun-dried samples were consistently and significantly lower than in shade-dried samples (Table 3.8) ranging from 8–19 and 15–30 days, respectively. The village-specific DRD was highest for Arando and Chutran and lowest for Chandopi, Passu, and Thesal.

Table 3.8 Average drying traits of sea buckthorn under sun-dried and shade-dried conditions in Gilgit-Baltistan, Pakistan.

Villages Drying Method n Moisture % DRD Sig Passu Shade 5 31 15 ac Sun 5 28 9 ab Thesal Shade 5 33 16 bc Sun 5 34 8 a Chandopi Shade 5 35 15 ac Sun 5 33 9 ab Chutran Shade 5 35 30 d Sun 5 34 15 ac Bisil Shade 5 31 20 cd Sun 5 30 12 ac Arando Shade 5 26 30 d Sun 5 26 19 c Total 60 n = number of samples; small letters indicate significant differences of DRD (days required for drying) at p < 0.05 among villages and between drying conditions (sharing the same letters indicates non- significant differences).

3.4.2.2 Concentration of Ascorbic Acid

Mean vitamin C concentrations among villages ranged between 6 and 275 mg 100 g−1, whereby sun-dried fruits showed significantly lower values than shade-dried ones (Figure 3.8). Also, values were lowest for Chandopi (12 and 20 mg 100 g−1, respectively), followed by those for Arando, Bisil, Thesal, Chutran, and highest for Passu (120 and 275 mg 100 g−1, respectively).

Figure 3.8 Boxplot diagram of vitamin C concentrations in sun-dried and shade-dried sea buckthorn fruits among the villages surveyed in Gilgit-Baltistan, Pakistan. Small letters indicate significant differences of vitamin C concentration in berries at p < 0.05 among villages and between drying conditions (means sharing the same letters are similar).

3.5 Discussion 3.5.1 Status of Collection, Post-Harvest Handling, and Management China and Mongolia provide subsidies to farmers to promote cultivation and collection of sea buckthorn berries; in Mongolia sea buckthorn is one of the major fruit crops and average annual income of a sea buckthorn collection household was reported to be 3413 US$ (Gonchigsumlaa, 2016; Balt et al., 2016). Collectors involved in value addition had a significantly higher income through byproduct sales than from sales of berries alone. In Pakistan, the price of sea buckthorn is not state-regulated and the current sale price of 1.8 US$ kg−1 is not satisfactory; collectors have demanded an increase to at least 2.8 US$ kg−1 (56%). In comparison, the current price for dried apricot, mulberry, and apples in Gilgit-Baltistan was approximately 3.0, 1.2, and 1.0 US$ kg−1, respectively. There were other benefits for households involved in sea buckthorn collection of which use as firewood for heating during winters and cooking contributed an equivalent of 511 US$ in annual savings. At the time of our survey most collectors of sea buckthorn berries had just started their activity due to ongoing awareness raising campaigns by NGOs coupled with an increasing consumer demand. As sea buckthorn is not commercially cultivated in the study area, harvesting takes place on private and common land. Despite the fact that mostly women are involved in the collection of berries, men dominate sales.

A range of harvesting methods were observed, which all caused some damage to individual plants. If correctly applied, targeted pruning can lead to better yield without risking stand destruction. Alternative harvesting methods such as milking by using chain gloves (MLUL, 2013) and shock freezing technologies through freeze chambers or liquid nitrogen applications (as known from Ludwigslust, Germany) are difficult to establish because either materials are not available (chain gloves) or infrastructure (road, power grid) is poor, preventing the installation and maintenance of low and constant temperature units. Another constraint related to harvesting observed in the study area is over- exploitation and premature harvesting of berries (most common practice for fruits and vegetables in Pakistan). This threatens plant survival as observed for other medicinal plants of the Northern Kashmir Himalayas in Pakistan (Malik et al., 2011). Poor harvesting of sea buckthorn fruit may result in the depletion of stand vitality; hence, it may cause the loss of genetic diversity as observed in species such as Hallea rubrostipulata (K. Schum) J-F Leroy (Rubiaceae) and Warburgia ugandensis Sprague (Canellaceae) in Uganda (Ssegawa and Kasenene, 2007). Most sea buckthorn collectors sun-dried the berries before selling them to agents (Figure 3.5b). Strong winds and precipitation during the collection period often required more than 10 days of sun drying; this was reported as problematic since it resulted in part or complete deterioration of quality characteristics, as also observed in other fruits and medicinal crops (Sagar and Kumar, 2010; Rocha and Melo, 2011). After drying, proper packaging is important to maintain berry quality (Martinazzo et al., 2009). The collectors used plastic fiber bags, which are sturdy, but do not allow aeration for the semi-dried organic material. This may lead to a rancid and/or moldy raw product (Smith et al., 1990; Marsh and Bugusu, 2007) which has been observed in the field several times (Figure 3.1f). Commission agents therefore often restart drying and cleaning berries once they have collected and/or purchased and transported the bags to their storage facilities. If bags of unidentified origin are reused, unknown contaminants may affect berry quality. In our study, most agents transferred berries into jute fiber bags and stored them under dry conditions between 40% and 50% relative humidity and 8–12 °C for two to three months (own data). Possible solutions to these problems may be advice on the use of more appropriate collection material or the establishment of cooperative collection and

storage mechanisms. This could be regulated by government agencies or NGOs as dealers are rarely interested in collectors’ problems (Larsen and Smith, 2004). Collectors often lack direct market access, transportation due to poor road infrastructure, and suffer from large price fluctuations. There is a range of studies for other medicinal plants confirming such constraints and showing the effects of dominance of a few middlemen and a basically unregulated supply chain (Schippmann et al., 2002; Hamilton, 2004; Mahapatra and Tewari, 2005; Kala et al., 2006; Larsen and Olsen, 2007). Price negotiations between collectors and commission agents about quality characteristics of sea buckthorn berries are very unbalanced as middlemen have much more knowledge about the quality produced in the region and thus an advantage over collectors, resulting in price dictation. This has been observed in several other medicinal plants from studies in India (Ravinder Reddy et al., 2008; Jalihal, 2009; Pradeep Kumar, 2016). As price is largely influenced by the physical quality of berries (Figure 3.1c−e), effective drying facilities are key for reducing post-harvest losses of quickly perishable crops (Kiaya, 2014; Bradford et al., 2018). In our study, collectors were interested in a greater number of fruits per plant, no thorns, and easy shattering. There are several known varieties of sea buckthorn exhibiting larger fruits and less/no thorns especially in China (’Hongguo’ and ’Liaohuyihao’), Mongolia (’Wulangemu’; Ruan et al., 2004), Germany (’Frugana’, ’Hergo’, ’Leikora’, and ’Dorana’; Albrecht, 1990), Finland (’Tytti’, ’Terhi’, and ’Tarmo’), and Russia (’Botanicheskaya Ljubitelskaya’, ’Prozrachnaya’, and ’Podarok Sadu’; Sanna and Petruneva, 2015). These varieties could be used for breeding purposes after a critical screening and evaluation of promising local plant genetic material (large fruits) such as found in the Shimshal valley and Skardu region (Nawaz et al., 2018). Using local materials for breeding would also help to preserve regional diversity.

3.5.2 Quality Loss Due to Sun Drying of Sea Buckthorn Berries In Gilgit-Baltistan, most collectors were involved in sun drying of sea buckthorn, a time-consuming process that needs constant physical attention and special infrastructure. Freeze-drying of fresh fruits would be hygienically and nutritionally best to produce a product with a long shelf-life and high biochemical quality. So far, lack of this technology in the study area prevents the production of a high quality and economically beneficial raw product suitable for national and international markets.

Very recently small initiatives started as they received funding from UNDP (United Nations Development Programme), WWF (World Wide Fund for Nature), and the Coca Cola Company to promote the interest of collectors for making value-added products (jams, juices, pulp, and squashes) for local markets. Although our study confirms that the quality of sea buckthorn berries is significantly affected by sun drying, we found no previous studies on such effects for this species. As for other crops, sun-dried plant products have an inadequate quality due to remaining moisture, dust, insect infestations, and microbial contamination (Yahya et al., 2001; Jain and Tiwari, 2003; Rocha and Melo, 2011; Belessiotis and Delyannis, 2011). The moisture content of sea buckthorn berries was similar in sun- dried and shade-dried samples showing that both drying methods are appropriate, though the period of DRD was pronouncedly extended under shade drying. Since ascorbic acid concentration was only measured after drying and not after harvest of fruits, the total vitamin C loss could not be determined. Our experiment demonstrated that current sun drying of sea buckthorn berries is inadequate in terms of biochemical quality and that there is an urgent need of alternative drying techniques or improved handling modes. Our study showed that the vitamin C concentration of sea buckthorn berries is almost twice as high in shade-dried than in sun-dried berries. These values are similar to those of kiwis (Actinidia deliciosa P.; Kaya et al., 2010; Chin et al., 2015), grapes and sultanas (Vitis vinifera L. cv. Sultanina; Çağlarirmak, 2006), mango (Mangifera indica L.; Ndawula et al., 2004), amla (Emblica officinalis L.; Murthy and Joshi, 2007), jack fruit (Artocarpus integer Spreng.; Chong et al., 2008a; Chong et al., 2008b), and chiko/sapota (Manilkara zapota L.; Chong et al., 2009), among others (Rocha and Melo, 2011). Hence, there is a trade-off between sun exposure (fast drying) and shade applications (reduced deterioration of active substances), while certainly a mix of both strategies might be interesting for sea buckthorn, particularly under tough weather conditions and limited infrastructure such as in Gilgit-Baltistan.

3.5.3 Sea Buckthorn Supply Chain The sea buckthorn supply chain linking local farmers/collectors of Gilgit-Baltistan with the global market has to our knowledge not been well studied. Operational in an informal market context, communication and coordination among the respective supply chain actors appeared as the driving factor for the related activities along the supply chain. The communication primarily remains informal. This

may be justified in the context of relationship-based business environments evident in such contexts (London and Hart, 2010). In the absence of formal market regulatory bodies, informal institutions such as kinship, family relationships, and community pressures are primarily used to organize supply chain relationships (Vachon and Klassen, 2006). Active communication among the buyers and suppliers leads to the creation of inclusive business opportunities and integration of suppliers (farmers). The supplier integration is evident on two fronts—logistical and technological. The logistical integration of buyers and suppliers is evident in the form of such practices as coordination on fruit pick-up time to decrease post-harvest storage time, transportation, and warehousing. Since no substantive technologies are used along the sea buckthorn value chain, the technological integration remains confined to the use of mobile phones for better communication among the dyadic actors and use of the sun-drying technique to lower down moisture content of berries. A strategic purchasing construct representing long-term orientation of buyers, while making purchasing-related decisions, comes next. Supplier integration serves as an antecedent to strategic purchasing and shows that the buyers take on board the suppliers with whom they have integrated on a technological and logistical end, while making long-term purchasing decisions. Stakeholder engagement appears last in this model which remains somewhat hard to justify, since the construct would ideally be an antecedent of supply chain activities in the background of informal markets. Nevertheless, the importance of stakeholders, particularly non-traditional stakeholders, has been observed during field research and depicted in the model. Missing infrastructure appeared to be a significant challenge affecting the efficiency of the local businesses at large. Furthermore, the institutional voids (Parmigiani and Rivera-Santos, 2015), particularly of financial institutions, keep the respective actors short of the capital required for upgrading their supply chains with the establishment of cold storage facilities and packaging units. Both are vital for reducing post-harvest losses and international marketing. Equitable distribution of value generated among the respective actors remains a challenge in the sea buckthorn supply chain. Uneven distribution of rents generated de-incentivize supply chain actors to make their business operations more efficient. Mechanisms have yet to be developed to safeguard the interests of vulnerable supply chain actors (farmers) in the context of the evident power asymmetries along the value

chain (Schippmann et al., 2002; Hamilton, 2004; Kala et al., 2006; Larsen and Olsen, 2007; Mahapatra and Tewari, 2005).

3.6 Conclusions Local collectors of sea buckthorn berries were unaware of effective, yet sustainable, harvesting/drying techniques that preserve the quality for the harvested fruits. There is an urgent need to set quality standards for the market and encourage fair trade of sea buckthorn. Current sun drying of berries is inappropriate as vitamin C concentrations drop dramatically, which calls for effective extension activities such as drying facilities. Establishing collector collectives and using simple, appropriate solar dryers could minimize these losses. As value added product sales are beneficial but limited to regional markets, there is a need for the expansion of value-added products to national local markets. This would also allow collectors to be more independent from agents, or on the contrary, develop strong, fair, and lasting relationships. The implementation of Fair-Trade Standards, Wild Collection, or Geographical Indication labels may foster the production and marketing of a unique and regional produce. To further assess the potential of sea buckthorn production and marketing in Pakistan, it may be worthwhile to conduct cross-border studies with China and India that cultivate the species in similar agro-ecological conditions but under different socio-economic and political settings.

Acknowledgments: We thank the German Federal Ministry for Economic Cooperation and Development (BMZ) for funding this study through a scholarship of the German Academic Exchange Service (DAAD) to the first author in the context of bulk funding to the International Center for Development and Decent Work (ICDD) at the University of Kassel as part of the EXCEED initiative. We thank Stefan Seuring for his scientific support and Mahmood Salam for his assistance in data collection. We are also indebted to our respondents in Gilgit-Baltistan and government and NGO initiatives such as the Agar Khan Rural Support Programme (AKRSP), which greatly facilitated our study.

3.7 Appendix

Table A3.1 Reliability test of the sustainable supply chain management constructs (SSCM) and their corresponding factors for interviewed households (collectors, n = 45; commission agents, n = 17) during 2017–2018 in Gilgit-Baltistan, Pakistan. No. Items/Factors Loadings Cronbachʼs α CR AVE

Stakeholder Engagement (SE) Take on board other supply chain actors while 1 0.908 making business decisions Share business-related information with other 2 0.910 supply chain actors Government and non-government organizations 0.858 0.904 0.704 3 (NGOs) provide relevant support for business 0.722 development Supplier/colleagues share business-related 4 0.801 information with you

Long-Term Relationship (LR) 1 Do business together for a long time 0.027 2 Crucial time agent stands with collector 0.753 3 Harvester committed to fulfill demand 0.139 0.322 0.354 0.224 Good mutual understanding for business 4 0.711 expansion Kinship/friendship is a basic trust tool for 5 −0.171 business

Technology Integration (TI) 1 Record keeping books used in business process 0.777 Mobile phones are the main source for business 2 0.864 dealings Payments are done through online bank 3 0.789 0.850 0.900 0.692 transactions Mobile phones are the main source for 5 communication with business 0.893 suppliers/colleagues

Logistics Integration (LI) 1 Face transportation/logistic problems 0.657 2 Sharing same logistic resources 0.649 Supplies reached warehouses on time at other 3 0.832 destinations 0.765 0.842 0.518 4 Quality deteriorates during transportation 0.721 Smooth flow of material and information from 5 0.731 suppliers to buyers

Strategic Purchasing (SP) 1 Multiple purchasers’ selection is done for selling 0.943 Strategic purchasing can play an important role 2 0.956 0.951 0.968 0.911 for future business sustainability 3 Purchasing as a tool of competition 0.965

Supplier Integration (SI) 1 Meet regularly with suppliers/colleagues 0.703 0.778 0.858 0.602 Capacity building and training are given to 2 0.841 suppliers Information regarding supply, demand, quality, 3 0.783 and price is shared Suppliers have rights in business planning 5 0.770 decisions

Communication and Coordination with

Suppliers (CCS) Good communication and coordination with 1 0.892 business-related 2 Information shared with suppliers 0.906 Information shared timely and frequently for 0.897 0.925 0.712 3 0.911 supplier business betterment 4 Market-related information is shared 0.710 5 Demand invoices are shared 0.783

CR: composite reliability, AVE: average variance extracted.

Table A3.2 Path coefficient (β) and T-statistics of the predicted model.

Hypothesized Path β T-statistics p-value Logistics integration -> Supplier integration 0.060 4.844 <0.001 Supplier integration -> Technology integration 0.097 5.384 <0.001 Strategic purchasing -> Stakeholder engagement 0.074 8.269 <0.001 Supplier integration -> Strategic purchasing 0.076 8.923 <0.001 Communication and coordination -> Supplier integration 0.054 13.302 <0.001

Table A3.3 Latent variable correlation between the SSCM constructs. CCS LI SP SE SI TI Communication and coordination (CCS) 1.000 Logistics integration (LI) 0.591 1.000 Strategic purchasing (SP) 0.654 0.530 1.000 Stakeholder engagement (SE) 0.749 0.522 0.624 1.000 Supplier integration (SI) 0.895 0.717 0.667 0.756 1.000 Technology integration (TI) 0.535 0.386 0.310 0.448 0.535 1.000

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Chapter 4 - Pheno-genetic studies of apple varieties in northern Pakistan: A hidden pool of diversity?

The contents of this chapter have been published in Scientia Horticulturae 2021, 281, 109950; https://doi.org/10.1016/j.scienta.2021.109950

Pheno-genetic studies of apple varieties in northern Pakistan: A hidden pool of diversity? Martin Wiehlea,b ‡, Muhammad Arslan Nawaza ‡, Richard Dahlemc, Iftikhar Alamd, Asif Ali Khane, Oliver Gailingf, Markus Muellerf, Andreas Buerkerta a Organic Plant Production and Agroecosystems Research in the Tropics and Subtropics, University of Kassel, Steinstrasse 19, D-37213 Witzenhausen, Germany; [email protected]; [email protected] b Center for International Rural Development (Tropenzentrum) and International Center for Development and Decent Work (ICDD), University of Kassel, Steinstrasse 19, D-37213 Witzenhausen, Germany c Pomologenverein, Landesgruppe Rheinland-Pfalz/Saarland/Luxemburg, Im Hopfengarten 1, D-54295 Trier, Germany; [email protected]; [email protected] d Agriculture and Food Technology, Karakoram International University, Main KIU Road, 15100 Gilgit, Pakistan; [email protected] e Plant Breeding and Genetics, Muhammad Nawaz Shareef University of Agriculture, 66000 Multan, Pakistan; [email protected] f Forest Genetics and Forest Tree Breeding, Georg-August University of Göttingen, Büsgenweg 2, D-37077 Göttingen, Germany; [email protected]; [email protected] ‡ Equal contribution

4.1 Abstract Apple (Malus × domestica) is a main fruit crop of cold temperate regions and traded globally. Despite being a comparatively well documented plant cultigen, available germplasm in many remote regions is still unexplored and threatened. Increasing market demands for modern varieties and farmers’ preference for high yields currently lead to the gradual loss of local and indigenous varieties. Gilgit-Baltistan in northern Pakistan – a mountainous and remote apple growing region – was selected to study local cultigens’ diversity by assessing varietal richness and diversity, arboriculture activities as well as phenotypic and genotypic characters of available germplasm. In total, 106 individual apple trees were sampled, and 35 tree owners were interviewed from seven villages of the two valleys Ishkoman and

Baltistan. Dendrometric parameters, fruit traits (qualitative and quantitative), and varietal diversity in each village were measured. Genetic variation was estimated with eleven SSR markers and synonyms and homonyms were identified based on cluster analyses. Sixty-one multi-locus genotypes (MLG; mean genotype diversity: 58%) and 18 putative clones (comprising 2 to 9 ramets) were identified. Varietal diversity was highest in Baltistan where even a wild apple relative (Malus baccata) was discovered.

Mean genetic diversity was moderate (He = 0.677), while negative inbreeding coefficients indicated excess of heterozygotes in three genetic clusters. A moderate correlation (r = 0.627, p = 0.001) between phenotypic and genetic dendrograms suggested genetically linked fruit traits, which merits further exploration. Considering the high genetic and phenotypic variability, Gilgit-Baltistan appears a promising source of apple germplasm for future breeding programs. The promotion of local varieties may allow farmers to diversify their produce and sources of income as well as to maintain a historically important biological heritage of Gilgit-Baltistan. To this end comprehensive conservation strategies and combined with participatory research will be needed.

Keywords: α-diversity, β-diversity, Dendrogram, Genetic diversity, Gilgit-Baltistan, Homonym, Microsatellite, SSR, Synonym, Tanglegram, Varietal diversity, Varietal richness

4.2 Introduction Apple (Malus × domestica Borkh.) is an important perennial fruit crop of the Rosaceae and widely spread across temperate climates of the world (Folta and Gardiner, 2009; Höfer et al., 2014). This cultigen originated most likely from the Tien Shan Mountains in Central Asia (Kazakhstan, Kyrgyzstan, Uzbekistan, Turkmenistan, and Tajikistan) and diffused through trade routes to other parts of Asia and Europe, while introgressing with other apple species (Cornille et al., 2014). Apples grow well in regions with average winter and summer temperature of -5 °C and 15 °C, respectively (Luton and Hamer, 1983). Gilgit-Baltistan (GB), located in the northern Karakoram Mountain region of Pakistan, climatically at the fringe of Central Asia and about 500 km beeline away from the supposed distribution center of the wild apple relative M. sieversii, hosts a large pool of plant genetic resources including cultigens such as apple for which it provides

suitable climatic and agricultural niche conditions (Khan et al., 2011). GB is characterized by long sun hours (Whiteman, 1985), low humidity, and abundant melt water from glaciers diverted through traditional karez irrigation systems (Figure A4.1a). Ninety-five percent of the population in GB directly depends on agriculture by doing subsistence farming within an extended family system (World Bank, 2011). In 2014, total fruit production amounted to 2,402.450 t (apricot 1,209.734 t, apple 370.117 t, cherry 155.772 t, mulberry 141.723 t, almond 123.791 t, walnut 122.973 t, grape 120.884 t, pomegranate 75.746 t, peach 41.061 t, and pear 40.648 t; Anonymous, 2014). Hence, in terms of quantity, apple is the second most essential agricultural product in the region. Local farmers receive 50% of the agricultural household income from fruit trees, which is thus also a major source of cash income (UNPO, 2015). Apple in GB has likely been introduced through trade along the Silk Road many centuries if not millennia ago, resulting in a pronounced varietal richness of this cultigen assembled in orchards and home gardens. This varietal richness also reflects the effects of generations of human selection in an extreme environment resulting in phenotypic differentiation, while preferred traits are maintained through vegetative propagation, as typically performed in GB (JICA, 2017). In recent years, GB’s local apple diversity is increasingly threatened. Due to the remoteness and weak research infrastructure in GB, its apple diversity has been largely neglected and it is unknown how many of the indigenous apple cultivars are currently preserved in any of the regional or worldwide germplasm banks. The most important driver of local apple extinction nowadays, is a successive substitution of local varieties by recently imported, well-known modern varieties such as ‘Red Delicious’, ‘Golden Delicious’, ‘Jonathan’, ‘McIntosh’ or ‘Cox’s Orange Pippin’ (Urrestarazu et al., 2016). These exhibit easily marketable traits such as sweetness, low bitterness and sourness, large size, and a homogenous colour. Their promotion also in GB has led to a massive varietal standardization of orchards (Gross et al., 2012), narrowing the traditional gene stock as predicted by Whiteman (1985) already decades before. Some rare varieties are thus likely in danger of extinction. Also, the degree of gene flow from modern to local varieties is an unknown component which may lead to losing genetic integrity of local apple varieties (Spengler, 2019). Moreover, pre- and post-harvest losses of fruits between 40% and 60% due to unskilled labourers as well as lack of disease management, proper packaging systems, and transportation

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facilities (Khan et al., 2019) affect apple farmers’ revenues and hamper progressively their willingness to further plant and cultivate local varieties. Hence, the decline in local production and the orphanage of non-profitable traditional orchards – sometimes triggered by decreasing or seasonal melting water availability (Figure A4.1b) – affects varietal richness and may jeopardize the strategy “conservation through use”. Local apple varieties, however, often demonstrate resistance to biotic and abiotic stress for instance to powdery mildew (Evans and James, 2003) and to drought (Tworkoski et al., 2016). As GB’s unexplored apple diversity may serve as pool for such potentially valuable and important traits (JICA, 2017), the quantification, characterization, and discrimination of local apple varieties based on a multidisciplinary approach is key to assess their distribution and status. In addition, particularly remote regions with multi-ethnic backgrounds, as valid for GB, are numerically rich in traditional varieties exerting the same local names (~homonyms), same varieties with different local names (~synonyms), and even unknown varieties (Hend et al., 2009; Rao et al., 2010). To untangle this complex assemblage and unknown amount of true varieties, the well-suited, yet rare approach of measuring alpha (α-) and beta (β-) diversity in combination with varietal richness offers the possibility to compare diversity across spatial scales (Crist et al., 2003). Studying and identifying locally used plant genetic resources in existing populations is of advantage because of its easiness of screening a large set of individuals in a short time rather than establishing, conducting, and monitoring long-term breeding and selection programs. The application of genetic tools to analyse traditional varieties further enhances our scientific understanding of diversity across scales and may in addition add to the knowledge on migration histories of this cultigen. For this purpose, simple sequence repeat (SSR) markers are predominately used for genetic diversity analyses in apple and 8 to 24 markers are considered sufficient for this purpose (Liang et al., 2015; Urrestarazu et al., 2016). The aforementioned facts hence call for swift action to assess the distribution, phenotypic and genetic diversity as well as current use of traditional apple varieties in the region. Therefore, this study aims at i) examining dendrometry depending on management, ii) compare varietal richness and diversity of apple in differently distant villages, and iii) assess phenotypic and genetic variation among varieties and regions. This will allow to adopt site-specific management plans, to preserve this rich source of

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unrecognized varieties, including hidden and promising genes, and to pave the road for future domestication and conservation strategies.

4.3 Materials and Methods 4.3.1 Study site, plant material, and owner interview The study was carried out between September and October 2018 in Gilgit- Baltistan, the Karakoram Mountains of northern Pakistan at an altitudinal range of 1912 m to 2724 m (Table 4.1, Figure 4.1). A total of seven villages along an upstream chain were selected in two dead-end valleys. Baltistan Valley comprises part of Shigar Valley and Skardu Valley having Bisil, Tisar, Hashupi, and Kachura; and Ishkoman Valley having Imit, Chatorkhand, and Golodass (Table 4.1, Figure 4.1). The dead-end valley approach was established as we assumed that introduction of plant genetic materials occurs from its lower reaches (main trading roads, markets), rather than across steep mountain passes. Exhaustive snowball sampling was performed to select all local accessions of apple in a village, resulting in a minimum of five households per village, which maintained local varieties. Every variety (and every individual of every variety per household) was sampled (n = 98) until a new variety was identified or at least considered morphologically different from all sampled specimen so far. Moreover, samples (n = 8) of available local varieties in two governmental nurseries (Dept. Skardu and Dept. Thowar) were also collected as reference materials resulting in a total of 106 individual trees and 108 leaf samples (two trees contained one grafted variety each; Table 4.1). The exact location of all individuals was determined with a hand-held GPS device (Garmin-eTrex 30, horizontal accuracy ± 2 m, GARMIN® Ltd., Southampton, UK). Leaf samples were collected in tea filter bags and air-dried for genetic analysis (see below). Three pre-designed questionnaires were used in the field comprising individual i) dendrometric traits (tree dimensions and status – questionnaire A4.1) and fruit phenotypic traits including ii) a qualitative phenotypic description – questionnaire A4.2 and iii) a quantitative phenotypic data – questionnaire A4.3.

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Figure 4.1 Map of the studied villages used for local apple varieties collection in the Gilgit- Baltistan region, Karakoram Mountains, northern Pakistan. The remoteness of villages is indicated by the distance from the main roads (source: DIVA-GIS, www.diva-gis.org/gdata, accessed 28 January 2020).

Table 4.1 Average geographical coordinates and number of interviewed tree owners, their corresponding sampled trees, and varieties per village and nursery in seven villages of two valleys in Gilgit-Baltistan, Karakoram Mountains, northern Pakistan between September and October 2018.

Number of Villages/Govt. Elevation, Region trees Longitude E Latitude N nurseries interviewed m.a.s.l. trees with fruit tree owner samples Bisil 5 26 13 35.869392 75.4061 2724 Tisar 5 16 1 35.608169 75.5035 2400 Hashupi 5 16(+1) 4 35.453196 75.7217 2258 Kachura 5 14 6 35.439487 75.4496 2282

Baltistan Dept. Skardu - 4 4 35.297757 75.6337 2190 Dept. Thowar - 4 3 35.601074 75.2100 2379 Imit 5 5 1 36.507595 73.9116 2722 Chatorkhand 4 7 2 36.361559 73.8557 2204 Golodass (near Gilgit Gahkuch) 6 14(+1) 3 36.214992 73.7464 1912 Total 35 106(+2) 37 n (+1): in two cases, two leaf samples (rootstock + scion) were collected from one tree each

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4.3.2 Dendrometry, management, and use Height (m) of the tree was measured by intercept theorems. Stem girth (cm) at breast height or at base in case of deep canopy branching were determined with the help of a measuring tape and subsequently recalculated to the stem diameter. Canopy diameter (m) was recorded at the widest point. Other bio-physical conditions and management related information of an individual included self-assessed vitality, visibility of grafting spots, visibility of diseases and pest attacks, and agricultural settings (fodder field, agricultural land, house yard, forest or orchard). Also recorded were owner’s response about age, grafting history, uses, tree management, and fruit storage (questionnaire A4.1).

4.3.3 Fruit phenotypic description and phenotype Depending on the availability of fruits, up to ten fruits per sampled variety were randomly collected. Only clearly distinguishable phenotypes were used for fruit phenotypic description resulting in 37 fully characterized tree samples (35% of all sampled trees; Table 4.1). Qualitative fruit characters were based on the phenotypic fruit descriptor (questionnaire A4.2). Quantitative fruit phenotypic parameters comprised weight (g) and size measures (in mm each): fruit width and height; from the calyx side - pit depth, width, sepal width and length; from the petiole side - pit depth, petiole length, petiole thickness; cross section - calyx tube width (if present) and axis pit width; pippins – number, length, and width (questionnaire A4.3).

4.3.4 DNA isolation and SSR analysis Total genomic DNA was extracted using the DNeasy™ 96 Plant Kit (Qiagen GmbH, Hilden, Germany) from each of the 106 leaf samples. Literature was reviewed and colleagues from Marburg (Conservation Biology, Phillips-University of Marburg) were consulted for suitable, consistent and commonly used microsatellite markers (SSR), resulting in a total of sixteen screened SSRs. Out of these, eleven highly polymorphic SSR markers were used in this study (Table 4.2; Liebhard et al., 2002), eight of these were also applied by Urrestarazu et al., 2016.

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Table 4.2 Genetic diversity and differentiation of 11 SSR markers (Liebhard et al., 2002) applied on DNA of local apple samples from seven villages in two valleys of Gilgit-Baltistan, Karakoram Mountains, northern Pakistan.

Linkage groups Size range SSR Primer sequence (5'-3') Na He Ho FIs (bp) F: ACCACATTAGAGCAGTTGAGG Ch01f02 12 167-241 13 0.613 0.723 -0.145** R: CTGGTTTGTTTTCCTCCAGC F: GAGAAGCAAATGCAAAACCC Ch01f03b 9 139-246 13 0.729 0.938 -0.173 R: CTCCCCGGCTCCTATTCTAC F: TTATGTACCAACTTTGCTAACCTC Ch02c09 15 233-277 11 0.739 0.951 -0.166* R: AGAAGCAGCAGAGGAGGATG F: TCCAAAATGGCGTACCTCTC Ch02d08 11 200-275 11 0.684 0.803 -0.067*** R: GCAGACACTCACTCACTATCTCTC F: TCCCGCCATTTCTCTGC GD147 13 133-172 11 0.678 0.805 -0.061* R: GTTTAAACCGCTGCTGCTGAAC F: GACGCATAACTTCTCTTCCACC Ch03a04 5 152-223 13 0.738 0.968 -0.191*** R: TCAAGGTGTGCTAGACAAGGAG F: AGGCTAACAGAAATGTGGTTTG Ch04e05 7 164-251 13 0.682 0.744 -0.028** R: ATGGCTCCTATTGCCATCAT Ch05e03 F: CGAATATTTTCACTCTGACTGGG 2 92-138 14 0.555 0.644 -0.089*** R: CAAGTTGTTGTACTGCTCCGAC F: GGCCTTCCATGTCTCAGAAG Ch04c07 14 174-222 14 0.667 0.751 0.001*** R: CCTCATGCCCTCCACTAACA F: CCCTACACAGTTTCTCAACCC Ch01f07a 10 180-250 13 0.680 0.796 -0.083*** R: CGTTTTTGGAGCGTAGGAAC F: CAAATCAATGCAAAACTGTCA Ch03d07 6 97-162 14 0.685 0.807 -0.110*** R: GGCTTCTGGCCATGATTTTA Mean 13 0.677 0.812 -0.101 Na—number of alleles; He—expected heterozygosity; Ho—observed heterozygosity; FIS—fixation index; * p < 0.05, ** p < 0.01, *** p < 0.001

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M13-tailed forward primers and dye labelled M13 primers were employed to design four different multiplexes depending upon the polymerase chain reaction (PCR) product sizes. The PCR amplifications were performed in a total volume of 13 μL, containing 1 μL of genomic DNA (about 10 ng), 1X reaction buffer (0.8 M Tris-HCl pH 9.0, 0.2 M (NH4)2SO4, 0.2% w/v Tween-20; Solis BioDyne, Tartu, Estonia),

2.5 mM MgCl2, 0.2 mM of each dNTP, 0.3 μM of each forward and PIG-tailed

(Brownstein et al., 1996) reverse primer, M13 dye labelled forward primer and 1 unit of Taq DNA polymerase (HOT FIREPol® DNA Polymerase, Solis BioDyne OÜ, Tartu, Estonia). The amplification protocol was as follows: an initial denaturation step at

95 °C for 15 min, followed by 10 touch-down cycles at an annealing temperature (Ta) of 60 °C (-1 °C per cycle) and 25 cycles at 50 °C. Each cycle consisted of one denaturing step at 94 °C for 1 min, an annealing step at Ta for 1 min, and an extension step at 72 °C for 1 min. A final extension step at 72 °C for 20 min ended the program. Reproducibility was checked by repeating positive (from University of Marburg, Germany) and negative controls in all reaction plates. The PCR fragments were separated and sized on an ABI 3130xl Genetic Analyzer (Applied Biosystems Inc., Foster City, CA, USA). The GS 500 ROX (Applied Biosystems Inc.) was used as an internal size standard. The genotyping was done using the GeneMapper 4.1® software (Applied Biosystems Inc.). To evaluate the performance of the applied marker set, we extracted marker-characteristics from available studies (Table A4.1).

4.3.5 Data analysis All phenotypic, varietal, and parts of the genetic data were analysed using R (version 3.3.3, R core team, 2017, Vienna, Austria). Means and coefficient of variation (CV%) for dendrometric and fruit phenotypic traits per variety were calculated. The varietal richness and abundance were counted within and across village(s), while varietal alpha (α) diversity (based on the Simpson index and Pielou’s evenness) was estimated using the ‘vegan’ package (Dixon, 2003). According to the varietal composition per village a hierarchical cluster was created from varietal diversity data using Chord distance and a contiguity-constrained segmentation method (Legendre and Legendre, 2012). The β- diversity for each node of the dendrogram was calculated by weighting proportionally all putative varieties within the corresponding sub-cluster to their total abundance (Ricotta, 2017). The beta contribution (%β) of each variety was estimated per village and valley, respectively.

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MICRO-CHECKER (Van Oosterhout et al., 2004) was used to test and correct for potential genotyping errors due to stuttering, large-allele dropout, and null-alleles. Deviations from the Hardy-Weinberg equilibrium (HWE) based on χ2-tests for each locus and village were calculated again with GenAlEx 6.5. Genetic diversity parameters such as percentage of polymorphic loci, the number of alleles per locus

(Na), the number of effective allele (Ne), the number of private alleles, and expected

(He) and observed (Ho) heterozygosity were determined for each village and valley with GenAlEx 6.5 software (Smouse and Peakall, 2012). To account for differences in sample size, allelic richness was calculated with the HP-Rare program 1.0 (Kalinowski, 2005). Moreover, to potentially identify kinship across samples, the mismatch function in GenAlEx was applied to synthesize all multi-locus genotypes which was further used to determine genotype diversity (Arnaud-Haond et al., 2007) in each village and valley. The goodness of the number of markers applied was evaluated with the probability of identity of unrelated (PID) or related (PIDsib) individuals and computed based on the distribution of allele frequencies in villages and valleys samples (Table A4.2). Further calculations included Mantel tests to examine the isolation-by-distance (IBD) by comparing pairwise geographical distance and standardized genetic differentiation

G’ST (Hedrick, 2005) and analysis of molecular variance (AMOVA) to analyse differentiation between villages and valleys, each with 999 permutations using ΦST.

Both village and valley-wise fixation indices (FIS) and their significance were tested with 10,000 dememorization, 20 batches and 5000 iterations per batch for the Markov chain parameters in Genepop 4.7 software (Rousset, 2008). The genetic clusters (K) were inferred using a Bayesian hierarchical clustering algorithm implemented in the STRUCTURE 2.3.4 software (Pritchard et al., 2000). The admixture model with correlated allele frequencies and a burn-in period of 10,000 with 100,000 Markov Chain Monte Carlo (MCMC) replicates were used. We tested from 1 to 12 possible clusters (K), using 10 iterations each. The most likely number of K was determined with the software STRUCTURE-HARVESTER (Earl and vonHoldt, 2012), considering K with the highest value of ΔK and the lowest value of mean posterior probability of the data (LnP(K)) (Evanno et al., 2005). A dissimilarity matrix was created based on fruit traits (only completely available quantitative and qualitative data (coded and converted into dummy variables) for 37 individuals were considered) using the Gower distance embedded in the ‘daisy’

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package (Kaufman and Rousseeuw, 2005). Using the same approach, allelic data were used to estimate Rogers’ Euclidean distance with ‘poppr’ package (Kamvar et al., 2014) to construct a genetic dendrogram using the Ward method (Murtagh and Legendre, 2014) for the same 37 (s. above) and all 106 individuals. For the latter, the genetic cluster information served to quantify putative homonyms, synonyms, and unique accessions (Figure 4.6; Table A4.3). Finally, goodness of fit for both phenotypic and genetic distances (n = 37, each) were evaluated with a Mantel test and dendrograms were graphically merged into a tanglegram using the ‘dendextend’ package (Kaufman and Rousseeuw, 2005). As hierarchies for the different distance measures calculated and resulting dendrograms are based on different distance measures, so called cophenetic correlation matrices were created that are based on the dendrograms themselves by running a Mantel test again using ‘vegan’ package (Dixon, 2003). The resulting cophenetic correlation coefficient – a statistical index to quantify the degree of similarity between matrices – served to evaluate the goodness of the tanglegram. The number of clusters for the phenotypic as well as genetic dendrogram was assessed by applying the elbow criteria method embedded in the ‘factoextra’ package (Kassambara, 2017).

4.4 Results 4.4.1 Varietal diversity Among all accessions, 32 local variety names plus one wild apple species of the Siberian crab apple (Malus baccata (L.) Borkh.) were recorded. Richness and diversity measures differed largely between valleys. On average, α-diversity was higher in villages of the Baltistan Valley as compared to the Ishkoman Valley and highest for Hashupi followed by Bisil, Tisar, Kachura, Chatorkhand, Golodass, and Imit (Table 4.3). Three main compositionally distinct clusters were formed based on the beta diversity among villages (Figure 4.2).

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Figure 4.2 Dendrogram for 97 apple individuals (nursery reference material and one individual of Malus baccata was excluded from the analysis) in seven villages of two valleys in the Gilgit-Baltistan region, Karakoram Mountains, northern Pakistan with contiguity constraint abundance values based on Chord distance (Table 4.3). The corresponding β-diversity value is shown for each node. Overall β-diversity is 0.743.

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Table 4.3 Relative abundances and contribution of each apple variety to overall α- and β-diversity among villages and pooled valleys, surveyed in seven villages of two valleys in Gilgit-Baltistan, Karakoram Mountains, northern Pakistan, between September and October 2018.

Villages/Valleys %β Varieties ∑ ∑ Bisil Tisar Hashupi Kachura Imit Chatorkhand Golodass villages valleys Baltistan Ishkoman Kachura Ambary 1 5 6 6.4 6.2 Safaid Kachura 2 2 2.8 2.1 Ambary Sas Polo 3 2 5 4.5 5.2 Shakkar 4 4 3 4 15 6.1 15.5 Quetta Amry 1 1 2 1.8 2.1 Bong Kushu 4 3 7 6.3 7.2 Boo Kushu 2 1 3 2.8 3.1 Nuri Kushu 2 2 2.8 2.1 Za Kushu 3 3 4.2 3.1 Ambary Kushu 3 2 5 4.5 5.2 Skire Kushu 4 1 1 6 4.6 6.2 Kho Kushu 1 1 2 1.8 2.1 Mar Kushu 1 1 1.4 1.0 Sumerqand 1 1 2 1.8 2.1 Skirmu Kushu 2 2 2.8 2.1 Dyan Kushu 1 1 1.4 1.0 Oanh Kushu 1 1 1.4 1.0 Unknown 2 2 2.8 2.1 Normu Kushu 1 1 1.4 1.0 Nas Kushu 1 1 1.4 1.0 Karismin 1 1 1.4 1.0 Wardap 1 1 1.4 1.0 Desi Loop Moor 5 5 6.9 5.2 Frances Paloo 1 1 1.4 1.0

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Mamu Balt 1 3 4 3.9 4.1 Khushwati 1 1 1.4 1.0 Isdop 1 1 1.4 1.0 Shakar Paloo 3 3 4.2 3.1 Shikam Balt 2 2 2.8 2.1 Loqman 1 1 1.4 1.0 Shakoor Balt 1 1 1.4 1.0 Gohar Aman 6 6 8.3 6.2 Aliqan Balt 1 1 1.4 1.0 Simpson 0.877 0.851 0.882 0.745 0.911 0 0.735 0.735 0.858 index α Richness 10 9 11 5 22 1 5 6 11 diversity Pielou’s 0.381 0.387 0.368 0.463 0.295 - 0.456 0.41 0.358 Evenness The valleys were pooled in a separate column. The last two columns show the percent contribution (%β) of single variety to overall beta diversity of villages and valleys each. The %β value among villages and pooled valleys differs due to a differing proportional weight of each variety.

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The highest heterogeneity is linked with the upper node of the dendrogram governed by dominant varieties such as Gohar Aman, Desi Loop Moor, Kachura Ambary, and Bong Kushu that account for roughly one-fourth (28%) of the overall β-diversity of villages (Table 4.3). In two cases, farmers grafted a scion of Five Star (a non-local and commercial variety) on Sas Polo and Hunzoo Balt on Gohar Aman each. Some of these local varieties showed high popularity in local village markets (Table A4.4).

4.4.2 Dendrometry, management, and use Almost half (54%) of the individuals were 5 to 45 years old. Plant height averaged 8 m ranging from 2 to 17 m and stem diameter averaged 26 cm (12 to 56 cm) exhibited the highest CV% across all dendrometric traits (Table 4.4). Canopy diameter averaged 7 m (1 to 11 m). Generally, trees found upstream were larger than trees of downstream villages which may reflect age differences. About two-third of the under-tree area was utilized to cultivate fodder and food crops mostly for home consumption. More than half of the sampled trees showed grafting spots (Table 4.5), whereby rootstocks were always local, non-commercial plant materials. Most of these grafting materials were from own or neighbours’ trees and > 40% of the material was brought from different nurseries (Table 4.5) of the respective valley. Fifty-eight (59%) individual trees showed full vitality while almost 31% of the individuals had symptoms of disease or nutrient deficiency (Table 4.5). Most orchards were characterized by too dense planting distances that do not allow for an efficient utilization of water and sun light. Arboricultural measures were rarely mentioned by the interviewer or observed by the authors; respective equipment such as scissors, pickers, nets, and ladders were not present and pruning activities were restricted to the cut of main branches. Tree bark was only occasionally protected against browsing through thorny branches or cloths wrapped around the stem.

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Table 4.4 Average dendrometric traits of the local apple varieties collected from seven villages in two valleys of Gilgit-Baltistan, Karakoram Mountains, northern Pakistan between September and October 2018.

Varieties Dendrometry n Height Stem Canopy diameter (m) diameter (cm) (m) Aliqan Balt 1 4 22 6 Ambary Kushu 5 10 32 8 Bong Kushu 7 9 27 7 Boo Kushu 3 7 17 5 Desi Loop Moor 5 7 32 7 Dyan Kushu 1 12 13 8 Frances Paloo 1 7 41 2 Gohar Aman 6 6 24 6 Isdop 1 6 29 4 Kachura Ambary 6 9 28 8 Karismin 1 6 24 5 Kho Kushu 2 8 15 5 Khoju* 1 13 47 10 Khushwati 1 6 29 4 Loqman 1 5 20 6 Mamu Balt 4 6 20 6 Mar Kushu 1 10 18 4 Nas Kushu 1 13 54 9 Normu Kushu 1 14 36 11 Nuri Kushu 2 6 28 7 Oanh Kushu 1 2 15 1 Quetta Amry 2 6 22 6 Safaid Kachura Ambary 2 11 21 8 Sas Polo 5 9 27 7 Shakar Paloo 3 7 23 7 Shakkar 15 9 27 8 Shakoor Balt 1 4 12 4 Shikam Balt 2 6 20 7 Skire Kushu 6 8 28 6 Skirmu Kushu 2 9 25 7 Sumerqand 2 5 13 5 Unknown 2 10 23 8 Wardap 1 17 39 10 Za Kushu 3 12 45 9 Grand mean/Total 98 8 26 7 CV% 34 44 37 SD 3 37 3 *Bold indicated the wild relative (Malus baccata) found in one of the villages; n—number of individuals per variety; CV%— coefficient of variation; SD—standard deviation

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Table 4.5 Descriptive statistics about self-assessed tree status (n = 98) and owner’s response (n = 35) about history, uses and management of apple trees in seven villages of two valleys in Gilgit-Baltistan, Karakoram Mountains, northern Pakistan between September and October 2018.

Variable Groups/classes Frequency (%) Self-assessed Visible 66 Grafting spot Not visible 34 High 59 Vitality Moderate 39 Low 2 No disease 61 Disease 14 Visible disease and pest attack Insect attack 8 Nutrient deficiency 16 Fallow 10 Cropping area 31 Fodder field 35 Under tree usage Forest 3 House yard 18 Orchard 3 Owner's response Yes 69 Grafting history No 27 Do not know 4 Nursery (within a valley) 41 Local source (neighbour, Tree brought from 47 other villages) Do not know 12 Home consumption 84 Animal feed 3 Fruits used for Both 9 Nothing 4 Yes 37 Selling No 63 Cartoon box 5 Willow basket 11 Storage material Wooden box 28 Loose on the ground 39 Pick and use 17

Harvesting of apple fruits was done by climbing up the tree and picking fruits. Almost 60% of the apple trees were reported to show alternate fruit bearing behaviour varying from 50 to 150 kg per tree (Table A4.4). The recognition of the correct harvest time seems also a problem as some farmers harvested too early or too late. Fruits were largely used for home consumption, while only a few households processed fresh fruits to make chips, powder, and jams. Others used the fruits for sale (Table 4.5) or stored them as animal feed (field observation). Almost half (44%) of the fruit yield was

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stored in cartoon or wooden boxes as well as willow baskets (Table 4.5). A high proportion of fruits showed signs of physical damage as well as insect or disease infection (Table 4.5, Figure A4.1c).

4.4.3 Fruit phenotype Fruit weight ranged from 18 to 142 g with grand mean of 73 g (Table 4.6). The highest fruit weight was measured for a variety called Shikam Balt having an oval fruit shape and the thickest fruit petiole of 3.3 mm collected from Golodass, while the smallest fruit was recorded with 31 × 35 mm for Skire Kushu (Table 4.6; Figure 4.3). Fruits from local varieties were generally smaller than of commercial cultivars (pers. observation). The smallest fruit size was measured for a unique find of the Siberian crab apple in Bisil (Figure 4.3). The minimum and maximum petiole length was 6 and 32 mm, respectively. The longest petiole was found for Za Kushu, which was very sour in taste (Figure 4.3). We discovered a number of varieties with distinct features such as long petioles (Quetta Ambary, Skire Kushu, Mar Kushu), thick petioles (Shikam Balt, Gohar Aman, Shakkar, Sas Polo), sourness (Khoju – Malus baccata), Za Kushu, Mar Kushu, Skire Kushu), uncommon fruit shape (Aliqan Balt, Wardap), and big size (Shikam Balt, Shakar Paloo, Gohar Aman). The CV% was highest for calyx depth followed by fruit weight, axis pit width, calyx tube width, petiole (depth, length, thickness), calyx leaf width, fruit height, pippin number, fruit width, calyx (width, leaf length), pippin length and width (Table 4.6). Some of the sampled fruits from Bisil had a pronounced fluffy surface and were sour in taste. Basic fruit colour varied mostly from green to bright yellow, whereas yellow green was found only once; strong red (Mar Kushu) and orange (Shikam Balt, Skire Kushu, Za Kushu) coat colour was also rarely found (data not shown). After exposing a fruit intersection for some minutes to air, for most fruits a typical browning started (oxidation of polyphenolic compounds). This browning tended to be more frequent in samples from Baltistan Valley, especially for trees of Bisil village.

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Table 4.6 Average fruit phenotypic traits of local apple varieties collected from seven villages of two valleys in Gilgit-Baltistan, Karakoram Mountains, northern Pakistan, between September and October 2018.

Fruit Calyx Petiole Axis Pippin Varieties code n weight width length depth leaf leaf width tube depth length thick- pit n length width width length width ness width (g) (mm) Ambary Kushu 25,26 2 29 42 36 2.0 1.5 4.8 3.3 - 4 18 1.3 2.5 7 7.8 4.5 Bong Kushu D1 35 1 58 53 43 3.5 1.5 4.5 2.3 - 8 16 1.9 2.1 9 8.8 4.7 Bong Kushu D2 30 1 22 39 33 1.1 1.7 4.9 3.2 - 3 22 1.3 2.1 7 7.4 4.4 Boo Kushu 39 1 68 53 51 2.4 2.2 6.6 5.4 3.0 3 18 2.2 2.6 7 8.0 4.8 Desi Loop Moor 81D 1 82 60 49 4.3 1.9 3.5 2.6 - 9 9 2.0 1.6 6 7.4 4.5 Dyan Kushu 53 1 40 46 40 3.7 1.6 4.7 3.3 - 8 12 1.6 1.4 7 7.4 4.6 Gohar Aman 99 1 131 73 60 9.6 2.0 3.8 3.0 2.7 12 7 3.0 0 6 9.4 5.0 Kachura Ambary 4 1 90 57 61 3.0 2.0 4.6 3.1 - 9 20 1.8 0 4 7.4 4.9 Kachura Ambary R 1,3 2 114 65 61 4.9 1.2 3.9 3.3 - 11 18 1.9 2.2 9 7.7 4.1 Kho Kushu D1 73 1 88 57 52 6.8 1.9 4.7 2.9 - 8 11 2.1 2.6 8 8.4 4.2 Kho Kushu D2 33 1 47 49 45 1.2 1.4 3.4 3.1 1.3 5 17 1.6 2.1 8 6.9 4.7 Mar Kushu 38 1 62 53 46 3.2 1.8 3.9 2.4 - 8 23 1.9 1.6 9 8.6 3.6 Nas Kushu 62 1 50 48 42 3.9 1.6 3.6 2.3 1.4 9 20 1.6 2.0 8 9.4 4.3 Quetta Ambary 9 1 114 62 61 4.2 1.9 5.4 3.6 - 7 32 2.0 0.3 11 9.2 4.6 Safaid Kachura 15 1 89 59 60 4.3 1.0 3.5 3.5 - 10 12 2.0 2.8 7 8.3 3.8 Ambary Sas Polo 14 1 102 64 57 8.2 1.4 4.8 3.1 1.8 12 11 2.0 1.8 7 8.8 5.2 Sas Polo R 2 1 81 57 57 5.3 1.0 3.8 2.7 1.2 8 14 2.8 1.7 9 7.6 4.4 Shakar Paloo D1 92 1 121 69 57 4.9 2.1 3.9 3.8 2.0 10 11 2.0 4.3 8 8.4 4.6 Shakar Paloo D2 90 1 134 68 54 4.7 2.3 4.3 3.7 1.8 13 17 2.3 4.1 10 8.0 4.2 Shakkar D1 10 1 53 50 50 3.0 1.6 4.4 3.6 - 7 20 1.1 4.3 9 6.7 3.8 Shakkar D2 13 1 102 63 60 4.6 1.4 4.7 3.3 - 15 13 2.0 3.7 9 7.2 4.3 Shakkar D3 67 1 115 66 63 10.7 1.7 5.0 3.7 3.5 9 6 3.0 1.7 4 9.7 4.7 Shakkar D4 31 1 34 45 37 2.5 1.3 2.9 2.7 - 5 29 1.2 1.3 9 8.2 3.7 Shakoor Balt 97 1 67 54 48 4.5 2.0 4.0 3.1 1.8 9 25 2.0 2.1 11 8.0 4.4 Shikam Balt 94 1 142 70 59 3.4 2.5 4.1 4.6 2.1 8 12 3.3 1.5 7 8.2 4.6 Skire Kushu D1 37 1 30 42 37 3.1 2.2 5.9 3.5 0.1 4 19 1.8 2.0 8 7.6 4.6 Skire Kushu D2 27 1 18 35 31 1.6 1.8 4.0 3.6 - 3 25 1.0 1.6 9 7.3 4.2 Skire Kushu D3 32 1 35 44 39 1.6 1.2 3.8 2.7 1.1 5 17 1.3 2.2 6 6.8 4.3

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Snow White* R 19 1 91 58 62 3.9 1.0 3.6 2.6 - 10 13 2.0 2.4 7 8.2 4.1 Wardap 74 1 83 60 54 5.0 1.4 5.0 3.0 - 6 20 2.2 2.4 7 9.2 4.8 Za Kushu 24,45 2 21 37 30 0.7 1.2 3.6 2.6 - 3 20 1.2 1.4 7 7.4 3.9 Grand 34* 73 54 49 3.9 1.6 4.3 3.2 1.8 8 17 1.8 2.1 8 8 4.4 mean/Total CV% 52 20 22 59 26 19 20 48 41 36 30 49 22 10 9 SD 38 11 11 2 0.4 0.8 0.6 0.9 3 6 0.6 1 2 0.8 0.4 Name of the varieties with subsequent letter D shows the doubted variety with different characteristics and therefore assigned wrongly to another genetic cluster (see Figure 4.6). Letter R shows the varieties collected from nursery reference material. n—number of individuals per variety; CV%—coefficient of variation; SD—standard deviation. *Four varieties from Thowar nursery were unknown, thus not included in this table and one variety Snow White that is missing in rest of the analysis due to not amplification in genetic samples and also not found in farmer field

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Figure 4.3a-f Examples of one exotic species and local apple varieties collected in seven villages of two valleys in Gilgit-Baltistan, Karakoram Mountains, northern Pakistan between September and October 2018. a) Khoju (Malus baccata), Bisil, small fruits, very sour taste, b) Aliqan Balt; Golodass; irregular fruit shapes, rough surface, very sweet taste, c) Desi Loop Moor; Imit; crooked, bumps, 5-edged; d) Za Kushu; Bisil; long petiole (26-32 mm), very sour taste, e) Mar Kushu; Bisil; strong red coat colour, very sour taste, f) Shikam Balt; Golodass; thick petiole, oval fruit shape

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4.4.4 Genetic diversity and differentiation of markers Out of the 108 leaf samples, two were not amplified, resulting in a total of 106 leaf samples. Overall, 50 alleles were found in the seven villages for the 11 SSR markers. The number of alleles per locus (Na) averaged 13, ranging from 11 to

14 alleles. Observed (Ho) and expected heterozygosity (He) averaged 0.812 (0.644 to

0.968) and 0.677 (0.555 to 0.739), respectively. The mean FIS for SSR markers was -0.101. All loci had negative and significant values except for Ch04c07 and Ch01f03b, respectively (Table 4.2). Overall, the applied marker set revealed a slightly lower genetic variation in comparison to other studies, which on average deviated by up to +55% as well as up to -38% (Table A4.1). A low frequency of null alleles was observed at all loci (data not shown). PID was generally lower than PIDsib, but both parameters were highly correlated (r = 0.93) and expressed values below 0.000032 and 0.0056, respectively (Table A4.2).

4.4.5 Genetic diversity and differentiation of valleys and villages By pooling the villages per valley (Ishkoman and Baltistan), significant deviations from HWE for all loci were observed (data not shown). All loci at Bisil and Tisar village significantly deviated from HWE, except for GD147 and Ch02d08, respectively (Table 4.7). Generally, HWE was lower within than between valleys. Each village (except Imit, also the governmental nursery in Skardu) and valleys were entirely polymorphic for all SSR markers. Genetic richness measures were highest for Chatorkhand and Bisil and lowest for Imit (Table 4.8). The same was true for genetic diversity indices (Table 4.8). Overall, there was no obvious trend within and across valleys. AMOVA revealed highest genetic variation within villages (84%) and valleys (96%), while low among villages (16%) and between valleys (4%; Table 4.9). IBD showed non-significant positive and moderate correlations between and within valleys as well as across villages (Figure 4.4), although within valley IBD correlations were higher.

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Table 4.7 Summary of χ2-tests for Hardy-Weinberg equilibrium per village and nursery according to their geographical origin and microsatellite locus in apple varieties collected from seven villages in two valleys of Gilgit-Baltistan, Karakoram Mountains, northern Pakistan.

Ch01f02 Ch01f03b Ch02c09 Ch02d08 GD147 Ch03a04 Ch04e05 Ch5e3 Ch04c07 Ch1f7a Ch3d7 Villages Df χ2 Df χ2 Df χ2 Df χ2 Df χ2 Df χ2 Df χ2 Df χ2 Df χ2 Df χ2 Df χ2 Bisil 45 78** 55 90** 45 80** 10 43*** 10 16 36 99*** 45 78** 28 74*** 36 85*** 45 85*** 45 77** Tisar 21 54*** 21 60*** 15 37** 10 14 10 33*** 15 51*** 10 21* 6 21** 15 54*** 21 67*** 15 48*** Hashupi 28 26 21 28 28 24 21 31 21 17 55 74* 21 37* 28 42* 36 54* 28 30 21 42** Kachura 15 18 6 4 15 22 15 21 15 16 21 25 15 20 3 4 6 2 10 11 15 20 Dept. Skardu 1 0.1 3 3 3 3 3 3 3 3 3 3 3 6 m 1 0.8 1 0.12 3 3 Dept. Thowar 6 8 6 3 15 12 6 4 6 5 21 20 3 1 3 1 15 12 10 10 10 16 Imit 6 8 3 5 1 5* 6 15* 1 5* 1 5* 1 5* 1 5* 1 5* 1 5* 10 16 Chatorkhand 15 15 28 28 28 31 21 28 15 21 28 23 21 19 21 22 28 31 28 35 36 33 Golodass 28 38 21 25 28 38 15 10 15 22 21 55*** 10 6 10 14 36 75*** 36 69*** 36 83*** Df—degree of freedom; χ2—Chi-square; * p < 0.05, ** p < 0.01, *** p < 0.001. m—monomorphic allele.

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Table 4.8 Genetic diversity and differentiation parameters of collected apple samples from seven villages, two nurseries, and two valleys in Gilgit- Baltistan, Karakoram Mountains, northern Pakistan, between September and October 2018.

No. of Genotype Villages/valleys n PPL(%) Na Ne PNa A He Ho FIS clones diversity Bisil 26 100 2 (5) 8.8 5.1 17 3.8 0.773 0.836 -0.061*** 0.76 Tisar 15 100 1 (4) 5.8 3.6 0 3.3 0.705 0.873 -0.205*** 0.33 Hashupi 17 100 0 (8) 7.9 4.8 4 3.9 0.783 0.802 0.006*** 0.53 Kachura 14 100 1 (4) 5.3 3.4 1 3.3 0.677 0.773 -0.105* 0.31 Dept. Skardu 3 91 0 (2) 2.5 2.1 0 2.5 0.470 0.697 -0.314 0.33 Dept. Thowar 4 100 0 (4) 4.6 3.9 0 4.0 0.724 0.773 0.077 1.00 Imit 5 82 2 (2) 2.1 2.1 2 2.1 0.438 0.818 -0.837** 0.50 Chatorkhand 7 100 0 (2) 7.4 5.7 11 4.5 0.821 0.992 -0.047 0.83 Golodass 15 100 2 (3) 7.2 3.5 4 3.5 0.704 0.812 -0.120*** 0.62 Mean 97 1(4) 5.7 3.8 4 3.4 0.677 0.812 -0.178 0.58 12 0.55 Baltistan 79 100 (13) 10.9 5.3 32 8.9 0.795 0.816 -0.020*** Ishkoman 27 100 5 (6) 9.9 4.7 21 9.9 0.780 0.842 -0.061*** 0.65 n—number of individuals; PPL(%)—percentage of polymorphic loci; no. of clones within and in brackets among villages; Na—mean number of alleles; Ne—mean number of effective alleles; PNa—number of private alleles; A—allelic richness (corrected Na for sample size); He—expected heterozygosity; Ho—observed heterozygosity; FIS—fixation indices; * p < 0.05, ** p < 0.01, *** p < 0.001

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Table 4.9 Analysis of molecular variance (AMOVA) based on SSR of apple genotyped in seven villages of two valleys in Gilgit-Baltistan, Karakoram Mountains, northern Pakistan.

Grouping Source Df Sum of Squares Estimated Variation % ΦPT Villages Among 6 160 1.41 0.16 Within 92 681 7.41 0.84 Total 98 841 8.81 1.00 0.160*** Valleys Among 1 23 0.38 0.04 Within 97 818 8.43 0.96 Total 98 841 8.81 1.00 0.043** Df—degrees of freedom; ΦPT—population genetic differentiation parameter; ** p < 0.01, *** p < 0.001

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Figure 4.4 Isolation-by-distance correlations (r) and significance values (p) for genetic and geographical distances of local apple varieties for seven villages of two valleys in Gilgit- Baltistan, Karakoram Mountains, northern Pakistan, sampled between September and October 2018. 1Pairwise comparisons between two valleys.

The Bayesian clustering approach (STRUCTURE) indicated a sub-structure with the most likely number at K = 2 (ΔK: 4.39, LnP(K): -4026) and K = 3 (ΔK: 5.83, LnP(K): -3672) equalling two and three sub-populations, respectively (Figure 4.5a-b; Figure A4.2a-b).

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Figure 4.5a-b Bayesian inference of the most likely number of clusters of local apple varieties from seven villages of two valleys in Gilgit-Baltistan, Karakoram Mountains, northern Pakistan, sampled between September and October 2018. Stacked STRUCTURE bar graphs at K = 2 (a) and K = 3 (b), respectively. Three colours in vertical bars reflect the proportional likelihood of individual genotypes belong to one of the three clusters, respectively. Nursery reference material is also indicated (Table 4.1). Left - for individual village and nursery samples (*Dept Skardu, **Dept Thowar) each. Right - valley average each.

4.4.6 Synonyms and homonyms Eighteen clones (comprising 2 to 9 ramets) were found with a mean genotype diversity of 0.58 (Table 4.8; Table A4.3). Thirty-eight (36%) of the varieties (Quetta Amry, Kachura Ambary, Safaid Kachura Ambary, Shikam Balt, Sumerqand, Sas Polo, Desi Loop Moor, Gohar Aman, Za Kushu, and some individuals of Shakkar) were assigned as putatively true-to-type varieties as names were found in the same sub-clusters; for some, the nursery reference materials (Kachura Ambary R and Sas Polo R) additionally confirmed their correct assignment (Figure 4.6; Table A4.3).

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Figure 4.6 Maximum likelihood dendrogram based on 11 SSR of 106 individuals of apple individuals collected in seven villages of two valleys in Gilgit-Baltistan, Karakoram Mountains, northern Pakistan between September and October 2018. Same colours were manually added to the varieties which have similar names and collected several times in order to identify, putatively true-to-type varieties (same name, same genotype; grey), synonyms (different names, same genotype; yellow), homonyms (same name, different genotype; pink), and unique accessions (different names, different genotype; green) (see also Table A4.3). _a and _b: Grafted individuals with two different varietal scions (synonyms or genetically different, respectively). _R: Reference material and number n from local nurseries. Khoju (Malus baccata), a wild relative of apple, was found in a separate sub-cluster. B and I: Baltistan and Ishkoman Valley, respectively. The dashed line indicates the separation into two clusters according to the ‘elbow criterion’.

The remaining 68 (64%) individuals were classified as putative homonyms (n = 21, 20%), putative synonyms (n = 9, 8%), unique accessions (n = 8, 7%), ambiguous (homonym and synonym character, n = 24, 23%), and some as unknown individuals (n = 6, 6%) which were found as ramets of the known varieties (Table A4.3). Homonyms inaccurately attributed by local farmers, although phenotypically and genetically different, were Mamu Balt, Shakkar, Bong Kushu, Boo Kushu and Skire Kushu (Figures 6 and 7; Table A4.3). The two trees that bore one additional graft each, showed the following: Sas Polo and Five Star were found each in genetically separate sub-groups, hence not falsely assigned together (Figure 4.6). Five Star was in addition genetically unique (Figure 4.6; Table A4.3). Hunzoo Balt and Gohar Aman, all with the same genotype but named as two different varieties, are putative synonyms (Figure 4.6). Three varieties each from Ishkoman (Shakar Paloo, Shakoor Balt, Loqman) and Baltistan Valley (Shakkar, Sumerqand, Kho Kushu) were the same variety (Figure 4.6). The wild relative Khoju (Malus baccata) from Bisil was found in a separate sub-cluster. The Mantel test revealed similarity between phenotypic and genetic datasets with a significant positive correlation (r = 0.359, p = 0.001) allowing to create a tanglegram (Figure 4.7). The tanglegram indicated a significant positive cophenetic correlation (r = 0.627, p = 0.001) and the entanglement quality index was 0.14. Based on the phenotypic and genetic distance matrix of the 37 individuals, the most plausible number of clusters was two each (elbow criterion, Figure 4.7).

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Figure 4.7 Tanglegram of fruit phenotypic and genetic distance dendrograms of 37 apple individuals (s. Material and Methods section) in seven villages of two valleys in Gilgit-Baltistan, Karakoram Mountains, northern Pakistan. Cases with possible similar sub-cluster in both dendrograms were shown by coloured lines between individual IDs indicating putatively pure (1 and 3: Kachura Ambary) and synonym accessions (92: Shakar Paloo and 81D: Desi Loop Moor; 45: Za Kushu and 26: Ambary Kushu; codes as in Table 4.6). The dashed line indicates the separation into two clusters according to the ‘elbow criterion’.

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4.5 Discussion Apple trees in GB are integral components of orchards and homesteads. To our knowledge, this is the first study of Malus × domestica in Pakistan combining arboricultural, varietal richness, and diversity as well as phenotypic and genetic data, which allows drawing a comprehensive picture on the status of this supposedly threatened plant genetic resource.

4.5.1 Varietal diversity and management Considering only the varietal names, no variety was shared between both valleys, supported by a β-diversity value of 1. This reveals a vivid exchange within one valley as confirmed by farmers who collected and bought plant material from neighbours, villages, and nurseries, while exchange material across valleys was not reported despite old connections across mountain passes and along riverbeds and recent road connections. α-varietal diversity revealed that diversity decreases from remote to main road villages of the Baltistan Valley whereas an opposite trend was observed in villages of the Ishkoman Valley. A higher diversity in villages close to main trading routes might be attributed to their vicinity to the former Silk Road (now Karakoram Highway), enabling probably a faster introduction of different plant materials through time. Instead, higher diversity in remote regions may be linked to less disturbances, and thus a better preservation of ancient plant genetic resources (Forsline et al., 2003; Richards et al., 2009; Cornille et al., 2013; Omasheva et al., 2017). The β-diversity measures among villages in both valleys were high because of a high number of different varieties. However, we do not want to put too much emphasize on this outcome, since first, the relatively low number of samples and sites are insufficient to exclude randomness of obtained results and second, no study was yet conducted on the varietal α- and β-diversity of apple cultigens, which makes a comparison impossible. Nonetheless, with regard to the rather unknown varietal diversity distribution in space and time, we propose extended screening and sampling activities in the region and beyond. Across locations no arboricultural activity was witnessed. This is certainly due to the lack of facilities, but also due to the assumed knowledge erosion and training gap through agricultural extension services especially for younger, non-trained farmers. The lack of management was also reflected by marked differences in tree

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dimension across farms and villages. Trees higher than 4 m are technically and economically difficult to nurture and harvest and therefore regularly pruned or logged after some years in most commercial plantations worldwide. Also, slow-growing root stocks are used to prevent strong elongation growth of the grafted variety/cultivar (s. below). In this regard, two practices and pathways from Central Europe shall be mentioned that justify larger tree dimensions for commercial as well as nature conservation purposes. First, the main purpose of traditional orchards in Central Europe is to produce wine press (German: Kelterobst). For this, fruits are harvested by tree shaking and timely processed to juice and -depending on storage conditions and personal preferences -often gradually fermented and eventually further processed. The tree height for juice production is thus less important than for dessert apple trees. Second, large (old), non-trimmed trees are characterized by high habitat values for diverse biota such as shade provision, resting, feeding, and breeding. Hence, particularly old aged orchards are valuable landscape elements with an astonishing rich biodiversity and ecosystem function, and therefore protected by law in many European countries. Both uses could be suitable to foster orchard survival and to gain income from older trees also in GB. It was nonetheless obvious that farmers were more interested in commercial varieties, which were valued as cash crops. Although we missed to account also for the commercial cultivars on farm, the speed of the recent replacement of local apple varieties by modern cultivars is vital to understand varietal losses over time. In the USA for instance, the emergence of new markets, changing consumer preferences, and the extensive industrialization of apple production led to a tremendous loss of traditional (introduced and locally bred) varieties as observed in North Carolina (Veteto and Carlson, 2014), Ohio (Goland and Bauer, 2004), and Washington State (Jarosz and Qazi, 2000) during the last 20 years. The promotion of local varieties on regional markets as observed in Ohio (Goland and Bauer, 2004), helps instead to conserve indigenous apple cultivars (conservation through use), which might also be a valuable tool to conserve local apple varieties of GB. The grafting of local apple varieties remains a widespread mode of propagation in GB as visible through grafting spots in most of the trees. More than 30% of our sampled accessions, however, showed no grafting history implying their propagation through seeds. This was confirmed by the survey results, although in some cases,

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farmers did not remember the history of some of their trees or grafting spots may have been already overgrown by the bark. Popular apple rootstocks (M9, M26, M106 and M111) were not common especially not for local varieties due to monopolization of some commercial nurseries. Nowadays, local nurseries provide these rootstocks to those farmers who are willing to grow modern varieties in a subsidized form by assuring the purchase of the complete yield in every season. The majority of the sampled trees showed no symptoms of any disease indicating high vitality, which may indicate broad resistances in the studied germplasm. Studies on resistances against several diseases were proven for wild apple relatives such as Malus orientalis Uglitzk. from the North Caucasus region (Höfer et al., 2013), from Turkey and Southern Russia (Volk et al., 2008), and Malus sieversii (Ledeb.) M. Roem. from Kazakhstan (Forsline et al., 2003). In addition, the almost complete absence of pests could be related to the favourable growing conditions, low air moisture and agro-ecological separation between villages. Moreover, the small-scale farming with high crop richness and mosaic-like patterns including hedges and tree stands are important prerequisites for the survival of beneficiary animal species and may hence lead to relative agro-ecosystem health in GB. It needs to be emphasized that we observed sunburn (photo-bleached and eventually necrotic spots on apple peel, Figure A4.1d) on commercial plant material, while never on local apples. The high radiant energy available (1500–1900 kW m-² a-1 https://globalsolaratlas.info, accessed 10 April 2020) in the region, requires physiological adaptations that are likely prevalent in local apple germplasm. Although we have only yield estimates per tree, the values given by the farmers seem plausible as overaged trees in orchards of Central Europe are likely to provide similar quantities. The tree category (age 40 - 60 years), however, is hardly present in Central European stands, therefore comparisons to our study are problematic. The fact that almost all fruits were used for home consumption, while only a few were sold on local markets, shows their low public recognition, but certainly also the limited market access resulting from poor infrastructure, particularly for the most remote villages. Also, poor or inappropriate storage cause damage and therefore accelerate fruit quality loss and perishing over time. In addition, poor recognition of the best harvest time accelerates such problems: harvesting too early hinders full fruit quality development, while late harvesting shortens the shelf life. Similar handling and marketing constraints for apple have been reported from the neighbouring Pakistani

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district Chitral, Khyber Pakhtunkhwa (Khan and Bae, 2017), but also for apricot (Kousar et al., 2019) and sea buckthorn (Nawaz et al., 2019) in GB. Lastly, the still negligible knowledge of processing apples into value-added products such as jams, powders, chips, and beverages combined with lack of infrastructural facilities will keep down the usage of local varieties in GB, and beyond.

4.5.2 Fruit phenotype The phenotypic characterization confirmed a diverse range of the available apple germplasm in the GB region. This characterisation may serve as an important prerequisite for the effective and efficient utilization of the available germplasm in future apple breeding and conservation programs (Höfer et al., 2014). The identified quantitative traits of our study showed higher variation as compared to Malus samples collected from South Serbia (fruit weight; Mratinić and Akšić, 2012) and Iran (fruit length, width and weight; Damyar et al., 2007), whereas variation was lower than in Germany (fruit length and width, petiole length, number of pippins; Höfer et al., 2014). While the relative length of the petiole appeared to be an important characteristic to distinguish Malus species (Henning, 1947; Höfer et al., 2013; Höfer et al., 2014), this trait was only moderately distinctive in our case. Instead, the calyx depth and the presence or absence of the calyx tube were considered important parameters for fruit varietal characterization in the present work. Although we found a comparatively large variation in quantitative traits (shape, size, petiole thickness, and length), we identified less differences in qualitative traits such as smell and taste. Bitterness for instance was found a reliable discriminator especially for wild M. sieversii and M. orientalis (Forsline et al., 2003; Höfer et al., 2013), a parameter that was only marginally present in our collection. The browning of pulp due to the presence of polyphenolic compounds as found for local varieties of Bisil village was likewise observed for local apples from Germany (Kschonsek et al., 2018). With regard to health, polyphenols are considered active against cardiovascular diseases and cancers (Biedrzycka and Amarowicz, 2008). The sourness of some local varieties (for instance Khoju, Za Kushu, Skire Kushu) may allow for other uses such as for cider and vinegar production (Rabetafika et al., 2014). Overall, distinctive phenotypic character differentiating apple varieties across regions is still lacking. Many studies indicate that a broad set of quantitative and qualitative parameters such as fruit size and weight, peel colour, acidity (sourness),

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and petiole (length, width, and thickness) is crucial to distinguish varieties (Pereira- Lorenzo et al., 2003; Damyar et al., 2007; Federico et al., 2008; Santesteban et al., 2009; Bassil et al., 2009; Gasi et al., 2010; Mratinić and Akšić, 2012; Király et al., 2015; Pérez-Romero et al., 2015), wild relatives (Dzhangaliev, 2002), and hybridization processes between domesticated and wild Malus spp. germplasm along the Silk Road (Reim et al., 2013; Larsen et al., 2006; Spengler, 2019). Although the overall variability was apparently high, the observed variations are dependent on several environmental and sample-related factors that are difficult to disentangle under field conditions. Since we studied accessions over a period of about three weeks, we could not easily compare the overall variation across and within accessions at one time. Also, topographic and edaphic conditions – a fraction of many abiotic factors – vary along altitudes. Some of the observed accessions have been therefore excluded from a detailed description due to still unripe stages. Finally, differences in age, tree, and under-tree management are known to affect apple phenotypes significantly (Costes et al., 2006; Cavael et al., 2020) and can only be validated with sufficiently high sample sizes in combination with repeated sampling approaches.

4.5.3 Genetic diversity and differentiation Molecular characterization in combination with phenotypic description is an emerging trend in Malus taxonomy (Qian et al., 2008). SSRs were widely used in apple for varietal identification, ancestry studies, germplasm collection management, as well as genetic diversity and structure evaluation. Although we verified commonly used SSRs and tested promising new ones, the pre-screening on our samples revealed that it is difficult to keep the proposed set, as some SSRs (Ch01h01, Ch01e12, Ch05f06, Ch04f10 and Hi02c07) exhibited no polymorphism. The positive controls (‘Anhalter’, ‘Blenheim’ (Synonyms: ‘Goldrenette von Blenheim’, ‘Gaesdonker Renette’), and ‘Schöner aus Elmpt’) were of limited use since the initial screening identified them as triploids, making it impossible to objectively compare their genetics. We are aware that after years of molecular marker assisted research, harmonized SSR data sets (incl. adjusted SSR allele sizes) are much needed, particularly for comparative studies across space, research projects, and laboratories. Attempts for apple and pear (Pyrus communis L.) are for example fostered and under development by INRA (https://www.ecpgr.cgiar.org, accessed 09 April 2020).

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The PID and PIDsib values calculated as ≤ 0.000032 and ≤ 0.0056 were below the recommended value of < 0.01 (Waits et al., 2001), which indicates a sufficient to high power of the 11 SSR markers applied to separate individuals. The mean number of alleles (n = 13) per locus in our study was higher than in apple accessions of Bosnia and Herzegovina (39 accessions, 24 traditional and 15 modern cultivars, 10.4 alleles (Gasi et al., 2010) and in Italian and international varieties (48 accessions, eight varieties, 7.8 alleles (Guarino et al., 2006). Numbers were instead similar to Spanish accessions (114 local + 26 reference cultivars, 12.3 alleles (Pereira-Lorenzo et al., 2007) and 183 accession + 23 reference varieties, 12.8 alleles (Pina et al., 2014)). Based on this comparison, we found our set to be efficient and meaningful to further interpret outcomes. The identification of private alleles and their differences among villages and between valleys provides further evidence of the presence of unique plant genetic material. The high numbers of private alleles identified, especially in the villages Bisil (Baltistan Valley) and Chatorkhand (Ishkoman Valley), is considered important to maintain adaptive potentials of populations to future environmental changes (Allendorf and Luikart, 2007). Although we found a moderate to high genetic diversity

(He = 0.677), higher values with largely overlapping marker sets were reported for cultivars from Spain (Pereira-Lorenzo et al., 2007; Urrestarazu et al., 2012; Pina et al., 2014), Italy (Guarino et al., 2006; Testolin et al., 2019), Sweden and Finland (Garkava- Gustavsson et al., 2013), and Bosnia and Herzegovina (Gasi et al., 2010). A near complete absence of deviation from HWE (except Bisil and Tisar) and mostly negative FIS values reflected high levels of heterozygosity and the absence of a sub-structure. This high heterozygosity can be expected in a self-incompatible (outcrossing) species, but cannot be taken for granted as seen in other Malus spp. studies with higher levels of differentiation (Liang et al., 2015; Pereira-Lorenzo et al., 2018; Bitz et al., 2019). The Bayesian clustering underpins this finding as the clusters were shared across villages (except for Imit) and between valleys. Hence, we conclude that substantial gene flow is present among villages and even between both valleys. We did actually not expect this circumstance, because local varietal names were restricted to one valley each. Two factors, however, may govern the observed genetic variation and spatial distribution: 1) about two-third of the accessions studied were grafted with plant material originating from neighbours, neighbouring villages, and nurseries within the same valley. Especially the first two sources of plant material

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may have been in the region for centuries (Whiteman, 1985). Although grafting favours only a few renowned varieties and may lead to a sudden reduction of effective population size and hence a loss of genetic diversity as observed for many perennial species (Petit and Hampe, 2006; Miller and Schaal, 2006; Savolainen and Pyhäjärvi, 2007), there is no evidence of domestication bottlenecks for apple so far (Cornille et al., 2012; Spengler, 2019). It may therefore be not surprising to still find an overall high richness and diversity and similar varieties across villages; 2) the other one-third of the accessions that indicated no grafting histories are assumingly seedlings. Seedlings are created through natural pollination and experienced unknown pathways of dispersal, whereby a vast range of pollen (Kron et al., 2001; Larsen and Kjær, 2009; Reim et al., 2017) and seed vectors such as birds and mammals (Cornille et al., 2014; Spengler, 2019) are known, including humans (Cornille et al., 2015). For all dispersers it is even likely that mountain passes have been common dispersal routes for apple in the past. From the human sedentarisation history of the region, it is known that during the 9th and 11th century the Shigar Valley was colonized by tribes from Central Asia following trading routes along the Braldo River (west of Baltistan Valley) as well as through Hunza and Nagar following the Bashe Path (north of Baltistan Valley, including Bisil village) approximately. Both colonisation routes are relatively short (ca. 60 km beeline each), however, separated by the K2-Hidden Peak complex (min. 5900 m asl) and the Spantik-Sosban mountain range (min. 5400 m), respectively. It is known at the latest since the 16th century when Haydar Khan (1545-1570) ruled Baltistan that apple was dragged with other fruit trees from Xinjiang (China) to the distribution area of Malus spp. Nagir and Hunza and planted in Shigar Valley (Schuler, 1978). The upstream Indus Valley (south-east of Baltistan Valley) may have served as another less difficult route (see also Text A4.1). Thus, the influx of apple seed and planting material may have helped to diversify the locally available germplasm and likely contributed to today’s high richness and diversity in the region.

4.5.4 Synonyms and homonyms About one third of the apple varieties were true-to-type based on local names and their investigated pheno-genetic characteristics, partially confirmed by nursery reference materials. Surprisingly, genetically same varieties from Ishkoman (Shakar Paloo, Shakoor Balt, Loqman) and Baltistan Valley (Shakkar, Sumerqand, Kho Kushu) indicated germplasm exchange between valleys in the past. This is

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supported by the structure analyses, where clusters appear to be commonly shared between both valleys. Contrarily, tree owners named about 43% (putative homonyms and ambiguous) of the varieties incorrectly. False determinations and assignments are typical and largely prevailing problems for cultigens worldwide such as pear (Bassil et al., 2009), grape (Boz et al., 2011), olive (Işik et al., 2011), almond (Gouta et al., 2010), but also apple (Pereira-Lorenzo et al., 2018; Marconi et al., 2018). Misnaming can have several reasons and reach from linguistic differences across ethnicities (relevant in GB; Kreutzmann, 2014), unawareness and lack of interest (https://pamirtimes.net/2015/11/04/the-apple-of-baltistan/, accessed 14 April 2020), incorrect determination or inheritance, as well as somatic mutations that may lead to marked phenotypic differences (Shaw and Southwick, 1943). The tanglegram was statistically sound, showing very reliable alignments across two common sub-clusters (Figure 4.7). Across all, six individuals were similarly assigned in three sub-groups between both genetic and phenotypic dendrograms indicating two putative synonyms and one true-to-type variety (Figure 4.7). At the same time, this might be a sign of genetically linked traits which merits further studies. However, findings are largely similar to a study on indigenous wild apple in Europe where a significant correlation was found between phenotypic and genetic distance matrices (Reim et al., 2013). In contrast, a pheno-genetic correlation across 39 traditional and modern apple cultivars (24 from Bosnia and Herzegovina, 15 modern ones) failed, as unlike SSRs, only phenotypic traits appear to have been under agronomic selection pressure (Gasi et al., 2010). The marker system of SSRs, was found to be repeatedly insufficient to distinguish well between varieties (Doğru et al., 2019), which might have also influenced our results.

4.6 Conclusions The data indicate that GB contains a surprisingly large pool of still untapped varietal diversity in apple which certainly reflects its ancient role at the crossroads of international trade routes. The study, however, also showed that much more in-depth research and sample coverage is needed to better evaluate the status of traditional apple richness and diversity in GB. A larger sample would also help to unravel the ambiguous (homonym and synonym characters) accessions. Unfortunately, our study lacks the integration of and comparison to commercial varieties. However, the place

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of the one commercial Five Star cultivar in the dendrogram indicated that it is among the other local varieties, which thus belong to Malus × domestica. The comparatively poor awareness of local apple varieties may not become better if arboriculture activities remain on the level observed. Currently, local input markets act as push factors as they mainly offer commercial varieties that will likely lead to the gradual replacement of local varieties and thus to a loss of awareness of a still rich source of promising local germplasm. However, new consumer demands for niche and value-added products could help to promote some of the local varieties to compensate for the rather low yields and currently hardly marketable traits. The promotion of local varieties may allow farmers to diversify their produce and sources of income as well as to maintain a historically important biological heritage of Gilgit- Baltistan also with respect to the current trend of promoting increasingly agroforestry practices worldwide. To this end, comprehensive conservation strategies combined with participatory research and captive breeding approaches will be needed.

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Acknowledgements We gratefully acknowledge funding from the Federal Ministry for Economic Cooperation and Development (BMZ) and the German Academic Exchange Service (DAAD) through a scholarship of the German Academic Exchange Service (DAAD) to the second author in the context of bulk funding to the International Center for Development and Decent Work (ICDD) at the University of Kassel as part of the EXCEED initiative. We thank Alexandra Dolynska and Christine Radler, Department of Forest Genetics and Forest Tree Breeding, Georg- August-Universität Göttingen, for technical assistance during the laboratory analysis. We also acknowledge Christina Mengel from Conservation Biology, University of Marburg, for her technical support and sharing the marker related data and sending us reference samples as positive control. Last, but not least we are indebted to our respondents in Gilgit-Baltistan, our village hosts, and the Department of Agriculture, Government of Gilgit-Baltistan for sharing the nursery-maintained varieties and facilitating our study.

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4.7 Appendix Table A4.1 Comparison of applied marker characteristics with published (reference) studies based on genetic diversity (Na, He, and Ho) and differentiation (Fis). (see .xlxs file)

Table A4.2 Probability of identity values estimated as unrelated (PID) and sibling (P(ID)sib) from eleven SSR markers (Table 4.2) applied on collected apple samples from seven villages, two nurseries, and two valleys in Gilgit-Baltistan, Karakoram Mountains, northern Pakistan, between September and October 2018.

Villages/valleys n PID PIDsib Bisil 26 2.6×10-13 2.5×10-05 Tisar 15 1.5×10-10 9.1×10-05 Hashupi 17 2.1×10-13 2.1×10-05 Kachura 14 3.2×10-10 1.4×10-04 Dept. Skardu 3 5.2×10-06 3.2×10-03 Dept. Thowar 4 3.8×10-11 6.5×10-05 Imit 5 3.2×10-05 5.6×10-03 Chatorkhand 7 9.7×10-15 1.1×10-05 Golodass 15 7.8×10-11 8.8×10-05 Baltistan 79 5.1×10-14 1.7×10-05 Ishkoman 27 3.3×10-13 2.3×10-05 n—number of individuals

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Table A4.3 Number of individuals per putative classification using genetic dendrogram information (Figure 4.6) from 106 individuals of apple collected in seven villages of two valleys in Gilgit-Baltistan, Karakoram Mountains, northern Pakistan during September-October 2018.

True-to- Synonym & Varieties n type Synonym Homonym Unique homonym variety Quetta Amry 2 2 (3L) Kachura Ambary 8 8 (9K) Safaid Kachura Ambary 2 2 (2C) Shikam Balt 2 2 (2Q) Sumerqand 2 2 (7F) Wardap 1 1 Shakoor Balt 1 1 Dyan Kushu 1 1 Loqman 1 1 Normu Kushu 1 1 Hunzoo Balt 1 1 Nas Kushu 1 1 Skirmu Kushu 1 1 (6G) Oanh Kushu 1 1 (6G) Isdop 1 1 Five Star 1 1 (2p) Karismin 1 1 Frances Paloo 1 1 Khushwati 1 1 Mar Kushu 1 1 Aliqan Balt 1 1 Khoju (Malus baccata) 1 1 Mamu Balt 4 4 Sas Polo 6 5 (5D) 1 Desi Loop Moor 5 4 (2A,2B) 1 Gohar Aman 6 5 (5M) 1 (2J) Bong Kushu 7 3 4 (6G,3H,2N,3R) Skire Kushu 6 3 3 (6G,3R)

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Ambary Kushu 5 2 3 (3L,2N) Boo Kushu 3 1 2 (6G,3H) Shakar Paloo 3 1 2 (7F,2J) Kho Kushu 2 1 1 (2O) Nuri Kushu 2 1 1 Shakkar 15 6 (7F) 3 (2E) 6 (6G) Za Kushu 3 2 (2I) 1 Unknown 6 (2E,3H,9K,2O,2P,3R) Total 106 38 9 21 24 8 n−number of individuals assessed; the number in brackets indicate the number of individual ramets; letter in superscript indicate the respective ramet (see also Figure 4.6)

Table A4.4 Detailed description of the number of varieties and related individual data observed and discovered per village in Gilgit-Baltistan, Karakoram Mountains, northern Pakistan during September-October 2018.

History Storage Yield Yield Age Stored Village Varieties n Purpose Popularity Selling duration Stored in (kg) behaviour (Years) with Grafted Origin* (months)

Home Local Without Mostly consumption Popular Yes Nothing Kachura 100- (2) boxes (3), 5 alternate 15-35 Yes (5) (2), eating (4) to very (4), No < 5 (2), dry Ambary 200 nursery cartoon (4) and animal popular (1) (1) grass (3) (3) boxes (2) feed (3) Local Safaid Alternate Yes (1) Popular Without Dry grass Kachura 2 > 100 (1), regular 12-35 Yes (2) (2) (1), No ≥ 5 nursery (2) boxes (2) (2) Kachura Ambary (1) (1) (1) Quetta Home Without 1 > 100 Alternate 20 Yes Nursery Popular Yes ≥ 5 Dry grass Amry consumption boxes Without Home Nothing 100- Alternate Popular boxes (2), Shakkar 4 10-30 Yes (4) Nursery consumption Yes (4) ≥ 5 (1), Dry 200 (4) (4) cartoon (4) grass (2) boxes (2)

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Home Less consumption Yes Alternate Local popular (1) Sas Polo 2 > 100 9-30 Yes (2) (1), eating (1), No - - - (2) (2) to popular and animal (1) (1) feed (1) Without Local Less Alternate Home boxes (1), Ambary 100- Yes (1), (1) popular (1) Dry grass 2 (1), 70-90 consumption No (2) ≥ 5 willow Kushu 200 No (1) nursery to popular (2) Regular (1) (2) baskets (1) (1) (1) Home Without Local Less Alternate consumption boxes (3), Bong 100- (1) popular (2) Dry grass 4 (1), 60-70 Yes (4) (3), eating No (4) < 5 willow Kushu 200 nursery to popular (4) Regular (3) and animal baskets (3) (2) feed (1) (1) Local Home (1) Less Without Boo Kushu 2 > 100 Regular (2) 70 Yes (2) consumption No (2) ≥ 5 Dry grass nursery popular (2) boxes (2) (1) Home Less Cartoon Khoju 1 - Regular 150 No Local No > 1 Nothing consumption popular boxes Bisil Only animal Less Kho Kushu 1 - Regular - No Local No - - - feed popular Home Less Without Mar Kushu 1 > 100 Regular - Yes Nursery No ≥ 5 Dry grass consumption popular boxes Local Home Popular (1) Willow Nuri Kushu 2 > 100 Regular (2) 15-60 Yes consumption (1) to very No (2) > 1 Dry grass nursery baskets (2) popular (1) (1) Without Local Alternate Home boxes (2), 100- Yes (3), (1) very Dry grass Shakkar 4 (2), 12-70 consumption No (4) ≥ 5 Willow 200 No (1) nursery popular (4) (4) Regular (2) (4) baskets (3) (2) Alternate Home Without Skire 100- Yes (1), Local Less Dry grass 4 (3), 10-90 consumption No (4) ≥ 5 boxes (1), Kushu 200 No (3) (3) popular (4) (4) Regular (1) (2), only Willow

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nursery animal feed baskets (1) (2) (3)

Home very Without Sumerqand 1 > 100 5 Yes Nursery No ≥ 5 Dry grass consumption popular boxes Less Home Willow Local popular (1) Dry grass Za Kushu 2 < 200 Regular (2) 80-100 No (2) consumption No (2) ≥ 5 baskets (2) to popular (2) (2) (2) (1) Home Popular Bong 100- Yes (1), Local Without Dry grass 3 Regular (2) 7-150 consumption (1) to very No (3) < 5 Kushu 200 No (2) (3) boxes (3) (3) (3) popular (2) Home Without Boo Kushu 1 > 100 Alternate 50 Yes Local popular No ≥ 5 Dry grass consumption boxes Dyan 100- Home Without 1 Alternate 30 Yes Local No ≥ 5 Dry grass Kushu 200 consumption boxes Normu 100- Home Less Wooden cereal 1 Alternate 150 No Local No ≥ 5 Kushu 200 consumption popular boxes grains Oanh very Without 1 - - No Local No < 5 Dry grass Kushu popular boxes Alternate Home Tisar 100- Yes (1), Local very Without Dry grass Shakkar 4 (3), 60-80 consumption No (4) ≥ 5 200 No (3) (4) popular (4) boxes (4) (4) Regular (1) (4) Skire 100- Home Less Without 1 Alternate 150 No Local No ≥ 5 Dry grass Kushu 200 consumption popular boxes Home Alternate consumption Skirmu Local Less Without Dry grass 2 < 200 (1), 60-80 No (2) (1), eating No (2) ≥ 5 Kushu (2) popular (2) boxes (2) (2) Regular (1) and animal feed (1) Less Without Alternate Home Dry grass Local popular (1) boxes (1), Not known 2 > 100 (1), 70 No (2) consumption No (2) < 5 (1), cereal (2) to popular Wooden Regular (1) (2) grains (1) (1) boxes (1) Local Without Home Yes Ambary 100- Alternate (1) Popular boxes (1), Dry grass Hashupi 2 27 Yes (2) consumption (1), No ≥ 5 Kushu 200 (2) nursery (2) Wooden (2) (2) (1) (1) boxes (1)

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Kachura Home Wooden cereal 1 < 200 Alternate 30 Yes Nursery Popular Yes ≥ 5 Ambary consumption boxes grains Karismin Home Without 1 > 100 Alternate - Yes Nursery Popular Yes ≥ 5 Dry grass (non-local) consumption boxes 100- Home Without Kho Kushu 1 Regular 40 Yes Nursery Popular Yes ≥ 5 Dry grass 200 consumption boxes eating and Wooden cereal Nas Kushu 1 < 200 Alternate 80 No Local Popular Yes ≥ 5 animal feed boxes grains Quetta 100- Home Without 1 - Yes Nursery Popular Yes ≥ 5 Dry grass Amry 200 consumption boxes Home Alternate consumption Dry grass 100- Very Wooden Sas Polo 3 (1), 2-30 Yes Nursery (2), eating Yes < 5 (1), cereal 200 popular (3) boxes (2) Regular (2) and animal grains (1) feed (1) Home Popular Yes Dry grass Alternate Local Wooden Shakkar 2 < 200 30-70 No (2) consumption (1) to very (1), No ≥ 5 (1), cereal (2) (2) boxes (2) (2) popular (1) (1) grains (1) Skire Home Less Without 1 > 100 Regular 6 Yes Local Yes ≥ 5 Dry grass Kushu consumption popular boxes Home Wooden cereal Sumerqand 1 > 100 Alternate 20 Yes Local Popular Yes ≥ 5 consumption boxes grains eating and Wooden Wardap 1 < 200 Alternate 45 Yes Local Popular No < 5 Dry grass animal feed boxes Home Popular Desi Loop 100- Alternate Yes (3), Local Wooden Nothing Imit 5 10-100 consumption (2) to very No (5) < 5 Moor 200 (5) No (2) (4) boxes (4) (4) (5) popular (3) Frances 100- Home Very 1 Alternate 100 No Paloo 200 consumption popular Home Wooden Isdop 1 5 Yes No < 5 Nothing Chatorkhand consumption boxes Home Very Wooden Khushwati 1 > 100 Alternate 84 Yes Nursery No < 5 Nothing consumption popular boxes

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100- Home Wooden Mamu Balt 1 Alternate - Yes Nursery Popular No < 5 Nothing 200 consumption boxes Shakar 100- Home Very 1 Regular 60 Yes Nursery Yes - - - Paloo 200 consumption popular Home Aliqan Balt 1 > 100 Alternate - Yes Nursery consumption Local Home Popular Yes Gohar 100- Alternate Yes (3), (2) Wooden Nothing 4 6-35 consumption (1) to very (2), No < 5 Aman 200 (4) No (1) nursery boxes (4) (4) (4) popular (3) (2) (2) Home Very Loqman 1 > 100 Alternate 20 Yes Nursery Yes - - - consumption popular Golodass Home 100- Nursery Very Mamu Balt 2 Alternate 20-30 Yes (2) consumption Yes (2) - - - 200 (2) popular (2) (2) Shakoor Home Very Wooden 1 > 100 Alternate 12 Yes Nursery No < 5 Nothing Balt consumption popular boxes Local Without Home Popular Yes Shikam 100- Alternate (1) boxes (1), Nothing 2 20 Yes consumption (1) to very (1), No < 5 Balt 200 (2) nursery wooden (2) (2) popular (1) (1) (1) boxes (1) n−number of individuals per variety in each village; number in brackets indicate the response frequency of that variety out of the total occurrence of that variety n. * Nursery within valley and local source means neighbour, other villages.

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Questionnaire A4.1 Tree data form about status, dendrometry and owner response about particular individual collected during September-October 2018 in seven villages of two valleys in Gilgit-Baltistan, Karakoram Mountains, northern Pakistan. ID______Date ______Foto No. ______Tree data

Location Coordinates (close to stem) Tree height Stem girth at breast (estimated) height* Canopy diameter Grafting spot visible?

Yield Vitality (estimated) Diseases visible Under-tree use

Other

* if possible at 1.30 m, otherwise directly below branching of the canopy with indication of tree height

Notes from tree owner

Name, adress, contact

Name of variety Tree age (statement by owner) Distribution of variety Root stock & kind of (estimation by owner) grafting method

Purpose of fruits/use Yield behavior

Appreciation/ Sale/trade of fruits popularity

Length of storage period Method of storage

other

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Questionnaire A4.2 Fruit description (qualitative) form of the varieties collected during September-October 2018 in seven villages of two valleys in Gilgit-Baltistan, Karakoram Mountains, northern Pakistan.

Bold traits were used for dendrogram construction (see above)

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Questionnaire A4.3 Fruit description (quantitative) form of the varieties collected during September-October 2018 in seven villages of two valleys in Gilgit-Baltistan, Karakoram Mountains, northern Pakistan.

ID: ______Date: ______Measurements (in mm) and weight (in g).

Fruit Calyx Petiole Axis Pippins Fruit Leaf Leaf Tube Pit Weight Width Height Depth Width Depth Length Thickness Number Length Width No. width length width width 1 2 3 4 5 6 7 8 9 10

Comments:

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Figure A4.1a-d a) Mountain oasis Haider Abad Shigar in Baltistan Valley (Gilgit-Baltistan, Pakistan), b) Governmental fruit nursery of Thowar lacking water for irrigation c) collection of apple after harvest, d) sunburn on modern apple variety.

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Figure A4.2a-b a) Mean log-likelihood (Ln(K) ± s.d.) and b) delta K (mean (|L” (K)|)/s.d.(L(K)) values over 10 iterations each obtained by the STRUCTURE HARVESTER program to determine the most plausible number of groupings of all investigated 106 individuals of apple collected in seven villages of two valleys in Gilgit-Baltistan, Karakoram Mountains, northern Pakistan between September and October 2018.

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Text A4.1 - Historic views Traditional narrations from Ishkoman Valley say that the ancestors of Mir Karam Ali Shah (last ruling king of the Gilgit-Baltistan kingdom system) tamed Miza Katchat – a Jinn (commonly a supernatural creature in Islamic and Arabic traditions) – who served and brought fruit trees from Baltistan and planted them in the king’s orchards. Whether this Jinn was of fictive or real nature, the narration discloses two facts: First, fruits were on high demand, in the beginning certainly only by privileged people. Second, Baltistan was a source region for apple. Hence, two thoughts are outlined that may serve to underpin the reason for this cultigen to have spread rapidly regardless of physical barriers and making it one of the most important agricultural goods even in remote regions of Gilgit-Baltistan until today: (i) High altitudinal regions of Central Asia offer mostly a low number of vitamin-rich foods with a limited spatial distribution and temporal availability. Although we do not know the species composition and distribution of wild as well as domesticated species at the mentioned time horizons from the 9th century onward, humans may have depended on a few species only, such as rhubarb (Rheum rhabarbarum), barberries (Berberis sp.), sea buckthorn (Hippophae rhamnoides), and wild onions (Allium sp.). The consideration that fruit tree species such as apple trees (maybe also their scions and fruits, perhaps also seeds) were precious goods/gifts since they were considered rare and exotic in regions of the ancient Silk Road, may be hence justified. Historic transmissions exist that migration from Hunza to Ishkoman was common at the time of Gohar Aman, the ruler of Gilgit-Yasin region (including Ishkoman Valley), in the early to mid-19th century. The variety Gohar Aman was a gift from his tribe in honour of his political achievements. (ii) The esteemed local variety of Sas Polo is known and frequently mentioned by farmers to have been brought from the Sasplu village (34°14'37.9"N, 77°09'51.6"E, Jammu- Kashmir, India) by the Baltistan King of Skardu and planted in the Paari village (35°01'08.0"N, 76°07'47.0"E, Kharmang District, Baltistan V). In fact, the pathway through the Indus Valley with long established trading routes seems likely as high mountain ridges and glaciers do not need to be bridged. Therefore, Baltistan Valley might have been a hotspot for new varieties at least an important hub for their distribution.

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Chapter 5 – General discussion

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5.1 Relevance of current research Native and traditional perennial plants and varieties/landraces are usually well adapted to the soil and climatic conditions of the regions where they occur. Farmers of highland regions often rely on such local plant resources as they provide food, forage, medicine, and shade. Globally, their recognition, however, is poor as research on these species is lacking. Harvest censuses do not account for their yield, local markets remain unmonitored and informal, and appropriate marketing infrastructures are largely absent (Shackleton et al., 2007; Angelsen et al., 2014; Shackleton et al., 2011). These circumstances prevent an upscaling of cultivation and use, the diversification of derived products, and the beneficial exploitation of potential ecosystem services. Hence, traditional knowledge of these species may be lost, sustainable modes of production hindered, and rural development strategies using these species may be insufficiently implemented. Sea buckthorn and local apple varieties are typical representatives of such P/PGR in Gilgit-Baltistan (GB), Pakistan, as they contribute to farmers’ household incomes and provide essential ecosystem services. Although apple is GB’s second most important cash crop, traditional apple varieties remain unconsidered in local census data. Also, sea buckthorn, an internationally well-recognized superfood, remains a marginal subsistence source. Its berries are occasionally collected and sold, but its value as firewood is more important. Despite such benefits, these species are inadequately recognized by governmental institutions in Pakistan. Although both apple and sea buckthorn species have a certain significance in the region, both almost completely fail to exert their potential in traditional agro-ecosystems.

5.2 Testing the first hypothesis Human induced domestication in natural sea buckthorn populations is higher in stands near to settlements. To our knowledge, this study is the first investigation of the diversity status and ongoing domestication of sea buckthorn populations in GB. Overall, there was no evidence for domestication based on the assessed quantitative and qualitative traits. Although domestication was assumed to have occurred in a region that is inhabited for millennia, many factors seem to have prevented sea buckthorn from becoming domesticated. Thus, hypothesis 1 is rejected.

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Globally, sea buckthorn is considered a wild species (Rajwant et al., 2011) and is still largely harvested from natural stands. However, there are cultivars that have commercially interesting characteristics for famers such as a greater number of fruits per plant, larger fruits, and no/less thorns (Albrecht, 1990; Ruan et al., 2004; Sanna and Petruneva, 2015). Until today, there is no specific consumer preference for sea buckthorn berries because they are mainly consumed as a nutrition supplement and processed for jellies, jams, juices or for the cosmetic industry (Beveridge et al., 1999; Cordos and Dumitraș, 2013; Geertsen et al., 2016). This study used a reasonable number of individuals (n = 300) and sample sites (n = 8) to assess morphological and genetic agro-biodiversity and to evaluate the local status of the crop. The random selection of individuals with a minimum distance of 100 m as suggested for clonally propagated species (Muchugi et al., 2008) seemed suitable as no identical Multi Locus Genotypes (MLGs~clones) were found. The subdivision of stands into “village” and “wild” with a minimum distance of one kilometre instead, was likely too low to identify an anthropogenic effect. However, it was difficult to find accessions that exceeded a 2 km distance from a village, which may indicate a certain affinity of the species to human activities that itself merits further research. The application of handy and horticulturally well recognized RHS colour charts to assess colour differences across accessions and its colour tone display was applied for the first-time in sea-buckthorn. RHS charts appear suitable for such a small berry although several berries needed to be evaluated simultaneously under the same light qualities. It is evident that the maturity status of berries is critical for the fair determination of berry colours. No relationships between fruit quantitative traits such as volume and 20-berry weight for village and wild stands were observed as larger and smaller fruits were found in both stands with negligible differences. These traits were expected to be higher in village than wild stands as farmers favour such traits, triggering domestication. However, visible responses of human-based selection are usually delayed in tree species due to its long lifespan with lengthy growth and maturity phases (Parker et al., 2010). One of our preliminary hypotheses was that there are altitudinal effects on morphology and berry colour in natural sea buckthorn populations. However, a significant positive correlation with altitude was only found for leaf area. The increase in leaf area with altitude was already confirmed for Malosma laurinais in California,

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USA (Shelley and Gehring, 2014) and other vascular plants in China (Pan et al., 2013). Plant functioning is limited at high altitudes due to high irradiance, strong wind, and low temperatures (Li et al., 2008). Therefore, larger leaf lamina structure may provide mechanical support and resistance against static loads and drag forces (Niklas, 1999; Niinemets and Kull, 1999). It also may facilitate transport of water and nutrient thus facilitating proper functioning of the plant’s physiology (Pan et al., 2013). In contrast to the correlation of altitude with leaf area, effects of altitude on berry colour could not be confirmed, likely because fruit colour is influenced by several other environmental and genetic factors as well as interactions among them. Nonetheless, there are studies which show that variable climatic conditions along different altitudes affect ripening and colour in fruits such as cherry, apple, and apricot (Hashmi and Shafiullah, 2003; Karagiannis et al., 2020). Environmental factors include soil nutrients, water availability, sun exposure, decay, and infestation, which could possibly influence fruit morphological traits (Telias et al., 2008; McCallum et al., 2010; Paul and Pandey, 2014). Additionally, there are colour controlling genes which are influenced by single gene mutation and interactions of several genes as reported for pepper (Capsicum annuum; Naegele et al., 2016), tomato Lycopersicon esculentum; Tanksley, 2004), and apple (Malus domestica Borkh; Karagiannis et al., 2020). The colour determining proanthocyanins in sea buckthorn berries are also genetically controlled (Yang et al., 2016). Therefore, the above discussed genetic factors may have great influence, and further studies are needed to clarify the relative effects of genetics and environment (altitude) on colour change. As phenotypic variation in naturally grown species is generally high, factors responsible for variability are overall difficult to quantify (Mwase et al., 2010; Parker et al., 2010). To avoid speculations about the multiple effects of the above discussed environmental factors, genetic markers (EST-SSR; Jain et al., 2010), were applied to assess potential effects of domestication on genetic diversity of sea buckthorn (Finkeldey and Hattemer, 2007). Genetic data confirmed that there is no obvious difference between village and wild sites, suggesting a substantial gene flow between them and confirming the variability observed for phenotypic data. Sea buckthorn’s nature of anemophily favours geneflow (Fan et al., 2007; Mangla et al., 2015), particularly considering the small distance between sites, a common behaviour also in other wind-pollinated (outcrossing) woody species (Hamrick et al., 1992; Breton et al., 2008). The other reason for this lack of genetic differentiation among stands was the

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mode of propagation in the traditional management of sea buckthorn based on indigenous knowledge. Traditional silvicultural practices for sea buckthorn in GB include livestock browsing and pruning of branches for fire-wood collection and home fencing. Thus, propagation takes place mainly through assisted natural regeneration but also partially from sowing of seeds, cuttings, and the subsequent transplantation from the nearby areas. Thus, the selection of trees for re-growth is not based on desirable phenotypes but occurs rather randomly, which may have led to the low genetic differentiation between both stands. Similar findings were found for the tropical fruit tree Inga edulis reportedly having a similar genetic diversity in cultivated and wild populations (Hollingsworth et al., 2005) and Vitellaria paradoxa having higher genetic diversity in human managed forest stands (Kelly et al., 2004). The combination of quantitative and qualitative results provided clear evidence of lacking domestication in the investigated accessions. In the investigated area of GB populations of sea buckthorn are likely natural and share a considerable genetic variability. This may be due to the following: First, sea buckthorn is still considered a wild crop (though occasionally planted) throughout the study region and its robust re- growth or growing behaviour makes it little susceptible to losses of genetic diversity. Second, subsequent long-distance gene flow via wind mediated pollination (Mangla et al., 2015) and seeds through birds (Rousi, 1971) may increase the variation in the population as found for other crops species (Anderson, 2005). Also, sexually reproducing and outcrossing species should at least maintain variation within a population (Miller and Schaal, 2006). Third, sea buckthorn as a dioecious species promotes higher genetic diversity than monoecious plant species (Muyle et al., 2020). Also, in our study region, higher number of female plants were maintained for fruit collection and male plants were heavily pruned for fire wood (personal observation). This female-biased sex ratio leads to higher genetic diversity than a male-biased one (Vandepitte et al., 2010; Rosche et al., 2018). Fourth, perennial tree species tend to retain a high portion of variation in the population even during the process of domestication (Miller and Schaal, 2006; Pickersgill, 2007). Lastly, farmer-led management of P/PGR affects the spatial distribution of populations but may have no significant effect on genetic diversity within populations (Ekué et al., 2011). The diversity present in the studied sea buckthorn populations allows the selection of individuals with superior characteristics that can be employed for future breeding programs and cultivation strategies. However, the practical exploitation of

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sea buckthorn in GB (and neighbouring high altitude regions of Pakistan), appears to be difficult as the status of sea buckthorn among the different governmental units is somewhat unclear. The species is also not listed as a priority species on regional agendas contributing to the lack of government interest in it. Also, the agriculture and horticulture departments does not consider sea buckthorn as a crop but rather as a weed, while the forestry department does not account for sea buckthorn, as it does not fulfil the criteria of a forest plant. Hence, no reliable record and information on total naturally grown area, maintenance, conservation strategies, current uses, and multiplication in regional nurseries is available. This shows exemplarily the weak institutional awareness of a P/PGR among many in GB. In contrast, NGOs (foremost AKRSP) and entrepreneurs contribute substantially to the awareness of sea buckthorn across the northern regions of Pakistan.

5.3 Testing the second hypothesis Varietal richness and diversity in apple accessions decline from remote to main road areas. Areas away from main roads showed higher varietal diversity due to lower influence of modern varietal introduction. However, there was no obvious trend of genetic and morphological traits among varieties based on the locations (far from and close to the main road). Therefore, the second hypothesis is rejected. The methodology adapted to analyse the hypothesis was reasonable. Two dead-end valleys were selected by assuming that plant genetic materials can only be introduced from its lower areas such as main roads and trading markets instead of mountainous pathways. Therefore, the most remote village was considered the least influenced one. In order to guarantee enough sample coverage of local apple accessions from each village, an exhaustive snowball sampling was performed complemented by farmer interviews. Even accessions which were unattended and obviously different from the ones sampled and characterized were included. Thus, trees from the orchards, home gardens, and along fields or roads were sampled, which allowed comparisons across sites and ensures the gathering of sufficiently variable data for analysis. Fruit availability for characterization during the survey was challenging as fruit ripening times differ substantially along the altitudes sampled. The fruits from the lower altitudes ripened earlier and were mostly harvested for storage, home consumption or

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sale. Fruits from high altitudes in contrast were mostly unripe for appropriate characterization and could thus partly not be included. The timing of sampling is therefore a very important factor and should be considered when resampling will be performed. Revisiting different altitudinal regions and sites seems indispensable to exhaustively cover apple diversity. Along with the above discussed environmental factors, tree specific characteristics such as age and vitality as well as tree management (for instance pruning, fertilization, and irrigation) can cause considerable phenotypic variability in apple fruits (Costes et al., 2006; Cavael et al., 2020). Although these factors are important to consider, their effect could only be vaguely assessed with the comparably low number of samples. A larger number of samples and replicates is therefore required for future investigations. Nevertheless, despite these constraints, this study is useful in understanding the farmers’ classification system at the varietal diversity level for in situ conservation of agrobiodiversity. This involves interview-based surveys and a complete agroecosystem mapping in order to determine apple varietal diversity. This approach is very helpful because farmers often report fewer varieties during interviews as compared to actual mapping inventories of the varieties actually grown (Currey, 2009). Apple varieties which were marginally used for eating due to sour taste (mainly used as a pickle) and lack of marketable traits were rarely reported by the farmers. The calculation of alpha- and beta-diversity in our study was to our knowledge done the first time for Malus spp. Although this approach opened an interesting view on the available richness and diversity, it was difficult to compare these findings with other studies. On the other side, the study encourages the use of both measures in apple research and meta-studies with archived abundance and varietal richness data of Malus spp. Villages near to the main trading route (former Silk Route) exerted higher diversity due to higher introduction of plant genetic material. Overall, diversity in Baltistan Valley was higher as compared to Ishkoman Valley. The reason of this higher diversity might be that these areas are less affected by land use change and are therefore suitable for preservation of P/PGR as suggested in previous studies (Forsline et al., 2003; Richards et al., 2009; Cornille et al., 2013; Omasheva et al., 2017). However, SSR marker data showed that there is enough gene flow among villages as well as valleys. This indicates that remoteness and distance of regions is not necessarily responsible for genetic sub-structuring.

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The analyses of individuals based on genetic cluster assignments and farmers’ local classification system revealed five sample set-related affiliations that are putatively true-to-type (same name, same genotype), synonyms (different names, same genotype), homonyms (same name, different genotype), ambiguous (homonym and synonym character), and unique accessions (different names, different genotype). According to the results of SSR-based genetic fingerprinting, almost half of the varieties were erroneously assigned by the tree owners. False varietal identification is a prevailing problem not only for apples (Pereira-Lorenzo et al., 2018; Marconi et al., 2018), but also for other tree crops such as pear (Bassil et al., 2009), almond (Gouta et al., 2010), olive (Işik et al., 2011), and grape (Boz et al., 2011). All mentioned and other related studies were only focusing on synonyms and homonyms concepts but rarely discussed true-to-type, ambiguous and unique affiliations within a sample set. Thus, the current study enhances the understanding of classification concepts which could be potentially used in future studies. Additionally, identification of private alleles showed that there are unique plant genetic materials that are important for adaptation under changing environmental factors (Allendorf and Luikart, 2007). These are further favoured by fruit morphological characterization which revealed that there are high numbers of rare phenotypes. Given the existence of unique genotypes and the fact that apple diversity seems to be threatened in the region as a result of deforestation and progressive replacement by modern varieties, there is a great need to develop strategies for the conservation and protection of local varieties. The missing difference between the variability of genetic and morphological traits among varieties from remote as compared to those of main road areas may be due to several factors: First, apple propagation in GB is exclusively vegetative through grafting. Seedlings in contrast are usually not allowed to grow on managed modern agricultural lands. This led to a rather homogenous populations over time (Miller and Schaal, 2006). Second, propagules such as rootstocks, scions or even seedlings are exchanged within and occasionally between valleys. Third, the domestication syndrome and loss of genetic diversity is less prevalent for perennial fruit crops like apple (Cornille et al., 2014), because of less recombination and sexual propagation cycles in a given time period (Pickersgill, 2007). Fourth, apple planting is still performed in traditional or informal agriculture habitats in the region such as backyard gardens and orchards. The genetic variation in these habitats is typically higher than

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in modern plantations, thus acting as reservoirs for genetic diversity (Brush, 1995, 2000; Miller and Schaal, 2006). This study demonstrates that genetic analysis together with phenotypic and survey-based diversity assessment is crucial to understand varietal variability in the region. However, lack of sufficient repetitions in the form of dead-end valleys has likely prevented proper interpretation and needs to be considered in case of future resampling. To the best of our knowledge the local/traditional varieties identified and characterized never underwent taxonomic description previously, thus this study provides first insights into the region with complex evolutionary processes for apple in an infrastructurally difficult situation.

5.4 Testing the third hypothesis Underutilization of apple and sea buckthorn resources results from local peoples’ unawareness regarding their management practices and potential uses.

5.4.1 Sea buckthorn In comparison to Pakistan, China and Mongolia subsidize their sea buckthorn farmers and pay fixed prizes for the yield of wild collectors. In 1985, the Chinese government started an initiative to plant sea buckthorn in order to control deforestation in Northwest China due to which plantation area has experienced major increases (Li et al., 2015). Mongolia is promoting cultivation and processing through initiatives such as the Sea Buckthorn National Program – SBNP (MOFA, 2015). Harnessing the full potential of sea buckthorn collection results in annual household income of 3413 US$ (Balt et al., 2016). Pakistan instead is currently utilizing only about ~5% (ICIMOD, 2017b) of its natural sea buckthorn populations mainly found in Gilgit-Baltistan. People rather recently started utilizing it as a food crop, limited to the traditional local cuisine. All reports indicated that the market of sea buckthorn berries unsatisfactorily low for collectors. From the data obtained, it was shown that sea buckthorn is a highly undervalued P/PGR in GB and remains a wild plant, as no cultivation is performed, while growing wildly along roads, at shores, in riverbeds, and in many farmers’ fields. Its value is thus associated to ecosystem services such as forage provision and fuel supply, while indirect benefits are protection and reclamation of soils from erosion as well as provisions for wildlife habitat (Li and Schroeder, 1996). Traditionally, sea

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buckthorn has been used to cure several diseases such as pain, digestion problems, and cough. This traditional knowledge about medicinal plants including sea buckthorn, however, is nearly lost in the region (Salim et al., 2019). This largely reflects lack of interest and aptitude in learning about this traditional resource by the younger generation (Khan et al., 2013; Arshad et al., 2014). A few entrepreneurs and extension services that are largely promoted by AKRSP have raised some attention for this wild P/PGR especially due to its high vitamin C content, although overall remaining on a very limited level. Training workshops were recently organized for collection, maintenance, and value addition of sea buckthorn berries fostering niche product developments such as jams, syrup, squash, pulp or seed oil (ICIMOD, 2017a). One of the objectives in these trainings was to make sea buckthorn products more consumer appealing (as berries are sour in taste), by mixing the produce with other fruits such as apple and apricot. Our data revealed that collectors’ household income from value added products is significantly higher than berry sale alone, but very few households were involved in the value addition of berry harvest. Natural stand management as well as wild harvest and post-harvest handling is rather lacking on a broader scale in the region. Male to female ratio of sea buckthorn stands is not appropriate as some of the areas are rich in male plants which do not bear fruits, although they are important genetic diversity reservoirs. Significantly different harvesting and handling practices were noticed among different villages. However, local NGOs, foremost the Aga Khan Rural Support Program (AKRSP) recently introduced and encouraged the sophisticated harvesting and handling practices (ICIMOD, 2017b). Results furthermore showed that most of the collectors performing open-air sun-drying of berries before selling them to agent’s practise fruit protection with nets or transparent sheets against harsh weather conditions. Lack of suitable drying measures significantly affect berry quality caused by still high moisture contents, insect infestation, dust, rancidity, microbial contamination, and browning. These problems have been also recognized for other crops (Kaya et al., 2010; Rocha and Melo, 2011). Our study also confirms that vitamin C content in sea buckthorn berries decreases drastically under sun-drying. As collectors are mostly unaware of quality standards controlled by the above listed factors, the selling price of the raw product fluctuates tremendously in the region.

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Although sea buckthorn collection and trade offer a potential source of off-farm income and can support small-scale industry in GB, farmers are rather unwilling to further exploit this plant resource. Along with the comparatively difficult and time- consuming manual harvest and indecent price revenues, an unregulated supply chain prevails with a large dominance of middlemen (Larsen and Olsen, 2007). Their oligopoly discourages farmers to cultivate, and wild collectors to collect sea buckthorn. Also, collectors were not interested in value addition because generally, sale revenues of these products are low reflecting low market demand. Moreover, supply chains of NUS like sea buckthorn play an important role as stepping-stones by spreading income across multiple stakeholders providing economic safety nets. However, such a shift from subsistence to commercial may also hinder the poorest to access these infrastructures because of inadequate control of harvest negotiation (Marshall et al., 2006). Sustainability issues in supply chains are not very much emphasized due to involvement of informal and temporary stakeholders, thus overall poorly studied. Addressing such issues and their solutions will ultimately help to uplift supply chains for marginalized people of remote regions of the developing regions such as Gilgit- Baltistan.

5.4.2 Apple The study on apple showed a similar picture of neglect due to lack of awareness and management forces although favourable climatic conditions and abundant water resources make this region highly suitable for apple cultivation. Given increasing global warming, however, flower initiation, fruit colouration, texture, and taste may change. Insufficient chilling hours are known to reduce flower initiation and fruit quality (Rai et al., 2015) and therefore marketability. Moreover, higher temperatures along with moisture stress increases sunburn and cracking in apple particularly at higher altitudes. This was often observed in modern apple cultivars. Ongoing agricultural transformation processes such as changes to monocultures of cash crops (commercial apple varieties) and abandonment of the traditional karez irrigation system along with inadequate chilling make apple susceptible to diseases like scab, red spider mite infestation, and premature leaf fall (Rai et al., 2015). It is certainly difficult to make future projections, but farmers may have to shift apple cultivation from lower to higher altitudes because of lacking chilling. This in turn may require a shift from modern varieties to more locally adapted germplasm because

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of several reasons: First, many local varieties are physiologically well adapted to the available high radiant energy (1500–1900 kW m-2 a-1) of GB by resisting sunburn. Second, sampled local varieties are broadly resistant against diseases and pests of which almost no symptoms have been witnessed. A generally high vitality of local apple germplasm was also found in Kazakhstan (Forsline et al., 2003), Turkey, and Southern Russia (Volk et al., 2008), and North Caucasus regions (Höfer et al., 2013). Although most of the farmers favoured modern commercial apple varieties as cash crops in their agricultural fields, some of the local varieties were found to be popular on local markets. The taste, fragrance, and appearance of regional apple varieties are famous in GB as well as on national markets. For instance, the variety Sas Polo has a very soft pulp, is delicious in taste, develops mostly red coloured fruits, and is thus exported to national and international markets. This variety is widely grown in Baltistan region especially in Paari Valley, Kharmang, south of Skardu (Wazir, 2020). Fruit taste from this valley is reportedly unique as mentioned by the locals during our survey. Unfortunately, this village could not be included in this study as it is bordering with India and prohibited for foreigners. However, it is worth to explore and confirm such reports in future studies including the Indian Himalaya region to compare the available genetic resources of apple across the modern boarders. Examples of some other famous traditional varieties from Baltistan Valley are Kachura Ambary, Shakkar, and Gohar Aman, all marketed on local and national markets (Star Farms, 2013). During this survey, a number of suitable characteristics in other local varieties was observed such as taste (sweetness, juiciness, and freshness), appearance as well as fruit shape and size. However, the majority of these local varieties was not widely recognized among local traders. Moreover, local varieties were undervalued due to lack of knowledge about the available germplasm and their substitution by recently imported commercial cultivars such as ‘Golden Delicious’, ‘Red Delicious’, ‘McIntosh’, ‘Jonathan’, and/or ‘Cox’s Orange Pippin’ (Whiteman, 1985). In the past 20 years, such replacements in apple germplasm were observed in US states of Washington (Jarosz and Qazi, 2000), Ohio (Goland and Bauer, 2004), and North Carolina (Veteto and Carlson, 2014). Recognizing the potential and promotion of the local varieties in regional markets is very important for conservation through use (already observed for some varieties discussed above) as practiced widely in Ohio (Goland and Bauer, 2004).

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Some of the GB farmers were found unaware about the optimal harvest time of their crop which is problematic as early harvesting restricts development of full quality parameters and late harvesting limits the shelf life of the fruits (Testoni and Eccher Zerbini, 1989; PennState Extension, 2017). Also, they have negligible knowledge about possible value-added products as only very few farmers were processing fruits into jams, chips, powder, and beverages. This hinders the optional usage of local apple varieties in the region. Thus, fruits were mostly consumed as dessert fruit and stored for animal feed, while only small amounts were sold. Although grafting is a widely used and historically practiced for different fruit trees including apples in GB, farmers were not concerned about grafting and the planting history. Most of the surveyed traditional trees were planted by their forefathers and left abandoned due to limited usability. Some of them were even grown through seeds or the spot has been overgrown as no grafting spot was visible. Farmers also claimed lack of access to today’s popular rootstocks such as M9, M26, M106, and M111 for grafting with local varieties in order to improve their apple genetic pool. As commercial nurseries have a monopoly and favour modern varieties, they only provide classical rootstocks to large-scale farmers. This setup necessitates the grafting of modern cultivars in return of purchasing the whole produce of a season.

5.4.3 Common problems and constraints A range of common problems and constraints for farmers/collectors of apple and sea buckthorn was identified. Arboricultural activities such as pruning (which is currently limited to the cutting of main branches) and appropriate or maintained planting distance was not witnessed for both studied species throughout the region, although these measures are important factors for most species to facilitate harvesting and yield increase (Li and Beveridge, 2003). Pruning may also enhance the efficient utilization of water and sunlight which is essential for fruit development (Corelli- Grappadelli and Lakso, 2004). Also, many farmers lack knowledge, facilities, and equipment (pickers, scissors, nets, ladders, and chained gloves) for the diverse activities involved in effective fruit production. This indicates the deficiency of agricultural extension services in GB. At present, tree management practices focus on the protection of young plants from browsing with thorny branches of sea buckthorn and wrapped cloths around stems.

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The effective use of value chain approaches to refined consumer/customer- oriented products requires informed harvesting, post-harvest handling, transportation and storage conditions. Improper harvesting methods as observed for sea buckthorn (threshing with wooden sticks) and apple (collection by climbing trees and throwing down fruits) damage fruits unnecessarily and result in lower product prices. Poor storage conditions may cause damage, contaminations, mould and/or rancidity (Marsh and Bugusu, 2007), severely affecting the quality of the fruits and berries. Such pre- and post-harvest losses account for up to 60% of harvests (Khan et al., 2019) affecting the overall revenue from the crops. Moreover, collectors and farmers also claimed that annual yields were subjected to alternative fruit bearing behaviour and partly harsh weather conditions, reducing the predictability of revenues. Many additional factors hinder commercialization of these local resources such as lack of market access due to remoteness and poor road infrastructure, lack of cooling chains, low consumer awareness about the local products, low quality, and large price fluctuations. Therefore, local farmers and collectors are largely limited to regional markets rather than selling their products to national and international markets. In 2019, the total regional fruit production of Sas Polo (one of the most popular local apple variety) was approximately 8044 t out of which only about 2134 t were marketed, 3777 t were used for home consumption (eating and animal feed), and 2133 t were wasted (Baltistan Star, 2019). The above discussed constraints and problems result in the partial abandonment of local fruit resources by indigenous people. Similar handling and marketing related issues are also predominantly reported for apricot in GB (Kousar et al., 2019) and for apple in Chitral District of Khyber Pakhtunkhwa Province (Khan and Bae, 2017) as well as from other mountainous regions of developing and transition countries (Huddleston et al., 2003; Rasul, 2010; Tiwari and Joshi, 2012).

5.4.4 Solutions Currently, the agricultural departments together with NGO’s in GB are working on the establishment of plant nurseries to increase the availability of highly demanded planting material which are, however, foremost commercial cultivars. Since 2019, the Economic Transformation Initiative (ETI) program with the mutual funding of the Government of GB and International Fund for Agricultural Development (IFAD) are providing incentives to farmers to revive traditional apricot orchards (Abdul Ghaffar,

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2019). There is a need to foster such initiatives also with respect to other local fruit tree species including apple. The farmer and/or conservationist-assisted preservation of local apple germplasm would be a viable alternative to maintain local varieties as successfully done in many western nations (Veteläinen et al., 2009; Marconi et al., 2018; Bramel and Volk, 2019; Heinonen and Bitz, 2019). Fostering certification systems for traditional P/PGR resources such as fair wild certification for sea buckthorn (as harvested wild) and organic certification for local apple varieties (as grown without any pesticide and fertilizer application) could be viable options. Currently, value addition has only been performed at a very small scale but if promoted, could be considerably beneficial to improve farmers/collectors’ incomes and valuing local varieties and products. Certification schemes, particularly for producer groups, may play an important role. Whether local communities can stem such developments or national and international players may need to support such endeavours by providing incentives to local entrepreneurs and promoting local products as observed with a joint WWF-UNDP-Coca Cola initiative to produce sea buckthorn pulp, is still debatable.

5.4.4.1 Training for management practices Proper management practices involving agroecological, ethnoecological, and low external input technology (LEIT) approaches facilitating poor farmers or collectors of highlands could be appropriate in improving productivity (Altieri, 2002, 2004; Tripp, 2012). These approaches value the traditional or local knowledge by recognizing the limitations of the currently used practices and modifying them or introducing new practices with agroecological principles. Such practices may be beneficial by (i) improving short-term yield by enhancing proper tree pruning, thinning, and biological disease and pest control; (ii) improving soil quality through more effective nutrient and biomass recycling employing organic fertilizers and composting; (iii) ensuring agrobiodiversity maintenance by grafting, selection and establishment of suitable saplings (Currey, 2009; Tripp, 2012). At present only a few farmers practice pruning, fruit thinning, and composting. Therefore, trainings through agricultural extension services or different development programs may be beneficial. Such training initiatives were helpful in increasing farmer incomes in Kyrgyzstan (Currey, 2009). However, adaption of these practices and its diffusion from extension services staff to trainers and non-trainers (neighbour, or other

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villagers) also depends on other factors such as practical knowledge, plot area, risk aversion, lack of credit, and input availability (Mazvimavi and Twomlow, 2009). In this ecological/socio/cultural acceptance of the innovative practices for the farmer should not be neglected during adaption strategies (Swinton and Quiroz, 2003; Nazarea, 2003). Therefore, factors such as improvement in access to information, regular training programs, availability of well-trained agronomists in extension services, availability of micro-credits, and input supply for small groups could encourage households to adopt new management practices (Mazvimavi and Twomlow, 2009; Currey, 2009; Tripp, 2012).

5.4.4.2 Improving marketing/commercialization skills Small holder farmers of GB have a lack of direct contact with buyers (consumers, food processors, and exporters) which is one of the known major obstacles in improving household’s income (Wegren, 2004). Increase in market demand and distribution networks enhance the household production and may hence improve family income (Lerman, 2008). There is a need to educate farmers using a participatory education strategy geared towards agricultural business skill development and the important role of market linkages. Also, knowledge about how to best identify fruit buyers and marketing communities and how to establish village- based, collective bargaining groups by enhancing communication within villages helps to better deal with buyers. Such developmental initiative were successful in Kyrgyzstan and greatly facilitated fruit sales (Currey, 2009). Lastly, farmers often sell their produce at low prices when they need cash such as for household utilities, school fees, clothing. Ironically, they sometimes buy those value added products for which they have produced the raw material (Currey, 2009). Thus, there is a need for improved fruit storage and drying-facilities in such training programs which in combination with the availability of micro-credits can help farmers to better plan the sale of high quality produce (Marsh and Bugusu, 2007). Establishment of cooperative storage (particularly cold storage), drying facilities and packaging units are vital for minimizing post-harvest losses of wild and cultivated crops in highland regions such as GB.

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5.5 Concluding recommendations • Sea buckthorn and apple can act as model species that emphasize the need and development of locally suitable conservation and management strategies of P/PGR species. • In GB local nurseries should be encouraged to promote/protect traditional varieties along with modern varieties in order to maintain a diverse gene pool flexible for adaptation also in view of climate change. • It is important to foster governmental and non-governmental based incentives to farmers promoting awareness about the potential of the local germplasm for multiple value-added uses. • Government and non-government institutions may subsidize farmers to convert dense sea buckthorn thickets into productive stands by maintaining suitable plant distance, which allows an easier collection of berries. • To avoid quality deterioration and boost economic benefits, farmers should be educated about quality losses by current sun-drying methods. Central village- based processing, drying, storage, and grading facilities should be established, and trainings be conducted to process and market the produce. • It may be useful to mainstream neglected and underutilized food crops like the studied ones within the government agenda of policies and programs. • There is a need to characterize and document the available germplasm resources, indigenous knowledge on PGRs, and to ensure their availability to the local communities. • There is great potential to generate market facilities and linkages, improve access to credit, decentralize extension services, support local food chains and establish a local fruit processing industry. • It is necessary to conduct a cross-border analysis with China and India to improve the understanding of plant richness and diversity for both species as well as their long history of plant introduction and spread at the sub-continental level. • The comparatively high genetic diversity and naturalized populations of sea buckthorn and apple provide promising a justification for future on-farm (in situ) conservation, breeding potential traits, and use of effective domestication strategies.

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• The lack of genetic differentiation among human or farmer managed and natural ecosystems in both sea buckthorn and apple point to strong gene flow among populations without an apparent loss of genetic diversity.

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