S1609786 Copperthwaite G NS6344 Dissertation

University of Gloucestershire

NS6244 Ecological and Environmental Science Dissertation Topographical and Plant Density Effects on the Rates of Hybridisation of Bluebells (Hyacinthoide)

Ecology and Environmental Science Assessment 02 May 2019

Guy Copperthwaite s1609786

Presented as part of the requirement of an award within the Undergraduate Modular Scheme at the University of Gloucestershire

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Declaration: This dissertation is the product of my own work and does not infringe the ethical principles set put in the University’s Handbook for the Research Ethics. I agree that it may be made available for reference at the discretion of the University of Gloucestershire.

Signed: ……………………………………………..

Guy Copperthwaite

Dated: 1st of March 2019

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Abstract

The United Kingdom currently maintains the world’s highest distribution of Hyacinthoide non-scripta (Lilacease) of approximately 25% to 50%, but now sees this species under threat from anthropogenic mediated introductions primarily from the Iberian Peninsula (Kohn et al., 2009; Grundmann et al., 2010; Allum, 2016). Recent civilian science based surveys by the Natural History Museum and the Woodland Trust suggest the balance between the invasive Hyacinthoide hispanica and native species now places the endemic H. non-scripta under threat of national and international (Europe) elimination through hybridisation (Grundmann et al., 2010; Marquardt, 2016). Surveys and studies have clarified a genetic drift (Kohn et al., 2009; Grundmann et al., 2010; Allum, 2016; Marquardt, 2016) towards the potential prevalence of the Hyacinthoide x massartiana by assessing competitiveness and hybridising interactions between native and alien taxa through co-occurrence and abundance in relation to habitat occupied, land type cover and phenotypic variables on a large geographic scale (Kohn et al., 2009; Allum, 2016). The aim of this research/study is to establish whether hybridisation is limited by natural topographical features and flora density of a deciduous woodland or alternatively, demonstrate that no natural feature is able to limit the gradual silent extinction of the H. non-scripta from the United Kingdom. To do this a woodland was selected based on its variability of flora and topographical features. An area of 4.8km² was surveyed using geographical system positioning to plot every group of bluebells by position, area and elevation. Each group was counted using a random cluster sampling method and an in depth analysis was conducted at all elevations with the use of a random generator to determine area to be surveyed. All explanatory variables: density, flora types, atmospheric and ground temperatures, incline, pH, wind speed, luminosity and soil construct were recorded. Results showed (1) native species were only 42.17% of all bluebells recorded, (2) distribution of both species types were recorded at all elevations, (3) H. hispanica related to variable associated to areas of human habitation. The distribution of data suggests that through the introduction of invasive species the flow of genetic gradualisation is turning towards a landscape saturated by hybrids, (4) that elevation was not the determining factor that limited the complete hybridisation of H. non-scripta.

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Acknowledgements

My gratitude goes to Dr Richard Rolfe, Senior lecturer in Biology and Dr Oliver Moore Lecturer in Applied Ecology, Dr Robert Berry, Research Fellow, Countryside and Community Research Institute and Dr Lucy Clarke Senior Lecturer in Physical Geography, Environmental Sciences, for their guidance, support and enthusiasm.

To Dr Mark O’Connell, Lecturer in applied Ecology, Professor Adam Hart, Professor of Science Communication, Environmental Sciences, Mr William Carpenter, Laboratory Technician, Biosciences and Miss Caro McIntosh, Laboratory Technician, Cartography - my upmost thanks for not only the guidance shown in pursuit of the project but more importantly, the moral support that encouraged me to stay on task but also consider my future research aspirations.

My grateful thanks also goes to all staff that have listened to my proposals, wishes, desires and aspirations in the pursuit of my education but also more importantly, my wish to make a difference in the world of ecology and environmental science. I appreciate that not all requests by me, and consequently, support given, fell within the remit of the university. However, support was given and for that, I will be eternally thankful.

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Table of Contents Declaration II Abstract III Acknowledgements IV

1. Introduction 1

1.1 Evolution and Distribution of Asparagaceae Scilloideae 1 1.2 Distribution of H. non-scripta and H. hispanica 2 1.3 Ethno-medicinal and Industrial Use 4 1.4 Overview of Bluebells within the British Isles 4 1.5 Status and Protection of the Hyacinthoide non-scripta within the British Isles 5 1.6 Studies and Surveys to Date 6 1.7 Aim of Study 7

Fig 1 Geographical distribution of flower phylogeny of the Hyacinthoides 5

2. Materials and Methods 8

2.1 Study Area 8 2.2 Bluebell Taxa and Identification 11

2.2(a) Hyacinthoide non-scripta 11 2.2(b) Hyacinthoide hispanica 12 2.2(c) Hyacinthoide ‘x’ massartiana 13

Fig 2 Map Location of Cranham Village and Buckholt Woods 8 Fig 3 Overview map of the Gloucestershire’s Cotswold Commons and Beechwood National Nature Reserves (NNR) 9 Fig 4 Digitised map of Buckholt Wood and the surrounding area 10 Fig 5 Images of Hyacinthoide non-scripta 13 Fig 6 Images of Hyacinthoide hispanica 13 Fig 7 Images of Hyacinthoide ‘x’ massartiana 14

2.3 Sampling Strategy and Independent variables 14

2.3(a) Overview of Site and Geography 14 2.3(b) Survey Techniques 16 2.3(c) Elevation 18 2.3(d) Climate Conditions 19 2.3(e) Flora by Taxon and Soil Condition 19

Fig 8 Survey example by Region and Count Location 15 Fig 9 Overview of count area 18

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Table 1 Number of locations and quadrats per location 18

3. Results 20

3.1 Testing of Taxon by Elevation 20

3.1(a) Inter and Intra species Testing 21

3.2 Climate Conditions 23 3.3 Flora by Taxon and Soil Condition 29

3.3(a) Flora Distribution by Taxa 29 3.3(b) Soil Condition 32

Fig 10 Consolidated Yearly Frequency Counts 21 Fig 11 Non-transformed Frequency Count Data 21 Fig 12 Inter-species Correlation 22 Fig 13 Intra-species Correlation 22 Fig 14 Time Series Analysis for Prime Abiotic Factors 23 Fig 15 Overview of H. hispanica Frequency Counts using 3D Spatial Analysis 24 Fig 16 Overview of H. ‘x’ massartiana Frequency Counts using 3D Spatial Analysis 25 Fig 17 Overview of H. non-scripta Frequency Counts using 3D Spatial Analysis 26 Fig 18 Overview of hyacinthoide Frequency Counts by Taxa using 3D Spatial Analysis 27 Fig 19 3D topographical maps with hyacinthoide distribution using spatial analysis 28 Fig 20 Flora Data 2018 30 Fig 21 Tree Data 2018 30 Fig 22 Flora Data 2017 and 2019 31 Fig 23 Tree Data 2017 and 2019 31 Fig 24 Survey Type One Abiotic and Biotic Data 31 Fig 25 Survey Type One Abiotic and Biotic Data 32 Fig 26 Survey Type One Abiotic and Biotic Data 32 Fig 27 Correspondence of Bluebell Percentage to Soil pH 33 Fig 27(a) Sample Test Areas with no Flora Growth x 3. 33 Fig 28 Bluebell Distribution as a Percentage by Taxa 2D 34 Fig 29 Survey Type One Sample Sites 2D 35

Table 2 Taxa by Mean Average and Elevation 20 Table 3 Data Corresponding the Quantity of Bluebells by Taxa 23 Table 4 Data corresponding the Quantity of Bluebells by

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Taxa as a Percentage Compared to Soil pH. 33

4. Conclusion 36

4.1 Other Considerations 37 4.2 Limitations in Data Collection 38 4.3 Future Research 38

Supplementary Information

Fig 30 Images of Bluebells with Morphism from Cranham Woods 46 Fig 31 1:1000 Master Maps of Count Area (Example) 47 Fig 32 Count Data for 2018 48 Fig 33 Count Data for 2017 and 2019 49 Fig 34 Count Locations and Tracked Data using ‘Track Manager’ in Garmin GPSMAP 62 -2D 50 Fig 35 Images of Hybrid North and Hybrid South Iberian Peninsula 51

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Chapter 1: Introduction

1.1 Evolution and Distribution of Asparagaceae Scilloideae

Bluebells are a bulbous (monocotyledon) perennial that is part of the genus Hyacinthoide Heist. Ex Fabr. Presently there eleven species within the group with one known hybrid. Recently their taxonomy and relationship were phylogenetically revised from the group known as Hyacinthaceae (Grundmann et al., 2010) into the family Asparagaceae s.I (APG III, 2009), sub-family, Scilloideae, of the genus Hyacinthoides (Pierre Chouard: 1934) (Pfosser and Speta, 1999). Prior to the bluebells new classification, bluebells were commonly referred to as Endymion non- scriptus or Scilla non-scripta (Johann Centurius von Hoffmannsegg and Johann Heinrich Friedrich Link transferred species to Scilla in 1803 and Christian August Friedrich Garcke transferred species to Endymion in 1849).

The origin of the bluebell through the family Hyacinthoideae sensu (Chase et al., 2009) has been traced back to sub-Saharan-Africa where it is thought to have been established around the Miocene period (Ali et al., 2012; Buerki et al., 2012). Dispersal into the Mediterranean region was thought to have started around 20 million years ago (mya) (Buerki et al., 2012).

With the aid of molecular clock dating, using plastid sequences, it is suggested that the origins of the Iberian species originated approximately 5.81 million years ago (mya) (Ali et al., 2012) prompted by the start of diversification initiated through the large scale desiccation of the Mediterranean sea during the Messinian salinity crisis of around 5mya (Grundmann et al., 2010). Further diversification was thought to have occurred with the split of the H. non-scripta and H. hispanica clade by Pleistocene glaciation cycles around 2.58mya (Grundmann et al., 2010).

The family Hyacinthoideae has since divided into three monophyletic tribes; with one group restricted to the French/Italian Alps and two groups overlapping in the southern Iberian Peninsula and Northern Morocco. The Hyacinthoideae variants (reclassified as Scilloideae Hyacinthoides) are now considered to have a strict Mediterranean origin.

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Western Iberian Peninsula maintains a widespread distribution of five species within the genus Hyacinthoides. Grundman et al., (2010) confirmed the geographical distribution of the five variants using DNA extraction, PCR (Polymerase Chain Reaction) amplification and sequencing. These analysis confirmed the following species: H. non-scripta, H. hispanica, H. paivae, H. reverchonii and H. mauritanica (Figure 1). Grundman et al., (2010) also confirmed within that study, the existence of an unknown species located in north east of Spain.

The distribution of these five species are separated into two clades. The south western/central clade (southern Portugal and south eastern Spain) are comprised of the H. mauritanica (ma) and H. reverchonii (re). It is suggested that both species types (H. mauritanica and H. reverchonii) have achieved phenotypical variation as a consequence of speciation by geological separation due to no range overlap. This is in comparison to the second clade which covers the north east and mid northern area of Spain. Species variants includes: H. non-scripta (ns), H. paivae (pa) and H. hispanica (hi). The second clade (north east and mid northern Spain) comprises a widespread distribution resulting in two haplotypes of the H. non-scripta and H. hispanica plus an unknown phylogenetic origin for the H. paivae (Ortiz and Rodrguez-Oubi~na, 1996; Ortiz et al., 1999). Like the H. mauritanica and H. reverchonii, the unknown origin of the H. paivae is due to geographical separation.

1.2 Distribution of H. non-scripta and H. hispanica

Currently, the British form of the H. non-scripta (L.) Chouard ex Rothm., ranges from the north west of Spain, spreading along the Atlantic coast (northern France, northern Belgium and south west Holland) into the British Isles (Grundman et al., 2010). Expansion into the British Isles is thought to have occurred post glacial (cca., 8 TYA) from northern France using the English Channel land bridge that is thought to have been present during the that time (Hewitt, 1999); alternatively, it is postulated that bluebells were transported by migrating/trading humans that used the bluebell bulbs for their ethno-medicinal effects (Hodkinson and Thompson, 1997).

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ns

pa

hi

ma

re

Hybridisation zone

Figure 1. Geographical distribution showing flower variation with a simplified phylogeny of Hyacinthoides species. Dark pink circle indicates an area in northern Spain indicates with a known distribution of unidentified species.

(Distribution and phytogenic information by Grundman et al., 2010) (Images from Grundman et al., 2010)

Map: 1:250,000 Raster (TIFF Geo-Spatial) 1:250,000 OS Global Outline, Updated 2019, Using; Edina Digi-map Ordnance Survey Service < https://digimap.edina.ac.uk/roam/download/os> Downloaded: March 2019.

Maps created using QGIS 2.16.1 NØdebo.

Distribution of hyacinthoides is via two forms, seed germination and distribution through loculicidal dehiscence and natural vegetative reproduction. Bluebells prefer slightly acid soils as within the same woodland niche, alkaline conditions would normally be occupied by other species (Packham, 1992). As an adaptive woodland species, the young seed radicle is able to penetrate through a thick layer of leaf litter. Seed germination in both the H. non-scripta and H. hispanica is determined by a

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two-phase temperature treatment due to their need to adapt to their distribution range (Blackman and Rutter, 1954; Thompson and Cox, 1978; Vandelook and van Assche, 2008). Distribution is based on temperature with the highest and lowest seasonal peaks prompting either seeding or natural vegetative reproduction (Blackman and Rutter, 1954). Bulbs have contractile roots and over the season draw themselves deeper into the soil. Primary bulbs produce daughter bulbs with each new bulb giving rise to a new plant.

1.3 Ethno-medicinal and Industrial Use

The bulb of the bluebell contains reserves of carbohydrate and sucrose in the form of fructose (fructan) (Brocklebank and Hendry, 1989). Throughout history the sticky sap produced by the bulb has been used in the manufacture of arrow-heads, the fixing of book bindings and as a starch that created a rigidness to the cuffs and collars of Elizabethan clothing (Simmonds and Sims, 2004). Medicinally, bluebells have supported the treatment of leprosy, snake bites (Simmonds and Sims, 2004), and leucorrhoea (discharge of mucus from the vagina) (Mulholland et al., 2013). Bluebells contain glycosidase-inhibiting alkaloids (Watson et al., (1997) and are known to cause abdominal pain, dysentery, lethargy and dullness in mammals once consumed (Simmonds and Sims, 2004; Watson et al., 1997).

1.4 Overview of Bluebells in the British Isles

The United Kingdom currently maintains an estimated 25 to 50% of the world’s population (Ingrouille, 1995) of Hyacinthoide non-scripta (L) Chouard ex Rothm. In Scotland the native/British bluebell (H. non-scripta) is referred to as the harebell, Campanula rotundifolia. The distribution of the H. hispanica (Mill.) Rothm., in contrast, only occurs naturally in the central to western regions of the Iberian Peninsula (Grundmann et al., 2010).

The H. non-scripta has come under threat due to over grazing, changes in land use, over exploitation due to commercialisation and more importantly, through the introduction of non-native horticultural varieties (Kohn et al., 2009) such as the Hyacinthoide hispanica (Mill) Rothm. This has led to the hybridisation of the

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indigenous H. non-scripta, creating a newly recognised sub-species, Hyacinthoide ‘x’ massartiana (Geerinck).

Selling of H. hispanica on a large scale commercial basis has allowed the sub- species to become naturalised, and with pollination compatibility, ubiquitous on a national scale. Concerns have been expressed regarding the future of H. hispanica and H. ‘x’ massartiana and its ability to outcompete and replace native species through a degradation of the native bluebells genetic integrity (Kohn et al., 2009). Due to the H. hispanica and H. ‘x’ massartiana larger taxa (Figure 1), both species are now considered prevalent (Huxel, 1999 and Pilgrim and Hutchinson, 2004).

Further decline in the population of the H. non-scripta has to be considered, however, it is currently not clear in how that reversal will be achieved. Currently, restorative actions include the removal of invasive variants, reseeding from reliable seed sources, the possible introduction of Wild Boar (Sus scrofa) (Sims et al., 2014) and a study into natural ecological breaks or hybrid zones (Marquardt, 2017). To understand if a natural barrier such as topography and flora density are able to protect natural bluebell stocks is important for the future integrity of the H. non- scripta.

1.5 Status and Protection of the H. non-scripta within the British Isles

Bluebells are a well-known plant with an iconic status within the British Isles. It is highly regarded for the swathes of violet-blue flowers and sweet scent (similar to sweet pea) that it produces in the ancient woodlands of the United Kingdom during the month of cca; April (Pigott, 1984). Rose (1999) has suggested that the H. non- scripta is an indicator species often denoting areas of ancient (British) woodlands; even once the woodland has been removed.

Bluebells are not very resilient and are prone to damage, especially through cutting, trampling, and over grazing either by cattle (Bos tauros) and/or wild boar (Sus scrofa). This is substantiated through leaf regeneration after Short-term response and recovery of bluebells (H. non-scripta) after rooting by wild boar (Sus scrofa) (Sims et al., 2014). Bluebell leaves are redefined prior to season growth and once damaged cannot regrow during that season (Allun, 2016). As a consequence, the damage leads to a resource deficit in the present and subsequent year (Cooke,

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1997; Grime et al., 1988; Sims et al., 2014); affecting overall flora density and sustainability. Areas of bluebells in the past have been decimated due to exploitation whether that was for commercial or private use. Due to this, the H. non-scripta became a protected species 1998 (Kohn et al., 2009).

For over a decade, the advancement geographically in hybridisation has been studied. It is clear that the primary variable as to why hybridisation has increased significantly, is the modern retail ability to import invasive plant species into a country in such large quantities, that those plants once planted, have as a consequence, altered the natural balance (Kohn et al., 2009).

In 1998 the native H.non-scripta became a protected species and was listed under the Wildlife and Countryside Act (WCA, 1981).

1.6 Studies and Surveys to Date

The hybrid H. ‘x’ massartiana was first noted in 1963 and since then has proved to be a highly aggressive and adaptable sub-species (Pilgrim and Hutchinson, 2004). A study in southern Scotland has seen a discernible increase in hybrid bluebells in as little as three years, with research in 2009 noting how prolific the H. hispanica is compared to the native H. non-scripta (Kohn et al., 2009).

Due to reports of the decline in the density population of native bluebells, surveys have been conducted by established organisations such as the; Natural History Museum in conjunction with the Royal Botanic Garden Edinburgh (survey - 2006 to 2015), the Woodlands Trust (mapping - 2017) and the Royal Botanical Society for the British Isles (explore and record - 2019) (Rumsey 2006), to support research and gather information in regards to the potential loss of the native bluebell from all aspects of the United Kingdom’s landscape.

Reports and surveys have primarily dealt with the distribution of the three taxa, and information has been collated and analysed from sightings gathered on a social science basis. However, through a lack of clarification (Kohn et al., 2009, Rix, 2004 and Grundman et al., 2010) it cannot be concluded that these data has not considered the subtle genetic variations in its results.

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This research has considered all variations and based on current genetic analysis by Grundman et al., (2010) and Rix (2004), accepted the phenotypic criteria for the H. non-scripta. All other variations to the native bluebell criterion will be treated as invasive, however, due to the nature of the study, each variant will be confirmed statistically (Results: 3.1).

By accepting these principles of recognition, it is considered that a clearer overview will be gathered in how the variant hyacinthoide types (Rich and Woodruff, 1992) are distributed amongst a valley-situated deciduous woodland; clarifying how each variant is distributed from the potential point of source (Marquardt, 2016).

A preliminary review and count in 2017 of the village of Cranham, Gloucestershire and the adjacent woodland of the eastern side of Buckholt Wood (Figure 9), clearly indicated a change in genetic variations (reduction in inter-specific polymorphism) as the two invasive variants established themselves further away from the original point of source (Cranham village) in to the adjacent woodland (Marquardt, 2016 and Grundman et al., 2010). By assessing the observations taken, it was the aim of the research to understand how these changes were affected by distance and elevation and woodland dynamics (Allum, 2016) or whether the initial pattern observed was not consistent throughout the whole of Buckholt Woods.

1.7 Aim of Study

It is the aim of the study to establish quantitatively the following: (1) Can the natural environment protect the increased hybridisation of the H. non-scripta through woodland topography and flora density? (2) Does the local planting of the H. hispanica and/or the H ‘x’ massartiana residentially, impact the United Kingdom’s natural stock of H. non-scripta? (3) Does hybridisation increase or decrease through changes in the natural organic structure of the woodland? (4) How widespread and abundant are is the native bluebell compared to the invasive H. hispanica and hybridised H. ‘x’ massartiana? (5) To what extent do the variants co-occur?

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Chapter 2: Materials and Methods

2.1 Study Area

Figure 2. Map indicating the location of Cranham village and Buckholt woods, Gloucestershire: Village - SO 89667 12968, Buckholt Woods - SO 88944 13317. Maps created using QGIS 2.16.1 NØdebo.

The village of Cranham along with Buckholt Woods were chosen due to their proximity to each other. To understand all the variables associated in the hybridisation of bluebells, it was necessary to use a site where human mediated

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planting of invasive bluebells (residential plus gardens) were situated close enough to a healthy woodland of geographical variance in topography so that data collected could indicate whether any of these factors impeded or increased hybridisation.

With recent surveys suggesting a reduction in the population of native bluebells, in combination with a possible increase in the population of invasive bluebells, it was an additional aim to understand if the natural environment, with its complexities of geography and floral dynamics, could protect native bluebells from silent extinction.

Buckholt woods forms part of Gloucestershire’s Cotswold Commons and Beechwood National Nature Reserves (NNR). This NNR is currently the largest nature reserve in the Cotswolds and is protected as a European Special Area of Conservation due to its rare Beechwood, limestone grasslands and wildlife (Figure 3).

Last Upton St Leonards Upton St Leonards

Cranham

Sheepscombe

Painswick Painswick

Figure 3. Overview map of the Gloucestershire’s Cotswold Commons and Beechwoods National Nature Reserves (NNR) (Map from: NE335: Buckholt Wood: Cotswold Commons and Beechwoods National Nature Reserve., PDF: No scale) (Last accessed: 24/03/2019).

NNR extends across 7.5 km of the

Gloucestershire Cotswolds. Situated

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Stroud, there is ready access from the M5

motorway and the A417.

NNR extends across 7.5 km of the S1609786 Copperthwaite G NS6344 Dissertation

Figure 4. Digitised map of Buckholt Wood and the surrounding area including residential dwellings that make up Cranham Village. Maps created using QGIS 2.16.1 NØdebo. Map created from Edina Digimap, OS Historical Maps (Last accessed: 24/03/2019).

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2.2 Bluebell Taxa and Identification

All variants of bluebell in the United Kingdom flower in spring. They are a bulbous perennial which prefer slightly acidic soil, primarily in deciduous woodland. During spring, the bluebells are seen in high densities occupying areas without competition from foliage such as Holly (Ilex aquifolium), Ivy (Hedra helix) and Wild Blackberry (Rubus ulmifolius), however, they will share areas that are occupied by plants such as Ransom also known as wild Garlic (Allium ursinum), Sweet Woodruff (Galium ordoratum) and Wood Anemone (Anemone nemerosa).

Pollination is known to be mediated by both the Bombus and Syriphidae species with the bulb being renewed annually. Positioning with the woodland is important as all variants of bluebells are prone to draught with the H. non-scripta being more sensitive than the invasive hyacinthoides (Blackman and Rutter, 1954; Littlemore and Barker, 2001). Seeds are not adapted to dispersal (Knight, 1964) and have no known dormancy apart from surviving the first winter (Thompson and Cox, 1978; Thompson and Grime, 1979). Germination is in late autumn due to seed conditioning induced by high temperatures followed by a drop in temperature to 11 ºC or less (Thompson and Cox, 1978). Seed survivability in the earth and their establishment is facilitated by mycorrhizal association (Merryweather and Fitter, 1995).

Invasive bluebells within the United Kingdom are often regarded as H. hispanica but no definitive confirmation exists genetically, to actually clarify that all invasive and or hybridised bluebells are from this phenotype; this also relates to the plants ecological requirements based on phenotype (Turrill, 1952). It is however, considered that commercial cultivators may represent the greatest source of hybridisation across an unknown number of hyacinthoide variants which in turn leads to high density of H. hispanica and H. ‘x’ massartiana in the wild. Recent surveys generally classify the bluebell variants as either native or invasive/alien without actual genotypic or phenotypic certainty.

2.2(a) Hyacinthoide non-scripta

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H. non-scripta is a vigorous perennial with linear leaves (3 to 6) growing from the base of the plant, each 7 to 16 mm wide. The stem is erect bearing arching racemes (inflorescence of 5 to 12 flowers) of fragrant (Sweet pea / honey fragrance), narrowly tubular, violet-blue, or occasionally white, that are arranged in a drooped nodding pedicle construct.

Figure 5. Images of H. non-scripta (sourced from Google Images; Marquardt, 2016; Wetheral, 2017). Petal samples show pale cream anthers and pollen (Wetheral, 27 April 2017).

Each flower is 14-20mm with two bracts at the base. Tepals are strongly recurved at the tips and of a dark violet-blue colour. The stamens in the outer whorl are light in colour and are fused up to 75% of the perianth. Anthers are 2 to 3 mm and are covered in light cream / light golden coloured pollen.

Bulbs produce contractile roots that draw the bulb deeper into the soil horizons, seeking greater moisture. Bulbs can reach depths of 10 to 12cm but struggle with substrates that are difficult to penetrate – such as chalk. Enjoys inclement climates and reproduces well in wet and / or warm weather, although frost and colder weather can have a negative impact on dormant bulbs (Rose, 1981; Stace, 2010).

2.2(b) Hyacinthoide hispanica

A perennial adapted to warmer climates with linear leaves (5 to 20) growing from the base of the plant, each 10 to 35 mm wide. The stem is erect bearing arching to rigid racemes (inflorescence of 10 to 35 flowers joining in a spiral construct) with little to no fragrance supporting widely shaped perianth of a violet to light blue colour. Also, commonly occurring are plants with white and pink tepals.

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Figure 6. Images of H. hispanica (sourced from Google Images; Marquardt, 2016; Wetheral, 2017). Petal samples showing dull blue anthers and pollen (Wetheral, 27 April 2017).

Each flower is 14-18mm with one to three bracts at the base. Tepals are slightly curled back at the tips and of a light violet, with a darker violet stripe along the outside of the petal, mirroring the line of the internal stamen.

The stamens in the outer whorl are light in colour and are fused up to 25% of the perianth. Anthers are 2 to 3mm and are covered in dark violet / blue pollen. Bulbs also produce contractile roots that draw the bulb deeper into the soil horizons, seeking greater moisture to depths of 10 to 12cm. Enjoys higher temperatures but is not so well suited to wetter climates. During periods of excessive rain, can impede reproduction (Rose. 1981).

2.2(c) Hyacinthoide ‘x’ massartiana

H. ‘x’ massartiana (also known as H. ‘x’ variabillis (Sell and Murrell, 1996). Now native to the United Kingdom, however has in the last twenty years been noted in all countries with primary source of H. non-scripta and a human introduced source of H. hispanica. H. hispanica first established in Great Britain cca 1683 with hydride variations first recorded cca 1963 and recognised in 1987 (Preston et al., 2002).

A perennial with linear leaves (5 to 20) growing from the base of the plant, each 7 to 35 mm wide. The stem is erect bearing arching to rigid racemes (inflorescence of 10 to 35 flowers joining in a spiral construct) with little to no fragrance supporting widely shaped perianth of a darker violet colour than H. Hispanica. Some plants do support a lighter blue colour. Also, commonly occurring are plants with white tepals.

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Figure 7. Images of H. ‘x’ massartiana (sourced from Google Images; Marquardt, 2016; Wetheral, 2017). Petal samples show a variety of dull greyish undehisced anthers, but pale brown pollen (Wetheral, 27 April 2017).

Each flower is 14-18mm with one to three bracts at the base. Tepals are slightly recurved at the tips and of a darker violet-blue colour than the H. Hispanica - but lighter than the H. non scripta. The stamens in the outer whorl are light in colour and are fused up to 50% of the perianth. Anthers are 2 to 3mm and are covered in light yellow coloured pollen. Bulbs produce contractile roots to same and the conditions as H. hispanica (Rose. 1981).

2.3 Sampling Strategy and Independent variables

2.3(a) Overview of Site and Geography

It was planned that over a three year period (2017- 2019) the whole selected woodland area would be counted within the bluebell’s flowering time frame. To ensure accuracy of counts and that all areas were visited, 1:1000 Master Maps were created using the most recent available data (2016) from Digimap (https://digimap.edina.ac.uk/) (Example – Figure 31) supported by a Garmin GPSMAP 62 hand held device.

The terrain undulated considerably which made count areas difficult to access from an incline perspective. Based on this factor and the size of the areas, it was decided to use the main cycle and horse paths (Rides) to differentiate between count areas. The areas ran horizontally from left to right, with paths dividing the count locations into blocks (north to south). Further detail about count locations explained at 2.3(b).

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Position and length of valleys

2018 Count Area 2017 and 2019 Count Area

Meadow Field Scout Campsite

Car Park

Cranham Village

Figure 8. Overview of count area (red dots indicate circumference). (1:1,000 – Master Map: each Square =100m). Maps created using QGIS 2.16.1 NØdebo. Map Ordnance Survey from https://osmaps.ordnancesurvey.co.uk/51.81960,-2.15116,16 (Last accessed: 24/03/2019)

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At higher levels it proved more difficult to segment the counts due to topography. A ravine of significant depth runs from the northern edge of the Scout camp site up to the local minor road (Buckholt Road). Once the furthest edge of the camp site had been reached, counting was forced to the outer edge of the northwest area, rather than continuing the counting practice of moving from west to east horizontally; progressing up the rising incline from south to north (Figure 9 and 29).

Topography to the north western edge undulated to a greater degree with a higher density of trees. This made counting in smaller segments problematic and larger swathes were mapped to counter this.

Work maps (Example - Figure 30) of the area were produced prior to the counts taking place. The hope was to support movement and plan count areas prior to going to the woods. Once the counts started it was clear that human mediated change (horse and cycle) had introduced and degraded pathways that to this date have still not been mapped.

2.3(b) Survey Techniques

Areas were chosen based on their location and how their position fell within the remit of the thesis question (height and flora density affecting hybridisation). Counts were started at the southern south west corner and conducted horizontally (left to right) between mapped footpaths. This area is referred to as a ‘region’.

Regions were further defined into smaller ‘count areas’ based on bluebell density and ‘herb rich zone’ division. Once a count area had been selected, a numerical random generator would provide the grid reference to be surveyed (Figure 10). Dependent on area suitability one of two survey method types were chosen.

Two forms of survey adopted were;

Survey Type One (In-depth survey): involved a stratified random sampling format to fully survey the abundance of native, alien and hybridised bluebells. Additional information was gathered to see how those variables affected the growth of hybrids within each in-depth surveyed location. Additional information gathered included; elevation (m/above sea level (asl)), atmospheric temperature (ºC), wind speed (m/s), light measurement (Lux), soil moisture content (%), soil temperature (ºC), soil

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construct (depth = 12.7cm), pH and incline (degrees and ratio) (Table 3 and Figures 25 to 28). Up to 30m x 30m measured transect (‘X’ and ‘Y’ axis), dependent on topography, was mapped out and five numerical random generated grid references were chosen for review (n=5 counts per location) (https://www.random.org). Each grid reference was surveyed using a 1m x 1m (100 square) quadrat. All bluebells within the positioned quadrat were counted by taxon and plant and soil samples were collected for ‘keying’ (Table 31 to 32).

Survey Type Two (Bluebell area mapping and bluebell count): This was a variation on the planned sampling technique (Survey sample one), and was adjusted by the removal of the in depth method used to ascertain the true non-bias of taxonomic variation based on probable variables. The full count method proved very time consuming and was not conducive to surveying a full woodland of approximately 4.8km². To counter this, it was decided to try and plot all bluebells and count a selection of bluebells (n=5 counts per count area) using a cluster sampling method.

Where an area of bluebells was intersected by other foliage (‘margin’) and formed a discernible count location (Figure 10), a single start point was established near to the path (Ride). The area of bluebells was calculated by walking the circumference from the start point using the ‘Track Manager’ option on the Garmin GPSMAP 62 (GPS) and entering the track as a waypoint (Figures 34, page 50).

During this exercise, clusters of plants were counted to a maximum quantity of 100 plants. Depending on the size (m²) this count quantity was altered, as some groups of bluebells did not have a maximum quantity of 100 plants. Each count location was marked by date and time, height above sea level and GPS position.

Soil Sample Locations: Three random areas were selected based on the lack of vegetation. The aim of this was to compare the soil samples taken against the soil samples taken from the ‘full count’ areas where other vegetation was often present. Along with the soil samples additional readings were taken such as: elevation (m/asl), atmospheric temperature (ºC), wind speed (m/s), light measurement (Lux), soil moisture content (%), soil temperature (ºC), soil construct (depth = 12.7cm), pH and incline (degrees and ratio) (Figures 24 to 26).

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Locations 2017 count 1 count 2 count 3 count 4 count 5 Totals

5 Quadrats 6 3 3 3 3 18 Total

plants 100 64 58 344 105 671 counted

Locations 2018 count 1 count 2 count 3 count 4 count 5 count 6 Totals

64 Quadrats 64 32 30 19 17 12 174 Total plants 5000 2939 2589 1435 1382 1037 14382 counted

Locations 2019 count 1 count 2 count 3 count 4 count 5 count 6 count 7 Totals

64 Quadrats 79 34 24 17 13 7 3 177 Total plants 6250 3231 2035 1398 917 541 277 14649 counted

Table 1. Number of locations and quadrats per location counted within Buckholt Woods, Cranham, Gloucestershire, during the years 2017, 2018 and 2019.

SP – Start and finish Point

Count circumference

Count location 1 Count location 2 Count location 3 Count location 4

Region 1 Region 2 Ride

SP

Figure 9. Survey example by Region and Count Location (Photographs: Google Images; diagram: English 2.3(Woodlandc) Elevation Grant Scheme, 2005)

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Each taxon group by elevation were surveyed and counted to establish the population percentage by count location. Chi Squared Test of Independence and Bivariate Correlation (Spearman’s Rho) in SPSS were used to confirm whether there was an association between each taxonomic group and an increase in elevation using frequency data converted to percentage by population (Kohn et al., 2009). Co- occurrence was assessed graphically and descriptively based on elevation and also as an overall population indicator for the entire surveyed woodland. Further analysis considered habitat specificity evaluating the three taxa according to Levin’s B theory (Hulbert, 1978) to quantify observed deviation against expected habitat occupancy (based on information presented by the Cotswold Commons and Beechwood National Nature Reserves (NNR)).

2.3(d) Climate Conditions

Climatic influences were analysed using Time Series Modelling Analysis as a ‘Moving Average Computation’ and Bivariate Correlation (Spearman’s Rho) in IBM SPSS based on data provided by the Metrological Office for the South West of England and Wales 2019. The aim of these analysis was to see if there were a significant change in meteorological differences over time that would support the bluebell frequency data found within Buckholt Woods.

2.3(e) Woodland Flora by Taxon and Soil Samples

As part of the ‘Survey Type Two’ process, data collected were analysed using a Multi-nominal Regression analysis model in IBM SPSS. The aim of these analysis was to see if there were an association between each count year (west of woodland 2018 and east of woodland 2019), based on other topographical features rather than that of elevation.

Survey Type One gathered biotic samples for comparison and abiotic readings were collated to consider association to the frequency of bluebells noted in each specific sample location (Table 3). A Simple Linear Regression in SPSS was used to ascertain the association between frequency counts by taxa and pH levels in

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conjunction with graphical models to determine clarification between each abiotic reading, taxa frequency and location.

Chapter 3: Results

Survey data from both type one and type two surveys were consolidated by year into tables (2018; 2017 and 2019 combined) and standardised in the following formats for statistical testing:

3.1 Testing of taxa by elevation

Elevation range (165m to 174m) was condensed into five equal groups of metres above sea level. To complement this standardisation, frequency count data were also condensed under each elevation group (Table 2). Frequencies were averaged by taxa within in each elevation group. A Chi Squared Test of Independence was used with a weighted frequency conversion (Waite, 2000).

When elevation was tested against taxa to see whether increases in elevation would alter the percentage of hybridised bluebells found at the woodland, results demonstrated a non-significant correlation (Χ2(12)>=15.00, p=.241) (Table 2 and Figure 11) between the four variables (dependent – elevation; independent – 3 x taxa: H.’x’ massartiana, H. non-scripta and H. hispanica).

However, a Chi Square analysis using a weighted frequency NPAR test, whereby, each taxon was tested against elevation individually, proved significant; indicating the probability of a relationship between the elevations observed and the frequency of each of the two main species of Hyacinthoide; H. non-scripta - Χ2(12)>=45.00, p=<0.001 and H. ‘x’ massartiana - Χ2(12)>=45.00, p=<0.001 (Figure 10).

Elevation XM NS 180-209 82 18 210-229 36 64 230-249 33 67 240-259 82 18 260-279 13 87

Table 2. Taxa by mean average totals consolidated into five grouped ranges of elevation.

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Both sets of results indicate further consideration outside of the initial hypothesis. By testing each taxon individually against elevation, has pointed the research towards an alternative variable for consideration. The data at this point indicated a perceivable association of bluebells based on an east/west geographical and topographical divide rather than a comparison towards elevation only (Figure 18).

100 90

80

70

60 50 40 30 20

Percentage by Frequency 10 0 180-209 210-229 230-249 240-259 260-279 Grouped elevation

H. 'x' massartiana H. non-scripta

Figure 10. Consolidated yearly frequency counts by grouped elevation range.

700 1000 600 A B 800 500 600 400 300 400 200 200

100 count by Frequency

Frequency by count by Frequency 0 0 180 230 280 184 204 224 244 Elevation in metres above sea level Elevation in metres above sea level H. 'x' massartiana H. 'x' massartiana H. non-scripta H.non-scripta Linear (H. non-scripta) Linear (H.non-scripta)

Figure 11. Graphs show non-transformed frequency count data distribution when analysed against non- transformed elevation range. Graph A – 2018 counts (west). Graph B – 2017 and 2019 counts (east).

3.1(a) Inter and intra species testing

Comparisons of intra-specific and inter-specific taxa was carried out using a Bivariate Correlation (Spearman’s Rho) analysis and Chi Squared test of

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Independence using the full range of frequency data. Through a number of tests, a pattern occurred between the data collected in the west of the woodland (2018) and of that collected in east (2017 and 2019). Initial test was to ascertain whether a correlation could be seen between intra-species from across both years, looking for a frequency split that would highlight an association through numerical quantities. This graphed frequencies as expected (Figure 12).

A significant result between both sets of H. ‘x’ massartiana data (Figure 12) was seen, with a non-significant result noted for the combined sets of the H.non-scripta data. It is proposed that this result is due to the frequency of H. non-scripta data collected in 2018 (west) being of a much lower percentage than that collected in the east (2017 and 2019) (Table 3).

150 A 120 B 100 100 80 60

50 40 Axis Title Axis Title Axis 20 0 0 0 20 40 60 80 100 0 50 100 Axis Title Axis Title

NS 2018 NS 2019 XM 2018 XM 2019 Linear (NS 2019) Linear (XM 2018)

Figure 12. Correlation of intra-species data collected in 2018 (west) and 2019 (east). Correlation for both graphs registers as weak. H. non-scripta graph A indicates a non-significant result; Rho = -0.028 (F1, 77 = 0.05918, p=>0.81). H.’x’ massartiana graph B demonstrates a high probability of difference between those samples collected 2018 compared to sample collected in 2019 (Rho = -0.06 (F1, 77 = 4.840, p=<0.03)).

150 A 150 B 100 100

50 50 Axis Title Axis Title Axis 0 0 0 20 40 60 80 100 0 20 40 60 80 100 Axis Title Axis Title NS 2018 XM 2019 NS 2019 XM 2018 Linear (NS 2018) Linear (XM 2018)

Figure 13. Correlation of Inter-species data collected in 2018 (west) and 2019 (east).Correlation for both graphs registers as weak. A significant result for both data sets indicates a strong association between H. non-scripta vs H. ‘x’ massartiana by alternative years. This suggests that the difference between the frequency counts are clear alternatives and once plotted have an association through percentage total by topographical division: (A) NS 2018 vs XM 2019 = Rho = -0.081 (F1, 78 = 0.05159, p=<0.001), (B)22 NS | 2019P a g e vs XM 2018 = Rho = -0.38 (F1, 78 = 0.05634, p=<0.001).

S1609786 Copperthwaite G NS6344 Dissertation

2018 2017 & 2019 Total XM % 86.20 Total XM % 29.09 Total NS % 13.80 Total NS % 69.53 Total H % 0.01 Total H % 1.37

Grand total % 100.00 Grand total % 100.00

Table 3. Overall percentage cover of bluebells in Buckholt Woods, Cranham, Gloucestershire. 2018 = west side of Buckholt Woods; 2017 and 2019 east side of Buckholt Woods. Key: XM – H. ‘x’ massartiana, NS – H. non-scripta and H – H. hispanica.

Analysing the inter-specific data, based on the same parameters of west and east, highlighted a significant result across both tests (Figure 13). These results show a correlation between each data set over the two years and how, as a percentage of the total count, the alternative values for each taxa, demonstrates a swap in percentage totals by taxa across the west/east geographical divide (Table 3).

3.2 Climate Conditions

140.00 5.50 120.00 4.50 100.00 3.50 80.00

2.50

Year Year

1.50 60.00

1980 2010 1910 1920 1930 1940 1950 1960 1970 1990 2000

1991 2011 1961 1966 1971 1976 1981 1986 1996 2001 2006 2016 Mean Days of Air Frost by Frost Air of Days Mean 1961 to 2018 per 'mm' in Rainfall Mean 1910 to 2018 Linear (Series1) Linear (Series1) 2 per. Mov. Avg. (Series1) 2 per. Mov. Avg. (Series1)

11.00 150.00 10.50 140.00 10.00 130.00 9.50 120.00 9.00 110.00 8.50 Year

Celcius 8.00 100.00

1999 2006 1929 1936 1943 1950 1957 1964 1971 1978 1985 1992 2013

1910 1920 1930 1940 1950 1960 1970 1980 1990 2000 2010 1929 to 2018 1910 to 2018 per Sunshine of Hours Mean

Mean Tempersture by Year in Year by Tempersture Mean Linear (Series1) Linear (Series1) 2 per. Mov. Avg. (Series1) 2 per. Mov. Avg. (Series1)

Figure 14. Time Series Analysis for prime abiotic factors that may contribute to inter-species competition and an increased level of hybridisation of H. ‘x’ massartiana over H. non-scripta.

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Bluebells by %

Average Wind Direction

Figure 15. Overview of H. hispanica frequency counts using 3D spatial analysis. (1:50,000 – Explorer Map). Maps created using QGIS 2.16.1 NØdebo. Map Ordnance Survey from https://osmaps.ordnancesurvey.co.uk/51.81960,-2.15116,16 (Last accessed: 14/05/2019)

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Bluebells by %

Average Wind Direction

Figure 16. Overview of H. ‘x’ massartiana frequency counts using 3D spatial analysis. (1:50,000 – Explorer Map). Maps created using QGIS 2.16.1 NØdebo. Map Ordnance Survey from https://osmaps.ordnancesurvey.co.uk/51.81960,-2.15116,16 (Last accessed: 14/05/2019)

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Bluebells by %

Average Wind Direction

Figure 17. Overview of H. non-scripta frequency counts using 3D spatial analysis. (1:50,000 – Explorer Map). Maps created using QGIS 2.16.1 NØdebo.

Map Ordnance Survey from https://osmaps.ordnancesurvey.co.uk/51.81960,-2.15116,16 (Last accessed: 14/05/2019)

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Bluebell by % A B

Figure 18. Overview of hyacinthoide frequency counts by taxa using 3D spatial analysis including colour coded elevation. (1:50,000 – Explorer Map). Maps created using QGIS 2.16.1 NØdebo. Map Ordnance Survey from https://osmaps.ordnancesurvey.co.uk/51.81960,-2.15116,16 (Last accessed: 14/05/2019)

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N N A N B C

N N N D E F

Figure 19. 3D topographical maps with hyacinthoide distribution using spatial analysis. A – Sites of H.hispanica frequency collection. B – Sites of H.’x’ massartiana frequency collection. C – Sites of H. non-scripta frequency collection. D – Spatial analysis of taxon distribution from west to east. E – Main area of taxon division as seen from 3D spatial analysis. F- Taxon spatial analysis plotted to 1:50,000 OS map showing all localised infrastructure. (1:50,000 – Explorer Map). Maps created using QGIS 2.16.1 NØdebo. Map Ordnance Survey from https://osmaps.ordnancesurvey.co.uk/51.81960,-2.15116,16 (Last accessed: 14/05/2019) 28 | P a g e

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Data indicates a move to warmer mean temperatures by year (r = 0.255, n = 110, p = <0.001) with a reduction in mean days of air frost (r = -0.367, n = 58, p = 0.005), whilst mean average rainfall in ‘mm’ per year (r = -0.32, n = 109, p = <0.62) and mean hours of sunshine per year (r = 0.73, n = 90, p = 0.30) show little change over the data period.

Data indicates a general warming for the localised area with a reduction in air frost days which in turn favours the invasive H. hispanica and H. ‘x’ massartiana (Marquardt, 2016). H. non-scripta habitually is more reliant on ground cooling during the autumn and winter periods and more tolerant of wetter rather than dryer spring conditions (Marquardt, 2016).

3.3 Flora by Taxon and Soil Condition

3.3(a) Flora distribution by taxa

Flora distribution across the woodland is not fully uniform and data collected at this juncture is not able to definitively conclude as to why this should be the case (See 3.4(b)). However, a variety of trees can be seen throughout all levels with the Beech (Fagus sylvatica) being the most dominant. Most notable plant is Ivy (Hedra helix) (Figures 20 to 23)

Data collection was limited to twelve sites (Survey Type One), one of which included the village gardens of Cranham; of which no woodland plants were found. Associating flora with other abiotic and biotic factors in graph and table form (Χ2(25)>=21.50, p=.664), shows no correlation to each other with the exception of the level of pH compared to the density of bluebells sampled by taxa at those locations (Figures 24 to 26).

A vicariance can be defined by the change of percentage in taxa between where 2018 counts finish and 2017 and 2019 counts started. Topographically the terrain changes, moving from a relative flat plateau in the west (2018 count) in to a steep valley in the east (2017 and 2019 counts), culminating in a semi-flat plateau. Centrally this area is partitioned by a thin strip of calciferous grassland of approximately 6 to 8 meters wide.

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High percentages of H. ‘x’ massartiana can be seen in the northern area of the east (2017 and 2019 counts) (Figure 18 – position A) weakening the overall percentage of H. non-scripta in the eastern count area. It is suggested that this may be correlated to the adjacent woodland and placement of residential dwellings at this location. The contrary can be seen at the north-eastern side (Figure 18 – position B) where with the lack of residential dwellings, the maintenance of native bluebells is held at a higher percentage overall (69.53% - Table 3).

Survey Type One conducted at sample sites 1 to 6 shows a probability that the level of pH may have an effect on the type of bluebell that out competes the other at certain levels.

6 5 4 3 2 1 0

Number of sample locations 2018 locations sample of Number Taxa Loc 1 Loc 2 loc 3 loc 4 Loc 5 Loc 6

Figure 20. Survey Type One conducted on the western side of the woodland in 2018 and the plants sampled at each full sample site.

6 5

4

3 2 1

0 Beech Wych Elm Rowan Sycamore Melick Common Sedge

2018 locations sample of Number Taxa Series1 Series2 Series3 Series4 Series5 Series6

Figure 21. Survey Type One conducted on the western side of the woodland in 2018 and the trees sampled at each full sample site.

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6 5 4 3 2 1 0 2019

locations sample of Number Taxa Loc 1(2) Loc 2(2) Loc 3(2) Loc 4(2) Loc 5(2) Loc 6(2)

Figure 22. Survey Type One conducted on the eastern side of the woodland in 2017/2019 and the flora sampled at each full sample site.

5

4

3

2 2019 1

0 Beech Wych Elm Rowan Sycamore Melick Common Sedge locations sample of Number Taxa Loc 1(2) Loc 2(2) Loc 3(2) Loc 4(2) Loc 5(2) Loc 6(2)

Figure 23. Survey Type One conducted on the eastern side of the woodland in 2017/2019 and the trees sampled at each full sample site.

20 18 16 15 14 12 10 10 8 6 5 4 2

0

3 4 2 5 6

0 1

Soil Temperature in Celsius in TemperatureSoil

3(2) 4(2) 5(2) 6(2) 1 2 3 4 5 6 2(2) 3(2) 4(2) 5(2) 6(2) 2(2) Percentin Level Moisture Soil Sample Sites Sample Sites Soil Moisture Content (%) Soil Temperature (Celcius)

Figure 24. Survey Type One abiotic and biotic data. All locations sampled with the exception of 1(2), gardens within Cranham village.

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30 3.5 25 3 20 2.5 15 2 10 1.5

second 1 Celsius 5

0 0.5

2 3 4 5 6

1 0

2(2) 3(2) 4(2) 5(2) 6(2)

Wind speed in metres per metres in speed Wind

1 2 3 4 5 6

2(2) 3(2) 4(2) 5(2) 6(2) in Temperature Atmospheric Sample Sites Sample Sites

Atmospheric Temperature (Celsius) Wind Speed (m/s)

Figure 25. Survey Type One abiotic and biotic data. All locations sampled with the exception of 1(2), gardens within Cranham village.

3500 25 3000 20 2500 2000 15 1500 10 1000 5

Light Scale in Luxin Scale Light 500 Degreesin Incline

0 0

2 3 4 5 6 1 2 3 4 5 6

1

4(2) 5(2) 2(2) 3(2) 6(2) 2(2) 3(2) 4(2) 5(2) 6(2) Sample Sites Sample Sites

Light measurement (Lux) Incline in Degrees

Figure 26. Survey Type One abiotic and biotic data. All locations sampled with the exception of 1(2), gardens within Cranham village.

3.3(b) Soil Condition

Soil pH graphically indicates a discernible trend in the level of pH and the type of bluebell that grow predominantly in that location, however, whilst there is a strong correlation, the overall result indicates a non-significant result (R = .998, F1,3 = 156.986, p = <.06). Further research by G. H. Knight (1964) noted that bluebells can be found in dryer soils with a pH range of pH 4.5 to 5.0 as described by Blackman and Ritter (1954), but indicated that most bluebells were physically weaker and in minimal abundance. Bluebells found in moist, loamy soils with a pH range of

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between 7.5 and 8, were recorded in greater abundance with a strong phenotypic presence (Knight, 1964).

H. 'x' Total H. non Location massartiana Bluebell pH scripta Total Total Count 1 13 116 129 8.0 2 57 53 110 7.0 3 167 18 185 5.0 4 91 10 101 6.0

5 9 7 16 6.0

6 82 41 123 5.0 Table 4. Data corresponding the quantity of bluebells by taxa as a percentage compared to soil pH.

180 Site 3 160

140 Site 1 120 Site 4 100 Site 6

80 Site 2 60 40

Bluebellsof Frequency 20 Site 5 0 8.0 7.0 5.0 6.0 6.0 5.0

pH Levels per Site H. 'x' massartiana H. non-scripta

Figure 27. Graph demonstrating the correspondence of bluebells by taxa as a percentage in relation to soil pH.

9 8 8 8 8 7 6 5 4 3 3 2 2 Scale Numerical 1 1 0 0 0 0 Site pH Bluebells Location 1 1 8 0 Location 2 2 8 0 Location 3 3 8 0 Location 1 to 3 - soil sample area with no bluebells

Location 1 Location 2 Location 3

Figure 27(a). Sample test areas with no flora growth x 3.

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Bluebells by %

Figure 28. Bluebell distribution as a percentage by taxa compared to vegetation by type and areas where no bluebells were located due to varying biotic factors (1:50,000 – Explorer Map). Maps created using QGIS 2.16.1 NØdebo. Map Ordnance Survey from https://osmaps.ordnancesurvey.co.uk/51.81960,-2.15116,16 (Last accessed: 14/05/2019) 34 | P a g e

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Sites (2017 and 2019) 6 (2) 5(2) 4(2) 3 (2) 2(2) 1(2)

Sites (2018) 1 2 3 4 5 6

Figure 29. Survey Type One sample sites. (1:50,000 – Explorer Map). Maps created using QGIS 2.16.1 NØdebo. Map Ordnance Survey from https://osmaps.ordnancesurvey.co.uk/51.81960,-2.15116,16 (Last accessed: 14/05/2019)

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Chapter 4: Conclusion

The initial test survey in 2017 to understand co-occurrence and how it manifested itself within Buckholt Woods indicated a transition from invasive H.hispanica through to H. ‘x’ massartiana and finally concluding in higher intraspecific densities of H. non- scripta. This prompted further research to quantify the hypothesis that hybridisation could be reduced through woodland topography and/or flora density (le Roux et al., 2012).

The positioning of Cranham village in close proximity to the woodland, in conjunction with a significant point of source (gardens and hedge-ways) that mirrored the base width of the woodland, seemed ideal. This hypothetically, allowed for cross pollination from a south-westerly direction for wind mediated pollination and a close enough distribution of H. hispanica to support insect pollinators moving from the point of origin into the woodland (Myers and Bazely, 2003).

Survey data in 2018 started to change the original hypothesis with a shift inter- specifically between what was noted in 2017 on the eastern side of the woodland compared to the new data gathered on the western side of the woodland (Adams et al., 2014). In 2019 data collected substantiated the original survey data in 2017 but to a lesser percentage frequency.

A valley divides each count area, running from north to south. The data suggests that this acts as a natural transition zone between inter-specific densities, although questions still remain as to whether this change in frequency percentage is topographical alone or acts in-conjunction with the calciferous grasses that also run from north to south close to the division zone (Myers and Bazely, 2003).

It was also noted that the percentage frequency on the eastern side of the valley reduced once a larger area had been surveyed. It is suggested the results for 2017 compared to 2019 are supplemented due to the survey sites in 2017 not including areas near to the Buckholt road, a feature that circumvents the woodland. It is observed that higher percentages of H. ‘x’ massartiana can be seen to the western and northern edge of the woodland, which lay close to other sources of hybridised bluebells, such as adjacent woodland and residential dwellings.

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Results show spatial and temporal variability which moves towards genetic drift at this current point. Increases in weather patterns, especially those that increase ambient temperature, ground temperature and dryness, may not suit the ecological needs of the British Isles’ habitual H. non-scripta but lend itself to the habitual requirements of the H. hispanica and H. ‘x’ massartiana. Ranta et al., (2006) highlights the debate between genetic drift and natural selection through deterministic and directional forces (Fisher, 1930; Wright, 1932 and 1948) whereby spatial structures are necessary for the creation of the heterogeneity necessary for evolutionary change.

It is suggested that increases in abiotic factors, and the native bluebells slow adaptation in genetic resilience, will constitute a probable move towards a slow silent extinction that will be observed in the years to come as sympatric speciation continues (Kramer and Havens, 2009). Alternatively, it may well be that the polymorphic phenotypic variants noted from 2017 to 2019 are the heterogenetic adaptation due to global warming.

Although not conclusive and requiring further, long term research, it is hoped that the pure physiology of the native bluebell can be maintained by topography, flora density and/or a combination of both (Kramer and Havens, 2009).

It is clear that generalised ground dwelling plants such as Ramson (Allium ursinum) do not interfere or alter the density/polymorphic variations of bluebells. Although, plants of hardier nature such as bramble (Rosaceae rubus) do inhibit dispersal.

Notable was that no one count area of H. ‘x’ massartiana, maintained a 100% count of one species, whereas this was achieved by the H. non-scripta.

4.1 Other Considerations

General consensus questions as to what constitutes the full range of variation in the country’s population of bluebells, and Kohn et al., (2009) refers to the fact that no discernible proof through an in-depth study, at present, can quantify the actual level of hybridisation within the whole of the British Isles (Kohn et al., 2009). Marquardt (2016), has quantified two variants in the Iberian Peninsula (Figure 35, page 52) which may be treated as a baseline for understanding what constitutes certain morphological variations, however, morphological variations experienced within the

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woodland of Cranham do not restrictively meet those variations noted by Marquardt (2016) (Figure 30, page 46).

As described in the methods section, the basis of data collection used the parameters laid down by Rose (1999) and Stace (2010) and any plant that did not meet those accepted parameters were regarded as a hybrid. Since the release of Kohn et al., (2019) who suggests that the demise of the native bluebell is unlikely due to weakening pollen from invasive bluebells, those parameters have to be reconsidered at this juncture.

However, as for the case of this study, the data stands and so do the parameters that the data was surveyed against. Moreover, to class all recorded variants as H. ‘x’ masssartiana would be un-scientifically sound based on Marquardt (2016) and Kohn et al., (2019) findings. Variants need to be quantified with genetic testing and until the true origin can be substantiated, all variants recorded in Buckholt woodland will be referred to as ‘subtle variations’.

4.2 Limitations in Data Collection

Future counts or surveys could be enhanced with support. Geographically, whilst surveying full counts to ascertain area², larger areas made the process difficult to manage due to the density of the woodland. Flora density on occasions, limited the ability to easily find the original start point. Although data collected will be viable for future research, accuracy would have been enhanced with the addition of equipment that would have aided the start and finish of a GPS track survey.

4.3 Future Research

In Kohn et al., (2009) the paper summarises it case with the following statement, ‘it is evident that alien Hyacinthoides taxa pose a significant potential risk to native H. non-scripta.’ Although a number of papers exist focusing and highlighting genetic variation, it is none-the-less, important to substantiate those findings fully in the field. Additionally, this form of research will support those wild native species affected by anthropogenically introduced flora. The following research is proposed:

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• Expand research locations in 2020 to repeat and verify Buckholt Wood findings. • Test phenotypic variation with the use of DNA testing for those areas and plants already surveyed. • Research seed dispersal based on species type and test for differences in dispersal capability. • Research differences in natural vegetative reproduction to test for potential variation in ‘Hardiness Rating’. • Research whether inter-species root competition increases the likelihood of uneven dispersal and quantify if density dependence plays an active part in successful hybridisation. • Quantify variations in hydrological and pH requirements between species and establish any differences in hardiness. • Research hexapod invertebrates to understand what contribution insects have on hyacinthoide reproduction and distribution. Understand how wind pollination compares with hexapod mediated pollination. • Establish whether natural barriers such as calciferous grassland zones inhibit hybridisation. • To understand whether long term limited exposure to low densities of invasive species limits and/or slows down mutation compared to high density exposure as noted in the inter-competitive zones experienced in the Iberian Peninsula.

(Word Count: 6544)

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Supplementary Information

Figure 30. Polymorphic bluebell variants photographed from 2017 to 2019.

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Figure 31. 1:1000 Master Maps were created using the most recent available data (2016) from Digimap (https://digimap.edina.ac.uk/) to support ease of surveying

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Date Count QGIS Track and Elevation (m) Atmospheric Light Soil Photographs Wind Speed Soil Moisture Incline (Degrees Count 1 (X Count 1 (Non Count 1 % Cover (based % Cover (based Count 2 (X Count 2 (Non Count 1 % Cover (based % Cover (based Count 3 (X Count 3 (Non Count 1 % Cover (based % Cover (based Count 4 (X Count 4 (Non Count 1 % Cover (based % Cover (based Count 5 (X Count 5 (Non Count 1 % Cover (based % Cover (based Count 6 (X Count 6 (Non Count 1 % Cover (based % Cover (based Loation carried out Time of Track GPS Co-Ordinates Way point above Sea Temperature Area Size (m²) measurement Temperature numbers to Random Selector Total on 100 counted on 100 counted Total on 100 counted on 100 counted Total on 100 counted on 100 counted Total on 100 counted on 100 counted Total on 100 counted on 100 counted Total on 100 counted on 100 counted (m/s) Content (%) and ratio) Massartiana) Scripta (Hispanica) Massartiana) Scripta (Hispanica) Massartiana) Scripta (Hispanica) Massartiana) Scripta (Hispanica) Massartiana) Scripta (Hispanica) Massartiana) Scripta (Hispanica) (dd/mm/yryr) reference Level (Celsius) (Lux) (Celcius) support survey plants) plants) plants) plants) plants) plants) plants) plants) plants) plants) plants) plants)

1 07/05/2018 51.48977 -2.10209 2018_05_07 242 18.5 900.00 0 1350 10.9 14.5 0 50-56, 262 8x3, 9x9, 8x7, 5x2, 2x3 0 8 0 8 0.00 100.00 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0! 1 14 0 15 6.67 93.33 6 47 0 53 11.32 88.68 6 47 0 53 11.32 88.68

2 07/05/2018 51. 48961 -2. 10146 2018_05_07 225 20.1 900.00 0 204 15.8 16 0 73-77, 263 4x0, 2x2, 5x8, 7x6, 4x12 13 17 0 30 43.33 56.67 9 17 0 26 34.62 65.38 7 1 0 8 87.50 12.50 28 18 0 46 60.87 39.13 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0!

3 07/05/2018 51. 48971 -2.10032 2018_05_07 230 22.9 900.00 0 1930 14.3 16.5 11 / 1:567 105-108, 264 12x3, 10x8, 13x5, 14x5, 14x8, 14x9 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0! 90 1 0 91 98.90 1.10 77 17 0 94 81.91 18.09

4 08/05/2018 51. 48988 -2ᵒ 09941 2018_05_08 208 26.1 900.00 0.9 1310 17.8 8 15 / 1:401 118-121, 265 14x1, 12x1, 16x3, 16x9, 8x8 34 9 0 43 79.07 20.93 10 1 0 11 90.91 9.09 0 0 0 0 #DIV/0! #DIV/0! 2 0 0 2 100.00 0.00 45 0 0 45 100.00 0.00 0 0 0 0 #DIV/0! #DIV/0!

5 08/05/2018 51. 49050 -2. 09551 2018_05_08 219 16.9 900.00 3.1 2510 14.4 13 3 / 1:19.08 266, 10x1, 2x9, 4x2, 12x4, 11x5 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0! 9 6 0 15 60.00 40.00 0 0 0 0 #DIV/0! #DIV/0! 0 1 0 1 0.00 100.00 0 0 0 0 #DIV/0! #DIV/0!

6 11/05/2018 51. 49129 -2. 09467 2018_05_08 204 15.5 900.00 0 3110 11.2 12 20 / 1:2.15 267, Stratified due to slope - 1, 2, 6, 9, 11 2 0 13 84.62 15.38 20 6 0 26 76.92 23.08 31 8 0 39 79.49 20.51 16 3 0 19 84.21 15.79 4 22 0 26 15.38 84.62 0 0 0 0 #DIV/0! #DIV/0!

1 08/05/2018 51. 49021 -2. 09886 2018_05_08 217 15.4 0 1630 8.5 13 10 / 1:567 24, 258

2 08/05/2018 51. 49058 -2. 09708 2018_05_08 223 16 0 1840 12.2 14 10 / 1:567 51, 259

3 08/05/2018 51. 49023 -2. 09469 2018_05_15 207 15.8 0.8 1820 15 15 0 88, 260

1 07/05/2018 11:07:16 N 51ᵒ 48.966' W 002ᵒ 10.032' 221 14.04 57-59 56 44 0 100 56.00 44.00 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0!

2 07/05/2018 11:12:13 N 51ᵒ 48.968' W 002ᵒ 10.032' 221 34.25 60-62 74 26 0 100 74.00 26.00 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0!

3 07/05/2018 11:17:16 N 51ᵒ 48.976' W 002ᵒ 10.469' 216 93.98 63-67 74 26 0 100 74.00 26.00 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0!

4 07/05/2018 11:28:39 N 51ᵒ 4.965' W 002ᵒ 10.170' 215 2.68 68-72 29 5 0 34 85.29 14.71 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0!

5 07/05/2018 12:23:38 N 51ᵒ 48.966' W 002ᵒ 10.167' 206 22.78 77-81 60 39 0 99 60.61 39.39 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0!

6 07/05/2018 12:34:29 N 51ᵒ 48.958' W 002ᵒ 10.469' 214 7.24 84-86 27 2 0 29 93.10 6.90 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0!

7 07/05/2018 12:41:25 N 51ᵒ 48.970' W 002ᵒ 10.129' 217 61.05 89-96 100 0 0 100 100.00 0.00 70 3 0 73 95.89 4.11 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0!

8 07/05/2018 12:52:05 N 51ᵒ 48.972' W 002ᵒ 10.098' 212 14.83 97-98 67 6 0 73 91.78 8.22 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0!

9 07/05/2018 13:07:09 N 51ᵒ 48.989' W 002ᵒ 10.107' 217 73.16 99-104 64 8 0 72 88.89 11.11 21 48 0 69 30.43 69.57 62 16 0 78 79.49 20.51 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0!

10 07/05/2018 13:10:45 N 51ᵒ 48.983' W 002ᵒ 10.082' 220 33.20 Did not take 66 8 0 74 89.19 10.81 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0!

11 07/05/2018 13:17:55 N 51ᵒ 48.986' W 002ᵒ 10.062' 215 3.26 Did not take 85 13 0 98 86.73 13.27 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0!

12 07/05/2018 13:26:27 N 51ᵒ 48.977' W 002ᵒ 10.051' 217 2.55 Did not take 67 13 0 80 83.75 16.25 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0!

13 07/05/2018 14:38:22 N 51ᵒ 48.983' W 002ᵒ 10.021' 215 0.04 Did not take 46 9 0 55 83.64 16.36 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0!

14 07/05/2018 14:46:46 N 51ᵒ 49.004' W 002ᵒ 09.975' 220 12.43 109-113 80 3 0 83 96.39 3.61 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0!

15 07/05/2018 14:58:04 N 51ᵒ 49.001' W 002ᵒ 09.962' 224 933.98 114-116 76 8 0 84 90.48 9.52 90 10 0 100 90.00 10.00 76 9 0 85 89.41 10.59 88 12 0 100 88.00 12.00 96 4 0 100 96.00 4.00 89 11 0 100 89.00 11.00

16 07/05/2018 15:05:29 N 51ᵒ 49.003' W 002ᵒ 09.945' 222 15.75 117 56 2 0 58 96.55 3.45 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0!

17 07/05/2018 15:09:19 N 51ᵒ 49.006' W 002ᵒ 09.920' 221 128.16 122-123 76 2 0 78 97.44 2.56 56 2 0 58 96.55 3.45 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0!

18 07/05/2018 15:56:11 N 51ᵒ 48.980' W 002ᵒ 09.959' 228 447.49 124-125 76 18 0 94 80.85 19.15 58 16 0 74 78.38 21.62 24 6 0 30 80.00 20.00 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0!

19 08/05/2018 11:17:47 N 51ᵒ 49.004' W 002ᵒ 09.896' 217 15.93 1 to 2 80 0 0 80 100.00 0.00 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0!

20 08/05/2018 11:21:39 N 51ᵒ 49.998' W 002ᵒ 09.902' 208 146.71 3 to 4 60 40 0 100 60.00 40.00 100 0 0 100 100.00 0.00 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0!

21 08/05/2018 11:33:53 N 51ᵒ 49.010' W 002ᵒ 09.913' 209 1,466.10 5 to 16 76 24 0 100 76.00 24.00 88 12 0 100 88.00 12.00 64 9 0 73 87.67 12.33 55 8 0 63 87.30 12.70 48 18 0 66 72.73 27.27 75 14 0 89 84.27 15.73

22 08/05/2018 11:52:51 N 51ᵒ 49.007' W 002ᵒ 09.889' 213 104.65 17-22 13 10 0 23 56.52 43.48 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0!

23 08/05/2018 12:23:30 N 51ᵒ 49.026' W 002ᵒ 09.767' 221 403.16 25-37 65 35 0 100 65.00 35.00 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0!

24 08/05/2018 12:30:07 N 51ᵒ 49.030' W 002ᵒ 09.758' 231 404.15 38-46 70 30 0 100 70.00 30.00 44 19 0 63 69.84 30.16 88 36 0 124 70.97 29.03 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0!

25 08/05/2018 12:52:01 N 51ᵒ 49.049' W 002ᵒ 09.738' 233 32.77 47-50 89 11 0 100 89.00 11.00 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0!

26 08/05/2018 13:21:21 N 51ᵒ 49.046' W 002ᵒ 09.648' 223 15.06 52 76 12 0 88 86.36 13.64 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0!

27 08/05/2018 13:31:54 N 51ᵒ 49.057' W 002ᵒ 09.600' 220 74.52 53-57 77 23 0 100 77.00 23.00 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0!

28 08/05/2018 13:49:24 N 51ᵒ 49.043' W 002ᵒ 09.099' 198 1,005.40 58-62 66 12 0 78 84.62 15.38 87 9 0 96 90.63 9.38 24 4 0 28 85.71 14.29 48 17 0 65 73.85 26.15 94 6 0 100 94.00 6.00 81 19 0 100 81.00 19.00

29 08/05/2018 14:36:09 N 51ᵒ 48.988' W 002ᵒ 09.941' 219 3,350.30 63-79 92 8 0 100 92.00 8.00 78 22 0 100 78.00 22.00 95 5 0 100 95.00 5.00 0 0 0 #DIV/0! #DIV/0! 0 0 0 #DIV/0! #DIV/0! 0 0 0 #DIV/0! #DIV/0!

30 08/05/2018 14:56:34 N 51ᵒ 49.038' W 002ᵒ 09.503' 209 656.59 80-87 74 26 0 100 74.00 26.00 75 25 0 100 75.00 25.00 81 19 0 100 81.00 19.00 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0!

31 08/05/2018 15:30:54 N 51ᵒ 49.008' W 002ᵒ 09.450' 211 355.31 89-95 92 8 0 100 92.00 8.00 94 6 0 100 94.00 6.00 76 24 0 100 76.00 24.00 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0!

32 15/05/2018 11:19:17 N 51ᵒ 48.990' W 002ᵒ 09.408' 184 2,126.60 116-118 100 0 0 100 100.00 0.00 100 0 0 100 100.00 0.00 100 0 0 100 100.00 0.00 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0!

33 15/05/2018 11:27:05 N 51ᵒ 49.028' W 002ᵒ 09.418' 203 849.89 119-120 100 0 0 100 100.00 0.00 100 0 0 100 100.00 0.00 100 0 0 100 100.00 0.00 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0!

34 15/05/2018 11:32:02 N 51ᵒ 49.043' W 002ᵒ 09.446' 218 110.01 121-123 99 1 0 100 99.00 1.00 99 1 0 100 99.00 1.00 100 0 0 100 100.00 0.00 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0!

35 15/05/2018 11:39:18 N 51ᵒ 49.072' W 002ᵒ 09.539' 220 465.36 124-127 88 12 0 100 88.00 12.00 96 4 0 100 96.00 4.00 100 0 0 100 100.00 0.00 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0!

36 15/05/2018 11:55:33 N 51ᵒ 49.066' W 002ᵒ 09.571' 221 961.85 128-133 89 11 0 100 89.00 11.00 93 7 0 100 93.00 7.00 73 27 0 100 73.00 27.00 89 11 0 100 89.00 11.00 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0!

37 15/05/2018 11:59:39 N 51ᵒ 49.023' W 002ᵒ 09.469' 219 52.39 134-136 77 23 0 100 77.00 23.00 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0!

38 15/05/2018 12:08:43 N 51ᵒ 49.088' W 002ᵒ 09.618' 228 5.10 137-141 18 51 0 69 26.09 73.91 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0!

39 15/05/2018 12:19:46 N 51ᵒ 49.095' W 002ᵒ 09.629' 236 729.77 142-156 0 24 0 24 0.00 100.00 84 16 0 100 84.00 16.00 96 4 0 100 96.00 4.00 85 15 0 100 85.00 15.00 90 10 0 100 90.00 10.00 0 0 0 0 #DIV/0! #DIV/0!

40 15/05/2018 12:40:16 N 51ᵒ 49.102' W 002ᵒ 09.653' 235 2,000.30 157-168 92 8 0 100 92.00 8.00 80 20 0 100 80.00 20.00 100 0 0 100 100.00 0.00 98 2 0 100 98.00 2.00 94 6 0 100 94.00 6.00 68 32 0 100 68.00 32.00

41 15/05/2018 13:07:02 N 51ᵒ 49.111' W 002ᵒ 09.724' 241 1,876.80 169-180 95 5 0 100 95.00 5.00 100 0 0 100 100.00 0.00 100 0 0 100 100.00 0.00 93 7 0 100 93.00 7.00 95 5 0 100 95.00 5.00 86 14 0 100 86.00 14.00

42 15/05/2018 13:32:19 N 51ᵒ 49.120' W 002ᵒ 09.735' 239 2,261.00 181-198 100 0 0 100 100.00 0.00 12 88 0 100 12.00 88.00 70 30 0 100 70.00 30.00 80 20 0 100 80.00 20.00 98 2 0 100 98.00 2.00 0 0 0 0 #DIV/0! #DIV/0!

43 15/05/2018 13:42:04 N 51ᵒ 49.121' W 002ᵒ 09.679' 244 1,502.60 199-201 93 7 0 100 93.00 7.00 98 2 0 100 98.00 2.00 88 12 0 100 88.00 12.00 72 28 0 100 72.00 28.00 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0!

44 15/05/2018 13:55:44 N 51ᵒ 49.122' W 002ᵒ 09.551' 215 9.38 205-209 58 42 0 100 58.00 42.00 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0!

45 15/05/2018 14:15:35 N 51ᵒ 49.098' W 002ᵒ 09.500' 223 31.94 212-216 100 0 0 100 100.00 0.00 100 0 0 100 100.00 0.00 92 8 0 100 92.00 8.00 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0!

46 15/05/2018 14:22;48 N 51ᵒ 49.087' W 002ᵒ 09.488' 240 1,097.60 217-220 100 0 0 100 100.00 0.00 100 0 0 100 100.00 0.00 92 8 0 100 92.00 8.00 100 0 0 100 100.00 0.00 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0!

47 15/05/2018 14:29:11 N 51ᵒ 49.070' W 002ᵒ 09.480' 227 419.74 221-223 98 2 0 100 98.00 2.00 96 4 0 100 96.00 4.00 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0!

48 15/05/2018 14:39:11 N 51ᵒ 49.028' W 002ᵒ 09.427' 214 389.08 224 100 0 0 100 100.00 0.00 100 0 0 100 100.00 0.00 100 0 0 100 100.00 0.00 100 0 0 100 100.00 0.00 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0!

49 15/05/2018 14:45:24 N 51ᵒ 49.031' W 002ᵒ 09.434' 209 25.71 225 100 0 0 100 100.00 0.00 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0!

51 15/05/2018 15:10:40 N 51ᵒ 48.990' W 002ᵒ 09.348' 195 8,979.00 226-238 95 5 0 100 95.00 5.00 81 19 0 100 81.00 19.00 100 0 0 100 100.00 0.00 14 12 0 26 53.85 46.15 68 32 0 100 68.00 32.00 0 0 0 0 #DIV/0! #DIV/0!

52 15/05/2018 15:15:48 N 51ᵒ 49.067' W 002ᵒ 09.384' 203 41.77 239-240 8 30 0 38 21.05 78.95 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0!

53 15/05/2018 15:33:45 N 51ᵒ 49.170' W 002ᵒ 09.382' 215 78.70 241-242 72 28 0 100 72.00 28.00 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0!

54 18/05/2018 10:30:00 GPS Failed Various Various 243-257 100 0 0 100 100.00 0.00 100 0 0 100 100.00 0.00 55 54 0 109 50.46 49.54 0 0 0 0 #DIV/0! #DIV/0! 100 0 0 100 100.00 0.00 100 0 0 100 100.00 0.00

55 18/05/2018 10:30:00 GPS Failed Various Various As above 44 11 0 55 80.00 20.00 89 11 0 100 89.00 11.00 95 5 0 100 95.00 5.00 98 2 0 100 98.00 2.00 88 12 0 100 88.00 12.00 100 0 0 100 100.00 0.00

56 18/05/2018 10:30:00 GPS Failed Various Various As above 75 25 0 100 75.00 25.00 85 15 0 100 85.00 15.00 88 12 0 100 88.00 12.00 94 5 1 100 94.00 5.00 100 0 0 100 100.00 0.00 98 2 0 100 98.00 2.00

57 18/05/2018 10:30:00 GPS Failed Various Various As above 100 0 0 100 100.00 0.00 40 3 0 43 93.02 6.98 100 0 0 100 100.00 0.00 100 0 0 100 100.00 0.00 95 5 0 100 95.00 5.00 100 0 0 100 100.00 0.00

58 18/05/2018 10:30:00 GPS Failed Various Various As above 38 2 0 40 95.00 5.00 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 #DIV/0! #DIV/0! 0 0 0 #DIV/0! #DIV/0!

4206 794 0 5000 84.12 15.88 2553 386 0 2939 86.87 13.13 2286 303 0 2589 88.30 11.70 1261 174 1 1435 87.87 12.13 1211 171 0 1382 87.63 12.37 880 156 0 1036 84.94 15.06 39,346.08 Figure 32. Count data for 2018

48 | P a g e

S1609786 Copperthwaite G NS6344 Dissertation

Date Count QGIS Track and Elevation (m) Atmospheric Light Soil Photographs GPS Co- Wind Speed Soil Moisture Incline (Degrees Count 1 (X Count 1 (Non Count 1 % Cover (based % Cover (based Count 2 (X Count 2 (Non Count 1 % Cover (based % Cover (based Count 3 (X Count 3 (Non Count 1 % Cover (based % Cover (based Count 4 (X Count 4 (Non Count 1 % Cover (based % Cover (based Count 5 (X Count 5 (Non Count 1 % Cover (based % Cover (based Count 6 (X Count 6 (Non Count 1 % Cover (based % Cover (based Count 6 (X Count 6 (Non Count 1 % Cover (based % Cover (based Loation carried out Time of Track Way point above Sea Temperature Area Size (m²) measurement Temperature numbers to Random Selector Total on 100 counted on 100 counted Total on 100 counted on 100 counted Total on 100 counted on 100 counted Total on 100 counted on 100 counted Total on 100 counted on 100 counted Total on 100 counted on 100 counted Total on 100 counted on 100 counted Ordinates (m/s) Content (%) and ratio) Massartiana) Scripta (Hispanica) Massartiana) Scripta (Hispanica) Massartiana) Scripta (Hispanica) Massartiana) Scripta (Hispanica) Massartiana) Scripta (Hispanica) Massartiana) Scripta (Hispanica) Massartiana) Scripta (Hispanica) (dd/mm/yryr) reference Level (Celsius) (Lux) (Celcius) support survey plants) plants) plants) plants) plants) plants) plants) plants) plants) plants) plants) plants) plants) plants)

See below See below 1 14/04/2017 165 See attached table for 2017 14 14 100.00 0.00 24 24 100.00 0.00 18 18 100.00 0.00 36 36 100.00 0.00 7 7 100.00 0.00 1 8 1 100.00 0.00 0 #DIV/0! #DIV/0! attached table attached table See below See below 2 14/04/2017 185 See attached table for 2018 19 19 100.00 0.00 45 45 100.00 0.00 0 #DIV/0! #DIV/0! 0 #DIV/0! #DIV/0! 0 #DIV/0! #DIV/0! 0 #DIV/0! #DIV/0! 0 #DIV/0! #DIV/0! attached table attached table See below See below 3 14/04/2017 201 See attached table for 2019 25 7 32 78.13 21.88 3 1 4 75.00 25.00 22 22 100.00 0.00 0 #DIV/0! #DIV/0! 0 #DIV/0! #DIV/0! 0 #DIV/0! #DIV/0! 0 #DIV/0! #DIV/0! attached table attached table See below See below 4 14/04/2017 210 See attached table for 2020 32 105 137 23.36 76.64 110 16 126 87.30 12.70 9 75 84 10.71 89.29 0 #DIV/0! #DIV/0! 0 #DIV/0! #DIV/0! 0 #DIV/0! #DIV/0! 0 #DIV/0! #DIV/0! attached table attached table See below See below 5 14/04/2017 215 See attached table for 2021 0 #DIV/0! #DIV/0! 6 34 40 15.00 85.00 6 34 40 15.00 85.00 5 60 65 7.69 92.31 0 #DIV/0! #DIV/0! 0 #DIV/0! #DIV/0! 0 #DIV/0! #DIV/0! attached table attached table See below See below 6 14/04/2017 See attached table for 2022 0 #DIV/0! #DIV/0! 0 #DIV/0! #DIV/0! 0 #DIV/0! #DIV/0! 0 #DIV/0! #DIV/0! 0 #DIV/0! #DIV/0! 0 #DIV/0! #DIV/0! 0 #DIV/0! #DIV/0! attached table attached table 1 0 #DIV/0!

2 0 #DIV/0!

3 0 #DIV/0! N 51ᵒ 48.963' 5 19/04/2019 10:58:06 207 Road side 41-46 4 0 96 100 4.00 96.00 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0! W 002ᵒ 09.846' N 51ᵒ 48.963' 6 19/04/2019 10:58:06 207 Road side 41-47 0 0 100 100 0.00 100.00 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0! W 002ᵒ 09.846' N 51ᵒ 49.028' 7 19/04/2019 11:36:03 200 196.00 47 0 100 0 100 0.00 100.00 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0! W 002ᵒ 9.123' N 51ᵒ 49.046' 8 19/04/2019 11:42:38 196 143.55 48-50 0 100 0 100 0.00 100.00 0 100 0 100 0.00 100.00 0 100 0 100 0.00 100.00 0 100 0 100 0.00 100.00 1 99 0 100 1.00 99.00 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0! W 002ᵒ 09.127' N 51ᵒ 49.068' 9 19/04/2019 11:48:28 197 27.41 51-54 14 86 0 100 14.00 86.00 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0! W 002ᵒ 09.149' N 51ᵒ 49.104' 10 19/04/2019 12:12:33 180 174.92 55-56 25 75 0 100 25.00 75.00 13 63 0 76 17.11 82.89 18 82 0 100 18.00 82.00 25 75 0 100 25.00 75.00 11 89 0 100 11.00 89.00 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0! W 002ᵒ 09.145' N 51ᵒ 49.116' 11 19/04/2019 12:18:42 186 132.99 57 26 74 0 100 26.00 74.00 70 3 0 73 95.89 4.11 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0! W 002ᵒ 09.111' N 51ᵒ 49.161' 12 19/04/2019 12:31:30 191 192.43 58-62 8 92 0 100 8.00 92.00 10 90 0 100 10.00 90.00 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0! W 002ᵒ 09.078' N 51ᵒ 49.172' 13 19/04/2019 12:41:34 202 294.63 63-64 49 51 0 100 49.00 51.00 30 70 0 100 30.00 70.00 62 16 0 78 79.49 20.51 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0! W 002ᵒ 09.097' N 51ᵒ 49.186' 14 19/04/2019 12:49:53 194 166.34 65 14 86 0 100 14.00 86.00 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0! W 002ᵒ 09.101' N 51ᵒ 49.195' 15 19/04/2019 13:03:27 204 175.76 66-67 9 91 0 100 9.00 91.00 31 69 0 100 31.00 69.00 21 79 0 100 21.00 79.00 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0! W 002ᵒ 09.084' N 51ᵒ 49.192' 16 19/04/2019 13:09:35 223 38.26 68-69 10 90 0 100 10.00 90.00 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0! W 002ᵒ 09.073' N 51ᵒ 49.242' 17 19/04/2019 13:17:04 212 273.95 70-71 3 62 0 65 4.62 95.38 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0! W 002ᵒ 09.084' N 51ᵒ 49.248' 18 19/04/2019 Mark point 217 Small patch 71 0 62 0 62 0.00 100.00 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0! W 002ᵒ 09.079' N 51ᵒ 49.026' 19 19/04/2019 Mark point 180 Small patch 72 0 77 0 77 0.00 100.00 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0! W 002ᵒ 09.103' N 51ᵒ 49.033' 20 19/04/2019 Mark point 188 Small patch 73 0 66 0 66 0.00 100.00 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0! W 002ᵒ 09.108' N 51ᵒ 49.044' 21 19/04/2019 13:56:03 199 1,881.30 74-76 0 100 0 100 0.00 100.00 3 97 0 100 3.00 97.00 8 92 0 100 8.00 92.00 13 87 0 100 13.00 87.00 13 52 0 65 20.00 80.00 14 86 0 100 14.00 86.00 16 84 0 100 16.00 84.00 W 002ᵒ 09.098' N 51ᵒ 49.058' 22 19/04/2019 14:11:59 190 831.39 77 5 95 0 100 5.00 95.00 6 94 0 100 6.00 94.00 12 88 0 100 12.00 88.00 4 96 0 100 4.00 96.00 0 100 0 100 0.00 100.00 3 97 0 100 3.00 97.00 12 65 0 77 15.58 84.42 W 002ᵒ 09.066' N 51ᵒ 49.058' No photograph 23 19/04/2019 Mark point 194 Small patch 22 78 0 100 22.00 78.00 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0! W 002ᵒ 09.052' taken N 51ᵒ 49.084' No photograph 24 20/04/2019 Mark point 206 Small patch 14 48 0 62 22.58 77.42 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0! W 002ᵒ 09.059' taken N 51ᵒ 49.091' No photograph 25 20/04/2019 Mark point 204 Small patch 8 55 0 63 12.70 87.30 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0! W 002ᵒ 09.033' taken N 51ᵒ 49.119' No photograph 26 20/04/2019 Mark point 223 Small patch 3 12 0 15 20.00 80.00 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0! W 002ᵒ 09.024' taken N 51ᵒ 49.129' No photograph 27 20/04/2019 Mark point 219 Small patch 15 13 0 28 53.57 46.43 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0! W 002ᵒ 09.028' taken N 51ᵒ 49.256' No photograph 28 20/04/2019 14:38:54 227 588.01 22 88 0 110 20.00 80.00 54 46 0 100 54.00 46.00 22 24 0 46 47.83 52.17 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0! W 002ᵒ 08.950' taken N 51ᵒ 49.265' No photograph 29 20/04/2019 14:47:39 244 857.20 11 89 0 100 11.00 89.00 15 85 0 100 15.00 85.00 20 58 0 78 25.64 74.36 6 37 0 43 13.95 86.05 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0! W 002ᵒ 08.928' taken N 51ᵒ 49.277' 30 20/04/2019 11:33:28 271 804.12 4,5,6 15 85 0 100 15.00 85.00 15 85 0 100 15.00 85.00 10 90 0 100 10.00 90.00 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0! W 002ᵒ 08.936' N 51ᵒ 49.267' 31 20/04/2019 11:45:45 245 436.12 7 9 91 0 100 9.00 91.00 12 88 0 100 12.00 88.00 28 72 0 100 28.00 72.00 25 75 0 100 25.00 75.00 23 77 0 100 23.00 77.00 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0! W 002ᵒ 08.925' N 51ᵒ 49.282' 32 20/04/2019 12:04:39 236 1,868.60 8,9 99 401 0 500 19.80 80.20 49 51 0 100 49.00 51.00 72 8 0 80 90.00 10.00 41 59 0 100 41.00 59.00 36 64 0 100 36.00 64.00 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0! W 002ᵒ 08.891' N 51ᵒ 49.257' 33 20/04/2019 12:12:55 236 519.07 11,12 15 85 0 100 15.00 85.00 21 89 0 110 19.09 80.91 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0! W 002ᵒ 08.874' N 51ᵒ 49.249' 34 20/04/2019 12:34:30 239 3,574.90 13,14 31 69 0 100 31.00 69.00 28 22 0 50 56.00 44.00 59 41 0 100 59.00 41.00 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0! W 002ᵒ 08.876' N 51ᵒ 49.221' 35 20/04/2019 12:53:27 237 4,240.20 22,23,24,25 16 84 0 100 16.00 84.00 37 63 0 100 37.00 63.00 19 81 0 100 19.00 81.00 41 59 0 100 41.00 59.00 34 0 0 34 100.00 0.00 25 6 0 31 80.65 19.35 0 0 0 0 #DIV/0! #DIV/0! W 002ᵒ 08.829' N 51ᵒ 49.221' 36 20/04/2019 13:18:29 235 6,701.50 25 10 90 0 100 10.00 90.00 0 100 0 100 0.00 100.00 24 22 0 46 52.17 47.83 35 0 0 35 100.00 0.00 31 3 0 34 91.18 8.82 48 61 0 109 44.04 55.96 49 51 0 100 #DIV/0! 51.00 W 002ᵒ 08.221' N 51ᵒ 49.201' No photograph 37 20/04/2019 13:32:27 238 5,941.70 6 94 0 100 6.00 94.00 4 28 0 32 12.50 87.50 6 12 0 18 33.33 66.67 24 11 0 35 68.57 31.43 6 15 0 21 28.57 71.43 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0! W 002ᵒ 08.802' taken N 51ᵒ 49.188' 38 20/04/2019 13:58:40 231 11,589.00 26 40 2 0 42 95.24 4.76 8 92 0 100 8.00 92.00 16 1 0 17 94.12 5.88 31 7 0 38 81.58 18.42 15 42 0 57 26.32 73.68 10 90 0 100 10.00 90.00 0 0 0 0 #DIV/0! #DIV/0! W 002ᵒ 08.649' N 51ᵒ 49.119' No photograph 39 20/04/2019 Mark point 229 Small patch 15 31 0 46 32.61 67.39 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0! W 002ᵒ 08.554' taken N 51ᵒ 49.114' No photograph 40 20/04/2019 Mark point 230 Small patch 14 56 0 70 20.00 80.00 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0! W 002ᵒ 08.640' taken N 51ᵒ 49.105' 41 23/04/2019 Mark point 225 Small patch 258,29 0 76 0 76 0.00 100.00 30 70 0 100 30.00 70.00 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0! W 002ᵒ 08.654' N 51ᵒ 49.090' No photograph 42 23/04/2019 Mark point 216 Small patch 2 28 0 30 6.67 93.33 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0! W 002ᵒ 08.702' taken N 51ᵒ 49.084' No photograph 43 23/04/2019 Mark point 216 Small patch 11 36 0 47 23.40 76.60 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0! W 002ᵒ 08.703' taken N 51ᵒ 49.093' No photograph 44 23/04/2019 12:40:16 225 No flowers 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0! W 002ᵒ 08.807' taken N 51ᵒ 49.057' No photograph 45 23/04/2019 Mark point 199 Small patch 9 30 0 39 23.08 76.92 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0! W 002ᵒ 08.995' taken N 51ᵒ 49.046' 46 23/04/2019 14:43:12 203 2,144.10 30-33 26 74 0 100 26.00 74.00 19 81 0 100 19.00 81.00 46 54 0 100 46.00 54.00 23 66 0 89 25.84 74.16 21 62 0 83 25.30 74.70 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0! W 002ᵒ 09.023' N 51ᵒ 49.067' 47 25/04/2019 11:22:19 207 1,883.80 34 48 52 0 100 48.00 52.00 29 71 0 100 29.00 71.00 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0! W 002ᵒ 09.086' Old count N 51ᵒ 49.039' No photograph 48 25/04/2019 214 Small patch 6 44 0 50 12.00 88.00 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0! area W 002ᵒ 09.015' taken N 51ᵒ 49.076' 49 25/04/2019 11:43:12 205 1,047.90 35,36 36 64 0 100 36.00 64.00 16 84 0 100 16.00 84.00 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0! W 002ᵒ 08.991' N 51ᵒ 49.103' No photograph 50 25/04/2019 Mark point 213 Small patch 4 46 0 50 8.00 92.00 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0! W 002ᵒ 08.988' taken N 51ᵒ 49.132' 51 25/04/2019 Mark point 221 Small patch 221-223 6 0 0 6 100.00 0.00 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0! W 002ᵒ 08.943' N 51ᵒ 49.137' No photograph 52 25/04/2019 Mark point 217 Small patch 6 55 0 61 9.84 90.16 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0! W 002ᵒ 08.928' taken N 51ᵒ 49.142' 53 25/04/2019 12:00:06 234 4,948.60 39,40 34 66 0 100 34.00 66.00 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0! W 002ᵒ 08.195' N 51ᵒ 49.157' No photograph 54 25/04/2019 Mark point 228 Small patch 17 39 0 56 30.36 69.64 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0! W 002ᵒ 08.894' taken N 51ᵒ 49.168' 55 25/04/2019 12:17:17 239 10,931.00 41,42 34 66 0 100 34.00 66.00 44 56 0 100 44.00 56.00 32 68 0 100 32.00 68.00 28 72 0 100 28.00 72.00 23 77 0 100 23.00 77.00 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0! W 002ᵒ 08.866' N 51ᵒ 49.113' No photograph 56 25/04/2019 Mark point 230 Small patch 14 30 0 44 31.82 68.18 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0! W 002ᵒ 08.508' taken N 51ᵒ 49.057' 57 25/04/2019 Mark point 223 Small patch 43,44 0 56 0 56 0.00 100.00 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0! W 002ᵒ 08.511' N 51ᵒ 49.019' No photograph 58 25/04/2019 Mark point 222 Small patch 1 25 0 26 3.85 96.15 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0! W 002ᵒ 08.493' taken N 51ᵒ 48.994' No photograph 59 25/04/2019 Mark point 195 Small patch 14 60 0 74 18.92 81.08 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0! W 002ᵒ 08.686' taken N 51ᵒ 48.955' No photograph 60 26/04/2019 Raining on GPS - 193 Small patch 9 23 0 32 28.13 71.88 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0! pad soaked W 002ᵒ 08.657' taken N 51ᵒ 48.954' No photograph 61 26/04/2019 Raining on GPS - 215 Small patch 11 89 0 100 11.00 89.00 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0! pad soaked W 002ᵒ 08.642' taken N 51ᵒ 48.929' No photograph 62 26/04/2019 Raining on GPS - 185 Small patch 27 63 0 90 30.00 70.00 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0! pad soaked W 002ᵒ 08.613' taken N 51ᵒ 48.963' No photograph 63 26/04/2019 Raining on GPS - 198 Small patch 14 22 0 36 38.89 61.11 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0! pad soaked W 002ᵒ 08.813' taken

Raining on GPS - N 51ᵒ 48.976' No photograph 64 26/04/2019 194 Small patch 0 24 0 24 0.00 100.00 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0! pad soaked W 002ᵒ 08.805' taken

Raining on GPS - N 51ᵒ 48.986' No photograph 65 26/04/2019 192 Small patch 5 95 0 100 5.00 95.00 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0! pad soaked W 002ᵒ 08.805' taken

Raining on GPS - N 51ᵒ 49.254' 66 26/04/2019 213 Small patch 15 2 0 17 88.24 11.76 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0! pad soaked W 002ᵒ 09.059'

Raining on GPS - N 51ᵒ 49.280' 67 26/04/2019 220 Small patch 25 75 0 100 25.00 75.00 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0! pad soaked W 002ᵒ 09.103'

Raining on GPS - N 51ᵒ 49.293' 68 26/04/2019 220 Small patch 52 15 0 67 77.61 22.39 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0! pad soaked W 002ᵒ 09.121' N 51ᵒ 49.319' 69 26/04/2019 Raining on GPS - 219 Small patch 49 41 0 90 54.44 45.56 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0! pad soaked W 002ᵒ 09.120' N 51ᵒ 49.341' 70 26/04/2019 12:31:40 236 281.96 45,46,47 16 34 0 50 32.00 68.00 44 26 0 70 62.86 37.14 9 22 0 31 29.03 70.97 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0! W 002ᵒ 09.129'

Raining on GPS - N 51ᵒ 49.323' 71 26/04/2019 235 Small patch 17 0 0 17 100.00 0.00 14 4 0 18 77.78 22.22 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0! pad soaked W 002ᵒ 09.095'

Raining on GPS - N 51ᵒ 49.316' 72 26/04/2019 233 Small patch 35 2 0 37 94.59 5.41 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0! pad soaked W 002ᵒ 09.077' N 51ᵒ 49.199' 73 26/04/2019 13:01:58 229 612.06 48,49 26 74 0 100 26.00 74.00 63 37 0 100 63.00 37.00 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0! W 002ᵒ 08.629' N 51ᵒ 49.232' 74 26/04/2019 13:13:50 217 2,908.10 39 11 0 50 78.00 22.00 10 40 0 50 20.00 80.00 24 26 0 50 48.00 52.00 33 17 0 50 66.00 34.00 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0! W 002ᵒ 08.785'

Raining on GPS - N 51ᵒ 49.259' 75 26/04/2019 240 Small patch 22 8 0 30 73.33 26.67 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0! pad soaked W 002ᵒ 08.943'

Raining on GPS - N 51ᵒ 49.230' 76 26/04/2019 196 Small patch 2 10 0 12 16.67 83.33 1 12 0 13 7.69 92.31 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0! pad soaked W 002ᵒ 09.114' N 51ᵒ 49.214' 77 26/04/2019 13:45:11 192 1,371.30 54 27 73 0 100 27.00 73.00 32 68 0 100 32.00 68.00 0 27 0 27 0.00 100.00 7 0 0 7 100.00 0.00 0 16 0 16 0.00 100.00 4 96 0 100 4.00 96.00 0 0 0 0 #DIV/0! #DIV/0! W 002ᵒ 09.128' N 51ᵒ 49.201' 78 26/04/2019 13:51:10 204 214.70 67 33 0 100 67.00 33.00 56 44 0 100 56.00 44.00 64 36 0 100 64.00 36.00 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0! W 002ᵒ 09.129'

Raining on GPS - N 51ᵒ 49.180' 79 26/04/2019 196 Small patch 30 10 0 40 75.00 25.00 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0! pad soaked W 002ᵒ 09.171'

Raining on GPS - N 51ᵒ 49.092' 80 26/04/2019 189 Small patch 27 4 0 31 87.10 12.90 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0! pad soaked W 002ᵒ 09.326'

Raining on GPS - N 51ᵒ 49.185' 81 26/04/2019 233 Small patch 0 100 0 100 0.00 100.00 0 100 0 100 0.00 100.00 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0! pad soaked W 002ᵒ 09.240' N 51ᵒ 49.213' 82 26/04/2019 Raining on GPS - 249 Small patch 54 46 0 100 54.00 46.00 44 56 0 100 44.00 56.00 32 68 0 100 32.00 68.00 29 71 0 100 29.00 71.00 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0! pad soaked W 002ᵒ 09.232' N 51ᵒ 49.243' 83 26/04/2019 14:41:16 255 2,547.10 55,56,57,58,59 72 28 0 100 72.00 28.00 92 8 0 100 92.00 8.00 89 11 0 100 89.00 11.00 74 26 0 100 74.00 26.00 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0! W 002ᵒ 09.278' N 51ᵒ 49.323' 84 26/04/2019 Raining on GPS - 243 Small patch 71 29 0 100 71.00 29.00 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0! 0 0 0 0 #DIV/0! #DIV/0! pad soaked W 002ᵒ 09.191' 1602 4648 196 6250 25.63 74.37 1088 2143 0 3231 33.67 66.33 748 1287 0 2035 36.76 63.24 480 918 0 1398 34.33 65.67 221 696 0 917 24.10 75.90 105 436 8 541 19.41 80.59 77 200 0 277 27.80 72.20 59,608.96 Figure 33. Count data collected 2017 and 2019.

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S1609786 Copperthwaite G NS6344 Dissertation

Figure 34. Count locations and how the information was tracked using the ‘Track Manager’ option on the Garmin GPSMAP 62 (GPS) and entering the track as a waypoint.

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S1609786 Copperthwaite G NS6344 Dissertation

Figure 35. Images from Marquardt (2016) showing the hybridised phenotypic variations created in hybrid zone of Spain.

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